LVQ and backpropagation neural networks applied to NASA SSME data

NASA Technical Reports Server (NTRS)

Doniere, Timothy F.; Dhawan, Atam P.

1993-01-01

Feedfoward neural networks with backpropagation learning have been used as function approximators for modeling the space shuttle main engine (SSME) sensor signals. The modeling of these sensor signals is aimed at the development of a sensor fault detection system that can be used during ground test firings. The generalization capability of a neural network based function approximator depends on the training vectors which in this application may be derived from a number of SSME ground test-firings. This yields a large number of training vectors. Large training sets can cause the time required to train the network to be very large. Also, the network may not be able to generalize for large training sets. To reduce the size of the training sets, the SSME test-firing data is reduced using the learning vector quantization (LVQ) based technique. Different compression ratios were used to obtain compressed data in training the neural network model. The performance of the neural model trained using reduced sets of training patterns is presented and compared with the performance of the model trained using complete data. The LVQ can also be used as a function approximator. The performance of the LVQ as a function approximator using reduced training sets is presented and compared with the performance of the backpropagation network.

Enhancing the Reliability of Head Nodes in Underwater Sensor Networks

PubMed Central

Min, Hong; Cho, Yookun; Heo, Junyoung

2012-01-01

Underwater environments are quite different from terrestrial environments in terms of the communication media and operating conditions associated with those environments. In underwater sensor networks, the probability of node failure is high because sensor nodes are deployed in harsher environments than ground-based networks. The sensor nodes are surrounded by salt water and moved around by waves and currents. Many studies have focused on underwater communication environments in an effort to improve the data transmission throughput. In this paper, we present a checkpointing scheme for the head nodes to quickly recover from a head node failure. Experimental results show that the proposed scheme enhances the reliability of the networks and makes them more efficient in terms of energy consumption and the recovery latency compared to the previous scheme without checkpointing. PMID:22438707

Evaluation of small sensor technology for criteria air pollutants at ground-based sites and a citizen science network

EPA Science Inventory

A number of small sensor technologies for the measurement of NOz, O: and other criteriapollutants have recently emerged. There is a growing interest in understanding the capability ofsensor technology in accurately measuring ambient concentrations of gas-phase criteriapollutants....

Ground Monitoring Neotropical Dry Forests: A Sensor Network for Forest and Microclimate Dynamics in Semi-Arid Environments (Enviro-Net°)

NASA Astrophysics Data System (ADS)

Rankine, C. J.; Sánchez-Azofeifa, G.

2011-12-01

In the face of unprecedented global change driven by anthropogenic pressure on natural systems it has become imperative to monitor and better understand potential shifts in ecosystem functioning and services from local to global scales. The utilization of automated sensors technologies offers numerous advantages over traditional on-site ecosystem surveying techniques and, as a result, sensor networks are becoming a powerful tool in environmental monitoring programs. Tropical forests, renowned for their biodiversity, are important regulators of land-atmosphere fluxes yet the seasonally dry tropical forests, which account for 40% of forested ecosystems in the American tropics, have been severely degraded over the past several decades and not much is known of their capacity to recover. With less than 1% of these forests protected, our ability to monitor the dynamics and quantify changes in the remaining primary and recovering secondary tropical dry forests is vital to understanding mechanisms of ecosystem stress responses and climate feedback with respect to annual productivity and desertification processes in the tropics. The remote sensing component of the Tropi-Dry: Human and Biophysical Dimensions of Tropical Dry Forests in the Americas research network supports a network of long-term tropical ecosystem monitoring platforms which focus on the dynamics of seasonally dry tropical forests in the Americas. With over 25 sensor station deployments operating across a latitudinal gradient in Mexico, Costa Rica, Brazil, and Argentina continuously collecting hyper-temporal sensory input based on standardized deployment parameters, this monitoring system is unique among tropical environments. Technologies used in the network include optical canopy phenology towers, understory wireless sensing networks, above and below ground microclimate stations, and digital cameras. Sensory data streams are uploaded to a cyber-infrastructure initiative, denominated Enviro-Net°, for data storage, management, visualization, and retrieval for further analysis. The use of tower and ground-based optical sensor networks and meteorological monitoring instrumentation has proven effective in capturing seasonal growth patterns in primary and secondary forest stands. Furthermore, the observed trends in above and below ground microclimate variables are shown to closely correlate with in-situ vegetative indices (NDVI and EVI) across study sites. These long-term environmental sensory data streams provide valuable insights as to how these threatened semi-arid ecosystems regenerate after disturbances and how they respond to environmental stress such as climate change in the tropical and sub-tropical latitudes.

Exploring the impact of big data in economic geology using cloud-based synthetic sensor networks

NASA Astrophysics Data System (ADS)

Klump, J. F.; Robertson, J.

2015-12-01

In a market demanding lower resource prices and increasing efficiencies, resources companies are increasingly looking to the realm of real-time, high-frequency data streams to better measure and manage their minerals processing chain, from pit to plant to port. Sensor streams can include real-time drilling engineering information, data streams from mining trucks, and on-stream sensors operating in the plant feeding back rich chemical information. There are also many opportunities to deploy new sensor streams - unlike environmental monitoring networks, the mine environment is not energy- or bandwidth-limited. Although the promised efficiency dividends are inviting, the path to achieving these is difficult to see for most companies. As well as knowing where to invest in new sensor technology and how to integrate the new data streams, companies must grapple with risk-laden changes to their established methods of control to achieve maximum gains. What is required is a sandbox data environment for the development of analysis and control strategies at scale, allowing companies to de-risk proposed changes before actually deploying them to a live mine environment. In this presentation we describe our approach to simulating real-time scaleable data streams in a mine environment. Our sandbox consists of three layers: (a) a ground-truth layer that contains geological models, which can be statistically based on historical operations data, (b) a measurement layer - a network of RESTful synthetic sensor microservices which can simulate measurements of ground-truth properties, and (c) a control layer, which integrates the sensor streams and drives the measurement and optimisation strategies. The control layer could be a new machine learner, or simply a company's existing data infrastructure. Containerisation allows rapid deployment of large numbers of sensors, as well as service discovery to form a dynamic network of thousands of sensors, at a far lower cost than physically building the network.

Ground Control Point - Wireless System Network for UAV-based environmental monitoring applications

NASA Astrophysics Data System (ADS)

Mejia-Aguilar, Abraham

2016-04-01

In recent years, Unmanned Aerial Vehicles (UAV) have seen widespread civil applications including usage for survey and monitoring services in areas such as agriculture, construction and civil engineering, private surveillance and reconnaissance services and cultural heritage management. Most aerial monitoring services require the integration of information acquired during the flight (such as imagery) with ground-based information (such as GPS information or others) for improved ground truth validation. For example, to obtain an accurate 3D and Digital Elevation Model based on aerial imagery, it is necessary to include ground-based information of coordinate points, which are normally acquired with surveying methods based on Global Position Systems (GPS). However, GPS surveys are very time consuming and especially for longer time series of monitoring data repeated GPS surveys are necessary. In order to improve speed of data collection and integration, this work presents an autonomous system based on Waspmote technologies build on single nodes interlinked in a Wireless Sensor Network (WSN) star-topology for ground based information collection and later integration with surveying data obtained by UAV. Nodes are designed to be visible from the air, to resist extreme weather conditions with low-power consumption. Besides, nodes are equipped with GPS as well as Inertial Measurement Unit (IMU), accelerometer, temperature and soil moisture sensors and thus provide significant advantages in a broad range of applications for environmental monitoring. For our purpose, the WSN transmits the environmental data with 3G/GPRS to a database on a regular time basis. This project provides a detailed case study and implementation of a Ground Control Point System Network for UAV-based vegetation monitoring of dry mountain grassland in the Matsch valley, Italy.

Emerging Needs for Pervasive Passive Wireless Sensor Networks on Aerospace Vehicles

NASA Technical Reports Server (NTRS)

Wilson, William C.; Juarez, Peter D.

2014-01-01

NASA is investigating passive wireless sensor technology to reduce instrumentation mass and volume in ground testing, air flight, and space exploration applications. Vehicle health monitoring systems (VHMS) are desired on all aerospace programs to ensure the safety of the crew and the vehicles. Pervasive passive wireless sensor networks facilitate VHMS on aerospace vehicles. Future wireless sensor networks on board aerospace vehicles will be heterogeneous and will require active and passive network systems. Since much has been published on active wireless sensor networks, this work will focus on the need for passive wireless sensor networks on aerospace vehicles. Several passive wireless technologies such as microelectromechanical systems MEMS, SAW, backscatter, and chipless RFID techniques, have all shown potential to meet the pervasive sensing needs for aerospace VHMS applications. A SAW VHMS application will be presented. In addition, application areas including ground testing, hypersonic aircraft and spacecraft will be explored along with some of the harsh environments found in aerospace applications.

Autonomous Mission Operations for Sensor Webs

NASA Astrophysics Data System (ADS)

Underbrink, A.; Witt, K.; Stanley, J.; Mandl, D.

2008-12-01

We present interim results of a 2005 ROSES AIST project entitled, "Using Intelligent Agents to Form a Sensor Web for Autonomous Mission Operations", or SWAMO. The goal of the SWAMO project is to shift the control of spacecraft missions from a ground-based, centrally controlled architecture to a collaborative, distributed set of intelligent agents. The network of intelligent agents intends to reduce management requirements by utilizing model-based system prediction and autonomic model/agent collaboration. SWAMO agents are distributed throughout the Sensor Web environment, which may include multiple spacecraft, aircraft, ground systems, and ocean systems, as well as manned operations centers. The agents monitor and manage sensor platforms, Earth sensing systems, and Earth sensing models and processes. The SWAMO agents form a Sensor Web of agents via peer-to-peer coordination. Some of the intelligent agents are mobile and able to traverse between on-orbit and ground-based systems. Other agents in the network are responsible for encapsulating system models to perform prediction of future behavior of the modeled subsystems and components to which they are assigned. The software agents use semantic web technologies to enable improved information sharing among the operational entities of the Sensor Web. The semantics include ontological conceptualizations of the Sensor Web environment, plus conceptualizations of the SWAMO agents themselves. By conceptualizations of the agents, we mean knowledge of their state, operational capabilities, current operational capacities, Web Service search and discovery results, agent collaboration rules, etc. The need for ontological conceptualizations over the agents is to enable autonomous and autonomic operations of the Sensor Web. The SWAMO ontology enables automated decision making and responses to the dynamic Sensor Web environment and to end user science requests. The current ontology is compatible with Open Geospatial Consortium (OGC) Sensor Web Enablement (SWE) Sensor Model Language (SensorML) concepts and structures. The agents are currently deployed on the U.S. Naval Academy MidSTAR-1 satellite and are actively managing the power subsystem on-orbit without the need for human intervention.

Enviro-Net: From Networks of Ground-Based Sensor Systems to a Web Platform for Sensor Data Management

PubMed Central

Pastorello, Gilberto Z.; Sanchez-Azofeifa, G. Arturo; Nascimento, Mario A.

2011-01-01

Ecosystems monitoring is essential to properly understand their development and the effects of events, both climatological and anthropological in nature. The amount of data used in these assessments is increasing at very high rates. This is due to increasing availability of sensing systems and the development of new techniques to analyze sensor data. The Enviro-Net Project encompasses several of such sensor system deployments across five countries in the Americas. These deployments use a few different ground-based sensor systems, installed at different heights monitoring the conditions in tropical dry forests over long periods of time. This paper presents our experience in deploying and maintaining these systems, retrieving and pre-processing the data, and describes the Web portal developed to help with data management, visualization and analysis. PMID:22163965

Strategy of thunderstorm measurement with super dense ground-based observation network

NASA Astrophysics Data System (ADS)

Takahashi, Y.; Sato, M.

2014-12-01

It's not easy to understand the inside structure and developing process of thunderstorm only with existing meteorological instruments since its horizontal extent of the storm cell is sometimes smaller than an order of 10 km while one of the densest ground network in Japan, AMEDAS, consists of sites located every 17 km in average and the resolution of meteorological radar is 1-2 km in general. Even the X-band radar realizes the resolution of 250 m or larger. Here we suggest a new super dense observation network with simple and low cost sensors that can be used for measurement both of raindrop and vertical electric field change caused by cloud-to-ground lightning discharge. This sensor consists of two aluminum plates with a diameter of 10-20 cm. We carried out an observation campaign in summer of 2013 in the foothills of Mt. Yastugatake, Yamanashi and Nagano prefectures in Japan, installing 6 plate-type sensors at a distance of about 4 km. Horizontal location, height and charge amount of each lightning discharge are estimated successfully based on the information of electric field changes at several observing sites. Moreover, it was found that the thunderstorm has a very narrow structure well smaller than 300 m that cannot be measured by any other ways, counting the positive and negative pulses caused by attachment of raindrop to the sensor plate, respectively. We plan to construct a new super dense observation network in the north Kanto region, Japan, where the lightning activity is most prominent in summer Japan, distributing more than several tens of sensors at every 4 km or shorter, such as an order of 100 m at minimum. This kind of new type network will reveal the unknown fine structures of thunderstorms and open the door for constructing real time alert system of torrential rainfall and lightning stroke especially in the city area.

Architectural Design for European SST System

NASA Astrophysics Data System (ADS)

Utzmann, Jens; Wagner, Axel; Blanchet, Guillaume; Assemat, Francois; Vial, Sophie; Dehecq, Bernard; Fernandez Sanchez, Jaime; Garcia Espinosa, Jose Ramon; Agueda Mate, Alberto; Bartsch, Guido; Schildknecht, Thomas; Lindman, Niklas; Fletcher, Emmet; Martin, Luis; Moulin, Serge

2013-08-01

The paper presents the results of a detailed design, evaluation and trade-off of a potential European Space Surveillance and Tracking (SST) system architecture. The results have been produced in study phase 1 of the on-going "CO-II SSA Architectural Design" project performed by the Astrium consortium as part of ESA's Space Situational Awareness Programme and are the baseline for further detailing and consolidation in study phase 2. The sensor network is comprised of both ground- and space-based assets and aims at being fully compliant with the ESA SST System Requirements. The proposed ground sensors include a surveillance radar, an optical surveillance system and a tracking network (radar and optical). A space-based telescope system provides significant performance and robustness for the surveillance and tracking of beyond-LEO target objects.

A performance study of unmanned aerial vehicle-based sensor networks under cyber attack

NASA Astrophysics Data System (ADS)

Puchaty, Ethan M.

In UAV-based sensor networks, an emerging area of interest is the performance of these networks under cyber attack. This study seeks to evaluate the performance trade-offs from a System-of-Systems (SoS) perspective between various UAV communications architecture options in the context two missions: tracking ballistic missiles and tracking insurgents. An agent-based discrete event simulation is used to model a sensor communication network consisting of UAVs, military communications satellites, ground relay stations, and a mission control center. Network susceptibility to cyber attack is modeled with probabilistic failures and induced data variability, with performance metrics focusing on information availability, latency, and trustworthiness. Results demonstrated that using UAVs as routers increased network availability with a minimal latency penalty and communications satellite networks were best for long distance operations. Redundancy in the number of links between communication nodes helped mitigate cyber-caused link failures and add robustness in cases of induced data variability by an adversary. However, when failures were not independent, redundancy and UAV routing were detrimental in some cases to network performance. Sensitivity studies indicated that long cyber-caused downtimes and increasing failure dependencies resulted in build-ups of failures and caused significant degradations in network performance.

Optimized Autonomous Space In-situ Sensor-Web for volcano monitoring

USGS Publications Warehouse

Song, W.-Z.; Shirazi, B.; Kedar, S.; Chien, S.; Webb, F.; Tran, D.; Davis, A.; Pieri, D.; LaHusen, R.; Pallister, J.; Dzurisin, D.; Moran, S.; Lisowski, M.

2008-01-01

In response to NASA's announced requirement for Earth hazard monitoring sensor-web technology, a multidisciplinary team involving sensor-network experts (Washington State University), space scientists (JPL), and Earth scientists (USGS Cascade Volcano Observatory (CVO)), is developing a prototype dynamic and scaleable hazard monitoring sensor-web and applying it to volcano monitoring. The combined Optimized Autonomous Space -In-situ Sensor-web (OASIS) will have two-way communication capability between ground and space assets, use both space and ground data for optimal allocation of limited power and bandwidth resources on the ground, and use smart management of competing demands for limited space assets. It will also enable scalability and seamless infusion of future space and in-situ assets into the sensor-web. The prototype will be focused on volcano hazard monitoring at Mount St. Helens, which has been active since October 2004. The system is designed to be flexible and easily configurable for many other applications as well. The primary goals of the project are: 1) integrating complementary space (i.e., Earth Observing One (EO-1) satellite) and in-situ (ground-based) elements into an interactive, autonomous sensor-web; 2) advancing sensor-web power and communication resource management technology; and 3) enabling scalability for seamless infusion of future space and in-situ assets into the sensor-web. To meet these goals, we are developing: 1) a test-bed in-situ array with smart sensor nodes capable of making autonomous data acquisition decisions; 2) efficient self-organization algorithm of sensor-web topology to support efficient data communication and command control; 3) smart bandwidth allocation algorithms in which sensor nodes autonomously determine packet priorities based on mission needs and local bandwidth information in real-time; and 4) remote network management and reprogramming tools. The space and in-situ control components of the system will be integrated such that each element is capable of autonomously tasking the other. Sensor-web data acquisition and dissemination will be accomplished through the use of the Open Geospatial Consortium Sensorweb Enablement protocols. The three-year project will demonstrate end-to-end system performance with the in-situ test-bed at Mount St. Helens and NASA's EO-1 platform. ??2008 IEEE.

A New User Interface for On-Demand Customizable Data Products for Sensors in a SensorWeb

NASA Technical Reports Server (NTRS)

Mandl, Daniel; Cappelaere, Pat; Frye, Stuart; Sohlberg, Rob; Ly, Vuong; Chien, Steve; Sullivan, Don

2011-01-01

A SensorWeb is a set of sensors, which can consist of ground, airborne and space-based sensors interoperating in an automated or autonomous collaborative manner. The NASA SensorWeb toolbox, developed at NASA/GSFC in collaboration with NASA/JPL, NASA/Ames and other partners, is a set of software and standards that (1) enables users to create virtual private networks of sensors over open networks; (2) provides the capability to orchestrate their actions; (3) provides the capability to customize the output data products and (4) enables automated delivery of the data products to the users desktop. A recent addition to the SensorWeb Toolbox is a new user interface, together with web services co-resident with the sensors, to enable rapid creation, loading and execution of new algorithms for processing sensor data. The web service along with the user interface follows the Open Geospatial Consortium (OGC) standard called Web Coverage Processing Service (WCPS). This presentation will detail the prototype that was built and how the WCPS was tested against a HyspIRI flight testbed and an elastic computation cloud on the ground with EO-1 data. HyspIRI is a future NASA decadal mission. The elastic computation cloud stores EO-1 data and runs software similar to Amazon online shopping.

Autonomous Sensorweb Operations for Integrated Space, In-Situ Monitoring of Volcanic Activity

NASA Technical Reports Server (NTRS)

Chien, Steve A.; Doubleday, Joshua; Kedar, Sharon; Davies, Ashley G.; Lahusen, Richard; Song, Wenzhan; Shirazi, Behrooz; Mandl, Daniel; Frye, Stuart

2010-01-01

We have deployed and demonstrated operations of an integrated space in-situ sensorweb for monitoring volcanic activity. This sensorweb includes a network of ground sensors deployed to the Mount Saint Helens volcano as well as the Earth Observing One spacecraft. The ground operations and space operations are interlinked in that ground-based intelligent event detections can cause the space segment to acquire additional data via observation requests and space-based data acquisitions (thermal imagery) can trigger reconfigurations of the ground network to allocate increased bandwidth to areas of the network best situated to observe the activity. The space-based operations are enabled by an automated mission planning and tasking capability which utilizes several Opengeospatial Consortium (OGC) Sensorweb Enablement (SWE) standards which enable acquiring data, alerts, and tasking using web services. The ground-based segment also supports similar protocols to enable seamless tasking and data delivery. The space-based segment also supports onboard development of data products (thermal summary images indicating areas of activity, quicklook context images, and thermal activity alerts). These onboard developed products have reduced data volume (compared to the complete images) which enables them to be transmitted to the ground more rapidly in engineering channels.

Unattended Ground Sensors for Expeditionary Force 21 Intelligence Collections

DTIC Science & Technology

2015-06-01

tamper. 55  Size: 3 ½ x 3 ½ x 1 ¾ inches.  Wireless RF networked communications.  Built in seismic, acoustic , magnetic, and PIR sensors ...Marine Corps VHF Very High Frequency WSN Wireless Sensor Network xvi THIS PAGE INTENTIONALLY LEFT BLANK xvii ACKNOWLEDGMENTS I want...that allow digital wireless RF communications from each sensor interfaced into a variety of network architectures to relay critical data to a final

On-Board Mining in the Sensor Web

NASA Astrophysics Data System (ADS)

Tanner, S.; Conover, H.; Graves, S.; Ramachandran, R.; Rushing, J.

2004-12-01

On-board data mining can contribute to many research and engineering applications, including natural hazard detection and prediction, intelligent sensor control, and the generation of customized data products for direct distribution to users. The ability to mine sensor data in real time can also be a critical component of autonomous operations, supporting deep space missions, unmanned aerial and ground-based vehicles (UAVs, UGVs), and a wide range of sensor meshes, webs and grids. On-board processing is expected to play a significant role in the next generation of NASA, Homeland Security, Department of Defense and civilian programs, providing for greater flexibility and versatility in measurements of physical systems. In addition, the use of UAV and UGV systems is increasing in military, emergency response and industrial applications. As research into the autonomy of these vehicles progresses, especially in fleet or web configurations, the applicability of on-board data mining is expected to increase significantly. Data mining in real time on board sensor platforms presents unique challenges. Most notably, the data to be mined is a continuous stream, rather than a fixed store such as a database. This means that the data mining algorithms must be modified to make only a single pass through the data. In addition, the on-board environment requires real time processing with limited computing resources, thus the algorithms must use fixed and relatively small amounts of processing time and memory. The University of Alabama in Huntsville is developing an innovative processing framework for the on-board data and information environment. The Environment for On-Board Processing (EVE) and the Adaptive On-board Data Processing (AODP) projects serve as proofs-of-concept of advanced information systems for remote sensing platforms. The EVE real-time processing infrastructure will upload, schedule and control the execution of processing plans on board remote sensors. These plans provide capabilities for autonomous data mining, classification and feature extraction using both streaming and buffered data sources. A ground-based testbed provides a heterogeneous, embedded hardware and software environment representing both space-based and ground-based sensor platforms, including wireless sensor mesh architectures. The AODP project explores the EVE concepts in the world of sensor-networks, including ad-hoc networks of small sensor platforms.

Developing a robust wireless sensor network structure for environmental sensing

NASA Astrophysics Data System (ADS)

Zhang, Z.; Oroza, C.; Glaser, S. D.; Bales, R. C.; Conklin, M. H.

2013-12-01

The American River Hydrologic Observatory is being strategically deployed as a real-time ground-based measurement network that delivers accurate and timely information on snow conditions and other hydrologic attributes with a previously unheard of granularity of time and space. The basin-scale network involves 18 sub-networks set out at physiographically representative locations spanning the seasonally snow-covered half of the 5000 km2 American river basin. Each sub-network, covering about a 1-km2 area, consists of 10 wirelessly networked sensing nodes that continuously measure and telemeter temperature, and snow depth; plus selected locations are equipped with sensors for relative humidity, solar radiation, and soil moisture at several depths. The sensor locations were chosen to maximize the variance sampled for snow depth within the basin. Network design and deployment involves an iterative but efficient process. After sensor-station locations are determined, a robust network of interlinking sensor stations and signal repeaters must be constructed to route sensor data to a central base station with a two-way communicable data uplink. Data can then be uploaded from site to remote servers in real time through satellite and cell modems. Signal repeaters are placed for robustness of a self-healing network with redundant signal paths to the base station. Manual, trial-and-error heuristic approaches for node placement are inefficient and labor intensive. In that approach field personnel must restructure the network in real time and wait for new network statistics to be calculated at the base station before finalizing a placement, acting without knowledge of the global topography or overall network structure. We show how digital elevation plus high-definition aerial photographs to give foliage coverage can optimize planning of signal repeater placements and guarantee a robust network structure prior to the physical deployment. We can also 'stress test' the final network by simulating the failure of an individual node and investigating the effect and the self-healing ability of the stressed network. The resulting sensor network can survive temporary service interruption from a small subset of signal repeaters and sensor stations. The robustness and the resilient of the network performance ensure the integrity of the dataset and the real-time transmissibility during harsh conditions.

Optimized star sensors laboratory calibration method using a regularization neural network.

PubMed

Zhang, Chengfen; Niu, Yanxiong; Zhang, Hao; Lu, Jiazhen

2018-02-10

High-precision ground calibration is essential to ensure the performance of star sensors. However, the complex distortion and multi-error coupling have brought great difficulties to traditional calibration methods, especially for large field of view (FOV) star sensors. Although increasing the complexity of models is an effective way to improve the calibration accuracy, it significantly increases the demand for calibration data. In order to achieve high-precision calibration of star sensors with large FOV, a novel laboratory calibration method based on a regularization neural network is proposed. A multi-layer structure neural network is designed to represent the mapping of the star vector and the corresponding star point coordinate directly. To ensure the generalization performance of the network, regularization strategies are incorporated into the net structure and the training algorithm. Simulation and experiment results demonstrate that the proposed method can achieve high precision with less calibration data and without any other priori information. Compared with traditional methods, the calibration error of the star sensor decreased by about 30%. The proposed method can satisfy the precision requirement for large FOV star sensors.

Supervisory control of mobile sensor networks: math formulation, simulation, and implementation.

PubMed

Giordano, Vincenzo; Ballal, Prasanna; Lewis, Frank; Turchiano, Biagio; Zhang, Jing Bing

2006-08-01

This paper uses a novel discrete-event controller (DEC) for the coordination of cooperating heterogeneous wireless sensor networks (WSNs) containing both unattended ground sensors (UGSs) and mobile sensor robots. The DEC sequences the most suitable tasks for each agent and assigns sensor resources according to the current perception of the environment. A matrix formulation makes this DEC particularly useful for WSN, where missions change and sensor agents may be added or may fail. WSN have peculiarities that complicate their supervisory control. Therefore, this paper introduces several new tools for DEC design and operation, including methods for generating the required supervisory matrices based on mission planning, methods for modifying the matrices in the event of failed nodes, or nodes entering the network, and a novel dynamic priority assignment weighting approach for selecting the most appropriate and useful sensors for a given mission task. The resulting DEC represents a complete dynamical description of the WSN system, which allows a fast programming of deployable WSN, a computer simulation analysis, and an efficient implementation. The DEC is actually implemented on an experimental wireless-sensor-network prototyping system. Both simulation and experimental results are presented to show the effectiveness and versatility of the developed control architecture.

Sensing network for electromagnetic fields generated by seismic activities

NASA Astrophysics Data System (ADS)

Gershenzon, Naum I.; Bambakidis, Gust; Ternovskiy, Igor V.

2014-06-01

The sensors network is becoming prolific and play now increasingly more important role in acquiring and processing information. Cyber-Physical Systems are focusing on investigation of integrated systems that includes sensing, networking, and computations. The physics of the seismic measurement and electromagnetic field measurement requires special consideration how to design electromagnetic field measurement networks for both research and detection earthquakes and explosions along with the seismic measurement networks. In addition, the electromagnetic sensor network itself could be designed and deployed, as a research tool with great deal of flexibility, the placement of the measuring nodes must be design based on systematic analysis of the seismic-electromagnetic interaction. In this article, we review the observations of the co-seismic electromagnetic field generated by earthquakes and man-made sources such as vibrations and explosions. The theoretical investigation allows the distribution of sensor nodes to be optimized and could be used to support existing geological networks. The placement of sensor nodes have to be determined based on physics of electromagnetic field distribution above the ground level. The results of theoretical investigations of seismo-electromagnetic phenomena are considered in Section I. First, we compare the relative contribution of various types of mechano-electromagnetic mechanisms and then analyze in detail the calculation of electromagnetic fields generated by piezomagnetic and electrokinetic effects.

Optimizing placements of ground-based snow sensors for areal snow cover estimation using a machine-learning algorithm and melt-season snow-LiDAR data

NASA Astrophysics Data System (ADS)

Oroza, C.; Zheng, Z.; Glaser, S. D.; Bales, R. C.; Conklin, M. H.

2016-12-01

We present a structured, analytical approach to optimize ground-sensor placements based on time-series remotely sensed (LiDAR) data and machine-learning algorithms. We focused on catchments within the Merced and Tuolumne river basins, covered by the JPL Airborne Snow Observatory LiDAR program. First, we used a Gaussian mixture model to identify representative sensor locations in the space of independent variables for each catchment. Multiple independent variables that govern the distribution of snow depth were used, including elevation, slope, and aspect. Second, we used a Gaussian process to estimate the areal distribution of snow depth from the initial set of measurements. This is a covariance-based model that also estimates the areal distribution of model uncertainty based on the independent variable weights and autocorrelation. The uncertainty raster was used to strategically add sensors to minimize model uncertainty. We assessed the temporal accuracy of the method using LiDAR-derived snow-depth rasters collected in water-year 2014. In each area, optimal sensor placements were determined using the first available snow raster for the year. The accuracy in the remaining LiDAR surveys was compared to 100 configurations of sensors selected at random. We found the accuracy of the model from the proposed placements to be higher and more consistent in each remaining survey than the average random configuration. We found that a relatively small number of sensors can be used to accurately reproduce the spatial patterns of snow depth across the basins, when placed using spatial snow data. Our approach also simplifies sensor placement. At present, field surveys are required to identify representative locations for such networks, a process that is labor intensive and provides limited guarantees on the networks' representation of catchment independent variables.

Enhanced chemical weapon warning via sensor fusion

NASA Astrophysics Data System (ADS)

Flaherty, Michael; Pritchett, Daniel; Cothren, Brian; Schwaiger, James

2011-05-01

Torch Technologies Inc., is actively involved in chemical sensor networking and data fusion via multi-year efforts with Dugway Proving Ground (DPG) and the Defense Threat Reduction Agency (DTRA). The objective of these efforts is to develop innovative concepts and advanced algorithms that enhance our national Chemical Warfare (CW) test and warning capabilities via the fusion of traditional and non-traditional CW sensor data. Under Phase I, II, and III Small Business Innovative Research (SBIR) contracts with DPG, Torch developed the Advanced Chemical Release Evaluation System (ACRES) software to support non real-time CW sensor data fusion. Under Phase I and II SBIRs with DTRA in conjunction with the Edgewood Chemical Biological Center (ECBC), Torch is using the DPG ACRES CW sensor data fuser as a framework from which to develop the Cloud state Estimation in a Networked Sensor Environment (CENSE) data fusion system. Torch is currently developing CENSE to implement and test innovative real-time sensor network based data fusion concepts using CW and non-CW ancillary sensor data to improve CW warning and detection in tactical scenarios.

Volcano Monitoring: A Case Study in Pervasive Computing

NASA Astrophysics Data System (ADS)

Peterson, Nina; Anusuya-Rangappa, Lohith; Shirazi, Behrooz A.; Song, Wenzhan; Huang, Renjie; Tran, Daniel; Chien, Steve; Lahusen, Rick

Recent advances in wireless sensor network technology have provided robust and reliable solutions for sophisticated pervasive computing applications such as inhospitable terrain environmental monitoring. We present a case study for developing a real-time pervasive computing system, called OASIS for optimized autonomous space in situ sensor-web, which combines ground assets (a sensor network) and space assets (NASA’s earth observing (EO-1) satellite) to monitor volcanic activities at Mount St. Helens. OASIS’s primary goals are: to integrate complementary space and in situ ground sensors into an interactive and autonomous sensorweb, to optimize power and communication resource management of the sensorweb and to provide mechanisms for seamless and scalable fusion of future space and in situ components. The OASIS in situ ground sensor network development addresses issues related to power management, bandwidth management, quality of service management, topology and routing management, and test-bed design. The space segment development consists of EO-1 architectural enhancements, feedback of EO-1 data into the in situ component, command and control integration, data ingestion and dissemination and field demonstrations.

MicroSensors Systems: detection of a dismounted threat

NASA Astrophysics Data System (ADS)

Davis, Bill; Berglund, Victor; Falkofske, Dwight; Krantz, Brian

2005-05-01

The Micro Sensor System (MSS) is a layered sensor network with the goal of detecting dismounted threats approaching high value assets. A low power unattended ground sensor network is dependant on a network protocol for efficiency in order to minimize data transmissions after network establishment. The reduction of network 'chattiness' is a primary driver for minimizing power consumption and is a factor in establishing a low probability of detection and interception. The MSS has developed a unique protocol to meet these challenges. Unattended ground sensor systems are most likely dependant on batteries for power which due to size determines the ability of the sensor to be concealed after placement. To minimize power requirements, overcome size limitations, and maintain a low system cost the MSS utilizes advanced manufacturing processes know as Fluidic Self-Assembly and Chip Scale Packaging. The type of sensing element and the ability to sense various phenomenologies (particularly magnetic) at ranges greater than a few meters limits the effectiveness of a system. The MicroSensor System will overcome these limitations by deploying large numbers of low cost sensors, which is made possible by the advanced manufacturing process used in production of the sensors. The MSS program will provide unprecedented levels of real-time battlefield information which greatly enhances combat situational awareness when integrated with the existing Command, Control, Communications, Computers, Intelligence, Surveillance and Reconnaissance (C4ISR) infrastructure. This system will provide an important boost to realizing the information dominant, network-centric objective of Joint Vision 2020.

Kalman Filters in Geotechnical Monitoring of Ground Subsidence Using Data from MEMS Sensors

PubMed Central

Li, Cheng; Azzam, Rafig; Fernández-Steeger, Tomás M.

2016-01-01

The fast development of wireless sensor networks and MEMS make it possible to set up today real-time wireless geotechnical monitoring. To handle interferences and noises from the output data, Kalman filter can be selected as a method to achieve a more realistic estimate of the observations. In this paper, a one-day wireless measurement using accelerometers and inclinometers was deployed on top of a tunnel section under construction in order to monitor ground subsidence. The normal vectors of the sensors were firstly obtained with the help of rotation matrices, and then be projected to the plane of longitudinal section, by which the dip angles over time would be obtained via a trigonometric function. Finally, a centralized Kalman filter was applied to estimate the tilt angles of the sensor nodes based on the data from the embedded accelerometer and the inclinometer. Comparing the results from two sensor nodes deployed away and on the track respectively, the passing of the tunnel boring machine can be identified from unusual performances. Using this method, the ground settlement due to excavation can be measured and a real-time monitoring of ground subsidence can be realized. PMID:27447630

Sense, decide, act, communicate (SDAC): next generation of smart sensor systems

NASA Astrophysics Data System (ADS)

Berry, Nina; Davis, Jesse; Ko, Teresa H.; Kyker, Ron; Pate, Ron; Stark, Doug; Stinnett, Regan; Baker, James; Cushner, Adam; Van Dyke, Colin; Kyckelhahn, Brian

2004-09-01

The recent war on terrorism and increased urban warfare has been a major catalysis for increased interest in the development of disposable unattended wireless ground sensors. While the application of these sensors to hostile domains has been generally governed by specific tasks, this research explores a unique paradigm capitalizing on the fundamental functionality related to sensor systems. This functionality includes a sensors ability to Sense - multi-modal sensing of environmental events, Decide - smart analysis of sensor data, Act - response to environmental events, and Communication - internal to system and external to humans (SDAC). The main concept behind SDAC sensor systems is to integrate the hardware, software, and networking to generate 'knowledge and not just data'. This research explores the usage of wireless SDAC units to collectively make up a sensor system capable of persistent, adaptive, and autonomous behavior. These systems are base on the evaluation of scenarios and existing systems covering various domains. This paper presents a promising view of sensor network characteristics, which will eventually yield smart (intelligent collectives) network arrays of SDAC sensing units generally applicable to multiple related domains. This paper will also discuss and evaluate the demonstration system developed to test the concepts related to SDAC systems.

A New Design of Seismic Stations Deployed in South Tyrol

NASA Astrophysics Data System (ADS)

Melichar, P.; Horn, N.

2007-05-01

When designing the seismic network in South Tyrol, the seismic service of Austria and the Civil defense in South Tyrol combined more that 10 years experience in running seismic networks and private communication systems. In recent years the high data return rate of > 99% and network uptime of > 99.% is achieved by the combination of high quality station design and equipment, and the use of the Antelope data acquisition and processing software which comes with suite of network monitoring & alerting tools including Nagios, etc. The new Data Center is located in city of Bolzano and is connected to the other Data Centers in Austria, Switzerland, and Italy for data back up purposes. Each Data Center uses also redundant communication system if the primary system fails. When designing the South Tyrol network, new improvements were made in seismometer installations, grounding, lighting protection and data communications in order to improve quality of data recorded as well as network up-time, and data return. The new 12 stations are equipped with 6 Channels Q330+PB14f connected to STS2 + EpiSensor sensor. One of the key achievements was made in the grounding concept for the whole seismic station - and aluminum boxes were introduced which delivered Faraday cage isolation. Lightning protection devices are used for the equipment inside the aluminum housing where seismometer and data logger are housed. For the seismometer cables a special shielding was introduced. The broadband seismometer and strong-motion sensor are placed on a thick glass plate and therefore isolated from the ground. The precise seismometer orientation was done by a special groove on the glass plate and in case of a strong earthquake; the seismometer is tide up to the base plate. Temperature stability was achieved by styrofoam sheets inside the seismometer aluminum protection box.

A fiber Bragg grating acceleration sensor for ground surveillance

NASA Astrophysics Data System (ADS)

Jiang, Shaodong; Zhang, Faxiang; Lv, Jingsheng; Ni, Jiasheng; Wang, Chang

2017-10-01

Ground surveillance system is a kind of intelligent monitoring equipment for detecting and tracking the ground target. This paper presents a fiber Bragg grating (FBG) acceleration sensor for ground surveillance, which has the characteristics of no power supply, anti-electromagnetic interference, easy large-scale networking, and small size. Which make it able to achieve the advantage of the ground surveillance system while avoiding the shortcoming of the electric sensing. The sensor has a double cantilever beam structure with a sensitivity of 1000 pm/g. Field experiment has been carried out on a flood beach to examine the sensor performance. The result shows that the detection distance on the walking of personnel reaches 70m, and the detection distance on the ordinary motor vehicle reaches 200m. The performance of the FBG sensor can satisfy the actual needs of the ground surveillance system.

Flash Detection Efficiencies of Long Range Lightning Detection Networks During GRIP

NASA Technical Reports Server (NTRS)

Mach, Douglas M.; Bateman, Monte G.; Blakeslee, Richard J.

2012-01-01

We flew our Lightning Instrument Package (LIP) on the NASA Global Hawk as a part of the Genesis and Rapid Intensification Processes (GRIP) field program. The GRIP program was a NASA Earth science field experiment during the months of August and September, 2010. During the program, the LIP detected lighting from 48 of the 213 of the storms overflown by the Global Hawk. The time and location of tagged LIP flashes can be used as a "ground truth" dataset for checking the detection efficiency of the various long or extended range ground-based lightning detection systems available during the GRIP program. The systems analyzed included Vaisala Long Range (LR), Vaisala GLD360, the World Wide Lightning Location Network (WWLLN), and the Earth Networks Total Lightning Network (ENTLN). The long term goal of our research is to help understand the advantages and limitations of these systems so that we can utilize them for both proxy data applications and cross sensor validation of the GOES-R Geostationary Lightning Mapper (GLM) sensor when it is launched in the 2015 timeframe.

Evaluating the Capability of High-Altitude Infrasound Platforms to Cover Gaps in Existing Networks.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bowman, Daniel

A variety of Earth surface and atmospheric sources generate low frequency sound waves that can travel great distances. Despite a rich history of ground-based sensor studies, very few experiments have investigated the prospects of free floating microphone arrays at high altitudes. However, recent initiatives have shown that such networks have very low background noise and may sample an acoustic wave field that is fundamentally different than that at the Earth's surface. The experiments have been limited to at most two stations at altitude, limiting their utility in acoustic event detection and localization. We describe the deployment of five drifting microphonemore » stations at altitudes between 21 and 24 km above sea level. The stations detected one of two regional ground-based explosions as well as the ocean microbarom while traveling almost 500 km across the American Southwest. The explosion signal consisted of multiple arrivals; signal amplitudes did not correlate with sensor elevation or source range. A sparse network method that employed curved wave front corrections was able to determine the backazimuth from the free flying network to the acoustic source. Episodic broad band signals similar to those seen on previous flights in the same region were noted as well, but their source remains unclear. Background noise levels were commensurate with those on infrasound stations in the International Monitoring System (IMS) below 2 seconds, but sensor self noise appears to dominate at higher frequencies.« less

Acoustic event location and background noise characterization on a free flying infrasound sensor network in the stratosphere

NASA Astrophysics Data System (ADS)

Bowman, Daniel C.; Albert, Sarah A.

2018-06-01

A variety of Earth surface and atmospheric sources generate low-frequency sound waves that can travel great distances. Despite a rich history of ground-based sensor studies, very few experiments have investigated the prospects of free floating microphone arrays at high altitudes. However, recent initiatives have shown that such networks have very low background noise and may sample an acoustic wave field that is fundamentally different than that at Earth's surface. The experiments have been limited to at most two stations at altitude, making acoustic event detection and localization difficult. We describe the deployment of four drifting microphone stations at altitudes between 21 and 24 km above sea level. The stations detected one of two regional ground-based chemical explosions as well as the ocean microbarom while travelling almost 500 km across the American Southwest. The explosion signal consisted of multiple arrivals; signal amplitudes did not correlate with sensor elevation or source range. The waveforms and propagation patterns suggest interactions with gravity waves at 35-45 km altitude. A sparse network method that employed curved wave front corrections was able to determine the backazimuth from the free flying network to the acoustic source. Episodic signals similar to those seen on previous flights in the same region were noted, but their source remains unclear. Background noise levels were commensurate with those on infrasound stations in the International Monitoring System below 2 s.

Acoustic Event Location and Background Noise Characterization on a Free Flying Infrasound Sensor Network in the Stratosphere

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bowman, Daniel C.; Albert, Sarah A.

We present that a variety of Earth surface and atmospheric sources generate low frequency sound waves that can travel great distances. Despite a rich history of ground-based sensor studies, very few experiments have investigated the prospects of free floating microphone arrays at high altitudes. However, recent initiatives have shown that such networks have very low background noise and may sample an acoustic wave field that is fundamentally different than that at Earth’s surface. The experiments have been limited to at most two stations at altitude, making acoustic event detection and localization difficult. We describe the deployment of four drifting microphonemore » stations at altitudes between 21 and 24 km above sea level. The stations detected one of two regional ground-based chemical explosions as well as the ocean microbarom while traveling almost 500 km across the American Southwest. The explosion signal consisted of multiple arrivals; signal amplitudes did not correlate with sensor elevation or source range. The waveforms and propagation patterns suggest interactions with gravity waves in the 35-45 km altitude. A sparse network method that employed curved wave front corrections was able to determine the backazimuth from the free flying network to the acoustic source. Episodic signals similar to those seen on previous flights in the same region were noted, but their source remains unclear. Lastly, background noise levels were commensurate with those on infrasound stations in the International Monitoring System below 2 seconds.« less

Acoustic Event Location and Background Noise Characterization on a Free Flying Infrasound Sensor Network in the Stratosphere

DOE PAGES

Bowman, Daniel C.; Albert, Sarah A.

2018-02-22

We present that a variety of Earth surface and atmospheric sources generate low frequency sound waves that can travel great distances. Despite a rich history of ground-based sensor studies, very few experiments have investigated the prospects of free floating microphone arrays at high altitudes. However, recent initiatives have shown that such networks have very low background noise and may sample an acoustic wave field that is fundamentally different than that at Earth’s surface. The experiments have been limited to at most two stations at altitude, making acoustic event detection and localization difficult. We describe the deployment of four drifting microphonemore » stations at altitudes between 21 and 24 km above sea level. The stations detected one of two regional ground-based chemical explosions as well as the ocean microbarom while traveling almost 500 km across the American Southwest. The explosion signal consisted of multiple arrivals; signal amplitudes did not correlate with sensor elevation or source range. The waveforms and propagation patterns suggest interactions with gravity waves in the 35-45 km altitude. A sparse network method that employed curved wave front corrections was able to determine the backazimuth from the free flying network to the acoustic source. Episodic signals similar to those seen on previous flights in the same region were noted, but their source remains unclear. Lastly, background noise levels were commensurate with those on infrasound stations in the International Monitoring System below 2 seconds.« less

Monitoring Animal Behaviour and Environmental Interactions Using Wireless Sensor Networks, GPS Collars and Satellite Remote Sensing

PubMed Central

Handcock, Rebecca N.; Swain, Dave L.; Bishop-Hurley, Greg J.; Patison, Kym P.; Wark, Tim; Valencia, Philip; Corke, Peter; O'Neill, Christopher J.

2009-01-01

Remote monitoring of animal behaviour in the environment can assist in managing both the animal and its environmental impact. GPS collars which record animal locations with high temporal frequency allow researchers to monitor both animal behaviour and interactions with the environment. These ground-based sensors can be combined with remotely-sensed satellite images to understand animal-landscape interactions. The key to combining these technologies is communication methods such as wireless sensor networks (WSNs). We explore this concept using a case-study from an extensive cattle enterprise in northern Australia and demonstrate the potential for combining GPS collars and satellite images in a WSN to monitor behavioural preferences and social behaviour of cattle. PMID:22412327

Multisensor interoperability for persistent surveillance and FOB protection with multiple technologies during the TNT exercise at Camp Roberts, California

NASA Astrophysics Data System (ADS)

Murarka, Naveen; Chambers, Jon

2012-06-01

Multiple sensors, providing actionable intelligence to the war fighter, often have difficulty interoperating with each other. Northrop Grumman (NG) is dedicated to solving these problems and providing complete solutions for persistent surveillance. In August, 2011, NG was invited to participate in the Tactical Network Topology (TNT) Capabilities Based Experimentation at Camp Roberts, CA to demonstrate integrated system capabilities providing Forward Operating Base (FOB) protection. This experiment was an opportunity to leverage previous efforts from NG's Rotorcraft Avionics Innovation Laboratory (RAIL) to integrate five prime systems with widely different capabilities. The five systems included a Hostile Fire and Missile Warning Sensor System, SCORPION II Unattended Ground Sensor system, Smart Integrated Vehicle Area Network (SiVAN), STARLite Synthetic Aperture Radar (SAR)/Ground Moving Target Indications (GMTI) radar system, and a vehicle with Target Location Module (TLM) and Laser Designation Module (LDM). These systems were integrated with each other and a Tactical Operations Center (TOC) equipped with RaptorX and Falconview providing a Common Operational Picture (COP) via Cursor on Target (CoT) messages. This paper will discuss this exercise, and the lessons learned, by integrating these five prime systems for persistent surveillance and FOB protection.

Multi-Sensor Aerosol Products Sampling System

NASA Technical Reports Server (NTRS)

Petrenko, M.; Ichoku, C.; Leptoukh, G.

2011-01-01

Global and local properties of atmospheric aerosols have been extensively observed and measured using both spaceborne and ground-based instruments, especially during the last decade. Unique properties retrieved by the different instruments contribute to an unprecedented availability of the most complete set of complimentary aerosol measurements ever acquired. However, some of these measurements remain underutilized, largely due to the complexities involved in analyzing them synergistically. To characterize the inconsistencies and bridge the gap that exists between the sensors, we have established a Multi-sensor Aerosol Products Sampling System (MAPSS), which consistently samples and generates the spatial statistics (mean, standard deviation, direction and rate of spatial variation, and spatial correlation coefficient) of aerosol products from multiple spacebome sensors, including MODIS (on Terra and Aqua), MISR, OMI, POLDER, CALIOP, and SeaWiFS. Samples of satellite aerosol products are extracted over Aerosol Robotic Network (AERONET) locations as well as over other locations of interest such as those with available ground-based aerosol observations. In this way, MAPSS enables a direct cross-characterization and data integration between Level-2 aerosol observations from multiple sensors. In addition, the available well-characterized co-located ground-based data provides the basis for the integrated validation of these products. This paper explains the sampling methodology and concepts used in MAPSS, and demonstrates specific examples of using MAPSS for an integrated analysis of multiple aerosol products.

Exploring the "what if?" in geology through a RESTful open-source framework for cloud-based simulation and analysis

NASA Astrophysics Data System (ADS)

Klump, Jens; Robertson, Jess

2016-04-01

The spatial and temporal extent of geological phenomena makes experiments in geology difficult to conduct, if not entirely impossible and collection of data is laborious and expensive - so expensive that most of the time we cannot test a hypothesis. The aim, in many cases, is to gather enough data to build a predictive geological model. Even in a mine, where data are abundant, a model remains incomplete because the information at the level of a blasting block is two orders of magnitude larger than the sample from a drill core, and we have to take measurement errors into account. So, what confidence can we have in a model based on sparse data, uncertainties and measurement error? Our framework consist of two layers: (a) a ground-truth layer that contains geological models, which can be statistically based on historical operations data, and (b) a network of RESTful synthetic sensor microservices which can query the ground-truth for underlying properties and produce a simulated measurement to a control layer, which could be a database or LIMS, a machine learner or a companies' existing data infrastructure. Ground truth data are generated by an implicit geological model which serves as a host for nested models of geological processes as smaller scales. Our two layers are implemented using Flask and Gunicorn, which are open source Python web application framework and server, the PyData stack (numpy, scipy etc) and Rabbit MQ (an open-source queuing library). Sensor data is encoded using a JSON-LD version of the SensorML and Observations and Measurements standards. Containerisation of the synthetic sensors using Docker and CoreOS allows rapid and scalable deployment of large numbers of sensors, as well as sensor discovery to form a self-organized dynamic network of sensors. Real-time simulation of data sources can be used to investigate crucial questions such as the potential information gain from future sensing capabilities, or from new sampling strategies, or the combination of both, and it enables us to test many "what if?" questions, both in geology and in data engineering. What would we be able to see if we could obtain data at higher resolution? How would real-time data analysis change sampling strategies? Does our data infrastructure handle many new real-time data streams? What feature engineering can be deducted for machine learning approaches? By providing a 'data sandbox' able to scale to realistic geological scenarios we hope to start answering some of these questions. Faults happen in real world networks. Future work will investigate the effect of failure on dynamic sensor networks and the impact on the predictive capability of machine learning algorithms.

Building an Intelligent Water Information System - American River Prototype

NASA Astrophysics Data System (ADS)

Glaser, S. D.; Bales, R. C.; Conklin, M. H.

2013-12-01

With better management, California's existing water supplies could go further to meeting the needs of the state's urban and agricultural uses. For example, California's water reservoirs are currently controlled and regulated using forecasts based upon more than 75 years of historical data. In the face of global climate change, these forecasts are becoming increasingly inadequate to precisely manage water resources. We propose implementing Leveraging the newest frontiers of information technology, we are developing a basin-scale real-time intelligent water infrastructure system that enables more information-intensive decision support. The complete system is made up of four key components. First, a strategically deployed ground-observation system will complement satellite measurements and provide continuous and accurate estimates of snowpack, soil moisture, vegetation state and energy balance across watersheds. Using our recently developed but mature technologies, we deliver measurements of hydrologic variables over a multi- tiered network of wireless sensor arrays, with a granularity of time and space previously unheard of. Second, satellite and aircraft remote sensing provide the only practical means of spatially continuous basin-wide measurement and monitoring of snow properties, vegetation characteristics and other watershed conditions. The ground-based system is designed to blend with remote sensing data on Sierra Nevada snow properties, and provide value-added products of unprecedented spatial detail and accuracy that are useable on a watershed level. Third, together the satellite and ground-based data make possible the updating of forecast tools, and routine use of physically based hydrologic models. The decision-support framework will provide tools to extract and visualize information of interest from the measured and modeled data, to assess uncertainties, and to optimize operations. Fourth, the advanced cyber infrastructure blends and transforms the numbers recorded by sensors into information in the form that is useful for decision-making. In a sense it 'monetizes' the data. It is the cyber infrastructure that links measurements, data processing, models and users. System software must provide flexibility for multiple types of access from user queries to automated and direct links with analysis tools and decision-support systems. We are currently installing a basin-scale ground-based sensor network focusing on measurements of snowpack, solar radiation, temperature, rH and soil moisture across the American River basin. Although this is a research network, it also provides core elements of a full ground-based operational system.

Wireless canopy sensing network systems for automated control of irrigation and water use efficiency

USDA-ARS?s Scientific Manuscript database

Ground-based instrumentation for plant canopy sensing (infrared thermometry and spectral reflectance sensors) has been used extensively in agriculture to monitor crop status. Typically, measurements are accomplished with handheld or vehicle mounted instrumentation during limited periods of a day, an...

Multidirectional seismo-acoustic wavefield of strombolian explosions at Yasur, Vanuatu using a broadband seismo-acoustic network, infrasound arrays, and infrasonic sensors on tethered balloons

NASA Astrophysics Data System (ADS)

Matoza, R. S.; Jolly, A. D.; Fee, D.; Johnson, R.; Kilgour, G.; Christenson, B. W.; Garaebiti, E.; Iezzi, A. M.; Austin, A.; Kennedy, B.; Fitzgerald, R.; Key, N.

2016-12-01

Seismo-acoustic wavefields at volcanoes contain rich information on shallow magma transport and subaerial eruption processes. Acoustic wavefields from eruptions are predicted to be directional, but sampling this wavefield directivity is challenging because infrasound sensors are usually deployed on the ground surface. We attempt to overcome this observational limitation using a novel deployment of infrasound sensors on tethered balloons in tandem with a suite of dense ground-based seismo-acoustic, geochemical, and eruption imaging instrumentation. We present preliminary results from a field experiment at Yasur Volcano, Vanuatu from July 26th to August 4th 2016. Our observations include data from a temporary network of 11 broadband seismometers, 6 single infrasonic microphones, 7 small-aperture 3-element infrasound arrays, 2 infrasound sensor packages on tethered balloons, an FTIR, a FLIR, 2 scanning Flyspecs, and various visual imaging data. An introduction to the dataset and preliminary analysis of the 3D seismo-acoustic wavefield and source process will be presented. This unprecedented dataset should provide a unique window into processes operating in the shallow magma plumbing system and their relation to subaerial eruption dynamics.

Complexity, Robustness, and Multistability in Network Systems with Switching Topologies: A Hierarchical Hybrid Control Approach

DTIC Science & Technology

2015-05-22

sensor networks for managing power levels of wireless networks ; air and ground transportation systems for air traffic control and payload transport and... network systems, large-scale systems, adaptive control, discontinuous systems 16. SECURITY CLASSIFICATION OF: 17. LIMITATION OF ABSTRACT 18. NUMBER OF...cover a broad spectrum of ap- plications including cooperative control of unmanned air vehicles, autonomous underwater vehicles, distributed sensor

Autonomous Sensors for Large Scale Data Collection

NASA Astrophysics Data System (ADS)

Noto, J.; Kerr, R.; Riccobono, J.; Kapali, S.; Migliozzi, M. A.; Goenka, C.

2017-12-01

Presented here is a novel implementation of a "Doppler imager" which remotely measures winds and temperatures of the neutral background atmosphere at ionospheric altitudes of 87-300Km and possibly above. Incorporating both recent optical manufacturing developments, modern network awareness and the application of machine learning techniques for intelligent self-monitoring and data classification. This system achieves cost savings in manufacturing, deployment and lifetime operating costs. Deployed in both ground and space-based modalities, this cost-disruptive technology will allow computer models of, ionospheric variability and other space weather models to operate with higher precision. Other sensors can be folded into the data collection and analysis architecture easily creating autonomous virtual observatories. A prototype version of this sensor has recently been deployed in Trivandrum India for the Indian Government. This Doppler imager is capable of operation, even within the restricted CubeSat environment. The CubeSat bus offers a very challenging environment, even for small instruments. The lack of SWaP and the challenging thermal environment demand development of a new generation of instruments; the Doppler imager presented is well suited to this environment. Concurrent with this CubeSat development is the development and construction of ground based arrays of inexpensive sensors using the proposed technology. This instrument could be flown inexpensively on one or more CubeSats to provide valuable data to space weather forecasters and ionospheric scientists. Arrays of magnetometers have been deployed for the last 20 years [Alabi, 2005]. Other examples of ground based arrays include an array of white-light all sky imagers (THEMIS) deployed across Canada [Donovan et al., 2006], oceans sensors on buoys [McPhaden et al., 2010], and arrays of seismic sensors [Schweitzer et al., 2002]. A comparable array of Doppler imagers can be constructed and deployed on the ground, to compliment the CubeSat data.

Community Seismic Network (CSN)

NASA Astrophysics Data System (ADS)

Clayton, R. W.; Heaton, T. H.; Kohler, M. D.; Cheng, M.; Guy, R.; Chandy, M.; Krause, A.; Bunn, J.; Olson, M.; Faulkner, M.

2011-12-01

The CSN is a network of low-cost accelerometers deployed in the Pasadena, CA region. It is a prototype network with the goal of demonstrating the importance of dense measurements in determining the rapid lateral variations in ground motion due to earthquakes. The main product of the CSN is a map of peak ground produced within seconds of significant local earthquakes that can be used as a proxy for damage. Examples of this are shown using data from a temporary network in Long Beach, CA. Dense measurements in buildings are also being used to determine the state of health of structures. In addition to fixed sensors, portable sensors such as smart phones are also used in the network. The CSN has necessitated several changes in the standard design of a seismic network. The first is that the data collection and processing is done in the "cloud" (Google cloud in this case) for robustness and the ability to handle large impulsive loads (earthquakes). Second, the database is highly de-normalized (i.e. station locations are part of waveform and event-detection meta data) because of the mobile nature of the sensors. Third, since the sensors are hosted and/or owned by individuals, the privacy of the data is very important. The location of fixed sensors is displayed on maps as sensor counts in block-wide cells, and mobile sensors are shown in a similar way, with the additional requirement to inhibit tracking that at least two must be present in a particular cell before any are shown. The raw waveform data are only released to users outside of the network after a felt earthquake.

The GEOS-5 Neural Network Retrieval for AOD

NASA Astrophysics Data System (ADS)

Castellanos, P.; da Silva, A. M., Jr.

2017-12-01

One of the difficulties in data assimilation is the need for multi-sensor data merging that can account for temporal and spatial biases between satellite sensors. In the Goddard Earth Observing System Model Version 5 (GEOS-5) aerosol data assimilation system, a neural network retrieval (NNR) is used as a mapping between satellite observed top of the atmosphere (TOA) reflectance and AOD, which is the target variable that is assimilated in the model. By training observations of TOA reflectance from multiple sensors to map to a common AOD dataset (in this case AOD observed by the ground based Aerosol Robotic Network, AERONET), we are able to create a global, homogenous, satellite data record of AOD from MODIS observations on board the Terra and Aqua satellites. In this talk, I will present the implementation of and recent updates to the GEOS-5 NNR for MODIS collection 6 data.

The GEOS-5 Neural Network Retrieval (NNR) for AOD

NASA Technical Reports Server (NTRS)

Castellanos, Patricia; Da Silva, Arlindo

2017-01-01

One of the difficulties in data assimilation is the need for multi-sensor data merging that can account for temporal and spatial biases between satellite sensors. In the Goddard Earth Observing System Model Version 5 (GEOS-5) aerosol data assimilation system, a neural network retrieval (NNR) is used as a mapping between satellite observed top of the atmosphere (TOA) reflectance and AOD, which is the target variable that is assimilated in the model. By training observations of TOA reflectance from multiple sensors to map to a common AOD dataset (in this case AOD observed by the ground based Aerosol Robotic Network, AERONET), we are able to create a global, homogenous, satellite data record of AOD from MODIS observations on board the Terra and Aqua satellites. In this talk, I will present the implementation of and recent updates to the GEOS-5 NNR for MODIS collection 6 data.

netPICOmag: from Design to Network Implementation

NASA Astrophysics Data System (ADS)

Schofield, I.; Connors, M.; Russell, C.

2009-05-01

netPICOmag is the successful conclusion of a design effort involving networking based on Rabbit microcontrollers, PIC microcontrollers, and pulsed magnetometer sensors. GPS timing allows both timestamping of data and the precision counting of the number of pulses produced by the sensor heads in one second. Power over Ethernet, use of DHCP, and broadcast of UDP packets mean a very simple local installation, with one wire leading to a relatively small integrated sensor package which is vertically placed in the ground. Although we continue to make improvements, including through investigating new sensor types, we regard the design as mature and well tested. Here we focus on the need for yet denser magnetometer networks, technological applications which become practical using sensitive yet inexpensive magnetometers, and deployment methods for large numbers of sensors. With careful calibration, netPICOmags overlap with research grade magnetometers. Without it, they still sensitively detect magnetic variations and can be used for an education or outreach program. Due to their low cost, such an application allows many students to be directly involved in gathering data that can be very relevant to them personally when they witness auroras.

Nighttime Aerosol Optical Depth Measurements Using a Ground-based Lunar Photometer

NASA Technical Reports Server (NTRS)

Berkoff, Tim; Omar, Ali; Haggard, Charles; Pippin, Margaret; Tasaddaq, Aasam; Stone, Tom; Rodriguez, Jon; Slutsker, Ilya; Eck, Tom; Holben, Brent;

The HUMSAT System: a CubeSat-based Constellation for In-situ and Inexpensive Environmental Measurements

NASA Astrophysics Data System (ADS)

Tubío-Pardavila, R.; Vigil, S. A.; Puig-Suari, J.; Aguado Agelet, F.

2014-12-01

There is a requirement for low cost in-situ measurements of environmental parameters such as air quality, meteorological data, and water quality in remote areas. Currently available solutions for such measurements include remote sensing from satellite and aircraft platforms, and in-situ measurements from mobile and aircraft platforms. Fixed systems such as eddy covariance networks, tall towers, and the Total Carbon Column Observing Network (TCCON) are providing precision greenhouse gas measurements. Within this context, the HUMSAT system designed by the University of Vigo (Spain) will complement existing high-precision measurement systems with low cost in-situ ground based sensors in remote locations using a constellation of CubeSats as a communications relay. The HUMSAT system standardizes radio communications in between deployed sensors and the CubeSats of the constellation, which act as store and forward satellites to ground stations for uploading to the internet. Current ground stations have been established at the University of Vigo (Spain) and California Polytechnic State University (Cal Poly). Users of the system may deploy their own environmental sensors to meet local requirements. The sensors will be linked to a low-cost satellite data transceiver using a standard HUMSAT protocol. The transceiver is capable of receiving data from the HUMSAT constellation to remotely reconfigure sensors without the need of physically going to the sensor location. This transceiver uses a UHF channel around 437 MHz to exchange short data messages with the sensors. These data messages can contain up to 32 bytes of useful information and are transmitted at a speed around 300 bps. The protocol designed for this system handles the access to the channel by all these elements and guarantees a correct transmission of the information in such an scenario. The University of Vigo has launched the first satellite of the constellation, the HUMSAT-D CubeSat in November 2013 and has deployed sensors in Spain and Brazil. Sensors will be also deployed by Cal Poly in the near future. In the following months, the SERPENS CubeSAT Mission, a joint project of the University of Brasilia and the University of Vigo will launch the second CubeSat of the constellation.

Dynamic Agent Classification and Tracking Using an Ad Hoc Mobile Acoustic Sensor Network

NASA Astrophysics Data System (ADS)

Friedlander, David; Griffin, Christopher; Jacobson, Noah; Phoha, Shashi; Brooks, Richard R.

2003-12-01

Autonomous networks of sensor platforms can be designed to interact in dynamic and noisy environments to determine the occurrence of specified transient events that define the dynamic process of interest. For example, a sensor network may be used for battlefield surveillance with the purpose of detecting, identifying, and tracking enemy activity. When the number of nodes is large, human oversight and control of low-level operations is not feasible. Coordination and self-organization of multiple autonomous nodes is necessary to maintain connectivity and sensor coverage and to combine information for better understanding the dynamics of the environment. Resource conservation requires adaptive clustering in the vicinity of the event. This paper presents methods for dynamic distributed signal processing using an ad hoc mobile network of microsensors to detect, identify, and track targets in noisy environments. They seamlessly integrate data from fixed and mobile platforms and dynamically organize platforms into clusters to process local data along the trajectory of the targets. Local analysis of sensor data is used to determine a set of target attribute values and classify the target. Sensor data from a field test in the Marine base at Twentynine Palms, Calif, was analyzed using the techniques described in this paper. The results were compared to "ground truth" data obtained from GPS receivers on the vehicles.

Battlefield decision aid for acoustical ground sensors with interface to meteorological data sources

NASA Astrophysics Data System (ADS)

Wilson, D. Keith; Noble, John M.; VanAartsen, Bruce H.; Szeto, Gregory L.

2001-08-01

The performance of acoustical ground sensors depends heavily on the local atmospheric and terrain conditions. This paper describes a prototype physics-based decision aid, called the Acoustic Battlefield Aid (ABFA), for predicting these environ-mental effects. ABFA integrates advanced models for acoustic propagation, atmospheric structure, and array signal process-ing into a convenient graphical user interface. The propagation calculations are performed in the frequency domain on user-definable target spectra. The solution method involves a parabolic approximation to the wave equation combined with a ter-rain diffraction model. Sensor performance is characterized with Cramer-Rao lower bounds (CRLBs). The CRLB calcula-tions include randomization of signal energy and wavefront orientation resulting from atmospheric turbulence. Available performance characterizations include signal-to-noise ratio, probability of detection, direction-finding accuracy for isolated receiving arrays, and location-finding accuracy for networked receiving arrays. A suite of integrated tools allows users to create new target descriptions from standard digitized audio files and to design new sensor array layouts. These tools option-ally interface with the ARL Database/Automatic Target Recognition (ATR) Laboratory, providing access to an extensive library of target signatures. ABFA also includes a Java-based capability for network access of near real-time data from sur-face weather stations or forecasts from the Army's Integrated Meteorological System. As an example, the detection footprint of an acoustical sensor, as it evolves over a 13-hour period, is calculated.

Dynamic optimization of ISR sensors using a risk-based reward function applied to ground and space surveillance scenarios

NASA Astrophysics Data System (ADS)

DeSena, J. T.; Martin, S. R.; Clarke, J. C.; Dutrow, D. A.; Newman, A. J.

2012-06-01

As the number and diversity of sensing assets available for intelligence, surveillance and reconnaissance (ISR) operations continues to expand, the limited ability of human operators to effectively manage, control and exploit the ISR ensemble is exceeded, leading to reduced operational effectiveness. Automated support both in the processing of voluminous sensor data and sensor asset control can relieve the burden of human operators to support operation of larger ISR ensembles. In dynamic environments it is essential to react quickly to current information to avoid stale, sub-optimal plans. Our approach is to apply the principles of feedback control to ISR operations, "closing the loop" from the sensor collections through automated processing to ISR asset control. Previous work by the authors demonstrated non-myopic multiple platform trajectory control using a receding horizon controller in a closed feedback loop with a multiple hypothesis tracker applied to multi-target search and track simulation scenarios in the ground and space domains. This paper presents extensions in both size and scope of the previous work, demonstrating closed-loop control, involving both platform routing and sensor pointing, of a multisensor, multi-platform ISR ensemble tasked with providing situational awareness and performing search, track and classification of multiple moving ground targets in irregular warfare scenarios. The closed-loop ISR system is fullyrealized using distributed, asynchronous components that communicate over a network. The closed-loop ISR system has been exercised via a networked simulation test bed against a scenario in the Afghanistan theater implemented using high-fidelity terrain and imagery data. In addition, the system has been applied to space surveillance scenarios requiring tracking of space objects where current deliberative, manually intensive processes for managing sensor assets are insufficiently responsive. Simulation experiment results are presented. The algorithm to jointly optimize sensor schedules against search, track, and classify is based on recent work by Papageorgiou and Raykin on risk-based sensor management. It uses a risk-based objective function and attempts to minimize and balance the risks of misclassifying and losing track on an object. It supports the requirement to generate tasking for metric and feature data concurrently and synergistically, and account for both tracking accuracy and object characterization, jointly, in computing reward and cost for optimizing tasking decisions.

Optimal Design of Multitype Groundwater Monitoring Networks Using Easily Accessible Tools.

PubMed

Wöhling, Thomas; Geiges, Andreas; Nowak, Wolfgang

2016-11-01

Monitoring networks are expensive to establish and to maintain. In this paper, we extend an existing data-worth estimation method from the suite of PEST utilities with a global optimization method for optimal sensor placement (called optimal design) in groundwater monitoring networks. Design optimization can include multiple simultaneous sensor locations and multiple sensor types. Both location and sensor type are treated simultaneously as decision variables. Our method combines linear uncertainty quantification and a modified genetic algorithm for discrete multilocation, multitype search. The efficiency of the global optimization is enhanced by an archive of past samples and parallel computing. We demonstrate our methodology for a groundwater monitoring network at the Steinlach experimental site, south-western Germany, which has been established to monitor river-groundwater exchange processes. The target of optimization is the best possible exploration for minimum variance in predicting the mean travel time of the hyporheic exchange. Our results demonstrate that the information gain of monitoring network designs can be explored efficiently and with easily accessible tools prior to taking new field measurements or installing additional measurement points. The proposed methods proved to be efficient and can be applied for model-based optimal design of any type of monitoring network in approximately linear systems. Our key contributions are (1) the use of easy-to-implement tools for an otherwise complex task and (2) yet to consider data-worth interdependencies in simultaneous optimization of multiple sensor locations and sensor types. © 2016, National Ground Water Association.

Comparing distinct ground-based lightning location networks covering the Netherlands

NASA Astrophysics Data System (ADS)

de Vos, Lotte; Leijnse, Hidde; Schmeits, Maurice; Beekhuis, Hans; Poelman, Dieter; Evers, Läslo; Smets, Pieter

2015-04-01

Lightning can be detected using a ground-based sensor network. The Royal Netherlands Meteorological Institute (KNMI) monitors lightning activity in the Netherlands with the so-called FLITS-system; a network combining SAFIR-type sensors. This makes use of Very High Frequency (VHF) as well as Low Frequency (LF) sensors. KNMI has recently decided to replace FLITS by data from a sub-continental network operated by Météorage which makes use of LF sensors only (KNMI Lightning Detection Network, or KLDN). KLDN is compared to the FLITS system, as well as Met Office's long-range Arrival Time Difference (ATDnet), which measures Very Low Frequency (VLF). Special focus lies on the ability to detect Cloud to Ground (CG) and Cloud to Cloud (CC) lightning in the Netherlands. Relative detection efficiency of individual flashes and lightning activity in a more general sense are calculated over a period of almost 5 years. Additionally, the detection efficiency of each system is compared to a ground-truth that is constructed from flashes that are detected by both of the other datasets. Finally, infrasound data is used as a fourth lightning data source for several case studies. Relative performance is found to vary strongly with location and time. As expected, it is found that FLITS detects significantly more CC lightning (because of the strong aptitude of VHF antennas to detect CC), though KLDN and ATDnet detect more CG lightning. We analyze statistics computed over the entire 5-year period, where we look at CG as well as total lightning (CC and CG combined). Statistics that are considered are the Probability of Detection (POD) and the so-called Lightning Activity Detection (LAD). POD is defined as the percentage of reference flashes the system detects compared to the total detections in the reference. LAD is defined as the fraction of system recordings of one or more flashes in predefined area boxes over a certain time period given the fact that the reference detects at least one flash, compared to the total recordings in the reference dataset. The reference for these statistics is taken to be either another dataset, or a dataset consisting of flashes detected by two datasets. Extreme thunderstorm case evaluation shows that the weather alert criterion for severe thunderstorm is reached by FLITS when this is not the case in KLDN and ATD, suggesting the need for KNMI to modify that weather alert criterion when using KLDN.

A Study on the Performance of Low Cost MEMS Sensors in Strong Motion Studies

NASA Astrophysics Data System (ADS)

Tanırcan, Gulum; Alçık, Hakan; Kaya, Yavuz; Beyen, Kemal

2017-04-01

Recent advances in sensors have helped the growth of local networks. In recent years, many Micro Electro Mechanical System (MEMS)-based accelerometers have been successfully used in seismology and earthquake engineering projects. This is basically due to the increased precision obtained in these downsized instruments. Moreover, they are cheaper alternatives to force-balance type accelerometers. In Turkey, though MEMS-based accelerometers have been used in various individual applications such as magnitude and location determination of earthquakes, structural health monitoring, earthquake early warning systems, MEMS-based strong motion networks are not currently available in other populated areas of the country. Motivation of this study comes from the fact that, if MEMS sensors are qualified to record strong motion parameters of large earthquakes, a dense network can be formed in an affordable price at highly populated areas. The goals of this study are 1) to test the performance of MEMS sensors, which are available in the inventory of the Institute through shake table tests, and 2) to setup a small scale network for observing online data transfer speed to a trusted in-house routine. In order to evaluate the suitability of sensors in strong motion related studies, MEMS sensors and a reference sensor are tested under excitations of sweeping waves as well as scaled earthquake recordings. Amplitude response and correlation coefficients versus frequencies are compared. As for earthquake recordings, comparisons are carried out in terms of strong motion(SM) parameters (PGA, PGV, AI, CAV) and elastic response of structures (Sa). Furthermore, this paper also focuses on sensitivity and selectivity for sensor performances in time-frequency domain to compare different sensing characteristics and analyzes the basic strong motion parameters that influence the design majors. Results show that the cheapest MEMS sensors under investigation are able to record the mid-frequency dominant SM parameters PGV and CAV with high correlation. PGA and AI, the high frequency components of the ground motion, are underestimated. Such a difference, on the other hand, does not manifest itself on intensity estimations. PGV and CAV values from the reference and MEMS sensors converge to the same seismic intensity level. Hence a strong motion network with MEMS sensors could be a modest option to produce PGV-based damage impact of an urban area under large magnitude earthquake threats in the immediate vicinity.

DEVELOPMENT OF QUALITY ASSURANCE AND QUALITY CONTROL GUIDANCE FOR GROUND-BASED REMOTE SENSORS FOR USE IN REGULATORY MONITORING

EPA Science Inventory

The U.S. Environmental Protection Agency's (EPA) authority for enhanced monitoring activities is provided for in Title I, Section 182 of the Clean Air Act Amendment of 1990. or example, the Photochemical Assessment Monitoring Station (PAMS) network is one such program which requi...

The Rondonia Lightning Detection Network: Network Description, Science Objectives, Data Processing/Archival Methodology, and First Results

NASA Technical Reports Server (NTRS)

Blakelee, Richard

1999-01-01

A four station Advanced Lightning Direction Finder (ALDF) network was recently established in the state of Rondonia in western Brazil through a collaboration of U.S. and Brazilian participants from NASA, INPE, INMET, and various universities. The network utilizes ALDF IMPACT (Improved Accuracy from Combined Technology) sensors to provide cloud-to-ground lightning observations (i.e., stroke/flash locations, signal amplitude, and polarity) using both time-of-arrival and magnetic direction finding techniques. The observations are collected, processed and archived at a central site in Brasilia and at the NASA/Marshall Space Flight Center (MSFC) in Huntsville, Alabama. Initial, non-quality assured quick-look results are made available in near real-time over the internet. The network will remain deployed for several years to provide ground truth data for the Lightning Imaging Sensor (LIS) on the Tropical Rainfall Measurement Mission (TRMM) satellite which was launched in November 1997. The measurements will also be used to investigate the relationship between the electrical, microphysical and kinematic properties of tropical convection. In addition, the long-term observations from this network will contribute in establishing a regional lightning climatological data base, supplementing other data bases in Brazil that already exist or may soon be implemented. Analytic inversion algorithms developed at NASA/MSFC are now being applied to the Rondonian ALDF lightning observations to obtain site error corrections and improved location retrievals. The processing methodology and the initial results from an analysis of the first 6 months of network operations will be presented.

The Rondonia Lightning Detection Network: Network Description, Science Objectives, Data Processing/Archival Methodology, and First Results

NASA Technical Reports Server (NTRS)

Blakeslee, Rich; Bailey, Jeff; Koshak, Bill

1999-01-01

A four station Advanced Lightning Direction Finder (ALDF) network was recently established in the state of Rondonia in western Brazil through a collaboration of U.S. and Brazilian participants from NASA, INPE, INMET, and various universities. The network utilizes ALDF IMPACT (Improved Accuracy from Combined Technology) sensors to provide cloud-to-ground lightning observations (i.e., stroke/flash locations, signal amplitude, and polarity) using both time-of-arrival and magnetic direction finding techniques. The observations are collected, processed and archived at a central site in Brasilia and at the NASA/ Marshall Space Flight Center (MSFC) in Huntsville, Alabama. Initial, non-quality assured quick-look results are made available in near real-time over the internet. The network will remain deployed for several years to provide ground truth data for the Lightning Imaging Sensor (LIS) on the Tropical Rainfall Measuring Mission (TRMM) satellite which was launched in November 1997. The measurements will also be used to investigate the relationship between the electrical, microphysical and kinematic properties of tropical convection. In addition, the long-term observations from this network will contribute in establishing a regional lightning climatological data base, supplementing other data bases in Brazil that already exist or may soon be implemented. Analytic inversion algorithms developed at NASA/Marshall Space Flight Center (MSFC) are now being applied to the Rondonian ALDF lightning observations to obtain site error corrections and improved location retrievals. The processing methodology and the initial results from an analysis of the first 6 months of network operations will be presented.

Estimating Snow Water Equivalent over the American River in the Sierra Nevada Basin Using Wireless Sensor Networks

NASA Astrophysics Data System (ADS)

Welch, S. C.; Kerkez, B.; Glaser, S. D.; Bales, R. C.; Rice, R.

2011-12-01

We have designed a basin-scale (>2000 km2) instrument cluster, made up of 20 local-scale (1-km footprint) wireless sensor networks (WSNs), to measure patterns of snow depth and snow water equivalent (SWE) across the main snowmelt producing area within the American River basin. Each of the 20 WSNs has on the order of 25 wireless nodes, with over 10 nodes actively sensing snow depth, and thus snow accumulation and melt. When combined with existing snow density measurements and full-basin satellite snowcover data, these measurements are designed to provide dense ground-truth snow properties for research and real-time SWE for water management. The design of this large-scale network is based on rigorous testing of previous, smaller-scale studies, permitting for the development of methods to significantly, and efficiently scale up network operations. Recent advances in WSN technology have resulted in a modularized strategy that permits rapid future network deployment. To select network and sensor locations, various sensor placement approaches were compared, including random placement, placement of WSNs in locations that have captured the historical basin mean, as well as a placement algorithm leveraging the covariance structure of the SWE distribution. We show that that the optimal network locations do not exhibit a uniform grid, but rather follow strategic patterns based on physiographic terrain parameters. Uncertainty estimates are also provided to assess the confidence in the placement approach. To ensure near-optimal coverage of the full basin, we validated each placement approach with a multi-year record of SWE derived from reconstruction of historical satellite measurements.

Analysis of sensor network observations during some simulated landslide experiments

NASA Astrophysics Data System (ADS)

Scaioni, M.; Lu, P.; Feng, T.; Chen, W.; Wu, H.; Qiao, G.; Liu, C.; Tong, X.; Li, R.

2012-12-01

A multi-sensor network was tested during some experiments on a landslide simulation platform established at Tongji University (Shanghai, P.R. China). Here landslides were triggered by means of artificial rainfall (see Figure 1). The sensor network currently incorporates contact sensors and two imaging systems. This represent a novel solution, because the spatial sensor network incorporate either contact sensors and remote sensors (video-cameras). In future, these sensors will be installed on two real ground slopes in Sichuan province (South-West China), where Wenchuan earthquake occurred in 2008. This earthquake caused the immediate activation of several landslide, while other area became unstable and still are a menace for people and properties. The platform incorporates the reconstructed scale slope, sensor network, communication system, database and visualization system. Some landslide simulation experiments allowed ascertaining which sensors could be more suitable to be deployed in Wenchuan area. The poster will focus on the analysis of results coming from down scale simulations. Here the different steps of the landslide evolution can be followed on the basis of sensor observations. This include underground sensors to detect the water table level and the pressure in the ground, a set of accelerometers and two inclinometers. In the first part of the analysis the full data series are investigated to look for correlations and common patterns, as well as to link them to the physical processes. In the second, 4 subsets of sensors located in neighbor positions are analyzed. The analysis of low- and high-speed image sequences allowed to track a dense field of displacement on the slope surface. These outcomes have been compared to the ones obtained from accelerometers for cross-validation. Images were also used for the photogrammetric reconstruction of the slope topography during the experiment. Consequently, volume computation and mass movements could be evaluated on the basis of processed images.; Figure 1 - The landslide simulation platform at Tongji University at the end of an experiment. The picture shows the body of simulated landslide.

An In Depth Look at Lightning Trends in Hurricane Harvey using Satellite and Ground-Based Measurements

NASA Astrophysics Data System (ADS)

Ringhausen, J.

2017-12-01

This research combines satellite measurements of lightning in Hurricane Harvey with ground-based lightning measurements to get a better sense of the total lightning occurring in the hurricane, both intra-cloud (IC) and cloud-to-ground (CG), and how it relates to the intensification and weakening of the tropical system. Past studies have looked at lightning trends in hurricanes using the space based Lightning Imaging Sensor (LIS) or ground-based lightning detection networks. However, both of these methods have drawbacks. For instance, LIS was in low earth orbit, which limited lightning observations to 90 seconds for a particular point on the ground; hence, continuous lightning coverage of a hurricane was not possible. Ground-based networks can have a decreased detection efficiency, particularly for ICs, over oceans where hurricanes generally intensify. With the launch of the Geostationary Lightning Mapper (GLM) on the GOES-16 satellite, researchers can study total lightning continuously over the lifetime of a tropical cyclone. This study utilizes GLM to investigate total lightning activity in Hurricane Harvey temporally; this is augmented with spatial analysis relative to hurricane structure, similar to previous studies. Further, GLM and ground-based network data are combined using Bayesian techniques in a new manner to leverage the strengths of each detection method. This methodology 1) provides a more complete estimate of lightning activity and 2) enables the derivation of the IC:CG ratio (Z-ratio) throughout the time period of the study. In particular, details of the evolution of the Z-ratio in time and space are presented. In addition, lightning stroke spatiotemporal trends are compared to lightning flash trends. This research represents a new application of lightning data that can be used in future study of tropical cyclone intensification and weakening.

Lights Out Operations of a Space, Ground, Sensorweb

NASA Technical Reports Server (NTRS)

Chien, Steve; Tran, Daniel; Johnston, Mark; Davies, Ashley Gerard; Castano, Rebecca; Rabideau, Gregg; Cichy, Benjamin; Doubleday, Joshua; Pieri, David; Scharenbroich, Lucas;

Coarse Scale In Situ Albedo Observations over Heterogeneous Land Surfaces and Validation Strategy

NASA Astrophysics Data System (ADS)

Xiao, Q.; Wu, X.; Wen, J.; BAI, J., Sr.

2017-12-01

To evaluate and improve the quality of coarse-pixel land surface albedo products, validation with ground measurements of albedo is crucial over the spatially and temporally heterogeneous land surface. The performance of albedo validation depends on the quality of ground-based albedo measurements at a corresponding coarse-pixel scale, which can be conceptualized as the "truth" value of albedo at coarse-pixel scale. The wireless sensor network (WSN) technology provides access to continuously observe on the large pixel scale. Taking the albedo products as an example, this paper was dedicated to the validation of coarse-scale albedo products over heterogeneous surfaces based on the WSN observed data, which is aiming at narrowing down the uncertainty of results caused by the spatial scaling mismatch between satellite and ground measurements over heterogeneous surfaces. The reference value of albedo at coarse-pixel scale can be obtained through an upscaling transform function based on all of the observations for that pixel. We will devote to further improve and develop new method that that are better able to account for the spatio-temporal characteristic of surface albedo in the future. Additionally, how to use the widely distributed single site measurements over the heterogeneous surfaces is also a question to be answered. Keywords: Remote sensing; Albedo; Validation; Wireless sensor network (WSN); Upscaling; Heterogeneous land surface; Albedo truth at coarse-pixel scale

Country-wide rainfall maps from cellular communication networks

PubMed Central

Overeem, Aart; Leijnse, Hidde; Uijlenhoet, Remko

2013-01-01

Accurate and timely surface precipitation measurements are crucial for water resources management, agriculture, weather prediction, climate research, as well as ground validation of satellite-based precipitation estimates. However, the majority of the land surface of the earth lacks such data, and in many parts of the world the density of surface precipitation gauging networks is even rapidly declining. This development can potentially be counteracted by using received signal level data from the enormous number of microwave links used worldwide in commercial cellular communication networks. Along such links, radio signals propagate from a transmitting antenna at one base station to a receiving antenna at another base station. Rain-induced attenuation and, subsequently, path-averaged rainfall intensity can be retrieved from the signal’s attenuation between transmitter and receiver. Here, we show how one such a network can be used to retrieve the space–time dynamics of rainfall for an entire country (The Netherlands, ∼35,500 km2), based on an unprecedented number of links (∼2,400) and a rainfall retrieval algorithm that can be applied in real time. This demonstrates the potential of such networks for real-time rainfall monitoring, in particular in those parts of the world where networks of dedicated ground-based rainfall sensors are often virtually absent. PMID:23382210

Networked high-speed auroral observations combined with radar measurements for multi-scale insights

NASA Astrophysics Data System (ADS)

Hirsch, M.; Semeter, J. L.

2015-12-01

Networks of ground-based instruments to study terrestrial aurora for the purpose of analyzing particle precipitation characteristics driving the aurora have been established. Additional funding is pouring into future ground-based auroral observation networks consisting of combinations of tossable, portable, and fixed installation ground-based legacy equipment. Our approach to this problem using the High Speed Tomography (HiST) system combines tightly-synchronized filtered auroral optical observations capturing temporal features of order 10 ms with supporting measurements from incoherent scatter radar (ISR). ISR provides a broader spatial context up to order 100 km laterally on one minute time scales, while our camera field of view (FOV) is chosen to be order 10 km at auroral altitudes in order to capture 100 m scale lateral auroral features. The dual-scale observations of ISR and HiST fine-scale optical observations may be coupled through a physical model using linear basis functions to estimate important ionospheric quantities such as electron number density in 3-D (time, perpendicular and parallel to the geomagnetic field).Field measurements and analysis using HiST and PFISR are presented from experiments conducted at the Poker Flat Research Range in central Alaska. Other multiscale configuration candidates include supplementing networks of all-sky cameras such as THEMIS with co-locations of HiST-like instruments to fuse wide FOV measurements with the fine-scale HiST precipitation characteristic estimates. Candidate models for this coupling include GLOW and TRANSCAR. Future extensions of this work may include incorporating line of sight total electron count estimates from ground-based networks of GPS receivers in a sensor fusion problem.

Distributed cluster management techniques for unattended ground sensor networks

NASA Astrophysics Data System (ADS)

Essawy, Magdi A.; Stelzig, Chad A.; Bevington, James E.; Minor, Sharon

2005-05-01

Smart Sensor Networks are becoming important target detection and tracking tools. The challenging problems in such networks include the sensor fusion, data management and communication schemes. This work discusses techniques used to distribute sensor management and multi-target tracking responsibilities across an ad hoc, self-healing cluster of sensor nodes. Although miniaturized computing resources possess the ability to host complex tracking and data fusion algorithms, there still exist inherent bandwidth constraints on the RF channel. Therefore, special attention is placed on the reduction of node-to-node communications within the cluster by minimizing unsolicited messaging, and distributing the sensor fusion and tracking tasks onto local portions of the network. Several challenging problems are addressed in this work including track initialization and conflict resolution, track ownership handling, and communication control optimization. Emphasis is also placed on increasing the overall robustness of the sensor cluster through independent decision capabilities on all sensor nodes. Track initiation is performed using collaborative sensing within a neighborhood of sensor nodes, allowing each node to independently determine if initial track ownership should be assumed. This autonomous track initiation prevents the formation of duplicate tracks while eliminating the need for a central "management" node to assign tracking responsibilities. Track update is performed as an ownership node requests sensor reports from neighboring nodes based on track error covariance and the neighboring nodes geo-positional location. Track ownership is periodically recomputed using propagated track states to determine which sensing node provides the desired coverage characteristics. High fidelity multi-target simulation results are presented, indicating the distribution of sensor management and tracking capabilities to not only reduce communication bandwidth consumption, but to also simplify multi-target tracking within the cluster.

Data fusion concept in multispectral system for perimeter protection of stationary and moving objects

NASA Astrophysics Data System (ADS)

Ciurapiński, Wieslaw; Dulski, Rafal; Kastek, Mariusz; Szustakowski, Mieczyslaw; Bieszczad, Grzegorz; Życzkowski, Marek; Trzaskawka, Piotr; Piszczek, Marek

2009-09-01

The paper presents the concept of multispectral protection system for perimeter protection for stationary and moving objects. The system consists of active ground radar, thermal and visible cameras. The radar allows the system to locate potential intruders and to control an observation area for system cameras. The multisensor construction of the system ensures significant improvement of detection probability of intruder and reduction of false alarms. A final decision from system is worked out using image data. The method of data fusion used in the system has been presented. The system is working under control of FLIR Nexus system. The Nexus offers complete technology and components to create network-based, high-end integrated systems for security and surveillance applications. Based on unique "plug and play" architecture, system provides unmatched flexibility and simplistic integration of sensors and devices in TCP/IP networks. Using a graphical user interface it is possible to control sensors and monitor streaming video and other data over the network, visualize the results of data fusion process and obtain detailed information about detected intruders over a digital map. System provides high-level applications and operator workload reduction with features such as sensor to sensor cueing from detection devices, automatic e-mail notification and alarm triggering.

Capacity Model and Constraints Analysis for Integrated Remote Wireless Sensor and Satellite Network in Emergency Scenarios

PubMed Central

Zhang, Wei; Zhang, Gengxin; Dong, Feihong; Xie, Zhidong; Bian, Dongming

2015-01-01

This article investigates the capacity problem of an integrated remote wireless sensor and satellite network (IWSSN) in emergency scenarios. We formulate a general model to evaluate the remote sensor and satellite network capacity. Compared to most existing works for ground networks, the proposed model is time varying and space oriented. To capture the characteristics of a practical network, we sift through major capacity-impacting constraints and analyze the influence of these constraints. Specifically, we combine the geometric satellite orbit model and satellite tool kit (STK) engineering software to quantify the trends of the capacity constraints. Our objective in analyzing these trends is to provide insights and design guidelines for optimizing the integrated remote wireless sensor and satellite network schedules. Simulation results validate the theoretical analysis of capacity trends and show the optimization opportunities of the IWSSN. PMID:26593919

Capacity Model and Constraints Analysis for Integrated Remote Wireless Sensor and Satellite Network in Emergency Scenarios.

PubMed

Zhang, Wei; Zhang, Gengxin; Dong, Feihong; Xie, Zhidong; Bian, Dongming

2015-11-17

This article investigates the capacity problem of an integrated remote wireless sensor and satellite network (IWSSN) in emergency scenarios. We formulate a general model to evaluate the remote sensor and satellite network capacity. Compared to most existing works for ground networks, the proposed model is time varying and space oriented. To capture the characteristics of a practical network, we sift through major capacity-impacting constraints and analyze the influence of these constraints. Specifically, we combine the geometric satellite orbit model and satellite tool kit (STK) engineering software to quantify the trends of the capacity constraints. Our objective in analyzing these trends is to provide insights and design guidelines for optimizing the integrated remote wireless sensor and satellite network schedules. Simulation results validate the theoretical analysis of capacity trends and show the optimization opportunities of the IWSSN.

UAV Cooperation Architectures for Persistent Sensing

DOE Office of Scientific and Technical Information (OSTI.GOV)

Roberts, R S; Kent, C A; Jones, E D

2003-03-20

With the number of small, inexpensive Unmanned Air Vehicles (UAVs) increasing, it is feasible to build multi-UAV sensing networks. In particular, by using UAVs in conjunction with unattended ground sensors, a degree of persistent sensing can be achieved. With proper UAV cooperation algorithms, sensing is maintained even though exceptional events, e.g., the loss of a UAV, have occurred. In this paper a cooperation technique that allows multiple UAVs to perform coordinated, persistent sensing with unattended ground sensors over a wide area is described. The technique automatically adapts the UAV paths so that on the average, the amount of time thatmore » any sensor has to wait for a UAV revisit is minimized. We also describe the Simulation, Tactical Operations and Mission Planning (STOMP) software architecture. This architecture is designed to help simulate and operate distributed sensor networks where multiple UAVs are used to collect data.« less

Imaging the atmosphere using volcanic infrasound recorded on a dense local sensor network

NASA Astrophysics Data System (ADS)

Marcillo, O. E.; Johnson, J. B.; Johnson, R.

2010-12-01

We deployed a 47-node infrasound sensor network around Kilauea’s Halemaumau Vent to image the atmospheric conditions of the near-surface. This active vent is a persistent radiator of energetic infrasound enabling us to probe atmospheric winds and temperatures. This research builds upon a previous experiment that recorded infrasound on a three-node network, to determine relative phase delay and invert for atmospheric wind. The technique developed for this previous analysis assumed the intrinsic sound speed and was able to track the evolution of the average wind field in a large area (around 10 km2) and was largely insensitive to local meteorological effects, caused by topography and vegetation. The results of this previous experiment showed the potential of this technique for atmospheric studies and called for a following experiment with a denser sensor network over a larger area. During the summer 2010, we returned to Kilauea and deployed a 47-sensor network in three different configurations around Kilauea summit and down the volcano’s flanks. Persistent infrasonic tremor was ‘loud’ with excess pressures up to 10 Pa (when scaled to 1 km) and periods of high acoustic emissions that lasted from hours to days. The instrumentation for this experiment was composed of single-channel RefTek RT125A Texan digitizers and InfraNMT infrasound sensors. The Texan digitizers provide high-resolution 24-bit analog to digital conversion and can operate continuously for approximately five days with two D-cell batteries. The InfraNMT sensor is based on a piezo-electric transducer and was developed at the Infrasound Laboratory at New Mexico Tech. This sensor features low power (< 3 mA at 9 V) and flat response between 0.02 to 50 Hz. Three different network topologies were tested during this two-week experiment. For the first and second topologies, the sensors were deployed along established roads on two almost perpendicular sensor lines centered at the Halema’uma’u crater. The furthest sensors were located at ~24 km and ~10 km from the vent respectively. Numerical analysis indicates that these two configurations will be able to probe the atmospheric conditions up to 2 km above the ground. The third topology featured most of the sensors on the summit crater at similar radial distances (2-4 km) and different azimuths. The data collected with the third topology is expected to provide detailed information of the very-local infrasonic field. Each configuration was on the ground and operational for around 84 hours. This full dataset will provide an opportunity to investigate source phenomenology and/or propagation effects of the infrasonic field. Tomographic studies of the atmosphere are expected to provide meteorological data that will be of value for ash and gas propagation models.

Deep Space Wide Area Search Strategies

NASA Astrophysics Data System (ADS)

Capps, M.; McCafferty, J.

There is an urgent need to expand the space situational awareness (SSA) mission beyond catalog maintenance to providing near real-time indications and warnings of emerging events. While building and maintaining a catalog of space objects is essential to SSA, this does not address the threat of uncatalogued and uncorrelated deep space objects. The Air Force therefore has an interest in transformative technologies to scan the geostationary (GEO) belt for uncorrelated space objects. Traditional ground based electro-optical sensors are challenged in simultaneously detecting dim objects while covering large areas of the sky using current CCD technology. Time delayed integration (TDI) scanning has the potential to enable significantly larger coverage rates while maintaining sensitivity for detecting near-GEO objects. This paper investigates strategies of employing TDI sensing technology from a ground based electro-optical telescope, toward providing tactical indications and warnings of deep space threats. We present results of a notional wide area search TDI sensor that scans the GEO belt from three locations: Maui, New Mexico, and Diego Garcia. Deep space objects in the NASA 2030 debris catalog are propagated over multiple nights as an indicative data set to emulate notional uncatalogued near-GEO orbits which may be encountered by the TDI sensor. Multiple scan patterns are designed and simulated, to compare and contrast performance based on 1) efficiency in coverage, 2) number of objects detected, and 3) rate at which detections occur, to enable follow-up observations by other space surveillance network (SSN) sensors. A step-stare approach is also modeled using a dedicated, co-located sensor notionally similar to the Ground-Based Electro-Optical Deep Space Surveillance (GEODSS) tower. Equivalent sensitivities are assumed. This analysis quantifies the relative benefit of TDI scanning for the wide area search mission.

Cloud-to-Ground Lightning Estimates Derived from SSMI Microwave Remote Sensing and NLDN

NASA Technical Reports Server (NTRS)

Winesett, Thomas; Magi, Brian; Cecil, Daniel

2015-01-01

Lightning observations are collected using ground-based and satellite-based sensors. The National Lightning Detection Network (NLDN) in the United States uses multiple ground sensors to triangulate the electromagnetic signals created when lightning strikes the Earth's surface. Satellite-based lightning observations have been made from 1998 to present using the Lightning Imaging Sensor (LIS) on the NASA Tropical Rainfall Measuring Mission (TRMM) satellite, and from 1995 to 2000 using the Optical Transient Detector (OTD) on the Microlab-1 satellite. Both LIS and OTD are staring imagers that detect lightning as momentary changes in an optical scene. Passive microwave remote sensing (85 and 37 GHz brightness temperatures) from the TRMM Microwave Imager (TMI) has also been used to quantify characteristics of thunderstorms related to lightning. Each lightning detection system has fundamental limitations. TRMM satellite coverage is limited to the tropics and subtropics between 38 deg N and 38 deg S, so lightning at the higher latitudes of the northern and southern hemispheres is not observed. The detection efficiency of NLDN sensors exceeds 95%, but the sensors are only located in the USA. Even if data from other ground-based lightning sensors (World Wide Lightning Location Network, the European Cooperation for Lightning Detection, and Canadian Lightning Detection Network) were combined with TRMM and NLDN, there would be enormous spatial gaps in present-day coverage of lightning. In addition, a globally-complete time history of observed lightning activity is currently not available either, with network coverage and detection efficiencies varying through the years. Previous research using the TRMM LIS and Microwave Imager (TMI) showed that there is a statistically significant correlation between lightning flash rates and passive microwave brightness temperatures. The physical basis for this correlation emerges because lightning in a thunderstorm occurs where ice is first present in the cloud and electric charge separation occurs. These ice particles efficiently scatter the microwave radiation at the 85 and 37 GHz frequencies, thus leading to large brightness temperature depressions. Lightning flash rate is related to the total amount of ice passing through the convective updraft regions of thunderstorms. Confirmation of this relationship using TRMM LIS and TMI data, however, remains constrained to TRMM observational limits of the tropics and subtropics. Satellites from the Defense Meteorology Satellite Program (DMSP) have global coverage and are equipped with passive microwave imagers that, like TMI, observe brightness temperatures at 85 and 37 GHz. Unlike the TRMM satellite, however, DMSP satellites do not have a lightning sensor, and the DMSP microwave data has never been used to derive global lightning. In this presentation, a relationship between DMSP Special Sensor Microwave Imager (SSMI) data and ground-based cloud-to-ground (CG) lightning data from NLDN is investigated to derive a spatially complete time history of CG lightning for the USA study area. This relationship is analogous to the established using TRMM LIS and TMI data. NLDN has the most spatially and temporally complete CG lightning data for the USA, and therefore provides the best opportunity to find geospatially coincident observations with SSMI sensors. The strongest thunderstorms generally have minimum 85 GHz Polarized Corrected brightness Temperatures (PCT) less than 150 K. Archived radar data was used to resolve the spatial extent of the individual storms. NLDN data for that storm spatial extent defined by radar data was used to calculate the CG flash rate for the storm. Similar to results using TRMM sensors, a linear model best explained the relationship between storm-specific CG flash rates and minimum 85 GHz PCT. However, the results in this study apply only to CG lightning. To extend the results to weaker storms, the probability of CG lightning (instead of the flash rate) was calculated for storms having 85 GHz PCT greater than 150 K. NLDN data was used to determine if a CG strike occurred for a storm. This probability of CG lightning was plotted as a function of minimum 85 GHz PCT and minimum 37 GHz PCT. These probabilities were used in conjunction with the linear model to estimate the CG flash rate for weaker storms with minimum 85 GHz PCTs greater than 150 K. Results from the investigation of CG lightning and passive microwave radiation signals agree with the previous research investigating total lightning and brightness temperature. Future work will take the established relationships and apply them to the decades of available DMSP data for the USA to derive a map of CG lightning flash rates. Validation of this method and uncertainty analysis will be done by comparing the derived maps of CG lightning flash rates against existing NLDN maps of CG lightning flash rates.

Wi-GIM system: a new wireless sensor network (WSN) for accurate ground instability monitoring

NASA Astrophysics Data System (ADS)

Mucchi, Lorenzo; Trippi, Federico; Schina, Rosa; Fornaciai, Alessandro; Gigli, Giovanni; Nannipieri, Luca; Favalli, Massimiliano; Marturia Alavedra, Jordi; Intrieri, Emanuele; Agostini, Andrea; Carnevale, Ennio; Bertolini, Giovanni; Pizziolo, Marco; Casagli, Nicola

2016-04-01

Landslides are among the most serious and common geologic hazards around the world. Their impact on human life is expected to increase in the next future as a consequence of human-induced climate change as well as the population growth in proximity of unstable slopes. Therefore, developing better performing technologies for monitoring landslides and providing local authorities with new instruments able to help them in the decision making process, is becoming more and more important. The recent progresses in Information and Communication Technologies (ICT) allow us to extend the use of wireless technologies in landslide monitoring. In particular, the developments in electronics components have permitted to lower the price of the sensors and, at the same time, to actuate more efficient wireless communications. In this work we present a new wireless sensor network (WSN) system, designed and developed for landslide monitoring in the framework of EU Wireless Sensor Network for Ground Instability Monitoring - Wi-GIM project (LIFE12 ENV/IT/001033). We show the preliminary performance of the Wi-GIM system after the first period of monitoring on the active Roncovetro Landslide and on a large subsiding area in the neighbourhood of Sallent village. The Roncovetro landslide is located in the province of Reggio Emilia (Italy) and moved an inferred volume of about 3 million cubic meters. Sallent village is located at the centre of the Catalan evaporitic basin in Spain. The Wi-GIM WSN monitoring system consists of three levels: 1) Master/Gateway level coordinates the WSN and performs data aggregation and local storage; 2) Master/Server level takes care of acquiring and storing data on a remote server; 3) Nodes level that is based on a mesh of peripheral nodes, each consisting in a sensor board equipped with sensors and wireless module. The nodes are located in the landslide ground perimeter and are able to create an ad-hoc WSN. The location of each sensor on the ground is determined by integrating an ultra wideband technology with a radar technology; this integration allows to push the accuracy towards the cm. An extended Kalman filter is also used to reduce the noise and enhance the accuracy of the measures. The sensor nodes are organized as a hierarchical cluster, composed by one master and several slave nodes. The landslide movement is detected by comparing day by day the x, y and z coordinates of each nodes. The 3D movements of each sensor during the monitoring period are represented as vector and displayed on a Web-GIS which is accessible at the following link: www.life-wigim.eu.

Multi-objects recognition for distributed intelligent sensor networks

NASA Astrophysics Data System (ADS)

He, Haibo; Chen, Sheng; Cao, Yuan; Desai, Sachi; Hohil, Myron E.

2008-04-01

This paper proposes an innovative approach for multi-objects recognition for homeland security and defense based intelligent sensor networks. Unlike the conventional way of information analysis, data mining in such networks is typically characterized with high information ambiguity/uncertainty, data redundancy, high dimensionality and real-time constrains. Furthermore, since a typical military based network normally includes multiple mobile sensor platforms, ground forces, fortified tanks, combat flights, and other resources, it is critical to develop intelligent data mining approaches to fuse different information resources to understand dynamic environments, to support decision making processes, and finally to achieve the goals. This paper aims to address these issues with a focus on multi-objects recognition. Instead of classifying a single object as in the traditional image classification problems, the proposed method can automatically learn multiple objectives simultaneously. Image segmentation techniques are used to identify the interesting regions in the field, which correspond to multiple objects such as soldiers or tanks. Since different objects will come with different feature sizes, we propose a feature scaling method to represent each object in the same number of dimensions. This is achieved by linear/nonlinear scaling and sampling techniques. Finally, support vector machine (SVM) based learning algorithms are developed to learn and build the associations for different objects, and such knowledge will be adaptively accumulated for objects recognition in the testing stage. We test the effectiveness of proposed method in different simulated military environments.

Ground Optical Signal Processing Architecture for Contributing SSA Space Based Sensor Data

NASA Astrophysics Data System (ADS)

Koblick, D.; Klug, M.; Goldsmith, A.; Flewelling, B.; Jah, M.; Shanks, J.; Piña, R.

2014-09-01

The main objective of the DARPA program Orbit Outlook (O^2) is to improve the metric tracking and detection performance of the Space Situational Network (SSN) by adding a diverse low-cost network of contributing sensors to the Space Situational Awareness (SSA) mission. In order to accomplish this objective, not only must a sensor be in constant communication with a planning and scheduling system to process tasking requests, there must be an underlying framework to provide useful data products, such as angles only measurements. Existing optical signal processing implementations such as the Optical Processing Architecture at Lincoln (OPAL) are capable of converting mission data collections to angles only observations, but may be difficult for many users to obtain, support, and customize for low-cost missions and demonstration programs. The Ground Optical Signal Processing Architecture (GOSPA) will ingest raw imagery and telemetry data from a space based electro optical sensor and perform a background removal process to remove anomalous pixels, interpolate over bad pixels, and dominant temporal noise. After background removal, the streak end points and target centroids are located using a corner detection algorithm developed by Air Force Research Laboratory. These identified streak locations are then fused with the corresponding spacecraft telemetry data to determine the Right Ascension and Declination measurements with respect to time. To demonstrate the performance of GOSPA, non-rate tracking collections against a satellite in Geosynchronous Orbit are simulated from a visible optical imaging sensor in a polar Low Earth Orbit. Stars, noise and bad pixels are added to the simulated images based on look angles and sensor parameters. These collections are run through the GOSPA framework to provide angles- only measurements to the Air Force Research Laboratory Constrained Admissible Region Multiple Hypothesis Filter (CAR-MHF) in which an Initial Orbit Determination is performed and compared to truth data.

Obstacle negotiation control for a mobile robot suspended on overhead ground wires by optoelectronic sensors

NASA Astrophysics Data System (ADS)

Zheng, Li; Yi, Ruan

2009-11-01

Power line inspection and maintenance already benefit from developments in mobile robotics. This paper presents mobile robots capable of crossing obstacles on overhead ground wires. A teleoperated robot realizes inspection and maintenance tasks on power transmission line equipment. The inspection robot is driven by 11 motor with two arms, two wheels and two claws. The inspection robot is designed to realize the function of observation, grasp, walk, rolling, turn, rise, and decline. This paper is oriented toward 100% reliable obstacle detection and identification, and sensor fusion to increase the autonomy level. An embedded computer based on PC/104 bus is chosen as the core of control system. Visible light camera and thermal infrared Camera are both installed in a programmable pan-and-tilt camera (PPTC) unit. High-quality visual feedback rapidly becomes crucial for human-in-the-loop control and effective teleoperation. The communication system between the robot and the ground station is based on Mesh wireless networks by 700 MHz bands. An expert system programmed with Visual C++ is developed to implement the automatic control. Optoelectronic laser sensors and laser range scanner were installed in robot for obstacle-navigation control to grasp the overhead ground wires. A novel prototype with careful considerations on mobility was designed to inspect the 500KV power transmission lines. Results of experiments demonstrate that the robot can be applied to execute the navigation and inspection tasks.

Fault Tolerant Computer Network Study

DTIC Science & Technology

1980-04-01

2. 1.2. 2 Air Data The air data function processes air pressures, temperature , and angle- of-attack measurements, and provides calibrated airspeed...attitude direction indicator. 2.1.5.2 Fixtaking Sensors used for fixtaking include the radar (in ground map mode), head- up display (for visual...VFR interdiction mission. The radar (ground map mode) is also the primary sensor at night and in adverse weather if the target presents a

Intelligent On-Board Processing in the Sensor Web

NASA Astrophysics Data System (ADS)

Tanner, S.

2005-12-01

Most existing sensing systems are designed as passive, independent observers. They are rarely aware of the phenomena they observe, and are even less likely to be aware of what other sensors are observing within the same environment. Increasingly, intelligent processing of sensor data is taking place in real-time, using computing resources on-board the sensor or the platform itself. One can imagine a sensor network consisting of intelligent and autonomous space-borne, airborne, and ground-based sensors. These sensors will act independently of one another, yet each will be capable of both publishing and receiving sensor information, observations, and alerts among other sensors in the network. Furthermore, these sensors will be capable of acting upon this information, perhaps altering acquisition properties of their instruments, changing the location of their platform, or updating processing strategies for their own observations to provide responsive information or additional alerts. Such autonomous and intelligent sensor networking capabilities provide significant benefits for collections of heterogeneous sensors within any environment. They are crucial for multi-sensor observations and surveillance, where real-time communication with external components and users may be inhibited, and the environment may be hostile. In all environments, mission automation and communication capabilities among disparate sensors will enable quicker response to interesting, rare, or unexpected events. Additionally, an intelligent network of heterogeneous sensors provides the advantage that all of the sensors can benefit from the unique capabilities of each sensor in the network. The University of Alabama in Huntsville (UAH) is developing a unique approach to data processing, integration and mining through the use of the Adaptive On-Board Data Processing (AODP) framework. AODP is a key foundation technology for autonomous internetworking capabilities to support situational awareness by sensors and their on-board processes. The two primary research areas for this project are (1) the on-board processing and communications framework itself, and (2) data mining algorithms targeted to the needs and constraints of the on-board environment. The team is leveraging its experience in on-board processing, data mining, custom data processing, and sensor network design. Several unique UAH-developed technologies are employed in the AODP project, including EVE, an EnVironmEnt for on-board processing, and the data mining tools included in the Algorithm Development and Mining (ADaM) toolkit.

UGV navigation in wireless sensor and actuator network environments

NASA Astrophysics Data System (ADS)

Zhang, Guyu; Li, Jianfeng; Duncan, Christian A.; Kanno, Jinko; Selmic, Rastko R.

2012-06-01

We consider a navigation problem in a distributed, self-organized and coordinate-free Wireless Sensor and Ac- tuator Network (WSAN). We rst present navigation algorithms that are veried using simulation results. Con- sidering more than one destination and multiple mobile Unmanned Ground Vehicles (UGVs), we introduce a distributed solution to the Multi-UGV, Multi-Destination navigation problem. The objective of the solution to this problem is to eciently allocate UGVs to dierent destinations and carry out navigation in the network en- vironment that minimizes total travel distance. The main contribution of this paper is to develop a solution that does not attempt to localize either the UGVs or the sensor and actuator nodes. Other than some connectivity as- sumptions about the communication graph, we consider that no prior information about the WSAN is available. The solution presented here is distributed, and the UGV navigation is solely based on feedback from neigh- boring sensor and actuator nodes. One special case discussed in the paper, the Single-UGV, Multi-Destination navigation problem, is essentially equivalent to the well-known and dicult Traveling Salesman Problem (TSP). Simulation results are presented that illustrate the navigation distance traveled through the network. We also introduce an experimental testbed for the realization of coordinate-free and localization-free UGV navigation. We use the Cricket platform as the sensor and actuator network and a Pioneer 3-DX robot as the UGV. The experiments illustrate the UGV navigation in a coordinate-free WSAN environment where the UGV successfully arrives at the assigned destinations.

Combined Characterisation of GOME and TOMS Total Ozone Using Ground-Based Observations from the NDSC

NASA Technical Reports Server (NTRS)

Lambert, J.-C.; VanRoozendael, M.; Simon, P. C.; Pommereau, J.-P.; Goutail, F.; Andersen, S. B.; Arlander, D. W.; BuiVan, N. A.; Claude, H.; deLaNoee, J.;

Smart Rocks for Bridge Scour Monitoring: Design and Localization Using Electromagnetic Techniques and Embedded Orientation Sensors

NASA Astrophysics Data System (ADS)

Radchenko, Andro

River bridge scour is an erosion process in which flowing water removes sediment materials (such as sand, rocks) from a bridge foundation, river beds and banks. As a result, the level of the river bed near a bridge pier is lowering such that the bridge foundation stability can be compromised, and the bridge can collapse. The scour is a dynamic process, which can accelerate rapidly during a flood event. Thus, regular monitoring of the scour progress is necessary to be performed at most river bridges. Present techniques are usually expensive, require large man/hour efforts, and often lack the real-time monitoring capabilities. In this dissertation a new method--'Smart Rocks Network for bridge scour monitoring' is introduced. The method is based on distributed wireless sensors embedded in ground underwater nearby the bridge pillars. The sensor nodes are unconstrained in movement, are equipped with years-lasting batteries and intelligent custom designed electronics, which minimizes power consumption during operation and communication. The electronic part consists of a microcontroller, communication interfaces, orientation and environment sensors (such as are accelerometer, magnetometer, temperature and pressure sensors), supporting power supplies and circuitries. Embedded in the soil nearby a bridge pillar the Smart Rocks can move/drift together with the sediments, and act as the free agent probes transmitting the unique signature signals to the base-station monitors. Individual movement of a Smart Rock can be remotely detected processing the orientation sensors reading. This can give an indication of the on-going scour progress, and set a flag for the on-site inspection. The map of the deployed Smart Rocks Network can be obtained utilizing the custom developed in-network communication protocol with signals intensity (RSSI) analysis. Particle Swarm Optimization (PSO) is applied for map reconstruction. Analysis of the map can provide detailed insight into the scour progress and topology. Smart Rocks Network wireless communication is based on the magnetoinductive (MI) link, at low (125 KHz) frequency, allowing for signal to penetrate through the water, rocks, and the bridge structure. The dissertation describes the Smart Rocks Network implementation, its electronic design and the electromagnetic/computational intelligence techniques used for the network mapping.

Sensor Technology Baseline Study for Enabling Condition Based Maintenance Plus in Army Ground Vehicles

DTIC Science & Technology

2012-03-01

for enabling condition based maintenance plus in Army ground vehicles. The sensor study was driven from Failure Mode Effects Analysis ( FMEA ...of Tables Table 1. Sensor technology baseline study based on engine FMEA report. ...................................5 Table 2. Sensor technology...baseline study based on transmission FMEA report. .........................8 Table 3. Sensor technology baseline study based on alternator FMEA report

Towards a Community Environmental Observation Network

NASA Astrophysics Data System (ADS)

Mertl, Stefan; Lettenbichler, Anton

2014-05-01

The Community Environmental Observation Network (CEON) is dedicated to the development of a free sensor network to collect and distribute environmental data (e.g. ground shaking, climate parameters). The data collection will be done with contributions from citizens, research institutions and public authorities like communities or schools. This will lead to a large freely available data base which can be used for public information, research, the arts,..... To start a free sensor network, the most important step is to provide easy access to free data collection and -distribution tools. The initial aims of the project CEON are dedicated to the development of these tools. A high quality data logger based on open hardware and free software is developed and a software suite of already existing free software for near-real time data communication and data distribution over the Internet will be assembled. Foremost, the development focuses on the collection of data related to the deformation of the earth (such as ground shaking, surface displacement of mass movements and glaciers) and the collection of climate data. The extent to other measurements will be considered in the design. The data logger is built using open hardware prototyping platforms like BeagleBone Black and Arduino. Main features of the data logger are: a 24Bit analog-to-digital converter; a GPS module for time reference and positioning; wireless mesh networking using Optimized Link State Routing; near real-time data transmission and communication; and near real-time differential GNSS positioning using the RTKLIB software. The project CEON is supported by the Internet Foundation Austria (IPA) within the NetIdee 2013 call.

Low-Cost Ground Sensor Network for Intrusion Detection

DTIC Science & Technology

2017-09-01

NAVAL POSTGRADUATE SCHOOL MONTEREY, CALIFORNIA THESIS Approved for public release. Distribution is unlimited. LOW- COST GROUND...Gurminder Singh THIS PAGE INTENTIONALLY LEFT BLANK i REPORT DOCUMENTATION PAGE Form Approved OMB No. 0704-0188 Public reporting burden for this...

Eco-hydrological Wireless Sensor Network and upscaling method research in the Heihe River Basin, China

NASA Astrophysics Data System (ADS)

Jin, Rui; kang, Jian

2017-04-01

Wireless Sensor Networks are recognized as one of most important near-surface components of GEOSS (Global Earth Observation System of Systems), with flourish development of low-cost, robust and integrated data loggers and sensors. A nested eco-hydrological wireless sensor network (EHWSN) was installed in the up- and middle-reaches of the Heihe River Basin, operated to obtain multi-scale observation of soil moisture, soil temperature and land surface temperature from 2012 till now. The spatial distribution of EHWSN was optimally designed based on the geo-statistical theory, with the aim to capture the spatial variations and temporal dynamics of soil moisture and soil temperature, and to produce ground truth at grid scale for validating the related remote sensing products and model simulation in the heterogeneous land surface. In terms of upscaling research, we have developed a set of method to aggregate multi-point WSN observations to grid scale ( 1km), including regression kriging estimation to utilize multi-resource remote sensing auxiliary information, block kriging with homogeneous measurement errors, and bayesian-based upscaling algorithm that utilizes MODIS-derived apparent thermal inertia. All the EHWSN observation are organized as datasets to be freely published at http://westdc.westgis.ac.cn/hiwater. EHWSN integrates distributed observation nodes to achieve an automated, intelligent and remote-controllable network that provides superior integrated, standardized and automated observation capabilities for hydrological and ecological processes research at the basin scale.

An Event-based Assessment of Uncertainty in Measurements Between Multiple Precipitation Sensors During the North American Monsoon

NASA Astrophysics Data System (ADS)

Kautz, M. A.; Keefer, T.; Demaria, E. M.; Goodrich, D. C.; Hazenberg, P.; Petersen, W. A.; Wingo, M. T.; Smith, J.

2017-12-01

The USDA - Agricultural Research Service (USDA-ARS) Long-Term Agroecosystem Research network (LTAR) is a partnership between 18 long-term research sites across the United States. As part of the program, LTAR aims to assemble a network of common sensors and measurements of hydrological, meteorological, and biophysical variables to accompany the legacy datasets of individual LTAR sites. Uncertainty remains as to how the common sensor-based measurements will compare to those measured with existing sensors at each site. The USDA-ARS Southwest Watershed Research Center (SWRC) operated Walnut Gulch Experimental Watershed (WGEW) represents the semiarid grazing lands located in southeastern Arizona in the LTAR network. The bimodal precipitation regime of this region is characterized by large-scale frontal precipitation in the winter and isolated, high-intensity, convective thunderstorms in the summer during the North American Monsoon (NAM). SWRC maintains a network of 90 rain gauges across the 150 km2 WGEW and surrounding area, with measurements dating back to the 1950's. The high intensity and isolated nature of the summer storms has historically made it difficult to quantify compared to other regimes in the US. This study assesses the uncertainty of measurement between the common LTAR Belfort All Weather Precipitation Gauge (AEPG 600) and the legacy WGEW weighing-type raingage. Additionally, in a collaboration with NASA Global Precipitation Measurement mission (GPM) and the University of Arizona a dense array of precipitation measuring sensors was installed at WGEW within a 10 meter radius for observation during the NAM, July through October 2017. In addition to two WGEW weighing-type gauges, the array includes: an AEPG 600, a tipping bucket, a weighing-bucket installed with orifice at ground level, an OTT Pluvio2 rain gauge, a Two-Dimensional Video Disdrometer (2DVD), and three OTT Parsivel2 disdrometers. An event-based comparison was made between precipitation sensors using metrics including total depth, peak intensity (1, 15, 30, and 60 minute), event duration, time to peak intensity, and start time of event. These results provide further insight into the uncertainties of measuring point-based precipitation in this unique precipitation regime and representation in large-scale observation networks.

Optimized autonomous space in-situ sensor web for volcano monitoring

USGS Publications Warehouse

Song, W.-Z.; Shirazi, B.; Huang, R.; Xu, M.; Peterson, N.; LaHusen, R.; Pallister, J.; Dzurisin, D.; Moran, S.; Lisowski, M.; Kedar, S.; Chien, S.; Webb, F.; Kiely, A.; Doubleday, J.; Davies, A.; Pieri, D.

2010-01-01

In response to NASA's announced requirement for Earth hazard monitoring sensor-web technology, a multidisciplinary team involving sensor-network experts (Washington State University), space scientists (JPL), and Earth scientists (USGS Cascade Volcano Observatory (CVO)), have developed a prototype of dynamic and scalable hazard monitoring sensor-web and applied it to volcano monitoring. The combined Optimized Autonomous Space In-situ Sensor-web (OASIS) has two-way communication capability between ground and space assets, uses both space and ground data for optimal allocation of limited bandwidth resources on the ground, and uses smart management of competing demands for limited space assets. It also enables scalability and seamless infusion of future space and in-situ assets into the sensor-web. The space and in-situ control components of the system are integrated such that each element is capable of autonomously tasking the other. The ground in-situ was deployed into the craters and around the flanks of Mount St. Helens in July 2009, and linked to the command and control of the Earth Observing One (EO-1) satellite. ?? 2010 IEEE.

2008 Year in Review

NASA Technical Reports Server (NTRS)

Figueroa, Jorge Fernando

2008-01-01

In February of 2008; NASA Stennis Space Center (SSC), NASA Kennedy Space Center (KSC), and The Applied Research Laboratory at Penn State University demonstrated a pilot implementation of an Integrated System Health Management (ISHM) capability at the Launch Complex 20 of KSC. The following significant accomplishments are associated with this development: (1) implementation of an architecture for ground operations ISHM, based on networked intelligent elements; (2) Use of standards for management of data, information, and knowledge (DIaK) leading to modular ISHM implementation with interoperable elements communicating according to standards (three standards were used: IEEE 1451 family of standards for smart sensors and actuators, Open Systems Architecture for Condition Based Maintenance (OSA-CBM) standard for communicating DIaK describing the condition of elements of a system, and the OPC standard for communicating data); (3) ISHM implementation using interoperable modules addressing health management of subsystems; and (4) use of a physical intelligent sensor node (smart network element or SNE capable of providing data and health) along with classic sensors originally installed in the facility. An operational demonstration included detection of anomalies (sensor failures, leaks, etc.), determination of causes and effects, communication among health nodes, and user interfaces.

Distributive, Non-destructive Real-time System and Method for Snowpack Monitoring

NASA Technical Reports Server (NTRS)

Frolik, Jeff (Inventor); Skalka, Christian (Inventor)

2013-01-01

A ground-based system that provides quasi real-time measurement and collection of snow-water equivalent (SWE) data in remote settings is provided. The disclosed invention is significantly less expensive and easier to deploy than current methods and less susceptible to terrain and snow bridging effects. Embodiments of the invention include remote data recovery solutions. Compared to current infrastructure using existing SWE technology, the disclosed invention allows more SWE sites to be installed for similar cost and effort, in a greater variety of terrain; thus, enabling data collection at improved spatial resolutions. The invention integrates a novel computational architecture with new sensor technologies. The invention's computational architecture is based on wireless sensor networks, comprised of programmable, low-cost, low-powered nodes capable of sophisticated sensor control and remote data communication. The invention also includes measuring attenuation of electromagnetic radiation, an approach that is immune to snow bridging and significantly reduces sensor footprints.

Integrated Land- and Underwater-Based Sensors for a Subduction Zone Earthquake Early Warning System

NASA Astrophysics Data System (ADS)

Pirenne, B.; Rosenberger, A.; Rogers, G. C.; Henton, J.; Lu, Y.; Moore, T.

2016-12-01

Ocean Networks Canada (ONC — oceannetworks.ca/ ) operates cabled ocean observatories off the coast of British Columbia (BC) to support research and operational oceanography. Recently, ONC has been funded by the Province of BC to deliver an earthquake early warning (EEW) system that integrates offshore and land-based sensors to deliver alerts of incoming ground shaking from the Cascadia Subduction Zone. ONC's cabled seismic network has the unique advantage of being located offshore on either side of the surface expression of the subduction zone. The proximity of ONC's sensors to the fault can result in faster, more effective warnings, which translates into more lives saved, injuries avoided and more ability for mitigative actions to take place.ONC delivers near real-time data from various instrument types simultaneously, providing distinct advantages to seismic monitoring and earthquake early warning. The EEW system consists of a network of sensors, located on the ocean floor and on land, that detect and analyze the initial p-wave of an earthquake as well as the crustal deformation on land during the earthquake sequence. Once the p-wave is detected and characterized, software systems correlate the data streams of the various sensors and deliver alerts to clients through a Common Alerting Protocol-compliant data package. This presentation will focus on the development of the earthquake early warning capacity at ONC. It will describe the seismic sensors and their distribution, the p-wave detection algorithms selected and the overall architecture of the system. It will further overview the plan to achieve operational readiness at project completion.

Behavior analysis for elderly care using a network of low-resolution visual sensors

NASA Astrophysics Data System (ADS)

Eldib, Mohamed; Deboeverie, Francis; Philips, Wilfried; Aghajan, Hamid

2016-07-01

Recent advancements in visual sensor technologies have made behavior analysis practical for in-home monitoring systems. The current in-home monitoring systems face several challenges: (1) visual sensor calibration is a difficult task and not practical in real-life because of the need for recalibration when the visual sensors are moved accidentally by a caregiver or the senior citizen, (2) privacy concerns, and (3) the high hardware installation cost. We propose to use a network of cheap low-resolution visual sensors (30×30 pixels) for long-term behavior analysis. The behavior analysis starts by visual feature selection based on foreground/background detection to track the motion level in each visual sensor. Then a hidden Markov model (HMM) is used to estimate the user's locations without calibration. Finally, an activity discovery approach is proposed using spatial and temporal contexts. We performed experiments on 10 months of real-life data. We show that the HMM approach outperforms the k-nearest neighbor classifier against ground truth for 30 days. Our framework is able to discover 13 activities of daily livings (ADL parameters). More specifically, we analyze mobility patterns and some of the key ADL parameters to detect increasing or decreasing health conditions.

Thunderstorm monitoring with VLF network and super dense meteorological observation system

NASA Astrophysics Data System (ADS)

Takahashi, Yukihiro; Sato, Mitsuteru

2015-04-01

It's not easy to understand the inside structure and developing process of thunderstorm only with existing meteorological instruments since its horizontal extent of the storm cell is sometimes smaller than an order of 10 km while one of the densest ground network in Japan, AMEDAS, consists of sites located every 17 km in average and the resolution of meteorological radar is 1-2 km in general. Even the X-band radar realizes the resolution of 250 m or larger. Here we suggest a thunderstorm monitoring system consisting of the network of VLF radio wave receivers and the super dense meteorological observation system with simple and low cost plate-type sensors that can be used for measurement both of raindrop and vertical electric field change caused by cloud-to-ground lightning discharge, adding to basic equipments for meteorological measurements. The plate-type sensor consists of two aluminum plates with a diameter of 10-20 cm. We carried out an observation campaign in summer of 2013 in the foothills of Mt. Yastugatake, Yamanashi and Nagano prefectures in Japan, installing 6 plate-type sensors at a distance of about 4 km. Horizontal location, height and charge amount of each lightning discharge are estimated successfully based on the information of electric field changes at several observing sites. Moreover, it was found that the thunderstorm has a very narrow structure smaller than 300 m that cannot be measured by any other ways, counting the positive and negative pulses caused by attachment of raindrop to the sensor plate, respectively. We plan to construct a new super dense observation network in the north Kanto region, Japan, where the lightning activity is most prominent in summer Japan and surrounded by our VLF systems developed for detecting sferics from lightning discharge, distributing more than several tens of sensors at every 4 km or shorter, such as an order of 100 m at minimum. This kind of new type network will reveal the unknown fine structures of thunderstorms and open the door for constructing real time alert system of torrential rainfall and lightning stroke especially in the city area.

Community Seismic Network (CSN)

NASA Astrophysics Data System (ADS)

Clayton, R. W.; Heaton, T. H.; Kohler, M. D.; Chandy, M.; Krause, A.

2010-12-01

In collaboration with computer science and earthquake engineering, we are developing a dense network of low-cost accelerometers that send their data via the Internet to a cloud-based center. The goal is to make block-by-block measurements of ground shaking in urban areas, which will provide emergency response information in the case of large earthquakes, and an unprecedented high-frequency seismic array to study structure and the earthquake process with moderate shaking. When deployed in high-rise buildings they can be used to monitor the state of health of the structure. The sensors are capable of a resolution of approximately 80 micro-g, connect via USB ports to desktop computers, and cost about $100 each. The network will adapt to its environment by using network-wide machine learning to adjust the picking sensitivity. We are also looking into using other motion sensing devices such as cell phones. For a pilot project, we plan to deploy more than 1000 sensors in the greater Pasadena area. The system is easily adaptable to other seismically vulnerable urban areas.

Systematic Review of Real-time Remote Health Monitoring System in Triage and Priority-Based Sensor Technology: Taxonomy, Open Challenges, Motivation and Recommendations.

PubMed

Albahri, O S; Albahri, A S; Mohammed, K I; Zaidan, A A; Zaidan, B B; Hashim, M; Salman, Omar H

2018-03-22

The new and ground-breaking real-time remote monitoring in triage and priority-based sensor technology used in telemedicine have significantly bounded and dispersed communication components. To examine these technologies and provide researchers with a clear vision of this area, we must first be aware of the utilised approaches and existing limitations in this line of research. To this end, an extensive search was conducted to find articles dealing with (a) telemedicine, (b) triage, (c) priority and (d) sensor; (e) comprehensively review related applications and establish the coherent taxonomy of these articles. ScienceDirect, IEEE Xplore and Web of Science databases were checked for articles on triage and priority-based sensor technology in telemedicine. The retrieved articles were filtered according to the type of telemedicine technology explored. A total of 150 articles were selected and classified into two categories. The first category includes reviews and surveys of triage and priority-based sensor technology in telemedicine. The second category includes articles on the three-tiered architecture of telemedicine. Tier 1 represents the users. Sensors acquire the vital signs of the users and send them to Tier 2, which is the personal gateway that uses local area network protocols or wireless body area network. Medical data are sent from Tier 2 to Tier 3, which is the healthcare provider in medical institutes. Then, the motivation for using triage and priority-based sensor technology in telemedicine, the issues related to the obstruction of its application and the development and utilisation of telemedicine are examined on the basis of the findings presented in the literature.

Conceptual Design of a Communication-Based Deep Space Navigation Network

NASA Technical Reports Server (NTRS)

Anzalone, Evan J.; Chuang, C. H.

2012-01-01

As the need grows for increased autonomy and position knowledge accuracy to support missions beyond Earth orbit, engineers must push and develop more advanced navigation sensors and systems that operate independent of Earth-based analysis and processing. Several spacecraft are approaching this problem using inter-spacecraft radiometric tracking and onboard autonomous optical navigation methods. This paper proposes an alternative implementation to aid in spacecraft position fixing. The proposed method Network-Based Navigation technique takes advantage of the communication data being sent between spacecraft and between spacecraft and ground control to embed navigation information. The navigation system uses these packets to provide navigation estimates to an onboard navigation filter to augment traditional ground-based radiometric tracking techniques. As opposed to using digital signal measurements to capture inherent information of the transmitted signal itself, this method relies on the embedded navigation packet headers to calculate a navigation estimate. This method is heavily dependent on clock accuracy and the initial results show the promising performance of a notional system.

Enhanced technologies for unattended ground sensor systems

NASA Astrophysics Data System (ADS)

Hartup, David C.

2010-04-01

Progress in several technical areas is being leveraged to advantage in Unattended Ground Sensor (UGS) systems. This paper discusses advanced technologies that are appropriate for use in UGS systems. While some technologies provide evolutionary improvements, other technologies result in revolutionary performance advancements for UGS systems. Some specific technologies discussed include wireless cameras and viewers, commercial PDA-based system programmers and monitors, new materials and techniques for packaging improvements, low power cueing sensor radios, advanced long-haul terrestrial and SATCOM radios, and networked communications. Other technologies covered include advanced target detection algorithms, high pixel count cameras for license plate and facial recognition, small cameras that provide large stand-off distances, video transmissions of target activity instead of still images, sensor fusion algorithms, and control center hardware. The impact of each technology on the overall UGS system architecture is discussed, along with the advantages provided to UGS system users. Areas of analysis include required camera parameters as a function of stand-off distance for license plate and facial recognition applications, power consumption for wireless cameras and viewers, sensor fusion communication requirements, and requirements to practically implement video transmission through UGS systems. Examples of devices that have already been fielded using technology from several of these areas are given.

Bluetooth-based wireless sensor networks

NASA Astrophysics Data System (ADS)

You, Ke; Liu, Rui Qiang

2007-11-01

In this work a Bluetooth-based wireless sensor network is proposed. In this bluetooth-based wireless sensor networks, information-driven star topology and energy-saved mode are used, through which a blue master node can control more than seven slave node, the energy of each sensor node is reduced and secure management of each sensor node is improved.

A Practical Application Combining Wireless Sensor Networks and Internet of Things: Safety Management System for Tower Crane Groups

PubMed Central

Zhong, Dexing; Lv, Hongqiang; Han, Jiuqiang; Wei, Quanrui

2014-01-01

The so-called Internet of Things (IoT) has attracted increasing attention in the field of computer and information science. In this paper, a specific application of IoT, named Safety Management System for Tower Crane Groups (SMS-TC), is proposed for use in the construction industry field. The operating status of each tower crane was detected by a set of customized sensors, including horizontal and vertical position sensors for the trolley, angle sensors for the jib and load, tilt and wind speed sensors for the tower body. The sensor data is collected and processed by the Tower Crane Safety Terminal Equipment (TC-STE) installed in the driver's operating room. Wireless communication between each TC-STE and the Local Monitoring Terminal (LMT) at the ground worksite were fulfilled through a Zigbee wireless network. LMT can share the status information of the whole group with each TC-STE, while the LMT records the real-time data and reports it to the Remote Supervision Platform (RSP) through General Packet Radio Service (GPRS). Based on the global status data of the whole group, an anti-collision algorithm was executed in each TC-STE to ensure the safety of each tower crane during construction. Remote supervision can be fulfilled using our client software installed on a personal computer (PC) or smartphone. SMS-TC could be considered as a promising practical application that combines a Wireless Sensor Network with the Internet of Things. PMID:25196106

A practical application combining wireless sensor networks and Internet of Things: Safety Management System for Tower Crane Groups.

PubMed

Zhong, Dexing; Lv, Hongqiang; Han, Jiuqiang; Wei, Quanrui

2014-07-30

The so-called Internet of Things (IoT) has attracted increasing attention in the field of computer and information science. In this paper, a specific application of IoT, named Safety Management System for Tower Crane Groups (SMS-TC), is proposed for use in the construction industry field. The operating status of each tower crane was detected by a set of customized sensors, including horizontal and vertical position sensors for the trolley, angle sensors for the jib and load, tilt and wind speed sensors for the tower body. The sensor data is collected and processed by the Tower Crane Safety Terminal Equipment (TC-STE) installed in the driver's operating room. Wireless communication between each TC-STE and the Local Monitoring Terminal (LMT) at the ground worksite were fulfilled through a Zigbee wireless network. LMT can share the status information of the whole group with each TC-STE, while the LMT records the real-time data and reports it to the Remote Supervision Platform (RSP) through General Packet Radio Service (GPRS). Based on the global status data of the whole group, an anti-collision algorithm was executed in each TC-STE to ensure the safety of each tower crane during construction. Remote supervision can be fulfilled using our client software installed on a personal computer (PC) or smartphone. SMS-TC could be considered as a promising practical application that combines a Wireless Sensor Network with the Internet of Things.

Development of Integration Framework for Sensor Network and Satellite Image based on OGC Web Services

NASA Astrophysics Data System (ADS)

Ninsawat, Sarawut; Yamamoto, Hirokazu; Kamei, Akihide; Nakamura, Ryosuke; Tsuchida, Satoshi; Maeda, Takahisa

2010-05-01

With the availability of network enabled sensing devices, the volume of information being collected by networked sensors has increased dramatically in recent years. Over 100 physical, chemical and biological properties can be sensed using in-situ or remote sensing technology. A collection of these sensor nodes forms a sensor network, which is easily deployable to provide a high degree of visibility into real-world physical processes as events unfold. The sensor observation network could allow gathering of diverse types of data at greater spatial and temporal resolution, through the use of wired or wireless network infrastructure, thus real-time or near-real time data from sensor observation network allow researchers and decision-makers to respond speedily to events. However, in the case of environmental monitoring, only a capability to acquire in-situ data periodically is not sufficient but also the management and proper utilization of data also need to be careful consideration. It requires the implementation of database and IT solutions that are robust, scalable and able to interoperate between difference and distributed stakeholders to provide lucid, timely and accurate update to researchers, planners and citizens. The GEO (Global Earth Observation) Grid is primarily aiming at providing an e-Science infrastructure for the earth science community. The GEO Grid is designed to integrate various kinds of data related to the earth observation using the grid technology, which is developed for sharing data, storage, and computational powers of high performance computing, and is accessible as a set of services. A comprehensive web-based system for integrating field sensor and data satellite image based on various open standards of OGC (Open Geospatial Consortium) specifications has been developed. Web Processing Service (WPS), which is most likely the future direction of Web-GIS, performs the computation of spatial data from distributed data sources and returns the outcome in a standard format. The interoperability capabilities and Service Oriented Architecture (SOA) of web services allow incorporating between sensor network measurement available from Sensor Observation Service (SOS) and satellite remote sensing data from Web Mapping Service (WMS) as distributed data sources for WPS. Various applications have been developed to demonstrate the efficacy of integrating heterogeneous data source. For example, the validation of the MODIS aerosol products (MOD08_D3, the Level-3 MODIS Atmosphere Daily Global Product) by ground-based measurements using the sunphotometer (skyradiometer, Prede POM-02) installed at Phenological Eyes Network (PEN) sites in Japan. Furthermore, the web-based framework system for studying a relationship between calculated Vegetation Index from MODIS satellite image surface reflectance (MOD09GA, the Surface Reflectance Daily L2G Global 1km and 500m Product) and Gross Primary Production (GPP) field measurement at flux tower site in Thailand and Japan has been also developed. The success of both applications will contribute to maximize data utilization and improve accuracy of information by validate MODIS satellite products using high degree of accuracy and temporal measurement of field measurement data.

Building SDN-Based Agricultural Vehicular Sensor Networks Based on Extended Open vSwitch.

PubMed

Huang, Tao; Yan, Siyu; Yang, Fan; Pan, Tian; Liu, Jiang

2016-01-19

Software-defined vehicular sensor networks in agriculture, such as autonomous vehicle navigation based on wireless multi-sensor networks, can lead to more efficient precision agriculture. In SDN-based vehicle sensor networks, the data plane is simplified and becomes more efficient by introducing a centralized controller. However, in a wireless environment, the main controller node may leave the sensor network due to the dynamic topology change or the unstable wireless signal, leaving the rest of network devices without control, e.g., a sensor node as a switch may forward packets according to stale rules until the controller updates the flow table entries. To solve this problem, this paper proposes a novel SDN-based vehicular sensor networks architecture which can minimize the performance penalty of controller connection loss. We achieve this by designing a connection state detection and self-learning mechanism. We build prototypes based on extended Open vSwitch and Ryu. The experimental results show that the recovery time from controller connection loss is under 100 ms and it keeps rule updating in real time with a stable throughput. This architecture enhances the survivability and stability of SDN-based vehicular sensor networks in precision agriculture.

Building SDN-Based Agricultural Vehicular Sensor Networks Based on Extended Open vSwitch

PubMed Central

Huang, Tao; Yan, Siyu; Yang, Fan; Pan, Tian; Liu, Jiang

2016-01-01

Software-defined vehicular sensor networks in agriculture, such as autonomous vehicle navigation based on wireless multi-sensor networks, can lead to more efficient precision agriculture. In SDN-based vehicle sensor networks, the data plane is simplified and becomes more efficient by introducing a centralized controller. However, in a wireless environment, the main controller node may leave the sensor network due to the dynamic topology change or the unstable wireless signal, leaving the rest of network devices without control, e.g., a sensor node as a switch may forward packets according to stale rules until the controller updates the flow table entries. To solve this problem, this paper proposes a novel SDN-based vehicular sensor networks architecture which can minimize the performance penalty of controller connection loss. We achieve this by designing a connection state detection and self-learning mechanism. We build prototypes based on extended Open vSwitch and Ryu. The experimental results show that the recovery time from controller connection loss is under 100 ms and it keeps rule updating in real time with a stable throughput. This architecture enhances the survivability and stability of SDN-based vehicular sensor networks in precision agriculture. PMID:26797616

The Multi-Parameter Wireless Sensing System (MPwise): Its Description and Application to Earthquake Risk Mitigation.

PubMed

Boxberger, Tobias; Fleming, Kevin; Pittore, Massimiliano; Parolai, Stefano; Pilz, Marco; Mikulla, Stefan

2017-10-20

The Multi-Parameter Wireless Sensing (MPwise) system is an innovative instrumental design that allows different sensor types to be combined with relatively high-performance computing and communications components. These units, which incorporate off-the-shelf components, can undertake complex information integration and processing tasks at the individual unit or node level (when used in a network), allowing the establishment of networks that are linked by advanced, robust and rapid communications routing and network topologies. The system (and its predecessors) was originally designed for earthquake risk mitigation, including earthquake early warning (EEW), rapid response actions, structural health monitoring, and site-effect characterization. For EEW, MPwise units are capable of on-site, decentralized, independent analysis of the recorded ground motion and based on this, may issue an appropriate warning, either by the unit itself or transmitted throughout a network by dedicated alarming procedures. The multi-sensor capabilities of the system allow it to be instrumented with standard strong- and weak-motion sensors, broadband sensors, MEMS (namely accelerometers), cameras, temperature and humidity sensors, and GNSS receivers. In this work, the MPwise hardware, software and communications schema are described, as well as an overview of its possible applications. While focusing on earthquake risk mitigation actions, the aim in the future is to expand its capabilities towards a more multi-hazard and risk mitigation role. Overall, MPwise offers considerable flexibility and has great potential in contributing to natural hazard risk mitigation.

The Multi-Parameter Wireless Sensing System (MPwise): Its Description and Application to Earthquake Risk Mitigation

PubMed Central

Boxberger, Tobias; Fleming, Kevin; Pittore, Massimiliano; Parolai, Stefano; Pilz, Marco; Mikulla, Stefan

2017-01-01

The Multi-Parameter Wireless Sensing (MPwise) system is an innovative instrumental design that allows different sensor types to be combined with relatively high-performance computing and communications components. These units, which incorporate off-the-shelf components, can undertake complex information integration and processing tasks at the individual unit or node level (when used in a network), allowing the establishment of networks that are linked by advanced, robust and rapid communications routing and network topologies. The system (and its predecessors) was originally designed for earthquake risk mitigation, including earthquake early warning (EEW), rapid response actions, structural health monitoring, and site-effect characterization. For EEW, MPwise units are capable of on-site, decentralized, independent analysis of the recorded ground motion and based on this, may issue an appropriate warning, either by the unit itself or transmitted throughout a network by dedicated alarming procedures. The multi-sensor capabilities of the system allow it to be instrumented with standard strong- and weak-motion sensors, broadband sensors, MEMS (namely accelerometers), cameras, temperature and humidity sensors, and GNSS receivers. In this work, the MPwise hardware, software and communications schema are described, as well as an overview of its possible applications. While focusing on earthquake risk mitigation actions, the aim in the future is to expand its capabilities towards a more multi-hazard and risk mitigation role. Overall, MPwise offers considerable flexibility and has great potential in contributing to natural hazard risk mitigation. PMID:29053608

Develop Measures of Effectiveness and Deployment Optimization Rules for Networked Ground Micro-Sensors

DTIC Science & Technology

2001-05-01

types and total #) Ø Control of Sensors ( Scheduling ) Ø Coverage (Time & Area) Uncontrollable Inputs ØWeather Ø Atmospheric Effects Ø Equipment...are widely scattered and used to cue or wakeup other higher-level sensors. Trip line sensors consist of some combination of acoustic, seismic and...Employ a mix if different sensor types in order to increase detection probability 4.4.4.2 Minimize Battery Power • Set schedule turn on and off

The Coverage Problem in Video-Based Wireless Sensor Networks: A Survey

PubMed Central

Costa, Daniel G.; Guedes, Luiz Affonso

2010-01-01

Wireless sensor networks typically consist of a great number of tiny low-cost electronic devices with limited sensing and computing capabilities which cooperatively communicate to collect some kind of information from an area of interest. When wireless nodes of such networks are equipped with a low-power camera, visual data can be retrieved, facilitating a new set of novel applications. The nature of video-based wireless sensor networks demands new algorithms and solutions, since traditional wireless sensor networks approaches are not feasible or even efficient for that specialized communication scenario. The coverage problem is a crucial issue of wireless sensor networks, requiring specific solutions when video-based sensors are employed. In this paper, it is surveyed the state of the art of this particular issue, regarding strategies, algorithms and general computational solutions. Open research areas are also discussed, envisaging promising investigation considering coverage in video-based wireless sensor networks. PMID:22163651

Real-Time Alpine Measurement System Using Wireless Sensor Networks

PubMed Central

2017-01-01

Monitoring the snow pack is crucial for many stakeholders, whether for hydro-power optimization, water management or flood control. Traditional forecasting relies on regression methods, which often results in snow melt runoff predictions of low accuracy in non-average years. Existing ground-based real-time measurement systems do not cover enough physiographic variability and are mostly installed at low elevations. We present the hardware and software design of a state-of-the-art distributed Wireless Sensor Network (WSN)-based autonomous measurement system with real-time remote data transmission that gathers data of snow depth, air temperature, air relative humidity, soil moisture, soil temperature, and solar radiation in physiographically representative locations. Elevation, aspect, slope and vegetation are used to select network locations, and distribute sensors throughout a given network location, since they govern snow pack variability at various scales. Three WSNs were installed in the Sierra Nevada of Northern California throughout the North Fork of the Feather River, upstream of the Oroville dam and multiple powerhouses along the river. The WSNs gathered hydrologic variables and network health statistics throughout the 2017 water year, one of northern Sierra’s wettest years on record. These networks leverage an ultra-low-power wireless technology to interconnect their components and offer recovery features, resilience to data loss due to weather and wildlife disturbances and real-time topological visualizations of the network health. Data show considerable spatial variability of snow depth, even within a 1 km2 network location. Combined with existing systems, these WSNs can better detect precipitation timing and phase in, monitor sub-daily dynamics of infiltration and surface runoff during precipitation or snow melt, and inform hydro power managers about actual ablation and end-of-season date across the landscape. PMID:29120376

Real-Time Alpine Measurement System Using Wireless Sensor Networks.

PubMed

Malek, Sami A; Avanzi, Francesco; Brun-Laguna, Keoma; Maurer, Tessa; Oroza, Carlos A; Hartsough, Peter C; Watteyne, Thomas; Glaser, Steven D

2017-11-09

Monitoring the snow pack is crucial for many stakeholders, whether for hydro-power optimization, water management or flood control. Traditional forecasting relies on regression methods, which often results in snow melt runoff predictions of low accuracy in non-average years. Existing ground-based real-time measurement systems do not cover enough physiographic variability and are mostly installed at low elevations. We present the hardware and software design of a state-of-the-art distributed Wireless Sensor Network (WSN)-based autonomous measurement system with real-time remote data transmission that gathers data of snow depth, air temperature, air relative humidity, soil moisture, soil temperature, and solar radiation in physiographically representative locations. Elevation, aspect, slope and vegetation are used to select network locations, and distribute sensors throughout a given network location, since they govern snow pack variability at various scales. Three WSNs were installed in the Sierra Nevada of Northern California throughout the North Fork of the Feather River, upstream of the Oroville dam and multiple powerhouses along the river. The WSNs gathered hydrologic variables and network health statistics throughout the 2017 water year, one of northern Sierra's wettest years on record. These networks leverage an ultra-low-power wireless technology to interconnect their components and offer recovery features, resilience to data loss due to weather and wildlife disturbances and real-time topological visualizations of the network health. Data show considerable spatial variability of snow depth, even within a 1 km 2 network location. Combined with existing systems, these WSNs can better detect precipitation timing and phase in, monitor sub-daily dynamics of infiltration and surface runoff during precipitation or snow melt, and inform hydro power managers about actual ablation and end-of-season date across the landscape.

Location identification for indoor instantaneous point contaminant source by probability-based inverse Computational Fluid Dynamics modeling.

PubMed

Liu, X; Zhai, Z

2008-02-01

Indoor pollutions jeopardize human health and welfare and may even cause serious morbidity and mortality under extreme conditions. To effectively control and improve indoor environment quality requires immediate interpretation of pollutant sensor readings and accurate identification of indoor pollution history and source characteristics (e.g. source location and release time). This procedure is complicated by non-uniform and dynamic contaminant indoor dispersion behaviors as well as diverse sensor network distributions. This paper introduces a probability concept based inverse modeling method that is able to identify the source location for an instantaneous point source placed in an enclosed environment with known source release time. The study presents the mathematical models that address three different sensing scenarios: sensors without concentration readings, sensors with spatial concentration readings, and sensors with temporal concentration readings. The paper demonstrates the inverse modeling method and algorithm with two case studies: air pollution in an office space and in an aircraft cabin. The predictions were successfully verified against the forward simulation settings, indicating good capability of the method in finding indoor pollutant sources. The research lays a solid ground for further study of the method for more complicated indoor contamination problems. The method developed can help track indoor contaminant source location with limited sensor outputs. This will ensure an effective and prompt execution of building control strategies and thus achieve a healthy and safe indoor environment. The method can also assist the design of optimal sensor networks.

Air Pollution Measurements by Citizen Scientists and NASA Satellites: Data Integration and Analysis

NASA Astrophysics Data System (ADS)

Gupta, P.; Maibach, J.; Levy, R. C.; Doraiswamy, P.; Pikelnaya, O.; Feenstra, B.; Polidori, A.

2017-12-01

PM2.5, or fine particulate matter, is a category of air pollutant consisting of solid particles with effective aerodynamic diameter of less than 2.5 microns. These particles are hazardous to human health, as their small size allows them to penetrate deep into the lungs. Since the late 1990's, the US Environmental Protection Agency has been monitoring PM2.5 using a network of ground-level sensors. Due to cost and space restrictions, the EPA monitoring network remains spatially sparse. That is, while the network spans the extent of the US, the distance between sensors is large enough that significant spatial variation in PM concentration can go undetected. To increase the spatial resolution of monitoring, previous studies have used satellite data to estimate ground-level PM concentrations. From imagery, one can create a measure of haziness due to aerosols, called aerosol optical depth (AOD), which then can be used to estimate PM concentrations using statistical and physical modeling. Additionally, previous research has identified a number of meteorological variables, such as relative humidity and mixing height, which aide in estimating PM concentrations from AOD. Although the high spatial resolution of satellite data is valuable alone for forecasting air quality, higher resolution ground-level data is needed to effectively study the relationship between PM2.5 concentrations and AOD. To this end, we discuss a citizen-science PM monitoring network deployed in California. Using low-cost PM sensors, this network achieves higher spatial resolution. We additionally discuss a software pipeline for integrating resulting PM measurements with satellite data, as well as initial data analysis.

Design and first tests of a Macroseismic Sensor System

NASA Astrophysics Data System (ADS)

Brueckl, Ewald; Polydor, Stefan; Ableitinger, Klaus; Rafeiner-Magor, Walter; Kristufek, Werner; Mertl, Stefan; Lenhardt, Wolfgang

2017-04-01

Seismic observatories are located in remote, low-noise areas for good reason and do not probe areas of dense and sensitive infrastructure. Complementary macroseismic data provide dense, qualitative information on ground motion in populated areas. Motivated by the QCN (Quake Catcher Network), a new low-cost sensor system (Macroseismic Sensor System = MSS) has been developed to support the evaluation of macroseismic data with quantitative information on ground movement in populated and industrial areas. Scholars, alumni and teachers from a technical high school contributed substantially to this development within the Sparkling Science project Schools & Quakes and the Citizen Science project QuakeWatch Austria. The MSS uses horizontal 4.5 Hz geophones and 16Bit AD conversion, and 100 Hz sampling, formatting to MiniSeed, and continuous data transmission via LAN or WLAN to a server are controlled by an integrated microcomputer (Raspberry Pi). Real-time generation of shake and source maps (based on proxies of the PGV in successive time windows) allows for differentiation between local seismic events (e.g., traffic noise, shock close to the sensor) and signals from earthquakes or quarry blasts. The inherent noise of the MSS is about 1% of the PGV corresponding to the lower boundary of intensity I = 2, which is below the ambient noise level at stations in highly populated or industrial areas. The MSS is already being tested at locations around a quarry with regular production blasts. An expansion to a local network in the Vienna Basin will be the next step.

Anomaly Detection for Data Reduction in an Unattended Ground Sensor (UGS) Field

DTIC Science & Technology

2014-09-01

information (shown with solid lines in the diagram). Typically, this would be a mobile ad - hoc network (MANET). The clusters are connected to other nodes...interquartile ranges MANET mobile ad - hoc network OSUS Open Standards for Unattended Sensors TOC tactical operations center UAVs unmanned aerial vehicles...19b. TELEPHONE NUMBER (Include area code ) 301-394-1221 Standard Form 298 (Rev. 8/98) Prescribed by ANSI Std. Z39.18 iii Contents List of

Sapphire: Canada's Answer to Space-Based Surveillance of Orbital Objects

NASA Astrophysics Data System (ADS)

Maskell, P.; Oram, L.

The Canadian Department of National Defence is in the process of developing the Canadian Space Surveillance System (CSSS) as the main focus of the Surveillance of Space (SofS) Project. The CSSS consists of two major elements: the Sapphire System and the Sensor System Operations Centre (SSOC). The space segment of the Sapphire System is comprised of the Sapphire Satellite - an autonomous spacecraft with an electro-optical payload which will act as a contributing sensor to the United States (US) Space Surveillance Network (SSN). It will operate in a circular, sunsynchronous orbit at an altitude of approximately 750 kilometers and image a minimum of 360 space objects daily in orbits ranging from 6,000 to 40,000 kilometers in altitude. The ground segment of the Sapphire System is composed of a Spacecraft Control Center (SCC), a Satellite Processing and Scheduling Facility (SPSF), and the Sapphire Simulator. The SPSF will be responsible for data transmission, reception, and processing while the SCC will serve to control and monitor the Sapphire Satellite. Surveillance data will be received from Sapphire through two ground stations. Following processing by the SPSF, the surveillance data will then be forwarded to the SSOC. The SSOC will function as the interface between the Sapphire System and the US Joint Space Operations Center (JSpOC). The JSpOC coordinates input from various sensors around the world, all of which are a part of the SSN. The SSOC will task the Sapphire System daily and provide surveillance data to the JSpOC for correlation with data from other SSN sensors. This will include orbital parameters required to predict future positions of objects to be tracked. The SSOC receives daily tasking instructions from the JSpOC to determine which objects the Sapphire spacecraft is required to observe. The advantage of this space-based sensor over ground-based telescopes is that weather and time of day are not factors affecting observation. Thus, space-based optical surveillance does not suffer outage periods of surveillance as is the case with ground-based optical sensors. This allows a space-based sensor to obtain more data and to collect it from a more flexible vantage point. The Sapphire launch is planned for July 2011. The Sapphire spacecraft is designed to operate for a minimum of five years. It will contribute considerably to establishing a significant space capability for Canada. This and other current Canadian space initiatives, will have wide-ranging benefits in the area of National Defence.

Neural Network Substorm Identification: Enabling TREx Sensor Web Modes

NASA Astrophysics Data System (ADS)

Chaddock, D.; Spanswick, E.; Arnason, K. M.; Donovan, E.; Liang, J.; Ahmad, S.; Jackel, B. J.

2017-12-01

Transition Region Explorer (TREx) is a ground-based sensor web of optical and radio instruments that is presently being deployed across central Canada. The project consists of an array of co-located blue-line, full-colour, and near-infrared all-sky imagers, imaging riometers, proton aurora spectrographs, and GNSS systems. A key goal of the TREx project is to create the world's first (artificial) intelligent sensor web for remote sensing space weather. The sensor web will autonomously control and coordinate instrument operations in real-time. To accomplish this, we will use real-time in-line analytics of TREx and other data to dynamically switch between operational modes. An operating mode could be, for example, to have a blue-line imager gather data at a one or two orders of magnitude higher cadence than it operates for its `baseline' mode. The software decision to increase the imaging cadence would be in response to an anticipated increase in auroral activity or other programmatic requirements. Our first test for TREx's sensor web technologies is to develop the capacity to autonomously alter the TREx operating mode prior to a substorm expansion phase onset. In this paper, we present our neural network analysis of historical optical and riometer data and our ability to predict an optical onset. We explore the preliminary insights into using a neural network to pick out trends and features which it deems are similar among substorms.

Learning a detection map for a network of unattended ground sensors.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Nguyen, Hung D.; Koch, Mark William

2010-03-01

We have developed algorithms to automatically learn a detection map of a deployed sensor field for a virtual presence and extended defense (VPED) system without apriori knowledge of the local terrain. The VPED system is an unattended network of sensor pods, with each pod containing acoustic and seismic sensors. Each pod has the ability to detect and classify moving targets at a limited range. By using a network of pods we can form a virtual perimeter with each pod responsible for a certain section of the perimeter. The site's geography and soil conditions can affect the detection performance of themore » pods. Thus, a network in the field may not have the same performance as a network designed in the lab. To solve this problem we automatically estimate a network's detection performance as it is being installed at a site by a mobile deployment unit (MDU). The MDU will wear a GPS unit, so the system not only knows when it can detect the MDU, but also the MDU's location. In this paper, we demonstrate how to handle anisotropic sensor-configurations, geography, and soil conditions.« less

Advanced wireless mobile collaborative sensing network for tactical and strategic missions

NASA Astrophysics Data System (ADS)

Xu, Hao

2017-05-01

In this paper, an advanced wireless mobile collaborative sensing network will be developed. Through properly combining wireless sensor network, emerging mobile robots and multi-antenna sensing/communication techniques, we could demonstrate superiority of developed sensing network. To be concrete, heterogeneous mobile robots including unmanned aerial vehicle (UAV) and unmanned ground vehicle (UGV) are equipped with multi-model sensors and wireless transceiver antennas. Through real-time collaborative formation control, multiple mobile robots can team the best formation that can provide most accurate sensing results. Also, formatting multiple mobile robots can also construct a multiple-input multiple-output (MIMO) communication system that can provide a reliable and high performance communication network.

Cooperation among wirelessly connected static and mobile sensor nodes for surveillance applications.

PubMed

de Freitas, Edison Pignaton; Heimfarth, Tales; Vinel, Alexey; Wagner, Flávio Rech; Pereira, Carlos Eduardo; Larsson, Tony

2013-09-25

This paper presents a bio-inspired networking strategy to support the cooperation between static sensors on the ground and mobile sensors in the air to perform surveillance missions in large areas. The goal of the proposal is to provide low overhead in the communication among sensor nodes, while allocating the mobile sensors to perform sensing activities requested by the static ones. Simulations have shown that the strategy is efficient in maintaining low overhead and achieving the desired coordination.

UAV-Assisted Dynamic Clustering of Wireless Sensor Networks for Crop Health Monitoring

PubMed Central

Ammad Uddin, Mohammad; Mansour, Ali; Le Jeune, Denis; Ayaz, Mohammad; Aggoune, el-Hadi M.

2018-01-01

In this study, a crop health monitoring system is developed by using state of the art technologies including wireless sensors and Unmanned Aerial Vehicles (UAVs). Conventionally data is collected from sensor nodes either by fixed base stations or mobile sinks. Mobile sinks are considered a better choice nowadays due to their improved network coverage and energy utilization. Usually, the mobile sink is used in two ways: either it goes for random walk to find the scattered nodes and collect data, or follows a pre-defined path established by the ground network/clusters. Neither of these options is suitable in our scenario due to the factors like dynamic data collection, the strict targeted area required to be scanned, unavailability of a large number of nodes, dynamic path of the UAV, and most importantly, none of these are known in advance. The contribution of this paper is the formation of dynamic runtime clusters of field sensors by considering the above mentioned factors. Furthermore a mechanism (Bayesian classifier) is defined to select best node as cluster head. The proposed system is validated through simulation results, lab and infield experiments using concept devices. The obtained results are encouraging, especially in terms of deployment time, energy, efficiency, throughput and ease of use. PMID:29439496

UAV-Assisted Dynamic Clustering of Wireless Sensor Networks for Crop Health Monitoring.

PubMed

Uddin, Mohammad Ammad; Mansour, Ali; Jeune, Denis Le; Ayaz, Mohammad; Aggoune, El-Hadi M

2018-02-11

In this study, a crop health monitoring system is developed by using state of the art technologies including wireless sensors and Unmanned Aerial Vehicles (UAVs). Conventionally data is collected from sensor nodes either by fixed base stations or mobile sinks. Mobile sinks are considered a better choice nowadays due to their improved network coverage and energy utilization. Usually, the mobile sink is used in two ways: either it goes for random walk to find the scattered nodes and collect data, or follows a pre-defined path established by the ground network/clusters. Neither of these options is suitable in our scenario due to the factors like dynamic data collection, the strict targeted area required to be scanned, unavailability of a large number of nodes, dynamic path of the UAV, and most importantly, none of these are known in advance. The contribution of this paper is the formation of dynamic runtime clusters of field sensors by considering the above mentioned factors. Furthermore a mechanism (Bayesian classifier) is defined to select best node as cluster head. The proposed system is validated through simulation results, lab and infield experiments using concept devices. The obtained results are encouraging, especially in terms of deployment time, energy, efficiency, throughput and ease of use.

Wireless Sensor Network Handles Image Data

NASA Technical Reports Server (NTRS)

2008-01-01

To relay data from remote locations for NASA s Earth sciences research, Goddard Space Flight Center contributed to the development of "microservers" (wireless sensor network nodes), which are now used commercially as a quick and affordable means to capture and distribute geographical information, including rich sets of aerial and street-level imagery. NASA began this work out of a necessity for real-time recovery of remote sensor data. These microservers work much like a wireless office network, relaying information between devices. The key difference, however, is that instead of linking workstations within one office, the interconnected microservers operate miles away from one another. This attribute traces back to the technology s original use: The microservers were originally designed for seismology on remote glaciers and ice streams in Alaska, Greenland, and Antarctica-acquiring, storing, and relaying data wirelessly between ground sensors. The microservers boast three key attributes. First, a researcher in the field can establish a "managed network" of microservers and rapidly see the data streams (recovered wirelessly) on a field computer. This rapid feedback permits the researcher to reconfigure the network for different purposes over the course of a field campaign. Second, through careful power management, the microservers can dwell unsupervised in the field for up to 2 years, collecting tremendous amounts of data at a research location. The third attribute is the exciting potential to deploy a microserver network that works in synchrony with robotic explorers (e.g., providing ground truth validation for satellites, supporting rovers as they traverse the local environment). Managed networks of remote microservers that relay data unsupervised for up to 2 years can drastically reduce the costs of field instrumentation and data rec

New-generation security network with synergistic IP sensors

NASA Astrophysics Data System (ADS)

Peshko, Igor

2007-09-01

Global Dynamic Monitoring and Security Network (GDMSN) for real-time monitoring of (1) environmental and atmospheric conditions: chemical, biological, radiological and nuclear hazards, climate/man-induced catastrophe areas and terrorism threats; (2) water, soil, food chain quantifiers, and public health care; (3) large government/public/ industrial/ military areas is proposed. Each GDMSN branch contains stationary or mobile terminals (ground, sea, air, or space manned/unmanned vehicles) equipped with portable sensors. The sensory data are transferred via telephone, Internet, TV, security camera and other wire/wireless or optical communication lines. Each sensor is a self-registering, self-reporting, plug-and-play, portable unit that uses unified electrical and/or optical connectors and operates with IP communication protocol. The variant of the system based just on optical technologies cannot be disabled by artificial high-power radio- or gamma-pulses or sunbursts. Each sensor, being supplied with a battery and monitoring means, can be used as a separate portable unit. Military personnel, police officers, firefighters, miners, rescue teams, and nuclear power plant personnel may individually use these sensors. Terminals may be supplied with sensors essential for that specific location. A miniature "universal" optical gas sensor for specific applications in life support and monitoring systems was designed and tested. The sensor is based on the physics of absorption and/or luminescence spectroscopy. It can operate at high pressures and elevated temperatures, such as in professional and military diving equipment, submarines, underground shelters, mines, command stations, aircraft, space shuttles, etc. To enable this capability, the multiple light emitters, detectors and data processing electronics are located within a specially protected chamber.

Zone-Based Routing Protocol for Wireless Sensor Networks

PubMed Central

Venkateswarlu Kumaramangalam, Muni; Adiyapatham, Kandasamy; Kandasamy, Chandrasekaran

2014-01-01

Extensive research happening across the globe witnessed the importance of Wireless Sensor Network in the present day application world. In the recent past, various routing algorithms have been proposed to elevate WSN network lifetime. Clustering mechanism is highly successful in conserving energy resources for network activities and has become promising field for researches. However, the problem of unbalanced energy consumption is still open because the cluster head activities are tightly coupled with role and location of a particular node in the network. Several unequal clustering algorithms are proposed to solve this wireless sensor network multihop hot spot problem. Current unequal clustering mechanisms consider only intra- and intercluster communication cost. Proper organization of wireless sensor network into clusters enables efficient utilization of limited resources and enhances lifetime of deployed sensor nodes. This paper considers a novel network organization scheme, energy-efficient edge-based network partitioning scheme, to organize sensor nodes into clusters of equal size. Also, it proposes a cluster-based routing algorithm, called zone-based routing protocol (ZBRP), for elevating sensor network lifetime. Experimental results show that ZBRP out-performs interims of network lifetime and energy conservation with its uniform energy consumption among the cluster heads. PMID:27437455

Zone-Based Routing Protocol for Wireless Sensor Networks.

PubMed

Venkateswarlu Kumaramangalam, Muni; Adiyapatham, Kandasamy; Kandasamy, Chandrasekaran

2014-01-01

Extensive research happening across the globe witnessed the importance of Wireless Sensor Network in the present day application world. In the recent past, various routing algorithms have been proposed to elevate WSN network lifetime. Clustering mechanism is highly successful in conserving energy resources for network activities and has become promising field for researches. However, the problem of unbalanced energy consumption is still open because the cluster head activities are tightly coupled with role and location of a particular node in the network. Several unequal clustering algorithms are proposed to solve this wireless sensor network multihop hot spot problem. Current unequal clustering mechanisms consider only intra- and intercluster communication cost. Proper organization of wireless sensor network into clusters enables efficient utilization of limited resources and enhances lifetime of deployed sensor nodes. This paper considers a novel network organization scheme, energy-efficient edge-based network partitioning scheme, to organize sensor nodes into clusters of equal size. Also, it proposes a cluster-based routing algorithm, called zone-based routing protocol (ZBRP), for elevating sensor network lifetime. Experimental results show that ZBRP out-performs interims of network lifetime and energy conservation with its uniform energy consumption among the cluster heads.

A multi-sensor study of the impact of ground-based glaciogenic seeding on clouds and precipitation over mountains in Wyoming. Part I: Project description

NASA Astrophysics Data System (ADS)

Pokharel, Binod; Geerts, Bart

2016-12-01

The AgI Seeding Cloud Impact Investigation (ASCII) campaign was conducted in early 2012 and 2013 over two mountain ranges in southern Wyoming to examine the impact of ground-based glaciogenic seeding on snow growth in winter orographic clouds. The campaign was supported by a network of ground-based instruments, including microwave radiometers, two profiling Ka-band Micro-Rain Radars (MRRs), a Doppler on Wheels (DOW) X-band radar, and a Parsivel disdrometer. The University of Wyoming King Air operated the profiling Wyoming Cloud Radar, the Wyoming Cloud Lidar, and in situ cloud and precipitation particle probes. The characteristics of the orographic clouds, flow field, and upstream stability profiles in 27 intensive observation periods (IOPs) are described here. A composite analysis of the impact of seeding on snow growth is presented in Part II of this study (Pokharel et al., 2017).

Multi-Spectral Image Analysis for Improved Space Object Characterization

NASA Astrophysics Data System (ADS)

Duggin, M.; Riker, J.; Glass, W.; Bush, K.; Briscoe, D.; Klein, M.; Pugh, M.; Engberg, B.

The Air Force Research Laboratory (AFRL) is studying the application and utility of various ground based and space-based optical sensors for improving surveillance of space objects in both Low Earth Orbit (LEO) and Geosynchronous Earth Orbit (GEO). At present, ground-based optical and radar sensors provide the bulk of remotely sensed information on satellites and space debris, and will continue to do so into the foreseeable future. However, in recent years, the Space Based Visible (SBV) sensor was used to demonstrate that a synthesis of space-based visible data with ground-based sensor data could provide enhancements to information obtained from any one source in isolation. The incentives for space-based sensing include improved spatial resolution due to the absence of atmospheric effects and cloud cover and increased flexibility for observations. Though ground-based optical sensors can use adaptive optics to somewhat compensate for atmospheric turbulence, cloud cover and absorption are unavoidable. With recent advances in technology, we are in a far better position to consider what might constitute an ideal system to monitor our surroundings in space. This work has begun at the AFRL using detailed optical sensor simulations and analysis techniques to explore the trade space involved in acquiring and processing data from a variety of hypothetical space-based and ground-based sensor systems. In this paper, we briefly review the phenomenology and trade space aspects of what might be required in order to use multiple band-passes, sensor characteristics, and observation and illumination geometries to increase our awareness of objects in space.

Community Seismic Network (CSN)

NASA Astrophysics Data System (ADS)

Clayton, R. W.; Kohler, M. D.; Heaton, T. H.; Massari, A.; Guy, R.; Bunn, J.; Chandy, M.

2015-12-01

The CSN now has approximately 600 stations in the northern Los Angeles region. The sensors are class-C MEMs accelerometers that are packaged with backup power and data memory and are connected to a cloud-based processing system through the Internet. Most of the sensors are located in an xy-spatial network with an average minimum station spacing of 800 m. This density allows the lateral variations in ground motion to be determined, which will lead to detailed microzonation maps of the region. Approximately 100 of the sensors are located on campuses of the Los Angeles Unified School District (LAUSD), and this is part of a plan to provide schools with critical earthquake information immediately following an earthquake using the ShakeCast system. The software system in the sensors is being upgraded to allow on site measurements of PGA and PVA to be sent directly to the ShakeMap and earthquake early warning systems. More than 160 of the sensor packages are located on multiple floors of buildings with typically one or two 3-component sensors per floor. With these data we can identify traveling waves in the building, as well as determine the eigenfrequencies and mode shapes. By monitoring these quantities with high spatial density before, during, and after a major shaking event, we hope to determine the state of health of the structure.

Development of Smart Grid for Community and Cyber based Landslide Hazard Monitoring and Early Warning System

NASA Astrophysics Data System (ADS)

Karnawati, D.; Wilopo, W.; Fathani, T. F.; Fukuoka, H.; Andayani, B.

2012-12-01

A Smart Grid is a cyber-based tool to facilitate a network of sensors for monitoring and communicating the landslide hazard and providing the early warning. The sensor is designed as an electronic sensor installed in the existing monitoring and early warning instruments, and also as the human sensors which comprise selected committed-people at the local community, such as the local surveyor, local observer, member of the local task force for disaster risk reduction, and any person at the local community who has been registered to dedicate their commitments for sending reports related to the landslide symptoms observed at their living environment. This tool is designed to be capable to receive up to thousands of reports/information at the same time through the electronic sensors, text message (mobile phone), the on-line participatory web as well as various social media such as Twitter and Face book. The information that should be recorded/ reported by the sensors is related to the parameters of landslide symptoms, for example the progress of cracks occurrence, ground subsidence or ground deformation. Within 10 minutes, this tool will be able to automatically elaborate and analyse the reported symptoms to predict the landslide hazard and risk levels. The predicted level of hazard/ risk can be sent back to the network of electronic and human sensors as the early warning information. The key parameters indicating the symptoms of landslide hazard were recorded/ monitored by the electrical and the human sensors. Those parameters were identified based on the investigation on geological and geotechnical conditions, supported with the laboratory analysis. The cause and triggering mechanism of landslide in the study area was also analysed in order to define the critical condition to launch the early warning. However, not only the technical but also social system were developed to raise community awareness and commitments to serve the mission as the human sensors, which will be responsible for reporting and informing the early warning. Therefore, a community empowerment and encouragement program through public education was conducted. Strategy and approach for this program was formulated based on the socio-engineering investigation. Finally, the results of technical and social engineering investigations, have been elaborated to further enhance the performance of expert system of the Smart Grid, in order to completely establish this system as an innovative and effective tool for the landslide monitoring and early warning in tropical-developing country.

Maritime Aerosol Network optical depth measurements and comparison with satellite retrievals from various different sensors

NASA Astrophysics Data System (ADS)

Smirnov, Alexander; Petrenko, Maksym; Ichoku, Charles; Holben, Brent N.

2017-10-01

The paper reports on the current status of the Maritime Aerosol Network (MAN) which is a component of the Aerosol Robotic Network (AERONET). A public domain web-based data archive dedicated to MAN activity can be found at https://aeronet.gsfc.nasa.gov/new_web/maritime_aerosol_network.html . Since 2006 over 450 cruises were completed and the data archive consists of more than 6000 measurement days. In this work, we present MAN observations collocated with MODIS Terra, MODIS Aqua, MISR, POLDER, SeaWIFS, OMI, and CALIOP spaceborne aerosol products using a modified version of the Multi-Sensor Aerosol Products Sampling System (MAPSS) framework. Because of different spatio-temporal characteristics of the analyzed products, the number of MAN data points collocated with spaceborne retrievals varied between 1500 matchups for MODIS to 39 for CALIOP (as of August 2016). Despite these unavoidable sampling biases, latitudinal dependencies of AOD differences for all satellite sensors, except for SeaWIFS and POLDER, showed positive biases against ground truth (i.e. MAN) in the southern latitudes (<50° S), and substantial scatter in the Northern Atlantic "dust belt" (5°-15° N). Our analysis did not intend to determine whether satellite retrievals are within claimed uncertainty boundaries, but rather show where bias exists and corrections are needed.

Intelligent detection and identification in fiber-optical perimeter intrusion monitoring system based on the FBG sensor network

NASA Astrophysics Data System (ADS)

Wu, Huijuan; Qian, Ya; Zhang, Wei; Li, Hanyu; Xie, Xin

2015-12-01

A real-time intelligent fiber-optic perimeter intrusion detection system (PIDS) based on the fiber Bragg grating (FBG) sensor network is presented in this paper. To distinguish the effects of different intrusion events, a novel real-time behavior impact classification method is proposed based on the essential statistical characteristics of signal's profile in the time domain. The features are extracted by the principal component analysis (PCA), which are then used to identify the event with a K-nearest neighbor classifier. Simulation and field tests are both carried out to validate its effectiveness. The average identification rate (IR) for five sample signals in the simulation test is as high as 96.67%, and the recognition rate for eight typical signals in the field test can also be achieved up to 96.52%, which includes both the fence-mounted and the ground-buried sensing signals. Besides, critically high detection rate (DR) and low false alarm rate (FAR) can be simultaneously obtained based on the autocorrelation characteristics analysis and a hierarchical detection and identification flow.

Coupling Flux Towers and Networks with Proximal and Remote Sensing Data: New Tools to Collect and Share Time-Synchronized Hourly Fluxes

NASA Astrophysics Data System (ADS)

Burba, George; Avenson, Tom; Burkart, Andreas; Gamon, John; Guan, Kaiyu; Julitta, Tommaso; Pastorello, Gilberto; Sakowska, Karolina

2017-04-01

Multiple hundreds of flux towers are presently operational as standalone projects and as parts of larger networks. However, the vast majority of these towers do not allow straight-forward coupling with satellite data, and even fewer have optical sensors for validation of satellite products and upscaling from field to regional levels. In 2016, new tools to collect, process, and share time-synchronized flux data from multiple towers were developed and deployed globally. Originally designed to automate site and data management, these new tools can also be effective in coupling tower data with satellite data due to the following present capabilities: Fully automated FluxSuite system combines hardware, software and web-services, and does not require an expert to run it It can be incorporated into a new flux station or added to a present station, using weatherized remotely-accessible microcomputer, SmartFlux2 It utilizes EddyPro software to calculate fully-processed fluxes and footprints in near-realtime, alongside radiation, optical, weather and soil data All site data are merged into a single quality-controlled file timed using PTP time protocol Data from optical sensors can be integrated into this complete dataset via compatible dataloggers Multiple stations can be linked into time-synchronized network with automated reports and email alerts visible to PIs in real-time Remote sensing researchers without stations can form "virtual networks" of stations by collaborating with tower PIs from different physical networks The present system can then be utilized to couple ground data with satellite data via the following proposed concept: GPS-driven PTP protocol will synchronize instrumentation within the station, different stations with each other, and all of these to satellite data to precisely align optical and flux data in time Footprint size and coordinates computed and stored with flux data will help correctly align footprints and satellite motion to precisely align optical and flux data in space Current flux towers can be augmented with ground optical sensors and use standard routines to deliver continuous products (e.g. SIF, PRI, NDVI, etc.) based on automated field spectrometers (e.g., FloX and RoX, etc.) and other optical systems Schedule can be developed to point ground optical sensor into the footprint, or to run leaf chamber measurements in the footprint, at the same time with the satellite or UAV above the footprint Full snapshot of the satellite pixel can then be constructed including leaf-level, ground optical sensor, and flux measurements from the same footprint area closely coupled with the satellite measurements to help interpret satellite data, validate models, and improve upscaling Several dozens of new towers already operational globally can be readily adapted for the proposed concept. In addition, over 500 active traditional towers can be updated to synchronize their data with satellite measurements. This presentation will show how FluxSuite system is used by major networks, and describe the concept of how this approach can be utilized to couple satellite and tower data.

Long-range acoustic observations of the Eyjafjallajökull eruption, Iceland, April-May 2010

NASA Astrophysics Data System (ADS)

Matoza, Robin S.; Vergoz, Julien; Le Pichon, Alexis; Ceranna, Lars; Green, David N.; Evers, Läslo G.; Ripepe, Maurizio; Campus, Paola; Liszka, Ludwik; Kvaerna, Tormod; Kjartansson, Einar; Höskuldsson, Ármann

2011-03-01

The April-May 2010 summit eruption of Eyjafjallajökull, Iceland, was recorded by 14 atmospheric infrasound sensor arrays at ranges between 1,700 and 3,700 km, indicating that infrasound from modest-size eruptions can propagate for thousands of kilometers in atmospheric waveguides. Although variations in both atmospheric propagation conditions and background noise levels at the sensors generate fluctuations in signal-to-noise ratios and signal detectability, array processing techniques successfully discriminate between volcanic infrasound and ambient coherent and incoherent noise. The current global infrasound network is significantly more dense and sensitive than any previously operated network and signals from large volcanic explosions are routinely recorded. Because volcanic infrasound is generated during the explosive release of fluid into the atmosphere, it is a strong indicator that an eruption has occurred. Therefore, long-range infrasonic monitoring may aid volcanic explosion detection by complementing other monitoring technologies, especially in remote regions with sparse ground-based instrument networks.

A radar-enabled collaborative sensor network integrating COTS technology for surveillance and tracking.

PubMed

Kozma, Robert; Wang, Lan; Iftekharuddin, Khan; McCracken, Ernest; Khan, Muhammad; Islam, Khandakar; Bhurtel, Sushil R; Demirer, R Murat

2012-01-01

The feasibility of using Commercial Off-The-Shelf (COTS) sensor nodes is studied in a distributed network, aiming at dynamic surveillance and tracking of ground targets. Data acquisition by low-cost (<$50 US) miniature low-power radar through a wireless mote is described. We demonstrate the detection, ranging and velocity estimation, classification and tracking capabilities of the mini-radar, and compare results to simulations and manual measurements. Furthermore, we supplement the radar output with other sensor modalities, such as acoustic and vibration sensors. This method provides innovative solutions for detecting, identifying, and tracking vehicles and dismounts over a wide area in noisy conditions. This study presents a step towards distributed intelligent decision support and demonstrates effectiveness of small cheap sensors, which can complement advanced technologies in certain real-life scenarios.

Urban-scale mapping of PM2.5 distribution via data fusion between high-density sensor network and MODIS Aerosol Optical Depth

NASA Astrophysics Data System (ADS)

Ba, Yu Tao; xian Liu, Bao; Sun, Feng; Wang, Li hua; Tang, Yu jia; Zhang, Da wei

2017-04-01

High-resolution mapping of PM2.5 is the prerequisite for precise analytics and subsequent anti-pollution interventions. Considering the large variances of particulate distribution, urban-scale mapping is challenging either with ground-based fixed stations, with satellites or via models. In this study, a dynamic fusion method between high-density sensor network and MODIS Aerosol Optical Depth (AOD) was introduced. The sensor network was deployed in Beijing ( > 1000 fixed monitors across 16000 km2 area) to provide raw observations with high temporal resolution (sampling interval < 1 hour), high spatial resolution in flat areas ( < 1 km), and low spatial resolution in mountainous areas ( > 5 km). The MODIS AOD was calibrated to provide distribution map with low temporal resolution (daily) and moderate spatial resolution ( = 3 km). By encoding the data quality and defects (e.g. could, reflectance, abnormal), a hybrid interpolation procedure with cross-validation generated PM2.5 distribution with both high temporal and spatial resolution. Several no-pollutant and high-pollution periods were tested to validate the proposed fusion method for capturing the instantaneous patterns of PM2.5 emission.

IBE-Lite: a lightweight identity-based cryptography for body sensor networks.

PubMed

Tan, Chiu C; Wang, Haodong; Zhong, Sheng; Li, Qun

2009-11-01

A body sensor network (BSN) is a network of sensors deployed on a person's body for health care monitoring. Since the sensors collect personal medical data, security and privacy are important components in a BSN. In this paper, we developed IBE-Lite, a lightweight identity-based encryption suitable for sensors in a BSN. We present protocols based on IBE-Lite that balance security and privacy with accessibility and perform evaluation using experiments conducted on commercially available sensors.

Wireless Sensor Buoys for Perimeter Security of Military Vessels and Seabases

DTIC Science & Technology

2015-12-01

however, additional sensors utilizing modern technology and a self -forming, as well as self - healing , network could further diminish attacks against...Space SSDF Ship’s Self -Defense Force UAV Unmanned Aerial Vehicle UGS Unattended Ground Sensor USB Universal Serial Bus USMC United States Marine...conditions may delay their reaction resulting in the attacking surface craft entering into a critically close position. The Ship’s Self -Defense

Improving Quantitative Precipitation Estimation via Data Fusion of High-Resolution Ground-based Radar Network and CMORPH Satellite-based Product

NASA Astrophysics Data System (ADS)

Cifelli, R.; Chen, H.; Chandrasekar, V.; Xie, P.

2015-12-01

A large number of precipitation products at multi-scales have been developed based upon satellite, radar, and/or rain gauge observations. However, how to produce optimal rainfall estimation for a given region is still challenging due to the spatial and temporal sampling difference of different sensors. In this study, we develop a data fusion mechanism to improve regional quantitative precipitation estimation (QPE) by utilizing satellite-based CMORPH product, ground radar measurements, as well as numerical model simulations. The CMORPH global precipitation product is essentially derived based on retrievals from passive microwave measurements and infrared observations onboard satellites (Joyce et al. 2004). The fine spatial-temporal resolution of 0.05o Lat/Lon and 30-min is appropriate for regional hydrologic and climate studies. However, it is inadequate for localized hydrometeorological applications such as urban flash flood forecasting. Via fusion of the Regional CMORPH product and local precipitation sensors, the high-resolution QPE performance can be improved. The area of interest is the Dallas-Fort Worth (DFW) Metroplex, which is the largest land-locked metropolitan area in the U.S. In addition to an NWS dual-polarization S-band WSR-88DP radar (i.e., KFWS radar), DFW hosts the high-resolution dual-polarization X-band radar network developed by the center for Collaborative Adaptive Sensing of the Atmosphere (CASA). This talk will present a general framework of precipitation data fusion based on satellite and ground observations. The detailed prototype architecture of using regional rainfall instruments to improve regional CMORPH precipitation product via multi-scale fusion techniques will also be discussed. Particularly, the temporal and spatial fusion algorithms developed for the DFW Metroplex will be described, which utilizes CMORPH product, S-band WSR-88DP, and X-band CASA radar measurements. In order to investigate the uncertainties associated with each individual product and demonstrate the precipitation data fusion performance, both individual and fused QPE products are evaluated using rainfall measurements from a disdrometer and gauge network.

Comparison of the KSC-ER Cloud-to-Ground Lightning Surveillance System (CGLSS) and the U.S. National Lightning Detection Network(TradeMark)(NLDN)

NASA Technical Reports Server (NTRS)

Ward, Jennifer G.; Cummins, Kenneth L.; Krider, E. Philip

2007-01-01

The NASA Kennedy Space Center (KSC) and Air Force Eastern Range (ER) use data from two cloud-to-ground lightning detection networks, CGLSS and NLDN, during ground and launch operations at the KSC-ER. For these applications, it is very important to understand the location accuracy and detection efficiency of each network near the KSC-ER. If a cloud-to-ground (CG) lightning strike is missed or mis-located by even a small amount, the result could have significant safety implications, require expensive retests, or create unnecessary delays or scrubs in launches. Therefore, it is important to understand the performance of each lightning detection system in considerable detail. To evaluate recent upgrades in the CGLSS sensors in 2000 and the entire NLDN in 2002- 2003, we have compared. measurements provided by these independent networks in the summers of 2005 and 2006. Our analyses have focused on the fraction of first strokes reported individually and in-common by each network (flash detection efficiency), the spatial separation between the strike points reported by both networks (relative location accuracy), and the values of the estimated peak current, Ip, reported by each network. The results within 100 km of the KSC-ER show that the networks produce very similar values of Ip (except for a small scaling difference) and that the relative location accuracy is consistent with model estimates that give median values of 200-300m for the CGLSS and 600-700m for the NLDN in the region of the KSC-ER. Because of differences in the network geometries and sensor gains, the NLDN does not report 10-20% of the flashes that have a low Ip (2 kA < |Ip| < 16 kA), both networks report 99 % of the flashes that have intermediate values of Ip (16< |Ip| < 50 kA), and the CGLSS fails to report 20-30% of the high-current events (|Ip| >=0 kA).

Optimizing Cluster Heads for Energy Efficiency in Large-Scale Heterogeneous Wireless Sensor Networks

DOE PAGES

Gu, Yi; Wu, Qishi; Rao, Nageswara S. V.

2010-01-01

Many complex sensor network applications require deploying a large number of inexpensive and small sensors in a vast geographical region to achieve quality through quantity. Hierarchical clustering is generally considered as an efficient and scalable way to facilitate the management and operation of such large-scale networks and minimize the total energy consumption for prolonged lifetime. Judicious selection of cluster heads for data integration and communication is critical to the success of applications based on hierarchical sensor networks organized as layered clusters. We investigate the problem of selecting sensor nodes in a predeployed sensor network to be the cluster heads tomore » minimize the total energy needed for data gathering. We rigorously derive an analytical formula to optimize the number of cluster heads in sensor networks under uniform node distribution, and propose a Distance-based Crowdedness Clustering algorithm to determine the cluster heads in sensor networks under general node distribution. The results from an extensive set of experiments on a large number of simulated sensor networks illustrate the performance superiority of the proposed solution over the clustering schemes based on k -means algorithm.« less

Multi-spectral image analysis for improved space object characterization

NASA Astrophysics Data System (ADS)

Glass, William; Duggin, Michael J.; Motes, Raymond A.; Bush, Keith A.; Klein, Meiling

2009-08-01

The Air Force Research Laboratory (AFRL) is studying the application and utility of various ground-based and space-based optical sensors for improving surveillance of space objects in both Low Earth Orbit (LEO) and Geosynchronous Earth Orbit (GEO). This information can be used to improve our catalog of space objects and will be helpful in the resolution of satellite anomalies. At present, ground-based optical and radar sensors provide the bulk of remotely sensed information on satellites and space debris, and will continue to do so into the foreseeable future. However, in recent years, the Space-Based Visible (SBV) sensor was used to demonstrate that a synthesis of space-based visible data with ground-based sensor data could provide enhancements to information obtained from any one source in isolation. The incentives for space-based sensing include improved spatial resolution due to the absence of atmospheric effects and cloud cover and increased flexibility for observations. Though ground-based optical sensors can use adaptive optics to somewhat compensate for atmospheric turbulence, cloud cover and absorption are unavoidable. With recent advances in technology, we are in a far better position to consider what might constitute an ideal system to monitor our surroundings in space. This work has begun at the AFRL using detailed optical sensor simulations and analysis techniques to explore the trade space involved in acquiring and processing data from a variety of hypothetical space-based and ground-based sensor systems. In this paper, we briefly review the phenomenology and trade space aspects of what might be required in order to use multiple band-passes, sensor characteristics, and observation and illumination geometries to increase our awareness of objects in space.

Wireless Sensing Opportunities for Aerospace Applications

NASA Technical Reports Server (NTRS)

Wilson, William; Atkinson, Gary

2007-01-01

Wireless sensors and sensor networks is an emerging technology area with many applications within the aerospace industry. Integrated vehicle health monitoring (IVHM) of aerospace vehicles is needed to ensure the safety of the crew and the vehicle, yet often high costs, weight, size and other constraints prevent the incorporation of instrumentation onto spacecraft. This paper presents a few of the areas such as IVHM, where new wireless sensing technology is needed on both existing vehicles as well as future spacecraft. From ground tests to inflatable structures to the International Space Station, many applications could receive benefits from small, low power, wireless sensors. This paper also highlights some of the challenges that need to overcome when implementing wireless sensor networks for aerospace vehicles.

Monitoring of Carbon Dioxide and Methane Plumes from Combined Ground-Airborne Sensors

NASA Astrophysics Data System (ADS)

Jacob, Jamey; Mitchell, Taylor; Honeycutt, Wes; Materer, Nicholas; Ley, Tyler; Clark, Peter

2016-11-01

A hybrid ground-airborne sensing network for real-time plume monitoring of CO2 and CH4 for carbon sequestration is investigated. Conventional soil gas monitoring has difficulty in distinguishing gas flux signals from leakage with those associated with meteorologically driven changes. A low-cost, lightweight sensor system has been developed and implemented onboard a small unmanned aircraft and is combined with a large-scale ground network that measures gas concentration. These are combined with other atmospheric diagnostics, including thermodynamic data and velocity from ultrasonic anemometers and multi-hole probes. To characterize the system behavior and verify its effectiveness, field tests have been conducted with simulated discharges of CO2 and CH4 from compressed gas tanks to mimic leaks and generate gaseous plumes, as well as field tests over the Farnsworth CO2-EOR site in the Anadarko Basin. Since the sensor response time is a function of vehicle airspeed, dynamic calibration models are required to determine accurate location of gas concentration in space and time. Comparisons are made between the two tests and results compared with historical models combining both flight and atmospheric dynamics. Supported by Department of Energy Award DE-FE0012173.

Toward Continental-scale Rainfall Monitoring Using Commercial Microwave Links From Cellular Communication Networks

NASA Astrophysics Data System (ADS)

Uijlenhoet, R.; Leijnse, H.; Overeem, A.

2017-12-01

Accurate and timely surface precipitation measurements are crucial for water resources management, agriculture, weather prediction, climate research, as well as ground validation of satellite-based precipitation estimates. However, the majority of the land surface of the earth lacks such data, and in many parts of the world the density of surface precipitation gauging networks is even rapidly declining. This development can potentially be counteracted by using received signal level data from the enormous number of microwave links used worldwide in commercial cellular communication networks. Along such links, radio signals propagate from a transmitting antenna at one base station to a receiving antenna at another base station. Rain-induced attenuation and, subsequently, path-averaged rainfall intensity can be retrieved from the signal's attenuation between transmitter and receiver. We have previously shown how one such a network can be used to retrieve the space-time dynamics of rainfall for an entire country (The Netherlands, ˜35,500 km2), based on an unprecedented number of links (˜2,400) and a rainfall retrieval algorithm that can be applied in real time. This demonstrated the potential of such networks for real-time rainfall monitoring, in particular in those parts of the world where networks of dedicated ground-based rainfall sensors are often virtually absent. The presentation will focus on the potential for upscaling this technique to continental-scale rainfall monitoring in Europe. In addition, several examples of recent applications of this technique on other continents (South America, Africa, Asia and Australia) will be given.

Communications for unattended sensor networks

NASA Astrophysics Data System (ADS)

Nemeroff, Jay L.; Angelini, Paul; Orpilla, Mont; Garcia, Luis; DiPierro, Stefano

2004-07-01

The future model of the US Army's Future Combat Systems (FCS) and the Future Force reflects a combat force that utilizes lighter armor protection than the current standard. Survival on the future battlefield will be increased by the use of advanced situational awareness provided by unattended tactical and urban sensors that detect, identify, and track enemy targets and threats. Successful implementation of these critical sensor fields requires the development of advanced sensors, sensor and data-fusion processors, and a specialized communications network. To ensure warfighter and asset survivability, the communications must be capable of near real-time dissemination of the sensor data using robust, secure, stealthy, and jam resistant links so that the proper and decisive action can be taken. Communications will be provided to a wide-array of mission-specific sensors that are capable of processing data from acoustic, magnetic, seismic, and/or Chemical, Biological, Radiological, and Nuclear (CBRN) sensors. Other, more powerful, sensor node configurations will be capable of fusing sensor data and intelligently collect and process data images from infrared or visual imaging cameras. The radio waveform and networking protocols being developed under the Soldier Level Integrated Communications Environment (SLICE) Soldier Radio Waveform (SRW) and the Networked Sensors for the Future Force Advanced Technology Demonstration are part of an effort to develop a common waveform family which will operate across multiple tactical domains including dismounted soldiers, ground sensor, munitions, missiles and robotics. These waveform technologies will ultimately be transitioned to the JTRS library, specifically the Cluster 5 requirement.

Differentially Private Distributed Sensing

DOE Office of Scientific and Technical Information (OSTI.GOV)

Fink, Glenn A.

The growth of the Internet of Things (IoT) creates the possibility of decentralized systems of sensing and actuation, potentially on a global scale. IoT devices connected to cloud networks can offer Sensing and Actuation as a Service (SAaaS) enabling networks of sensors to grow to a global scale. But extremely large sensor networks can violate privacy, especially in the case where IoT devices are mobile and connected directly to the behaviors of people. The thesis of this paper is that by adapting differential privacy (adding statistically appropriate noise to query results) to groups of geographically distributed sensors privacy could bemore » maintained without ever sending all values up to a central curator and without compromising the overall accuracy of the data collected. This paper outlines such a scheme and performs an analysis of differential privacy techniques adapted to edge computing in a simulated sensor network where ground truth is known. The positive and negative outcomes of employing differential privacy in distributed networks of devices are discussed and a brief research agenda is presented.« less

A survey on bio inspired meta heuristic based clustering protocols for wireless sensor networks

NASA Astrophysics Data System (ADS)

Datta, A.; Nandakumar, S.

2017-11-01

Recent studies have shown that utilizing a mobile sink to harvest and carry data from a Wireless Sensor Network (WSN) can improve network operational efficiency as well as maintain uniform energy consumption by the sensor nodes in the network. Due to Sink mobility, the path between two sensor nodes continuously changes and this has a profound effect on the operational longevity of the network and a need arises for a protocol which utilizes minimal resources in maintaining routes between the mobile sink and the sensor nodes. Swarm Intelligence based techniques inspired by the foraging behavior of ants, termites and honey bees can be artificially simulated and utilized to solve real wireless network problems. The author presents a brief survey on various bio inspired swarm intelligence based protocols used in routing data in wireless sensor networks while outlining their general principle and operation.

Geospace Science from Ground-based Magnetometer Arrays: Advances in Sensors, Data Collection, and Data Integration

NASA Astrophysics Data System (ADS)

Mann, Ian; Chi, Peter

2016-07-01

Networks of ground-based magnetometers now provide the basis for the diagnosis of magnetic disturbances associated with solar wind-magnetosphere-ionosphere coupling on a truly global scale. Advances in sensor and digitisation technologies offer increases in sensitivity in fluxgate, induction coil, and new micro-sensor technologies - including the promise of hybrid sensors. Similarly, advances in remote connectivity provide the capacity for truly real-time monitoring of global dynamics at cadences sufficient for monitoring and in many cases resolving system level spatio-temporal ambiguities especially in combination with conjugate satellite measurements. A wide variety of the plasmaphysical processes active in driving geospace dynamics can be monitored based on the response of the electrical current system, including those associated with changes in global convection, magnetospheric substorms and nightside tail flows, as well as due to solar wind changes in both dynamic pressure and in response to rotations of the direction of the IMF. Significantly, any changes to the dynamical system must be communicated by the propagation of long-period Alfven and/or compressional waves. These wave populations hence provide diagnostics for not only the energy transport by the wave fields themselves, but also provide a mechanism for diagnosing the structure of the background plasma medium through which the waves propagate. Ultra-low frequency (ULF) waves are especially significant in offering a monitor for mass density profiles, often invisible to particle detectors because of their very low energy, through the application of a variety of magneto-seismology and cross-phase techniques. Renewed scientific interest in the plasma waves associated with near-Earth substorm dynamics, including magnetosphere-ionosphere coupling at substorm onset and their relation to magnetotail flows, as well the importance of global scale ultra-low frequency waves for the energisation, transport, acceleration, and loss of electrons in the radiation belts promise high profile science returns. Integrated, global scale data products also have potential importance and application for real-time monitoring of the space weather threats to electrical power grids from geomagnetically induced currents. Such data exploitation increasingly relies on the collaborations between multiple national magnetometer arrays to generate single data products with common file format and data properties. We review advances in geospace science which can be delivered by networks of ground-based magnetometers - in terms of advances in sensors, data collection, and data integration - including through collaborations within the Ultra-Large Terrestrial International Magnetometer Array (ULTIMA) consortium.

Experience with Delay-Tolerant Networking from Orbit

NASA Technical Reports Server (NTRS)

Ivancic, W.; Eddy, W. M.; Stewart, D.; Wood, L.; Northam, J.; Jackson, C.

2010-01-01

We describe the first use from space of the Bundle Protocol for Delay-Tolerant Networking (DTN) and lessons learned from experiments made and experience gained with this protocol. The Disaster Monitoring Constellation (DMC), constructed by Surrey Satellite Technology Ltd (SSTL), is a multiple-satellite Earth-imaging low-Earth-orbit sensor network in which recorded image swaths are stored onboard each satellite and later downloaded from the satellite payloads to a ground station. Store-and-forward of images with capture and later download gives each satellite the characteristics of a node in a disruption-tolerant network. Originally developed for the Interplanetary Internet, DTNs are now under investigation in an Internet Research Task Force (IRTF) DTN research group (RG), which has developed a bundle architecture and protocol. The DMC is technically advanced in its adoption of the Internet Protocol (IP) for its imaging payloads and for satellite command and control, based around reuse of commercial networking and link protocols. These satellites use of IP has enabled earlier experiments with the Cisco router in Low Earth Orbit (CLEO) onboard the constellation s UK-DMC satellite. Earth images are downloaded from the satellites using a custom IP-based high-speed transfer protocol developed by SSTL, Saratoga, which tolerates unusual link environments. Saratoga has been documented in the Internet Engineering Task Force (IETF) for wider adoption. We experiment with the use of DTNRG bundle concepts onboard the UK-DMC satellite, by examining how Saratoga can be used as a DTN convergence layer to carry the DTNRG Bundle Protocol, so that sensor images can be delivered to ground stations and beyond as bundles. Our practical experience with the first successful use of the DTNRG Bundle Protocol in a space environment gives us insights into the design of the Bundle Protocol and enables us to identify issues that must be addressed before wider deployment of the Bundle Protocol. Published in 2010 by John Wiley & Sons, Ltd. KEY WORDS: Internet; UK-DMC; satellite; Delay-Tolerant Networking (DTN); Bundle Protocol

Preliminary analysis of the JAPE ground vehicle test data with an artificial neural network classifier

NASA Technical Reports Server (NTRS)

Larsen, Nathan F.; Carnes, Ben L.

1993-01-01

Remotely sensing and classifying military vehicles in a battlefield environment have been the source of much research over the past 20 years. The ability to know where threat vehicles are located is an obvious advantage to military personnel. In the past active methods of ground vehicle detection such as radar have been used, but with the advancement of technology to locate these active sensors, passive sensors are preferred. Passive sensors detect acoustic emissions, seismic movement, electromagnetic radiation, etc., produced by the target and use this information to describe it. Deriving the mathematical models to classify vehicles in this manner has been, and is, quite complex and not always reliable. However, with the resurgence of artificial neural network (ANN) research in the past few years, developing models for this work may be a thing of the past. Preliminary results from an ANN analysis to the tank signatures recorded at the Joint Acoustic Propagation Experiment (JAPE) at the US Army White Sands Missile Range, NM, in July 1991, are presented.

How well does WWLLN reproduce the satellite-observed distribution of flashes during the 2007-2012 time period?

NASA Astrophysics Data System (ADS)

Allen, D. J.; Pickering, K. E.; Ring, A.; Holzworth, R. H.

2013-12-01

Lightning is the dominant source of nitrogen oxides (NOx) involved in the production of ozone in the middle and upper troposphere in the tropics and in summer in the midlatitudes. Therefore it is imperative that the lightning NOx (LNOx) source strength per flash be better constrained. This process requires accurate information on the location and timing of lightning flashes. In the past fifteen years satellite-based lightning monitoring by the Optical Transient Detector (OTD) and Lightning Imaging Sensor (LIS) has greatly increased our understanding of the global distribution of lightning as a function of season and time-of-day. However, detailed information at higher temporal resolutions is only available for limited regions where ground-based networks such as the United States National Lightning Detection Network (NLDN) exist. In 2004, the ground-based World Wide Lightning Location Network (WWLLN) was formed with the goal of providing continuous flash rate information over the entire globe. It detects very low frequency (VLF) radio waves emitted by lightning with a detection efficiency (DE) that varies with stroke energy, time-of-day, surface type, and network coverage. This study evaluated the DE of WWLLN strokes relative to climatological OTD/LIS flashes using data from the 2007 to 2012 time period, a period during which the mean number of working sensors increased from 28 to 53. The analysis revealed that the mean global DE increased from 5% in 2007 to 13% in 2012. Regional variations were substantial with mean 2012 DEs of 5-10% over much of Argentina, Africa, and Asia and 15-30% over much of the Atlantic, Pacific, and Indian Oceans, the United States and the Maritime Continent. Detection-efficiency adjusted WWLLN flash rates were then compared to NLDN-based flash rates. Spatial correlations for individual summer months ranged from 0.66 to 0.93. Temporal correlations are currently being examined for regions of the U.S. and will also be shown.

Effects of Data Quality on the Characterization of Aerosol Properties from Multiple Sensors

NASA Technical Reports Server (NTRS)

Petrenko, Maksym; Ichoku, Charles; Leptoukh, Gregory

2011-01-01

Cross-comparison of aerosol properties between ground-based and spaceborne measurements is an important validation technique that helps to investigate the uncertainties of aerosol products acquired using spaceborne sensors. However, it has been shown that even minor differences in the cross-characterization procedure may significantly impact the results of such validation. Of particular consideration is the quality assurance I quality control (QA/QC) information - an auxiliary data indicating a "confidence" level (e.g., Bad, Fair, Good, Excellent, etc.) conferred by the retrieval algorithms on the produced data. Depending on the treatment of available QA/QC information, a cross-characterization procedure has the potential of filtering out invalid data points, such as uncertain or erroneous retrievals, which tend to reduce the credibility of such comparisons. However, under certain circumstances, even high QA/QC values may not fully guarantee the quality of the data. For example, retrievals in proximity of a cloud might be particularly perplexing for an aerosol retrieval algorithm, resulting in an invalid data that, nonetheless, could be assigned a high QA/QC confidence. In this presentation, we will study the effects of several QA/QC parameters on cross-characterization of aerosol properties between the data acquired by multiple spaceborne sensors. We will utilize the Multi-sensor Aerosol Products Sampling System (MAPSS) that provides a consistent platform for multi-sensor comparison, including collocation with measurements acquired by the ground-based Aerosol Robotic Network (AERONET), The multi-sensor spaceborne data analyzed include those acquired by the Terra-MODIS, Aqua-MODIS, Terra-MISR, Aura-OMI, Parasol-POLDER, and CalipsoCALIOP satellite instruments.

Bio-inspired UAV routing, source localization, and acoustic signature classification for persistent surveillance

NASA Astrophysics Data System (ADS)

Burman, Jerry; Hespanha, Joao; Madhow, Upamanyu; Pham, Tien

2011-06-01

A team consisting of Teledyne Scientific Company, the University of California at Santa Barbara and the Army Research Laboratory* is developing technologies in support of automated data exfiltration from heterogeneous battlefield sensor networks to enhance situational awareness for dismounts and command echelons. Unmanned aerial vehicles (UAV) provide an effective means to autonomously collect data from a sparse network of unattended ground sensors (UGSs) that cannot communicate with each other. UAVs are used to reduce the system reaction time by generating autonomous collection routes that are data-driven. Bio-inspired techniques for search provide a novel strategy to detect, capture and fuse data. A fast and accurate method has been developed to localize an event by fusing data from a sparse number of UGSs. This technique uses a bio-inspired algorithm based on chemotaxis or the motion of bacteria seeking nutrients in their environment. A unique acoustic event classification algorithm was also developed based on using swarm optimization. Additional studies addressed the problem of routing multiple UAVs, optimally placing sensors in the field and locating the source of gunfire at helicopters. A field test was conducted in November of 2009 at Camp Roberts, CA. The field test results showed that a system controlled by bio-inspired software algorithms can autonomously detect and locate the source of an acoustic event with very high accuracy and visually verify the event. In nine independent test runs of a UAV, the system autonomously located the position of an explosion nine times with an average accuracy of 3 meters. The time required to perform source localization using the UAV was on the order of a few minutes based on UAV flight times. In June 2011, additional field tests of the system will be performed and will include multiple acoustic events, optimal sensor placement based on acoustic phenomenology and the use of the International Technology Alliance (ITA) Sensor Network Fabric (IBM).

Development of a low cost unmanned aircraft system for atmospheric carbon dioxide leak detection

NASA Astrophysics Data System (ADS)

Mitchell, Taylor Austin

Carbon sequestration, the storage of carbon dioxide gas underground, has the potential to reduce global warming by removing a greenhouse gas from the atmosphere. These storage sites, however, must first be monitored to detect if carbon dioxide is leaking back out to the atmosphere. As an alternative to traditional large ground-based sensor networks to monitor CO2 levels for leaks, unmanned aircraft offer the potential to perform in-situ atmospheric leak detection over large areas for a fraction of the cost. This project developed a proof-of-concept sensor system to map relative carbon dioxide levels to detect potential leaks. The sensor system included a Sensair K-30 FR CO2 sensor, GPS, and altimeter connected an Arduino microcontroller which logged data to an onboard SD card. Ground tests were performed to verify and calibrate the system including wind tunnel tests to determine the optimal configuration of the system for the quickest response time (4-8 seconds based upon flowrate). Tests were then conducted over a controlled release of CO 2 in addition to over controlled rangeland fires which released carbon dioxide over a large area as would be expected from a carbon sequestration source. 3D maps of carbon dioxide were developed from the system telemetry that clearly illustrated increased CO2 levels from the fires. These tests demonstrated the system's ability to detect increased carbon dioxide concentrations in the atmosphere.

Comparison and Intercalibration of Vegetation Indices from Different Sensors for Monitoring Above-Ground Plant Nitrogen Uptake in Winter Wheat

PubMed Central

Yao, Xinfeng; Yao, Xia; Jia, Wenqing; Tian, Yongchao; Ni, Jun; Cao, Weixing; Zhu, Yan

2013-01-01

Various sensors have been used to obtain the canopy spectral reflectance for monitoring above-ground plant nitrogen (N) uptake in winter wheat. Comparison and intercalibration of spectral reflectance and vegetation indices derived from different sensors are important for multi-sensor data fusion and utilization. In this study, the spectral reflectance and its derived vegetation indices from three ground-based sensors (ASD Field Spec Pro spectrometer, CropScan MSR 16 and GreenSeeker RT 100) in six winter wheat field experiments were compared. Then, the best sensor (ASD) and its normalized difference vegetation index (NDVI (807, 736)) for estimating above-ground plant N uptake were determined (R2 of 0.885 and RMSE of 1.440 g·N·m−2 for model calibration). In order to better utilize the spectral reflectance from the three sensors, intercalibration models for vegetation indices based on different sensors were developed. The results indicated that the vegetation indices from different sensors could be intercalibrated, which should promote application of data fusion and make monitoring of above-ground plant N uptake more precise and accurate. PMID:23462622

Coastal Observations of Weather Features in Senegal during the AMMA SOP-3 Period

NASA Technical Reports Server (NTRS)

Jenkins, G.; Kucera, P.; Joseph, E.; Fuentes, J.; Gaye, A.; Gerlach, J.; Roux, F.; Viltard, N.; Papazzoni, M.; Protat, A.;

LWT Based Sensor Node Signal Processing in Vehicle Surveillance Distributed Sensor Network

NASA Astrophysics Data System (ADS)

Cha, Daehyun; Hwang, Chansik

Previous vehicle surveillance researches on distributed sensor network focused on overcoming power limitation and communication bandwidth constraints in sensor node. In spite of this constraints, vehicle surveillance sensor node must have signal compression, feature extraction, target localization, noise cancellation and collaborative signal processing with low computation and communication energy dissipation. In this paper, we introduce an algorithm for light-weight wireless sensor node signal processing based on lifting scheme wavelet analysis feature extraction in distributed sensor network.

A Technique to Determine the Self-Noise of Seismic Sensors for Performance Screening

NASA Astrophysics Data System (ADS)

Rademacher, H.; Hart, D.; Guralp, C.

2012-04-01

Seismic noise affects the performance of a seismic sensor and is thereby a limiting factor for the detection threshold of monitoring networks. Among the various sources of noise, the intrinsic self-noise of a seismic sensor is most diffcult to determine, because it is mostly masked by natural and anthropogenic ground noise and is also affected by the noise characteristic of the digitizer. Here we present a new technique to determine the self-noise of a seismic system (digitizer + sensors). It is based on a method introduced by Sleeman et al. (2005) to test the noise performance of digitizers. We infer the self-noise of a triplet of identical sensors by comparing coherent waveforms over a wide spectral band across the set-up. We will show first results from a proof-of-concept study done in a vault near Albuquerque, New Mexico. We will show, how various methods of shielding the sensors affect the results of this technique. This method can also be used as a means of quality control during sensor production, because poorly performing sensors can easily be identified.

Geographically distributed environmental sensor system

DOEpatents

French, Patrick; Veatch, Brad; O'Connor, Mike

2006-10-03

The present invention is directed to a sensor network that includes a number of sensor units and a base unit. The base station operates in a network discovery mode (in which network topology information is collected) in a data polling mode (in which sensed information is collected from selected sensory units). Each of the sensor units can include a number of features, including an anemometer, a rain gauge, a compass, a GPS receiver, a barometric pressure sensor, an air temperature sensor, a humidity sensor, a level, and a radiant temperature sensor.

Citizen sensors for SHM: use of accelerometer data from smartphones.

PubMed

Feng, Maria; Fukuda, Yoshio; Mizuta, Masato; Ozer, Ekin

2015-01-29

Ubiquitous smartphones have created a significant opportunity to form a low-cost wireless Citizen Sensor network and produce big data for monitoring structural integrity and safety under operational and extreme loads. Such data are particularly useful for rapid assessment of structural damage in a large urban setting after a major event such as an earthquake. This study explores the utilization of smartphone accelerometers for measuring structural vibration, from which structural health and post-event damage can be diagnosed. Widely available smartphones are tested under sinusoidal wave excitations with frequencies in the range relevant to civil engineering structures. Large-scale seismic shaking table tests, observing input ground motion and response of a structural model, are carried out to evaluate the accuracy of smartphone accelerometers under operational, white-noise and earthquake excitations of different intensity. Finally, the smartphone accelerometers are tested on a dynamically loaded bridge. The extensive experiments show satisfactory agreements between the reference and smartphone sensor measurements in both time and frequency domains, demonstrating the capability of the smartphone sensors to measure structural responses ranging from low-amplitude ambient vibration to high-amplitude seismic response. Encouraged by the results of this study, the authors are developing a citizen-engaging and data-analytics crowdsourcing platform towards a smartphone-based Citizen Sensor network for structural health monitoring and post-event damage assessment applications.

Human Mobility Monitoring in Very Low Resolution Visual Sensor Network

PubMed Central

Bo Bo, Nyan; Deboeverie, Francis; Eldib, Mohamed; Guan, Junzhi; Xie, Xingzhe; Niño, Jorge; Van Haerenborgh, Dirk; Slembrouck, Maarten; Van de Velde, Samuel; Steendam, Heidi; Veelaert, Peter; Kleihorst, Richard; Aghajan, Hamid; Philips, Wilfried

2014-01-01

This paper proposes an automated system for monitoring mobility patterns using a network of very low resolution visual sensors (30 × 30 pixels). The use of very low resolution sensors reduces privacy concern, cost, computation requirement and power consumption. The core of our proposed system is a robust people tracker that uses low resolution videos provided by the visual sensor network. The distributed processing architecture of our tracking system allows all image processing tasks to be done on the digital signal controller in each visual sensor. In this paper, we experimentally show that reliable tracking of people is possible using very low resolution imagery. We also compare the performance of our tracker against a state-of-the-art tracking method and show that our method outperforms. Moreover, the mobility statistics of tracks such as total distance traveled and average speed derived from trajectories are compared with those derived from ground truth given by Ultra-Wide Band sensors. The results of this comparison show that the trajectories from our system are accurate enough to obtain useful mobility statistics. PMID:25375754

A Radar-Enabled Collaborative Sensor Network Integrating COTS Technology for Surveillance and Tracking

PubMed Central

Kozma, Robert; Wang, Lan; Iftekharuddin, Khan; McCracken, Ernest; Khan, Muhammad; Islam, Khandakar; Bhurtel, Sushil R.; Demirer, R. Murat

2012-01-01

The feasibility of using Commercial Off-The-Shelf (COTS) sensor nodes is studied in a distributed network, aiming at dynamic surveillance and tracking of ground targets. Data acquisition by low-cost (<$50 US) miniature low-power radar through a wireless mote is described. We demonstrate the detection, ranging and velocity estimation, classification and tracking capabilities of the mini-radar, and compare results to simulations and manual measurements. Furthermore, we supplement the radar output with other sensor modalities, such as acoustic and vibration sensors. This method provides innovative solutions for detecting, identifying, and tracking vehicles and dismounts over a wide area in noisy conditions. This study presents a step towards distributed intelligent decision support and demonstrates effectiveness of small cheap sensors, which can complement advanced technologies in certain real-life scenarios. PMID:22438713

Wireless Sensor Network Based Subsurface Contaminant Plume Monitoring

DTIC Science & Technology

2012-04-16

Sensor Network (WSN) to monitor contaminant plume movement in naturally heterogeneous subsurface formations to advance the sensor networking based...time to assess the source and predict future plume behavior. This proof-of-concept research aimed at demonstrating the use of an intelligent Wireless

Neural Network-Based Sensor Validation for Turboshaft Engines

NASA Technical Reports Server (NTRS)

Moller, James C.; Litt, Jonathan S.; Guo, Ten-Huei

1998-01-01

Sensor failure detection, isolation, and accommodation using a neural network approach is described. An auto-associative neural network is configured to perform dimensionality reduction on the sensor measurement vector and provide estimated sensor values. The sensor validation scheme is applied in a simulation of the T700 turboshaft engine in closed loop operation. Performance is evaluated based on the ability to detect faults correctly and maintain stable and responsive engine operation. The set of sensor outputs used for engine control forms the network input vector. Analytical redundancy is verified by training networks of successively smaller bottleneck layer sizes. Training data generation and strategy are discussed. The engine maintained stable behavior in the presence of sensor hard failures. With proper selection of fault determination thresholds, stability was maintained in the presence of sensor soft failures.

Monitoring Street-Level Spatial-Temporal Variations of Carbon Monoxide in Urban Settings Using a Wireless Sensor Network (WSN) Framework

PubMed Central

Wen, Tzai-Hung; Jiang, Joe-Air; Sun, Chih-Hong; Juang, Jehn-Yih; Lin, Tzu-Shiang

2013-01-01

Air pollution has become a severe environmental problem due to urbanization and heavy traffic. Monitoring street-level air quality is an important issue, but most official monitoring stations are installed to monitor large-scale air quality conditions, and their limited spatial resolution cannot reflect the detailed variations in air quality that may be induced by traffic jams. By deploying wireless sensors on crossroads and main roads, this study established a pilot framework for a wireless sensor network (WSN)-based real-time monitoring system to understand street-level spatial-temporal changes of carbon monoxide (CO) in urban settings. The system consists of two major components. The first component is the deployment of wireless sensors. We deployed 44 sensor nodes, 40 transmitter nodes and four gateway nodes in this study. Each sensor node includes a signal processing module, a CO sensor and a wireless communication module. In order to capture realistic human exposure to traffic pollutants, all sensors were deployed at a height of 1.5 m on lampposts and traffic signs. The study area covers a total length of 1.5 km of Keelung Road in Taipei City. The other component is a map-based monitoring platform for sensor data visualization and manipulation in time and space. Using intensive real-time street-level monitoring framework, we compared the spatial-temporal patterns of air pollution in different time periods. Our results capture four CO concentration peaks throughout the day at the location, which was located along an arterial and nearby traffic sign. The hourly average could reach 5.3 ppm from 5:00 pm to 7:00 pm due to the traffic congestion. The proposed WSN-based framework captures detailed ground information and potential risk of human exposure to traffic-related air pollution. It also provides street-level insights into real-time monitoring for further early warning of air pollution and urban environmental management. PMID:24287859

Monitoring street-level spatial-temporal variations of carbon monoxide in urban settings using a wireless sensor network (WSN) framework.

PubMed

Wen, Tzai-Hung; Jiang, Joe-Air; Sun, Chih-Hong; Juang, Jehn-Yih; Lin, Tzu-Shiang

2013-11-27

Air pollution has become a severe environmental problem due to urbanization and heavy traffic. Monitoring street-level air quality is an important issue, but most official monitoring stations are installed to monitor large-scale air quality conditions, and their limited spatial resolution cannot reflect the detailed variations in air quality that may be induced by traffic jams. By deploying wireless sensors on crossroads and main roads, this study established a pilot framework for a wireless sensor network (WSN)-based real-time monitoring system to understand street-level spatial-temporal changes of carbon monoxide (CO) in urban settings. The system consists of two major components. The first component is the deployment of wireless sensors. We deployed 44 sensor nodes, 40 transmitter nodes and four gateway nodes in this study. Each sensor node includes a signal processing module, a CO sensor and a wireless communication module. In order to capture realistic human exposure to traffic pollutants, all sensors were deployed at a height of 1.5 m on lampposts and traffic signs. The study area covers a total length of 1.5 km of Keelung Road in Taipei City. The other component is a map-based monitoring platform for sensor data visualization and manipulation in time and space. Using intensive real-time street-level monitoring framework, we compared the spatial-temporal patterns of air pollution in different time periods. Our results capture four CO concentration peaks throughout the day at the location, which was located along an arterial and nearby traffic sign. The hourly average could reach 5.3 ppm from 5:00 pm to 7:00 pm due to the traffic congestion. The proposed WSN-based framework captures detailed ground information and potential risk of human exposure to traffic-related air pollution. It also provides street-level insights into real-time monitoring for further early warning of air pollution and urban environmental management.

Experimenting with an Evolving Ground/Space-based Software Architecture to Enable Sensor Webs

NASA Technical Reports Server (NTRS)

mandl, Daniel; Frye, Stuart

2005-01-01

A series of ongoing experiments are being conducted at the NASA Goddard Space Flight Center to explore integrated ground and space-based software architectures enabling sensor webs. A sensor web, as defined by Steve Talabac at NASA Goddard Space Flight Center(GSFC), is a coherent set of distributed nodes interconnected by a communications fabric, that collectively behave as a single, dynamically adaptive, observing system. The nodes can be comprised of satellites, ground instruments, computing nodes etc. Sensor web capability requires autonomous management of constellation resources. This becomes progressively more important as more and more satellites share resource, such as communication channels and ground station,s while automatically coordinating their activities. There have been five ongoing activities which include an effort to standardize a set of middleware. This paper will describe one set of activities using the Earth Observing 1 satellite, which used a variety of ground and flight software along with other satellites and ground sensors to prototype a sensor web. This activity allowed us to explore where the difficulties that occur in the assembly of sensor webs given today s technology. We will present an overview of the software system architecture, some key experiments and lessons learned to facilitate better sensor webs in the future.

A Risk Based Approach to Limit the Effects of Covert Channels for Internet Sensor Data Aggregators for Sensor Privacy

NASA Astrophysics Data System (ADS)

Viecco, Camilo H.; Camp, L. Jean

Effective defense against Internet threats requires data on global real time network status. Internet sensor networks provide such real time network data. However, an organization that participates in a sensor network risks providing a covert channel to attackers if that organization’s sensor can be identified. While there is benefit for every party when any individual participates in such sensor deployments, there are perverse incentives against individual participation. As a result, Internet sensor networks currently provide limited data. Ensuring anonymity of individual sensors can decrease the risk of participating in a sensor network without limiting data provision.

Towards the development of tamper-resistant, ground-based mobile sensor nodes

NASA Astrophysics Data System (ADS)

Mascarenas, David; Stull, Christopher; Farrar, Charles

2011-11-01

Mobile sensor nodes hold great potential for collecting field data using fewer resources than human operators would require and potentially requiring fewer sensors than a fixed-position sensor array. It would be very beneficial to allow these mobile sensor nodes to operate unattended with a minimum of human intervention. In order to allow mobile sensor nodes to operate unattended in a field environment, it is imperative that they be capable of identifying and responding to external agents that may attempt to tamper with, damage or steal the mobile sensor nodes, while still performing their data collection mission. Potentially hostile external agents could include animals, other mobile sensor nodes, or humans. This work will focus on developing control policies to help enable a mobile sensor node to identify and avoid capture by a hostile un-mounted human. The work is developed in a simulation environment, and demonstrated using a non-holonomic, ground-based mobile sensor node. This work will be a preliminary step toward ensuring the cyber-physical security of ground-based mobile sensor nodes that operate unattended in potentially unfriendly environments.

A Study of Mesoscale Probability Forecasting Performance Based on an Advanced Image Display System.

DTIC Science & Technology

1984-04-30

CLASSIFICATION lb. RESTRICTIVE MARKINGS Uncl assified 2&. SECURITY CLASSIFICATION AUTHORITY 3. DISTRIBUTION/AVAI LABILITY OF REPORT 2b. DE CLASSI FICAT... sensors in the surface network, an air-to-ground lightning detection system, and NWS 6Brown, R. C., 1983: Anatomy of a nesoscale instrumentation system...W. B. Sweezy, R. G. Strauch, E. R. Westwater, and C. G. Little, 1983: An automatic Profiler of the temperatura , wind, and humidity in the troposphere

Dynamic Hierarchical Energy-Efficient Method Based on Combinatorial Optimization for Wireless Sensor Networks.

PubMed

Chang, Yuchao; Tang, Hongying; Cheng, Yongbo; Zhao, Qin; Yuan, Baoqing Li andXiaobing

2017-07-19

Routing protocols based on topology control are significantly important for improving network longevity in wireless sensor networks (WSNs). Traditionally, some WSN routing protocols distribute uneven network traffic load to sensor nodes, which is not optimal for improving network longevity. Differently to conventional WSN routing protocols, we propose a dynamic hierarchical protocol based on combinatorial optimization (DHCO) to balance energy consumption of sensor nodes and to improve WSN longevity. For each sensor node, the DHCO algorithm obtains the optimal route by establishing a feasible routing set instead of selecting the cluster head or the next hop node. The process of obtaining the optimal route can be formulated as a combinatorial optimization problem. Specifically, the DHCO algorithm is carried out by the following procedures. It employs a hierarchy-based connection mechanism to construct a hierarchical network structure in which each sensor node is assigned to a special hierarchical subset; it utilizes the combinatorial optimization theory to establish the feasible routing set for each sensor node, and takes advantage of the maximum-minimum criterion to obtain their optimal routes to the base station. Various results of simulation experiments show effectiveness and superiority of the DHCO algorithm in comparison with state-of-the-art WSN routing algorithms, including low-energy adaptive clustering hierarchy (LEACH), hybrid energy-efficient distributed clustering (HEED), genetic protocol-based self-organizing network clustering (GASONeC), and double cost function-based routing (DCFR) algorithms.

The Multi-Sensor Aerosol Products Sampling System (MAPSS) for Integrated Analysis of Satellite Retrieval Uncertainties

NASA Technical Reports Server (NTRS)

Ichoku, Charles; Petrenko, Maksym; Leptoukh, Gregory

2010-01-01

Among the known atmospheric constituents, aerosols represent the greatest uncertainty in climate research. Although satellite-based aerosol retrieval has practically become routine, especially during the last decade, there is often disagreement between similar aerosol parameters retrieved from different sensors, leaving users confused as to which sensors to trust for answering important science questions about the distribution, properties, and impacts of aerosols. As long as there is no consensus and the inconsistencies are not well characterized and understood ', there will be no way of developing reliable climate data records from satellite aerosol measurements. Fortunately, the most globally representative well-calibrated ground-based aerosol measurements corresponding to the satellite-retrieved products are available from the Aerosol Robotic Network (AERONET). To adequately utilize the advantages offered by this vital resource,., an online Multi-sensor Aerosol Products Sampling System (MAPSS) was recently developed. The aim of MAPSS is to facilitate detailed comparative analysis of satellite aerosol measurements from different sensors (Terra-MODIS, Aqua-MODIS, Terra-MISR, Aura-OMI, Parasol-POLDER, and Calipso-CALIOP) based on the collocation of these data products over AERONET stations. In this presentation, we will describe the strategy of the MAPSS system, its potential advantages for the aerosol community, and the preliminary results of an integrated comparative uncertainty analysis of aerosol products from multiple satellite sensors.

Toward a Coherent Detailed Evaluation of Aerosol Data Products from Multiple Satellite Sensors

NASA Technical Reports Server (NTRS)

Ichoku, Charles; Petrenko, Maksym; Leptoukh, Gregory

2011-01-01

Atmospheric aerosols represent one of the greatest uncertainties in climate research. Although satellite-based aerosol retrieval has practically become routine, especially during the last decade, there is often disagreement between similar aerosol parameters retrieved from different sensors, leaving users confused as to which sensors to trust for answering important science questions about the distribution, properties, and impacts of aerosols. As long as there is no consensus and the inconsistencies are not well characterized and understood, there will be no way of developing reliable climate data records from satellite aerosol measurements. Fortunately, the most globally representative well-calibrated ground-based aerosol measurements corresponding to the satellite-retrieved products are available from the Aerosol Robotic Network (AERONET). To adequately utilize the advantages offered by this vital resource, an online Multi-sensor Aerosol Products Sampling System (MAPSS) was recently developed. The aim of MAPSS is to facilitate detailed comparative analysis of satellite aerosol measurements from different sensors (Terra-MODIS, Aqua-MODIS, TerraMISR, Aura-OMI, Parasol-POLDER, and Calipso-CALIOP) based on the collocation of these data products over AERONET stations. In this presentation, we will describe the strategy of the MASS system, its potential advantages for the aerosol community, and the preliminary results of an integrated comparative uncertainly analysis of aerosol products from multiple satellite sensors.

Potential use of ground-based sensor technologies for weed detection.

PubMed

Peteinatos, Gerassimos G; Weis, Martin; Andújar, Dionisio; Rueda Ayala, Victor; Gerhards, Roland

2014-02-01

Site-specific weed management is the part of precision agriculture (PA) that tries to effectively control weed infestations with the least economical and environmental burdens. This can be achieved with the aid of ground-based or near-range sensors in combination with decision rules and precise application technologies. Near-range sensor technologies, developed for mounting on a vehicle, have been emerging for PA applications during the last three decades. These technologies focus on identifying plants and measuring their physiological status with the aid of their spectral and morphological characteristics. Cameras, spectrometers, fluorometers and distance sensors are the most prominent sensors for PA applications. The objective of this article is to describe-ground based sensors that have the potential to be used for weed detection and measurement of weed infestation level. An overview of current sensor systems is presented, describing their concepts, results that have been achieved, already utilized commercial systems and problems that persist. A perspective for the development of these sensors is given. © 2013 Society of Chemical Industry.

The Quake-Catcher Network: Improving Earthquake Strong Motion Observations Through Community Engagement

NASA Astrophysics Data System (ADS)

Cochran, E. S.; Lawrence, J. F.; Christensen, C. M.; Chung, A. I.; Neighbors, C.; Saltzman, J.

2010-12-01

The Quake-Catcher Network (QCN) involves the community in strong motion data collection by utilizing volunteer computing techniques and low-cost MEMS accelerometers. Volunteer computing provides a mechanism to expand strong-motion seismology with minimal infrastructure costs, while promoting community participation in science. Micro-Electro-Mechanical Systems (MEMS) triaxial accelerometers can be attached to a desktop computer via USB and are internal to many laptops. Preliminary shake table tests show the MEMS accelerometers can record high-quality seismic data with instrument response similar to research-grade strong-motion sensors. QCN began distributing sensors and software to K-12 schools and the general public in April 2008 and has grown to roughly 1500 stations worldwide. We also recently tested whether sensors could be quickly deployed as part of a Rapid Aftershock Mobilization Program (RAMP) following the 2010 M8.8 Maule, Chile earthquake. Volunteers are recruited through media reports, web-based sensor request forms, as well as social networking sites. Using data collected to date, we examine whether a distributed sensing network can provide valuable seismic data for earthquake detection and characterization while promoting community participation in earthquake science. We utilize client-side triggering algorithms to determine when significant ground shaking occurs and this metadata is sent to the main QCN server. On average, trigger metadata are received within 1-10 seconds from the observation of a trigger; the larger data latencies are correlated with greater server-station distances. When triggers are detected, we determine if the triggers correlate to others in the network using spatial and temporal clustering of incoming trigger information. If a minimum number of triggers are detected then a QCN-event is declared and an initial earthquake location and magnitude is estimated. Initial analysis suggests that the estimated locations and magnitudes are similar to those reported in regional and global catalogs. As the network expands, it will become increasingly important to provide volunteers access to the data they collect, both to encourage continued participation in the network and to improve community engagement in scientific discourse related to seismic hazard. In the future, we hope to provide access to both images and raw data from seismograms in formats accessible to the general public through existing seismic data archives (e.g. IRIS, SCSN) and/or through the QCN project website. While encouraging community participation in seismic data collection, we can extend the capabilities of existing seismic networks to rapidly detect and characterize strong motion events. In addition, the dense waveform observations may provide high-resolution ground shaking information to improve source imaging and seismic risk assessment.

Infrasound from ground to space

NASA Astrophysics Data System (ADS)

Bowman, Daniel Charles

Acoustic detector networks are usually located on the Earth's surface. However, these networks suffer from shortcomings such as poor detection range and pervasive wind noise. An alternative is to deploy acoustic sensors on high altitude balloons. In theory, such platforms can resolve signals arriving from great distances, acquire others that never reach the surface at all, and avoid wind noise entirely. This dissertation focuses on scientific advances, instrumentation, and analytical techniques resulting from the development of such sensor arrays. Results from infrasound microphones deployed on balloon flights in the middle stratosphere are described, and acoustic sources such as the ocean microbarom and building ventilation systems are discussed. Electromagnetic noise originating from the balloon, flight system, and other payloads is shown to be a pervasive issue. An experiment investigating acoustic sensor calibration at low pressures is presented, and implications for high altitude recording are considered. Outstanding challenges and opportunities in sound measurement using sensors embedded in the free atmosphere are outlined. Acoustic signals from field scale explosions designed to emulate volcanic eruptions are described, and their generation mechanisms modeled. Wave forms recorded on sensors suspended from tethered helium balloons are compared with those detected on ground stations during the experiment. Finally, the Hilbert-Huang transform, a high time resolution spectral analysis method for nonstationary and nonlinear time series, is presented.

CAOS: the nested catchment soil-vegetation-atmosphere observation platform

NASA Astrophysics Data System (ADS)

Weiler, Markus; Blume, Theresa

2016-04-01

Most catchment based observations linking hydrometeorology, ecohydrology, soil hydrology and hydrogeology are typically not integrated with each other and lack a consistent and appropriate spatial-temporal resolution. Within the research network CAOS (Catchments As Organized Systems), we have initiated and developed a novel and integrated observation platform in several catchments in Luxembourg. In 20 nested catchments covering three distinct geologies the subscale processes at the bedrock-soil-vegetation-atmosphere interface are being monitored at 46 sensor cluster locations. Each sensor cluster is designed to observe a variety of different fluxes and state variables above and below ground, in the saturated and unsaturated zone. The numbers of sensors are chosen to capture the spatial variability as well the average dynamics. At each of these sensor clusters three soil moisture profiles with sensors at different depths, four soil temperature profiles as well as matric potential, air temperature, relative humidity, global radiation, rainfall/throughfall, sapflow and shallow groundwater and stream water levels are measured continuously. In addition, most sensors also measure temperature (water, soil, atmosphere) and electrical conductivity. This setup allows us to determine the local water and energy balance at each of these sites. The discharge gauging sites in the nested catchments are also equipped with automatic water samplers to monitor water quality and water stable isotopes continuously. Furthermore, water temperature and electrical conductivity observations are extended to over 120 locations distributed across the entire stream network to capture the energy exchange between the groundwater, stream water and atmosphere. The measurements at the sensor clusters are complemented by hydrometeorological observations (rain radar, network of distrometers and dense network of precipitation gauges) and linked with high resolution meteorological models. In this presentation, we will highlight the potential of this integrated observation platform to estimate energy and water exchange between the terrestrial and aquatic systems and the atmosphere, to trace water flow pathways in the unsaturated and saturated zone, and to understand the organization of processes and fluxes and thus runoff generation at different temporal and spatial scales.

Development of a Ground Water Data Portal for Interoperable Data Exchange within the U.S. National Ground Water Monitoring Network and Beyond

NASA Astrophysics Data System (ADS)

Booth, N. L.; Brodaric, B.; Lucido, J. M.; Kuo, I.; Boisvert, E.; Cunningham, W. L.

2011-12-01

The need for a national groundwater monitoring network within the United States is profound and has been recognized by organizations outside government as a major data gap for managing ground-water resources. Our country's communities, industries, agriculture, energy production and critical ecosystems rely on water being available in adequate quantity and suitable quality. To meet this need the Subcommittee on Ground Water, established by the Federal Advisory Committee on Water Information, created a National Ground Water Monitoring Network (NGWMN) envisioned as a voluntary, integrated system of data collection, management and reporting that will provide the data needed to address present and future ground-water management questions raised by Congress, Federal, State and Tribal agencies and the public. The NGWMN Data Portal is the means by which policy makers, academics and the public will be able to access ground water data through one seamless web-based application from disparate data sources. Data systems in the United States exist at many organizational and geographic levels and differing vocabulary and data structures have prevented data sharing and reuse. The data portal will facilitate the retrieval of and access to groundwater data on an as-needed basis from multiple, dispersed data repositories allowing the data to continue to be housed and managed by the data provider while being accessible for the purposes of the national monitoring network. This work leverages Open Geospatial Consortium (OGC) data exchange standards and information models. To advance these standards for supporting the exchange of ground water information, an OGC Interoperability Experiment was organized among international participants from government, academia and the private sector. The experiment focused on ground water data exchange across the U.S. / Canadian border. WaterML2.0, an evolving international standard for water observations, encodes ground water levels and is exchanged using the OGC Sensor Observation Service (SOS) standard. Ground Water Markup Language (GWML) encodes well log, lithology and construction information and is exchanged using the OGC Web Feature Service (WFS) standard. Within the NGWMN Data Portal, data exchange between distributed data provider repositories is achieved through the use of these web services and a central mediation hub, which performs both format (syntactic) and nomenclature (semantic) mediation, conforming heterogeneous inputs into common standards-based outputs. Through these common standards, interoperability between the U.S. NGWMN and Canada's Groundwater Information Network (GIN) is achieved, advancing a ground water virtual observatory across North America.

Bluetooth Roaming for Sensor Network System in Clinical Environment.

PubMed

Kuroda, Tomohiro; Noma, Haruo; Takase, Kazuhiko; Sasaki, Shigeto; Takemura, Tadamasa

2015-01-01

A sensor network is key infrastructure for advancing a hospital information system (HIS). The authors proposed a method to provide roaming functionality for Bluetooth to realize a Bluetooth-based sensor network, which is suitable to connect clinical devices. The proposed method makes the average response time of a Bluetooth connection less than one second by making the master device repeat the inquiry process endlessly and modifies parameters of the inquiry process. The authors applied the developed sensor network for daily clinical activities in an university hospital, and confirmed the stabilitya and effectiveness of the sensor network. As Bluetooth becomes a quite common wireless interface for medical devices, the proposed protocol that realizes Bluetooth-based sensor network enables HIS to equip various clinical devices and, consequently, lets information and communication technologies advance clinical services.

On Applicability of Network Coding Technique for 6LoWPAN-based Sensor Networks.

PubMed

Amanowicz, Marek; Krygier, Jaroslaw

2018-05-26

In this paper, the applicability of the network coding technique in 6LoWPAN-based sensor multihop networks is examined. The 6LoWPAN is one of the standards proposed for the Internet of Things architecture. Thus, we can expect the significant growth of traffic in such networks, which can lead to overload and decrease in the sensor network lifetime. The authors propose the inter-session network coding mechanism that can be implemented in resource-limited sensor motes. The solution reduces the overall traffic in the network, and in consequence, the energy consumption is decreased. Used procedures take into account deep header compressions of the native 6LoWPAN packets and the hop-by-hop changes of the header structure. Applied simplifications reduce signaling traffic that is typically occurring in network coding deployments, keeping the solution usefulness for the wireless sensor networks with limited resources. The authors validate the proposed procedures in terms of end-to-end packet delay, packet loss ratio, traffic in the air, total energy consumption, and network lifetime. The solution has been tested in a real wireless sensor network. The results confirm the efficiency of the proposed technique, mostly in delay-tolerant sensor networks.

System for critical infrastructure security based on multispectral observation-detection module

NASA Astrophysics Data System (ADS)

Trzaskawka, Piotr; Kastek, Mariusz; Życzkowski, Marek; Dulski, Rafał; Szustakowski, Mieczysław; Ciurapiński, Wiesław; Bareła, Jarosław

2013-10-01

Recent terrorist attacks and possibilities of such actions in future have forced to develop security systems for critical infrastructures that embrace sensors technologies and technical organization of systems. The used till now perimeter protection of stationary objects, based on construction of a ring with two-zone fencing, visual cameras with illumination are efficiently displaced by the systems of the multisensor technology that consists of: visible technology - day/night cameras registering optical contrast of a scene, thermal technology - cheap bolometric cameras recording thermal contrast of a scene and active ground radars - microwave and millimetre wavelengths that record and detect reflected radiation. Merging of these three different technologies into one system requires methodology for selection of technical conditions of installation and parameters of sensors. This procedure enables us to construct a system with correlated range, resolution, field of view and object identification. Important technical problem connected with the multispectral system is its software, which helps couple the radar with the cameras. This software can be used for automatic focusing of cameras, automatic guiding cameras to an object detected by the radar, tracking of the object and localization of the object on the digital map as well as target identification and alerting. Based on "plug and play" architecture, this system provides unmatched flexibility and simplistic integration of sensors and devices in TCP/IP networks. Using a graphical user interface it is possible to control sensors and monitor streaming video and other data over the network, visualize the results of data fusion process and obtain detailed information about detected intruders over a digital map. System provide high-level applications and operator workload reduction with features such as sensor to sensor cueing from detection devices, automatic e-mail notification and alarm triggering. The paper presents a structure and some elements of critical infrastructure protection solution which is based on a modular multisensor security system. System description is focused mainly on methodology of selection of sensors parameters. The results of the tests in real conditions are also presented.

Research on trust calculation of wireless sensor networks based on time segmentation

NASA Astrophysics Data System (ADS)

Su, Yaoxin; Gao, Xiufeng; Qiao, Wenxin

2017-05-01

Because the wireless sensor network is different from the traditional network characteristics, it is easy to accept the intrusion from the compromise node. The trust mechanism is the most effective way to defend against internal attacks. Aiming at the shortcomings of the existing trust mechanism, a method of calculating the trust of wireless sensor networks based on time segmentation is proposed. It improves the security of the network and extends the life of the network

Scalable Multicast Protocols for Overlapped Groups in Broker-Based Sensor Networks

NASA Astrophysics Data System (ADS)

Kim, Chayoung; Ahn, Jinho

In sensor networks, there are lots of overlapped multicast groups because of many subscribers, associated with their potentially varying specific interests, querying every event to sensors/publishers. And gossip based communication protocols are promising as one of potential solutions providing scalability in P(Publish)/ S(Subscribe) paradigm in sensor networks. Moreover, despite the importance of both guaranteeing message delivery order and supporting overlapped multicast groups in sensor or P2P networks, there exist little research works on development of gossip-based protocols to satisfy all these requirements. In this paper, we present two versions of causally ordered delivery guaranteeing protocols for overlapped multicast groups. The one is based on sensor-broker as delegates and the other is based on local views and delegates representing subscriber subgroups. In the sensor-broker based protocol, sensor-broker might lead to make overlapped multicast networks organized by subscriber's interests. The message delivery order has been guaranteed consistently and all multicast messages are delivered to overlapped subscribers using gossip based protocols by sensor-broker. Therefore, these features of the sensor-broker based protocol might be significantly scalable rather than those of the protocols by hierarchical membership list of dedicated groups like traditional committee protocols. And the subscriber-delegate based protocol is much stronger rather than fully decentralized protocols guaranteeing causally ordered delivery based on only local views because the message delivery order has been guaranteed consistently by all corresponding members of the groups including delegates. Therefore, this feature of the subscriber-delegate protocol is a hybrid approach improving the inherent scalability of multicast nature by gossip-based technique in all communications.

An efficient management system for wireless sensor networks.

PubMed

Ma, Yi-Wei; Chen, Jiann-Liang; Huang, Yueh-Min; Lee, Mei-Yu

2010-01-01

Wireless sensor networks have garnered considerable attention recently. Networks typically have many sensor nodes, and are used in commercial, medical, scientific, and military applications for sensing and monitoring the physical world. Many researchers have attempted to improve wireless sensor network management efficiency. A Simple Network Management Protocol (SNMP)-based sensor network management system was developed that is a convenient and effective way for managers to monitor and control sensor network operations. This paper proposes a novel WSNManagement system that can show the connections stated of relationships among sensor nodes and can be used for monitoring, collecting, and analyzing information obtained by wireless sensor networks. The proposed network management system uses collected information for system configuration. The function of performance analysis facilitates convenient management of sensors. Experimental results show that the proposed method enhances the alive rate of an overall sensor node system, reduces the packet lost rate by roughly 5%, and reduces delay time by roughly 0.2 seconds. Performance analysis demonstrates that the proposed system is effective for wireless sensor network management.

Energy Efficient Cluster Based Scheduling Scheme for Wireless Sensor Networks

PubMed Central

Srie Vidhya Janani, E.; Ganesh Kumar, P.

2015-01-01

The energy utilization of sensor nodes in large scale wireless sensor network points out the crucial need for scalable and energy efficient clustering protocols. Since sensor nodes usually operate on batteries, the maximum utility of network is greatly dependent on ideal usage of energy leftover in these sensor nodes. In this paper, we propose an Energy Efficient Cluster Based Scheduling Scheme for wireless sensor networks that balances the sensor network lifetime and energy efficiency. In the first phase of our proposed scheme, cluster topology is discovered and cluster head is chosen based on remaining energy level. The cluster head monitors the network energy threshold value to identify the energy drain rate of all its cluster members. In the second phase, scheduling algorithm is presented to allocate time slots to cluster member data packets. Here congestion occurrence is totally avoided. In the third phase, energy consumption model is proposed to maintain maximum residual energy level across the network. Moreover, we also propose a new packet format which is given to all cluster member nodes. The simulation results prove that the proposed scheme greatly contributes to maximum network lifetime, high energy, reduced overhead, and maximum delivery ratio. PMID:26495417

Adaptive Management of Computing and Network Resources for Spacecraft Systems

NASA Technical Reports Server (NTRS)

Pfarr, Barbara; Welch, Lonnie R.; Detter, Ryan; Tjaden, Brett; Huh, Eui-Nam; Szczur, Martha R. (Technical Monitor)

2000-01-01

It is likely that NASA's future spacecraft systems will consist of distributed processes which will handle dynamically varying workloads in response to perceived scientific events, the spacecraft environment, spacecraft anomalies and user commands. Since all situations and possible uses of sensors cannot be anticipated during pre-deployment phases, an approach for dynamically adapting the allocation of distributed computational and communication resources is needed. To address this, we are evolving the DeSiDeRaTa adaptive resource management approach to enable reconfigurable ground and space information systems. The DeSiDeRaTa approach embodies a set of middleware mechanisms for adapting resource allocations, and a framework for reasoning about the real-time performance of distributed application systems. The framework and middleware will be extended to accommodate (1) the dynamic aspects of intra-constellation network topologies, and (2) the complete real-time path from the instrument to the user. We are developing a ground-based testbed that will enable NASA to perform early evaluation of adaptive resource management techniques without the expense of first deploying them in space. The benefits of the proposed effort are numerous, including the ability to use sensors in new ways not anticipated at design time; the production of information technology that ties the sensor web together; the accommodation of greater numbers of missions with fewer resources; and the opportunity to leverage the DeSiDeRaTa project's expertise, infrastructure and models for adaptive resource management for distributed real-time systems.

Capacity Building for Research and Education in GIS/GPS Technology and Systems

DTIC Science & Technology

2015-05-20

In multi- sensor area Wireless Sensor Networking (WSN) fields will be explored. As a step forward the research to be conducted in WSN field is to...Agriculture Using Technology for Crops Scouting in Agriculture Application of Technology in Precision Agriculture Wireless Sensor Network (WSN) in...Cooperative Engagement Capability Range based algorithms for Wireless Sensor Network Self-configurable Wireless Sensor Network Energy Efficient Wireless

Infrasound signal detection and characterization using ground-coupled airwaves on a single seismo-acoustic sensor pair

NASA Astrophysics Data System (ADS)

McKee, K. F.; Fee, D.; Haney, M. M.; Lyons, J. J.; Matoza, R. S.

2016-12-01

A ground-coupled airwave (GCA) occurs when an incident atmospheric pressure wave encounters the Earth's surface and part of the energy of the wave is transferred to the ground (i.e. coupled to the ground) as a seismic wave. This seismic wave propagates as a surface Rayleigh wave evidenced by the retrograde particle motion detected on a three-component seismometer. Acoustic waves recorded on a collocated microphone and seismometer can be coherent and have a 90-degree phase difference, predicted by theory and in agreement with observations. If the sensors are separated relative to the frequencies of interest, usually 10s to 100s of meters, then recorded wind noise becomes incoherent and an additional phase shift is present due to the separation distance. These characteristics of GCAs have been used to distinguish wind noise from other sources as well as to determine the acoustic contribution to seismic recordings. Here we aim to develop a minimalist infrasound signal detection and characterization technique requiring just one microphone and one three-component seismometer. Based on GCA theory, determining a source azimuth should be possible using a single seismo-acoustic sensor pair by utilizing the phase difference and exploiting the characteristic particle motion. We will use synthetic seismo-acoustic data generated by a coupled Earth-atmosphere 3D finite difference code to test and tune the detection and characterization method. The method will then be further tested using various well-constrained sources (e.g. Chelyabinsk meteor, Pagan Volcano, Cleveland Volcano). Such a technique would be advantageous in situations where resources are limited and large sensor networks are not feasible.

Biology-Inspired Distributed Consensus in Massively-Deployed Sensor Networks

NASA Technical Reports Server (NTRS)

Jones, Kennie H.; Lodding, Kenneth N.; Olariu, Stephan; Wilson, Larry; Xin, Chunsheng

2005-01-01

Promises of ubiquitous control of the physical environment by large-scale wireless sensor networks open avenues for new applications that are expected to redefine the way we live and work. Most of recent research has concentrated on developing techniques for performing relatively simple tasks in small-scale sensor networks assuming some form of centralized control. The main contribution of this work is to propose a new way of looking at large-scale sensor networks, motivated by lessons learned from the way biological ecosystems are organized. Indeed, we believe that techniques used in small-scale sensor networks are not likely to scale to large networks; that such large-scale networks must be viewed as an ecosystem in which the sensors/effectors are organisms whose autonomous actions, based on local information, combine in a communal way to produce global results. As an example of a useful function, we demonstrate that fully distributed consensus can be attained in a scalable fashion in massively deployed sensor networks where individual motes operate based on local information, making local decisions that are aggregated across the network to achieve globally-meaningful effects.

Solution to the Problem of Calibration of Low-Cost Air Quality Measurement Sensors in Networks.

PubMed

Miskell, Georgia; Salmond, Jennifer A; Williams, David E

2018-04-27

We provide a simple, remote, continuous calibration technique suitable for application in a hierarchical network featuring a few well-maintained, high-quality instruments ("proxies") and a larger number of low-cost devices. The ideas are grounded in a clear definition of the purpose of a low-cost network, defined here as providing reliable information on air quality at small spatiotemporal scales. The technique assumes linearity of the sensor signal. It derives running slope and offset estimates by matching mean and standard deviations of the sensor data to values derived from proxies over the same time. The idea is extremely simple: choose an appropriate proxy and an averaging-time that is sufficiently long to remove the influence of short-term fluctuations but sufficiently short that it preserves the regular diurnal variations. The use of running statistical measures rather than cross-correlation of sites means that the method is robust against periods of missing data. Ideas are first developed using simulated data and then demonstrated using field data, at hourly and 1 min time-scales, from a real network of low-cost semiconductor-based sensors. Despite the almost naïve simplicity of the method, it was robust for both drift detection and calibration correction applications. We discuss the use of generally available geographic and environmental data as well as microscale land-use regression as means to enhance the proxy estimates and to generalize the ideas to other pollutants with high spatial variability, such as nitrogen dioxide and particulates. These improvements can also be used to minimize the required number of proxy sites.

Analysis of security and threat of underwater wireless sensor network topology

NASA Astrophysics Data System (ADS)

Yang, Guang; Wei, Zhiqiang; Cong, Yanping; Jia, Dongning

2012-04-01

Underwater wireless sensor networks (UWSNs) are a subclass of wireless sensor networks. Underwater sensor deployment is a significant challenge due to the characteristics of UWSNs and underwater environment. Recent researches for UWSNs deployment mostly focus on the maintenance of network connectivity and maximum communication coverage. However, the broadcast nature of the transmission medium incurs various types of security attacks. This paper studies the security issues and threats of UWSNs topology. Based on the cluster-based topology, an underwater cluster-based security scheme (U-CBSS) is presented to defend against these attacks. and safety.

How to Estimate Epidemic Risk from Incomplete Contact Diaries Data?

PubMed

Mastrandrea, Rossana; Barrat, Alain

2016-06-01

Social interactions shape the patterns of spreading processes in a population. Techniques such as diaries or proximity sensors allow to collect data about encounters and to build networks of contacts between individuals. The contact networks obtained from these different techniques are however quantitatively different. Here, we first show how these discrepancies affect the prediction of the epidemic risk when these data are fed to numerical models of epidemic spread: low participation rate, under-reporting of contacts and overestimation of contact durations in contact diaries with respect to sensor data determine indeed important differences in the outcomes of the corresponding simulations with for instance an enhanced sensitivity to initial conditions. Most importantly, we investigate if and how information gathered from contact diaries can be used in such simulations in order to yield an accurate description of the epidemic risk, assuming that data from sensors represent the ground truth. The contact networks built from contact sensors and diaries present indeed several structural similarities: this suggests the possibility to construct, using only the contact diary network information, a surrogate contact network such that simulations using this surrogate network give the same estimation of the epidemic risk as simulations using the contact sensor network. We present and compare several methods to build such surrogate data, and show that it is indeed possible to obtain a good agreement between the outcomes of simulations using surrogate and sensor data, as long as the contact diary information is complemented by publicly available data describing the heterogeneity of the durations of human contacts.

How to Estimate Epidemic Risk from Incomplete Contact Diaries Data?

PubMed Central

Mastrandrea, Rossana; Barrat, Alain

2016-01-01

Social interactions shape the patterns of spreading processes in a population. Techniques such as diaries or proximity sensors allow to collect data about encounters and to build networks of contacts between individuals. The contact networks obtained from these different techniques are however quantitatively different. Here, we first show how these discrepancies affect the prediction of the epidemic risk when these data are fed to numerical models of epidemic spread: low participation rate, under-reporting of contacts and overestimation of contact durations in contact diaries with respect to sensor data determine indeed important differences in the outcomes of the corresponding simulations with for instance an enhanced sensitivity to initial conditions. Most importantly, we investigate if and how information gathered from contact diaries can be used in such simulations in order to yield an accurate description of the epidemic risk, assuming that data from sensors represent the ground truth. The contact networks built from contact sensors and diaries present indeed several structural similarities: this suggests the possibility to construct, using only the contact diary network information, a surrogate contact network such that simulations using this surrogate network give the same estimation of the epidemic risk as simulations using the contact sensor network. We present and compare several methods to build such surrogate data, and show that it is indeed possible to obtain a good agreement between the outcomes of simulations using surrogate and sensor data, as long as the contact diary information is complemented by publicly available data describing the heterogeneity of the durations of human contacts. PMID:27341027

An Energy-Efficient Game-Theory-Based Spectrum Decision Scheme for Cognitive Radio Sensor Networks

PubMed Central

Salim, Shelly; Moh, Sangman

2016-01-01

A cognitive radio sensor network (CRSN) is a wireless sensor network in which sensor nodes are equipped with cognitive radio. In this paper, we propose an energy-efficient game-theory-based spectrum decision (EGSD) scheme for CRSNs to prolong the network lifetime. Note that energy efficiency is the most important design consideration in CRSNs because it determines the network lifetime. The central part of the EGSD scheme consists of two spectrum selection algorithms: random selection and game-theory-based selection. The EGSD scheme also includes a clustering algorithm, spectrum characterization with a Markov chain, and cluster member coordination. Our performance study shows that EGSD outperforms the existing popular framework in terms of network lifetime and coordination overhead. PMID:27376290

An Energy-Efficient Game-Theory-Based Spectrum Decision Scheme for Cognitive Radio Sensor Networks.

PubMed

Salim, Shelly; Moh, Sangman

2016-06-30

A cognitive radio sensor network (CRSN) is a wireless sensor network in which sensor nodes are equipped with cognitive radio. In this paper, we propose an energy-efficient game-theory-based spectrum decision (EGSD) scheme for CRSNs to prolong the network lifetime. Note that energy efficiency is the most important design consideration in CRSNs because it determines the network lifetime. The central part of the EGSD scheme consists of two spectrum selection algorithms: random selection and game-theory-based selection. The EGSD scheme also includes a clustering algorithm, spectrum characterization with a Markov chain, and cluster member coordination. Our performance study shows that EGSD outperforms the existing popular framework in terms of network lifetime and coordination overhead.

Dynamic Hierarchical Energy-Efficient Method Based on Combinatorial Optimization for Wireless Sensor Networks

PubMed Central

Tang, Hongying; Cheng, Yongbo; Zhao, Qin; Li, Baoqing; Yuan, Xiaobing

2017-01-01

Routing protocols based on topology control are significantly important for improving network longevity in wireless sensor networks (WSNs). Traditionally, some WSN routing protocols distribute uneven network traffic load to sensor nodes, which is not optimal for improving network longevity. Differently to conventional WSN routing protocols, we propose a dynamic hierarchical protocol based on combinatorial optimization (DHCO) to balance energy consumption of sensor nodes and to improve WSN longevity. For each sensor node, the DHCO algorithm obtains the optimal route by establishing a feasible routing set instead of selecting the cluster head or the next hop node. The process of obtaining the optimal route can be formulated as a combinatorial optimization problem. Specifically, the DHCO algorithm is carried out by the following procedures. It employs a hierarchy-based connection mechanism to construct a hierarchical network structure in which each sensor node is assigned to a special hierarchical subset; it utilizes the combinatorial optimization theory to establish the feasible routing set for each sensor node, and takes advantage of the maximum–minimum criterion to obtain their optimal routes to the base station. Various results of simulation experiments show effectiveness and superiority of the DHCO algorithm in comparison with state-of-the-art WSN routing algorithms, including low-energy adaptive clustering hierarchy (LEACH), hybrid energy-efficient distributed clustering (HEED), genetic protocol-based self-organizing network clustering (GASONeC), and double cost function-based routing (DCFR) algorithms. PMID:28753962

Community Seismic Network (CSN)

NASA Astrophysics Data System (ADS)

Clayton, R. W.; Heaton, T. H.; Kohler, M. D.; Cheng, M.; Guy, R.; Chandy, M.; Krause, A.; Bunn, J.; Olson, M.; Faulkner, M.; Liu, A.; Strand, L.

2012-12-01

We report on developments in sensor connectivity, architecture, and data fusion algorithms executed in Cloud computing systems in the Community Seismic Network (CSN), a network of low-cost sensors housed in homes and offices by volunteers in the Pasadena, CA area. The network has over 200 sensors continuously reporting anomalies in local acceleration through the Internet to a Cloud computing service (the Google App Engine) that continually fuses sensor data to rapidly detect shaking from earthquakes. The Cloud computing system consists of data centers geographically distributed across the continent and is likely to be resilient even during earthquakes and other local disasters. The region of Southern California is partitioned in a multi-grid style into sets of telescoping cells called geocells. Data streams from sensors within a geocell are fused to detect anomalous shaking across the geocell. Temporal spatial patterns across geocells are used to detect anomalies across regions. The challenge is to detect earthquakes rapidly with an extremely low false positive rate. We report on two data fusion algorithms, one that tessellates the surface so as to fuse data from a large region around Pasadena and the other, which uses a standard tessellation of equal-sized cells. Since September 2011, the network has successfully detected earthquakes of magnitude 2.5 or higher within 40 Km of Pasadena. In addition to the standard USB device, which connects to the host's computer, we have developed a stand-alone sensor that directly connects to the internet via Ethernet or wifi. This bypasses security concerns that some companies have with the USB-connected devices, and allows for 24/7 monitoring at sites that would otherwise shut down their computers after working hours. In buildings we use the sensors to model the behavior of the structures during weak events in order to understand how they will perform during strong events. Visualization models of instrumented buildings ranging between five and 22 stories tall have been constructed using Google SketchUp. Ambient vibration records are used to identify the first set of horizontal vibrational modal frequencies of the buildings. These frequencies are used to compute the response on every floor of the building, given either observed data or scenario ground motion input at the buildings' base.

Observation infrastructure for airborne hazards in the framework of the EUNADICS-AV project

NASA Astrophysics Data System (ADS)

Mona, Lucia; Pappalardo, Gelsomina; Stammes, Piet; Lihavainen, Heikki; Paatero, Jussi; Hirtl, Marcus; Schlager, Hans; Graf, Kaspar; Hedelt, Pascal; Theys, Nicolas; Coltelli, Mauro; Vargas, Arturo; Clarisse, Lieven; Nína Petersen, Guðrún; de Leeuw, Gerrit; Papagiannopoulos, Nikolaos; Apituley, Arnoud; Haefele, Alexander; Delcloo, Andy; Wotawa, Gerhard

2017-04-01

During the 2010 and 2011 Icelandic volcanic eruptions, the availability of integrated, validated data sets was identified as a major challenge in the effort to gain a rapid situation assessment. These environmental crisis situations may happen again, also from other types ofairborne hazards, like big fires. Currently, the issue is not so much that data and observations do not exist, it is rather the rapid accessibility, the cross-calibration of different sensors, the integration of new platforms and the harmonization of standards and protocols that needs further work and attention. A specific activity is planned within the H-2020 project EUNADICS -AV ("European Natural Disaster Coordination and Information System for Aviation") for addressing this critical issue. In order to achieve the rapid data accessibility, work will be carried out with full consideration of the main European Research Infrastructures, projects and national/international monitoring networks that are able to provide crucial information related to the dispersion of airborne hazards. The integrated data sets are based on satellite and ground-based remote sensing as well as in situ ground-based and aircraft observations. Networks of ground based remote sensing of atmospheric profiles are particularly important, since these will provide the needed height information that cannot be obtained unambiguously from the vast majority of space borne sensors. A new aspect not treated in any project and initiative so far is the integration of special crisis measurements, for example by aircraft or UAV systems. Particularly suited for the purposes of the project are satellite data from operational sensors aboard EUMETSAT and ESA satellites. Improved retrievals are investigated, and the new generation of Sentinel satellites currently being launched under the Copernicus umbrella and their added value are considered. Especially when the ground based and space borne observations are combined, the much needed spatial-temporal developments of the dispersion of atmospheric plumes can be followed. This capability will further be augmented by data assimilation, such that better homogeneity and reliability of data is assured where data is available and gaps can be identified. This integration initiative not only assures that such data can be used in the models during a crisis, but helps towards deploying such systems in a way that the added value can be maximised. Acknowledgments: EUNADICS-AV Project is funded by the European Union's Horizon 2020 research programme for Societal challenges - smart, green and integrated transport under grant agreement no. 723986.

A Wireless Platform for Energy Efficient Building Control Retrofits

DTIC Science & Technology

2012-08-01

University of Illinois at Urbana Champaign UTRC United Technologies Research Center VFD variable frequency drive WSN wireless sensor network ...demonstration area. .............................................................. 16 Table 4. Cost model for wireless sensor network ...buildings with MPC-based whole-building optimal control and (2) reduction in first costs achievable with a wireless sensor network (WSN)-based

Quantifying the Influence of Near-Surface Water-Energy Budgets on Soil Thermal Properties Using a Network of Coupled Meteorological and Vadose Zone Instrument Arrays in Indiana, USA

NASA Astrophysics Data System (ADS)

Naylor, S.; Gustin, A. R.; Ellett, K. M.

2012-12-01

Weather stations that collect reliable, sustained meteorological data sets are becoming more widely distributed because of advances in both instrumentation and data server technology. However, sites collecting soil moisture and soil temperature data remain sparse with even fewer locations where complete meteorological data are collected in conjunction with soil data. Thanks to the advent of sensors that collect continuous in-situ thermal properties data for soils, we have gone a step further and incorporated thermal properties measurements as part of hydrologic instrument arrays in central and northern Indiana. The coupled approach provides insights into the variability of soil thermal conductivity and diffusivity attributable to geologic and climatological controls for various hydrogeologic settings. These data are collected to facilitate the optimization of ground-source heat pumps (GSHPs) in the glaciated Midwest by establishing publicly available data that can be used to parameterize system design models. A network of six monitoring sites was developed in Indiana. Sensors that determine thermal conductivity and diffusivity using radial differential temperature measurements around a heating wire were installed at 1.2 meters below ground surface— a typical depth for horizontal GSHP systems. Each site also includes standard meteorological sensors for calculating reference evapotranspiration following the methods by the Food and Agriculture Organization (FAO) of the United Nations. Vadose zone instrumentation includes time domain reflectometry soil-moisture and temperature sensors installed at 0.3-meter depth intervals down to a 1.8-meter depth, in addition to matric potential sensors at 0.15, 0.3, 0.6, and 1.2 meters. Cores collected at 0.3-meter intervals were analyzed in a laboratory for grain size distribution, bulk density, thermal conductivity, and thermal diffusivity. Our work includes developing methods for calibrating thermal properties sensors based on known standards and comparing measurements from transient line heat source devices. Transform equations have been developed to correct in-situ measurements of thermal conductivity and comparing these results with soil moisture data indicates that thermal conductivity can increase by as much as 25 percent during wetting front propagation. Thermal dryout curves have also been modeled based on laboratory conductivity data collected from core samples to verify field measurements, and alternatively, temperature profile data are used to calibrate near-surface temperature gradient models. We compare data collected across various spatial scales to assess the potential for upscaling near-surface thermal regimes based on available soils data. A long-term goal of the monitoring effort is to establish continuous data sets that determine the effect of climate variability on soil thermal properties such that expected ranges in thermal conductivity can be used to determine optimal ground-coupling loop lengths for GSHP systems.

Secured network sensor-based defense system

NASA Astrophysics Data System (ADS)

Wei, Sixiao; Shen, Dan; Ge, Linqiang; Yu, Wei; Blasch, Erik P.; Pham, Khanh D.; Chen, Genshe

2015-05-01

Network sensor-based defense (NSD) systems have been widely used to defend against cyber threats. Nonetheless, if the adversary finds ways to identify the location of monitor sensors, the effectiveness of NSD systems can be reduced. In this paper, we propose both temporal and spatial perturbation based defense mechanisms to secure NSD systems and make the monitor sensor invisible to the adversary. The temporal-perturbation based defense manipulates the timing information of published data so that the probability of successfully recognizing monitor sensors can be reduced. The spatial-perturbation based defense dynamically redeploys monitor sensors in the network so that the adversary cannot obtain the complete information to recognize all of the monitor sensors. We carried out experiments using real-world traffic traces to evaluate the effectiveness of our proposed defense mechanisms. Our data shows that our proposed defense mechanisms can reduce the attack accuracy of recognizing detection sensors.

The Role of Advanced Information System Technology in Remote Sensing for NASA's Earth Science Enterprise in the 21st Century

NASA Technical Reports Server (NTRS)

Prescott, Glenn; Komar, George (Technical Monitor)

2001-01-01

Future NASA Earth observing satellites will carry high-precision instruments capable of producing large amounts of scientific data. The strategy will be to network these instrument-laden satellites into a web-like array of sensors to facilitate the collection, processing, transmission, storage, and distribution of data and data products - the essential elements of what we refer to as "Information Technology." Many of these Information Technologies will enable the satellite and ground information systems to function effectively in real-time, providing scientists with the capability of customizing data collection activities on a satellite or group of satellites directly from the ground. In future systems, extremely large quantities of data collected by scientific instruments will require the fastest processors, the highest communication channel transfer rates, and the largest data storage capacity to insure that data flows smoothly from the satellite-based instrument to the ground-based archive. Autonomous systems will control all essential processes and play a key role in coordinating the data flow through space-based communication networks. In this paper, we will discuss those critical information technologies for Earth observing satellites that will support the next generation of space-based scientific measurements of planet Earth, and insure that data and data products provided by these systems will be accessible to scientists and the user community in general.

Underwater Sensor Network Redeployment Algorithm Based on Wolf Search

PubMed Central

Jiang, Peng; Feng, Yang; Wu, Feng

2016-01-01

This study addresses the optimization of node redeployment coverage in underwater wireless sensor networks. Given that nodes could easily become invalid under a poor environment and the large scale of underwater wireless sensor networks, an underwater sensor network redeployment algorithm was developed based on wolf search. This study is to apply the wolf search algorithm combined with crowded degree control in the deployment of underwater wireless sensor networks. The proposed algorithm uses nodes to ensure coverage of the events, and it avoids the prematurity of the nodes. The algorithm has good coverage effects. In addition, considering that obstacles exist in the underwater environment, nodes are prevented from being invalid by imitating the mechanism of avoiding predators. Thus, the energy consumption of the network is reduced. Comparative analysis shows that the algorithm is simple and effective in wireless sensor network deployment. Compared with the optimized artificial fish swarm algorithm, the proposed algorithm exhibits advantages in network coverage, energy conservation, and obstacle avoidance. PMID:27775659

Comparison of Satellite Data with Ground-Based Measurements for Assessing Local Distributions of PM2.5 in Northeast Mexico.

NASA Astrophysics Data System (ADS)

Carmona, J.; Mendoza, A.; Lozano, D.; Gupta, P.; Mejia, G.; Rios, J.; Hernández, I.

2017-12-01

Estimating ground-level PM2.5 from satellite-derived Aerosol Optical Depth (AOD) through statistical models is a promising method to evaluate the spatial and temporal distribution of PM2.5 in regions where there are no or few ground-based observations, i.e. Latin America. Although PM concentrations are most accurately measured using ground-based instrumentation, the spatial coverage is too sparse to determine local and regional variations in PM. AOD satellite data offer the opportunity to overcome the spatial limitation of ground-based measurements. However, estimating PM surface concentrations from AOD satellite data is challenging, since multiple factors can affect the relationship between the total-column of AOD and the surface-concentration of PM. In this study, an Assembled Multiple Linear Regression Model (MLR) and a Neural Network Model (NN) were performed to estimate the relationship between the AOD and ground-concentrations of PM2.5 within the Monterrey Metropolitan Area (MMA). The MMA is located in northeast Mexico and is the third most populated urban area in the country. Episodes of high PM pollution levels are frequent throughout the year at the MMA. Daily averages of meteorological and air quality parameters were determined from data recorded at 5 monitoring sites of the MMA air quality monitoring network. Daily AOD data were retrieved from the MODIS sensor onboard the Aqua satellite. Overall, the best performance of the models was obtained using an AOD at 550 µm from the MYD04_3k product in combination with Temperature, Relative Humidity, Wind Speed and Wind Direction ground-based data. For the MLR performed, a correlation coefficient of R 0.6 and % bias of -6% were obtained. The NN showed a better performance than the MLR, with a correlation coefficient of R 0.75 and % bias -4%. The results obtained confirmed that satellite-derived AOD in combination with meteorological fields may allow to estimate PM2.5 local distributions.

An optical sensor network for vegetation phenology monitoring and satellite data calibration.

PubMed

Eklundh, Lars; Jin, Hongxiao; Schubert, Per; Guzinski, Radoslaw; Heliasz, Michal

2011-01-01

We present a network of sites across Fennoscandia for optical sampling of vegetation properties relevant for phenology monitoring and satellite data calibration. The network currently consists of five sites, distributed along an N-S gradient through Sweden and Finland. Two sites are located in coniferous forests, one in a deciduous forest, and two on peatland. The instrumentation consists of dual-beam sensors measuring incoming and reflected red, green, NIR, and PAR fluxes at 10-min intervals, year-round. The sensors are mounted on separate masts or in flux towers in order to capture radiation reflected from within the flux footprint of current eddy covariance measurements. Our computations and model simulations demonstrate the validity of using off-nadir sampling, and we show the results from the first year of measurement. NDVI is computed and compared to that of the MODIS instrument on-board Aqua and Terra satellite platforms. PAR fluxes are partitioned into reflected and absorbed components for the ground and canopy. The measurements demonstrate that the instrumentation provides detailed information about the vegetation phenology and variations in reflectance due to snow cover variations and vegetation development. Valuable information about PAR absorption of ground and canopy is obtained that may be linked to vegetation productivity.

An Optical Sensor Network for Vegetation Phenology Monitoring and Satellite Data Calibration

PubMed Central

Eklundh, Lars; Jin, Hongxiao; Schubert, Per; Guzinski, Radoslaw; Heliasz, Michal

2011-01-01

We present a network of sites across Fennoscandia for optical sampling of vegetation properties relevant for phenology monitoring and satellite data calibration. The network currently consists of five sites, distributed along an N-S gradient through Sweden and Finland. Two sites are located in coniferous forests, one in a deciduous forest, and two on peatland. The instrumentation consists of dual-beam sensors measuring incoming and reflected red, green, NIR, and PAR fluxes at 10-min intervals, year-round. The sensors are mounted on separate masts or in flux towers in order to capture radiation reflected from within the flux footprint of current eddy covariance measurements. Our computations and model simulations demonstrate the validity of using off-nadir sampling, and we show the results from the first year of measurement. NDVI is computed and compared to that of the MODIS instrument on-board Aqua and Terra satellite platforms. PAR fluxes are partitioned into reflected and absorbed components for the ground and canopy. The measurements demonstrate that the instrumentation provides detailed information about the vegetation phenology and variations in reflectance due to snow cover variations and vegetation development. Valuable information about PAR absorption of ground and canopy is obtained that may be linked to vegetation productivity. PMID:22164039

Content-Based Multi-Channel Network Coding Algorithm in the Millimeter-Wave Sensor Network

PubMed Central

Lin, Kai; Wang, Di; Hu, Long

2016-01-01

With the development of wireless technology, the widespread use of 5G is already an irreversible trend, and millimeter-wave sensor networks are becoming more and more common. However, due to the high degree of complexity and bandwidth bottlenecks, the millimeter-wave sensor network still faces numerous problems. In this paper, we propose a novel content-based multi-channel network coding algorithm, which uses the functions of data fusion, multi-channel and network coding to improve the data transmission; the algorithm is referred to as content-based multi-channel network coding (CMNC). The CMNC algorithm provides a fusion-driven model based on the Dempster-Shafer (D-S) evidence theory to classify the sensor nodes into different classes according to the data content. By using the result of the classification, the CMNC algorithm also provides the channel assignment strategy and uses network coding to further improve the quality of data transmission in the millimeter-wave sensor network. Extensive simulations are carried out and compared to other methods. Our simulation results show that the proposed CMNC algorithm can effectively improve the quality of data transmission and has better performance than the compared methods. PMID:27376302

Sensor Authentication in Collaborating Sensor Networks

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bielefeldt, Jake Uriah

2014-11-01

In this thesis, we address a new security problem in the realm of collaborating sensor networks. By collaborating sensor networks, we refer to the networks of sensor networks collaborating on a mission, with each sensor network is independently owned and operated by separate entities. Such networks are practical where a number of independent entities can deploy their own sensor networks in multi-national, commercial, and environmental scenarios, and some of these networks will integrate complementary functionalities for a mission. In the scenario, we address an authentication problem wherein the goal is for the Operator O i of Sensor Network S imore » to correctly determine the number of active sensors in Network Si. Such a problem is challenging in collaborating sensor networks where other sensor networks, despite showing an intent to collaborate, may not be completely trustworthy and could compromise the authentication process. We propose two authentication protocols to address this problem. Our protocols rely on Physically Unclonable Functions, which are a hardware based authentication primitive exploiting inherent randomness in circuit fabrication. Our protocols are light-weight, energy efficient, and highly secure against a number of attacks. To the best of our knowledge, ours is the first to addresses a practical security problem in collaborating sensor networks.« less

Neural networks for satellite remote sensing and robotic sensor interpretation

NASA Astrophysics Data System (ADS)

Martens, Siegfried

Remote sensing of forests and robotic sensor fusion can be viewed, in part, as supervised learning problems, mapping from sensory input to perceptual output. This dissertation develops ARTMAP neural networks for real-time category learning, pattern recognition, and prediction tailored to remote sensing and robotics applications. Three studies are presented. The first two use ARTMAP to create maps from remotely sensed data, while the third uses an ARTMAP system for sensor fusion on a mobile robot. The first study uses ARTMAP to predict vegetation mixtures in the Plumas National Forest based on spectral data from the Landsat Thematic Mapper satellite. While most previous ARTMAP systems have predicted discrete output classes, this project develops new capabilities for multi-valued prediction. On the mixture prediction task, the new network is shown to perform better than maximum likelihood and linear mixture models. The second remote sensing study uses an ARTMAP classification system to evaluate the relative importance of spectral and terrain data for map-making. This project has produced a large-scale map of remotely sensed vegetation in the Sierra National Forest. Network predictions are validated with ground truth data, and maps produced using the ARTMAP system are compared to a map produced by human experts. The ARTMAP Sierra map was generated in an afternoon, while the labor intensive expert method required nearly a year to perform the same task. The robotics research uses an ARTMAP system to integrate visual information and ultrasonic sensory information on a B14 mobile robot. The goal is to produce a more accurate measure of distance than is provided by the raw sensors. ARTMAP effectively combines sensory sources both within and between modalities. The improved distance percept is used to produce occupancy grid visualizations of the robot's environment. The maps produced point to specific problems of raw sensory information processing and demonstrate the benefits of using a neural network system for sensor fusion.

Coupling of ground biosensor networks for water monitoring with satellite observations in assessing Leptospirosis

NASA Astrophysics Data System (ADS)

Skouloudis, A. N.; Rickerby, D. G.

2012-12-01

Leptospirosis became recently a major public-health problem that is closely related with the environment (Nature review Oct 2009, Vol 7, pp 736-747). This disease originates from zoonotic pathogens associated with asymptomatic rodent carriers. Unfortunately, it effects human populations via various direct and indirect routes. This disease can claim many victims with large outbreaks during natural disasters or floods occurring during seasonal conditions. The severity of the illness ranges from subclinical infection to a fulminating fatal disease. Improved water quality monitoring techniques based on biosensor, optical, micro-fluidic and information technologies are leading to radical changes in our ability to perceive and monitor the aquatic environment. Biosensors are capable of providing specific, high spatial resolution information and allow unattended operation that will be particularly useful for water borne related diseases. Current research on biosensors is leading to solutions to problems for several contaminants that were previously irresolvable due to their high degree of complexity. Networking of the sensors enables sensitive monitoring systems allowing real-time monitoring of pollutants and facilitates data transmission between the measurement points and central control stations for continuous surveillance and to provide an early warning capability. The application of intelligent biosensor networks for water quality monitoring and detection of localized sources of pollution are discussed together with the setting up of a methodology that utilizes images from satellite coupled with in-situ sensors for anticipating the zones of potential evolution of this disease and assessing the population at risk. Environmental and climatic conditions that are associated the outbreaks are described and the rational of combining earth observations coupled with advanced in-situ biosensors is explained. The implementation of sensor networks for data collection and exposure mapping is reliant on the identification of location where such networks could be of use. Systematic monitoring from satellite images are utilized for increasing the potential areas of application, for assessing the geographical representativeness on the measurements of the sensors and proposing the methodology on assessing the environmental conditions that are associated with outbreaks of leptospirosis. Unfortunately, several combined deployments of earth observations with ground sensors are required before for the understanding of the connections between hydrology and the human health. Ultimately this will lead to the establishment of early warning system that might investigate the effectiveness of key control measures, including vaccine (when they will become available) and affront the water decontamination, and animal control issues.

Citizen Sensors for SHM: Use of Accelerometer Data from Smartphones

PubMed Central

Feng, Maria; Fukuda, Yoshio; Mizuta, Masato; Ozer, Ekin

2015-01-01

Ubiquitous smartphones have created a significant opportunity to form a low-cost wireless Citizen Sensor network and produce big data for monitoring structural integrity and safety under operational and extreme loads. Such data are particularly useful for rapid assessment of structural damage in a large urban setting after a major event such as an earthquake. This study explores the utilization of smartphone accelerometers for measuring structural vibration, from which structural health and post-event damage can be diagnosed. Widely available smartphones are tested under sinusoidal wave excitations with frequencies in the range relevant to civil engineering structures. Large-scale seismic shaking table tests, observing input ground motion and response of a structural model, are carried out to evaluate the accuracy of smartphone accelerometers under operational, white-noise and earthquake excitations of different intensity. Finally, the smartphone accelerometers are tested on a dynamically loaded bridge. The extensive experiments show satisfactory agreements between the reference and smartphone sensor measurements in both time and frequency domains, demonstrating the capability of the smartphone sensors to measure structural responses ranging from low-amplitude ambient vibration to high-amplitude seismic response. Encouraged by the results of this study, the authors are developing a citizen-engaging and data-analytics crowdsourcing platform towards a smartphone-based Citizen Sensor network for structural health monitoring and post-event damage assessment applications. PMID:25643056

Linking Simulation with Formal Verification and Modeling of Wireless Sensor Network in TLA+

NASA Astrophysics Data System (ADS)

Martyna, Jerzy

In this paper, we present the results of the simulation of a wireless sensor network based on the flooding technique and SPIN protocols. The wireless sensor network was specified and verified by means of the TLA+ specification language [1]. For a model of wireless sensor network built this way simulation was carried with the help of specially constructed software tools. The obtained results allow us to predict the behaviour of the wireless sensor network in various topologies and spatial densities. Visualization of the output data enable precise examination of some phenomenas in wireless sensor networks, such as a hidden terminal, etc.

Multi-Domain SDN Survivability for Agricultural Wireless Sensor Networks.

PubMed

Huang, Tao; Yan, Siyu; Yang, Fan; Liu, Jiang

2016-11-06

Wireless sensor networks (WSNs) have been widely applied in agriculture field; meanwhile, the advent of multi-domain software-defined networks (SDNs) have improved the wireless resource utilization rate and strengthened network management. In recent times, multi-domain SDNs have been applied to agricultural sensor networks, namely multi-domain software-defined wireless sensor networks (SDWSNs). However, when the SDNs controlling agriculture networks suddenly become unavailable, whether intra-domain or inter-domain, sensor network communication is abnormal because of the loss of control. Moreover, there are controller and switch info-updating problems even if the controller becomes available again. To resolve these problems, this paper proposes a new approach based on an Open vSwitch extension for multi-domain SDWSNs, which can enhance agriculture network survivability and stability. We achieved this by designing a connection-state mechanism, a communication mechanism on both L2 and L3, and an info-updating mechanism based on Open vSwitch. The experimental results show that, whether it is agricultural inter-domain or intra-domain during the controller failure period, the sensor switches can enter failure recovery mode as soon as possible so that the sensor network keeps a stable throughput, a short failure recovery time below 300 ms, and low packet loss. Further, the domain can smoothly control the domain network again once the controller becomes available. This approach based on an Open vSwitch extension can enhance the survivability and stability of multi-domain SDWSNs in precision agriculture.

Multi-Domain SDN Survivability for Agricultural Wireless Sensor Networks

PubMed Central

Huang, Tao; Yan, Siyu; Yang, Fan; Liu, Jiang

2016-01-01

Wireless sensor networks (WSNs) have been widely applied in agriculture field; meanwhile, the advent of multi-domain software-defined networks (SDNs) have improved the wireless resource utilization rate and strengthened network management. In recent times, multi-domain SDNs have been applied to agricultural sensor networks, namely multi-domain software-defined wireless sensor networks (SDWSNs). However, when the SDNs controlling agriculture networks suddenly become unavailable, whether intra-domain or inter-domain, sensor network communication is abnormal because of the loss of control. Moreover, there are controller and switch info-updating problems even if the controller becomes available again. To resolve these problems, this paper proposes a new approach based on an Open vSwitch extension for multi-domain SDWSNs, which can enhance agriculture network survivability and stability. We achieved this by designing a connection-state mechanism, a communication mechanism on both L2 and L3, and an info-updating mechanism based on Open vSwitch. The experimental results show that, whether it is agricultural inter-domain or intra-domain during the controller failure period, the sensor switches can enter failure recovery mode as soon as possible so that the sensor network keeps a stable throughput, a short failure recovery time below 300 ms, and low packet loss. Further, the domain can smoothly control the domain network again once the controller becomes available. This approach based on an Open vSwitch extension can enhance the survivability and stability of multi-domain SDWSNs in precision agriculture. PMID:27827971

TinyOS-based quality of service management in wireless sensor networks

USGS Publications Warehouse

Peterson, N.; Anusuya-Rangappa, L.; Shirazi, B.A.; Huang, R.; Song, W.-Z.; Miceli, M.; McBride, D.; Hurson, A.; LaHusen, R.

2009-01-01

Previously the cost and extremely limited capabilities of sensors prohibited Quality of Service (QoS) implementations in wireless sensor networks. With advances in technology, sensors are becoming significantly less expensive and the increases in computational and storage capabilities are opening the door for new, sophisticated algorithms to be implemented. Newer sensor network applications require higher data rates with more stringent priority requirements. We introduce a dynamic scheduling algorithm to improve bandwidth for high priority data in sensor networks, called Tiny-DWFQ. Our Tiny-Dynamic Weighted Fair Queuing scheduling algorithm allows for dynamic QoS for prioritized communications by continually adjusting the treatment of communication packages according to their priorities and the current level of network congestion. For performance evaluation, we tested Tiny-DWFQ, Tiny-WFQ (traditional WFQ algorithm implemented in TinyOS), and FIFO queues on an Imote2-based wireless sensor network and report their throughput and packet loss. Our results show that Tiny-DWFQ performs better in all test cases. ?? 2009 IEEE.

Wide-area littoral discreet observation: success at the tactical edge

NASA Astrophysics Data System (ADS)

Toth, Susan; Hughes, William; Ladas, Andrew

2012-06-01

In June 2011, the United States Army Research Laboratory (ARL) participated in Empire Challenge 2011 (EC-11). EC-11 was United States Joint Forces Command's (USJFCOM) annual live, joint and coalition intelligence, surveillance and reconnaissance (ISR) interoperability demonstration under the sponsorship of the Under Secretary of Defense for Intelligence (USD/I). EC-11 consisted of a series of ISR interoperability events, using a combination of modeling & simulation, laboratory and live-fly events. Wide-area Littoral Discreet Observation (WALDO) was ARL's maritime/littoral capability. WALDO met a USD(I) directive that EC-11 have a maritime component and WALDO was the primary player in the maritime scenario conducted at Camp Lejeune, North Carolina. The WALDO effort demonstrated the utility of a networked layered sensor array deployed in a maritime littoral environment, focusing on maritime surveillance targeting counter-drug, counter-piracy and suspect activity in a littoral or riverine environment. In addition to an embedded analytical capability, the sensor array and control infrastructure consisted of the Oriole acoustic sensor, iScout unattended ground sensor (UGS), OmniSense UGS, the Compact Radar and the Universal Distributed Management System (UDMS), which included the Proxy Skyraider, an optionally manned aircraft mounting both wide and narrow FOV EO/IR imaging sensors. The capability seeded a littoral area with riverine and unattended sensors in order to demonstrate the utility of a Wide Area Sensor (WAS) capability in a littoral environment focused on maritime surveillance activities. The sensors provided a cue for WAS placement/orbit. A narrow field of view sensor would be used to focus on more discreet activities within the WAS footprint. Additionally, the capability experimented with novel WAS orbits to determine if there are more optimal orbits for WAS collection in a littoral environment. The demonstration objectives for WALDO at EC-11 were: * Demonstrate a networked, layered, multi-modal sensor array deployed in a maritime littoral environment, focusing on maritime surveillance targeting counter-drug, counter-piracy and suspect activity * Assess the utility of a Wide Area Surveillance (WAS) sensor in a littoral environment focused on maritime surveillance activities * Demonstrate the effectiveness of using UGS sensors to cue WAS sensor tasking * Employ a narrow field of view full motion video (FMV) sensor package that is collocated with the WAS to conduct more discrete observation of potential items of interest when queued by near-real-time data from UGS or observers * Couple the ARL Oriole sensor with other modality UGS networks in a ground layer ISR capability, and incorporate data collected from aerial sensors with a GEOINT base layer to form a fused product * Swarm multiple aerial or naval platforms to prosecute single or multiple targets * Track fast moving surface vessels in littoral areas * Disseminate time sensitive, high value data to the users at the tactical edge In short we sought to answer the following question: how do you layer, control and display disparate sensors and sensor modalities in such a way as to facilitate appropriate sensor cross-cue, data integration, and analyst control to effectively monitor activity in a littoral (or novel) environment?

Application of wireless sensor network technology in logistics information system

NASA Astrophysics Data System (ADS)

Xu, Tao; Gong, Lina; Zhang, Wei; Li, Xuhong; Wang, Xia; Pan, Wenwen

2017-04-01

This paper introduces the basic concepts of active RFID (WSN-ARFID) based on wireless sensor networks and analyzes the shortcomings of the existing RFID-based logistics monitoring system. Integrated wireless sensor network technology and the scrambling point of RFID technology. A new real-time logistics detection system based on WSN and RFID, a model of logistics system based on WSN-ARFID is proposed, and the feasibility of this technology applied to logistics field is analyzed.

Sensor Webs as Virtual Data Systems for Earth Science

NASA Astrophysics Data System (ADS)

Moe, K. L.; Sherwood, R.

2008-05-01

The NASA Earth Science Technology Office established a 3-year Advanced Information Systems Technology (AIST) development program in late 2006 to explore the technical challenges associated with integrating sensors, sensor networks, data assimilation and modeling components into virtual data systems called "sensor webs". The AIST sensor web program was initiated in response to a renewed emphasis on the sensor web concepts. In 2004, NASA proposed an Earth science vision for a more robust Earth observing system, coupled with remote sensing data analysis tools and advances in Earth system models. The AIST program is conducting the research and developing components to explore the technology infrastructure that will enable the visionary goals. A working statement for a NASA Earth science sensor web vision is the following: On-demand sensing of a broad array of environmental and ecological phenomena across a wide range of spatial and temporal scales, from a heterogeneous suite of sensors both in-situ and in orbit. Sensor webs will be dynamically organized to collect data, extract information from it, accept input from other sensor / forecast / tasking systems, interact with the environment based on what they detect or are tasked to perform, and communicate observations and results in real time. The focus on sensor webs is to develop the technology and prototypes to demonstrate the evolving sensor web capabilities. There are 35 AIST projects ranging from 1 to 3 years in duration addressing various aspects of sensor webs involving space sensors such as Earth Observing-1, in situ sensor networks such as the southern California earthquake network, and various modeling and forecasting systems. Some of these projects build on proof-of-concept demonstrations of sensor web capabilities like the EO-1 rapid fire response initially implemented in 2003. Other projects simulate future sensor web configurations to evaluate the effectiveness of sensor-model interactions for producing improved science predictions. Still other projects are maturing technology to support autonomous operations, communications and system interoperability. This paper will highlight lessons learned by various projects during the first half of the AIST program. Several sensor web demonstrations have been implemented and resulting experience with evolving standards, such as the Open Geospatial Consortium (OGC) Sensor Web Enablement (SWE) among others, will be featured. The role of sensor webs in support of the intergovernmental Group on Earth Observations' Global Earth Observation System of Systems (GEOSS) will also be discussed. The GEOSS vision is a distributed system of systems that builds on international components to supply observing and processing systems that are, in the whole, comprehensive, coordinated and sustained. Sensor web prototypes are under development to demonstrate how remote sensing satellite data, in situ sensor networks and decision support systems collaborate in applications of interest to GEO, such as flood monitoring. Furthermore, the international Committee on Earth Observation Satellites (CEOS) has stepped up to the challenge to provide the space-based systems component for GEOSS. CEOS has proposed "virtual constellations" to address emerging data gaps in environmental monitoring, avoid overlap among observing systems, and make maximum use of existing space and ground assets. Exploratory applications that support the objectives of virtual constellations will also be discussed as a future role for sensor webs.

Integrated monitoring of ecological conditions in wetland-upland landscapes

USGS Publications Warehouse

Gallant, Alisa; Sadinski, Walt

2012-01-01

Landscapes of interwoven wetlands and uplands offer a rich set of ecosystem goods and services. Managing lands to maximize ecosystem services requires information that distinguishes change caused by local actions from broader-scale shifts in climate, land use, and other forms of global change. Satellite and airborne sensors collect valuable data for this purpose, especially when the data are analyzed along with data collected from ground-based sensors. The U.S. Geological Survey (USGS) is using remote sensing technology in this way as part of the Terrestrial Wetland Global Change Research Network to assess effects of climate change interacting with land-use change and other potential stressors along environmental gradients of wetland-upland landscapes in the United States and Canada.

Coherent Evaluation of Aerosol Data Products from Multiple Satellite Sensors

NASA Technical Reports Server (NTRS)

Ichoku, Charles

2011-01-01

Aerosol retrieval from satellite has practically become routine, especially during the last decade. However, there is often disagreement between similar aerosol parameters retrieved from different sensors, thereby leaving users confused as to which sensors to trust for answering important science questions about the distribution, properties, and impacts of aerosols. As long as there is no consensus, and the inconsistencies are not well characterized and understood, there will be no way of developing reliable model inputs and climate data records from satellite aerosol measurements. Fortunately, the Aerosol Robotic Network (AERONET) is providing well-calibrated globally representative ground-based aerosol measurements corresponding to the satellite-retrieved products. Through a recently developed web-based Multi-sensor Aerosol Products Sampling System (MAPSS), we are utilizing the advantages offered by collocated AERONET and satellite products to characterize and evaluate aerosol retrieval from multiple sensors. Indeed, MAPSS and its companion statistical tool AeroStat are facilitating detailed comparative uncertainty analysis of satellite aerosol measurements from Terra-MODIS, Aqua-MODIS, Terra-MISR, Aura-OMI, Parasol-POLDER, and Calipso-CALIOP. In this presentation, we will describe the strategy of the MAPSS system, its potential advantages for the aerosol community, and the preliminary results of an integrated comparative uncertainly analysis of aerosol products from multiple satellite sensors.

Validation of Distributed Soil Moisture: Airborne Polarimetric SAR vs. Ground-based Sensor Networks

NASA Astrophysics Data System (ADS)

Jagdhuber, T.; Kohling, M.; Hajnsek, I.; Montzka, C.; Papathanassiou, K. P.

2012-04-01

The knowledge of spatially distributed soil moisture is highly desirable for an enhanced hydrological modeling in terms of flood prevention and for yield optimization in combination with precision farming. Especially in mid-latitudes, the growing agricultural vegetation results in an increasing soil coverage along the crop cycle. For a remote sensing approach, this vegetation influence has to be separated from the soil contribution within the resolution cell to extract the actual soil moisture. Therefore a hybrid decomposition was developed for estimation of soil moisture under vegetation cover using fully polarimetric SAR data. The novel polarimetric decomposition combines a model-based decomposition, separating the volume component from the ground components, with an eigen-based decomposition of the two ground components into a surface and a dihedral scattering contribution. Hence, this hybrid decomposition, which is based on [1,2], establishes an innovative way to retrieve soil moisture under vegetation. The developed inversion algorithm for soil moisture under vegetation cover is applied on fully polarimetric data of the TERENO campaign, conducted in May and June 2011 for the Rur catchment within the Eifel/Lower Rhine Valley Observatory. The fully polarimetric SAR data were acquired in high spatial resolution (range: 1.92m, azimuth: 0.6m) by DLR's novel F-SAR sensor at L-band. The inverted soil moisture product from the airborne SAR data is validated with corresponding distributed ground measurements for a quality assessment of the developed algorithm. The in situ measurements were obtained on the one hand by mobile FDR probes from agricultural fields near the towns of Merzenhausen and Selhausen incorporating different crop types and on the other hand by distributed wireless sensor networks (SoilNet clusters) from a grassland test site (near the town of Rollesbroich) and from a forest stand (within the Wüstebach sub-catchment). Each SoilNet cluster incorporates around 150 wireless measuring devices on a grid of approximately 30ha for distributed soil moisture sensing. Finally, the comparison of both distributed soil moisture products results in a discussion on potentials and limitations for obtaining soil moisture under vegetation cover with high resolution fully polarimetric SAR. [1] S.R. Cloude, Polarisation: applications in remote sensing. Oxford, Oxford University Press, 2010. [2] Jagdhuber, T., Hajnsek, I., Papathanassiou, K.P. and Bronstert, A.: A Hybrid Decomposition for Soil Moisture Estimation under Vegetation Cover Using Polarimetric SAR. Proc. of the 5th International Workshop on Science and Applications of SAR Polarimetry and Polarimetric Interferometry, ESA-ESRIN, Frascati, Italy, January 24-28, 2011, p.1-6.

Bridging the Scales from Field to Region with Practical Tools to Couple Time- and Space-Synchronized Data from Flux Towers and Networks with Proximal and Remote Sensing Data

NASA Astrophysics Data System (ADS)

Burba, G. G.; Avenson, T.; Burkart, A.; Gamon, J. A.; Guan, K.; Julitta, T.; Pastorello, G.; Sakowska, K.

2017-12-01

Many hundreds of flux towers are presently operational as standalone projects and as parts of regional networks. However, the vast majority of these towers do not allow straightforward coupling with remote sensing (drone, aircraft, satellite, etc.) data, and even fewer have optical sensors for validation of remote sensing products, and upscaling from field to regional levels. In 2016-2017, new tools to collect, process, and share time-synchronized flux data from multiple towers were developed and deployed globally. Originally designed to automate site and data management, and to streamline flux data analysis, these tools allow relatively easy matching of tower data with remote sensing data: GPS-driven PTP time protocol synchronizes instrumentation within the station, different stations with each other, and all of these to remote sensing data to precisely align remote sensing and flux data in time Footprint size and coordinates computed and stored with flux data help correctly align tower flux footprints and drone, aircraft or satellite motion to precisely align optical and flux data in space Full snapshot of the remote sensing pixel can then be constructed, including leaf-level, ground optical sensor, and flux tower measurements from the same footprint area, closely coupled with the remote sensing measurements to help interpret remote sensing data, validate models, and improve upscaling Additionally, current flux towers can be augmented with advanced ground optical sensors and can use standard routines to deliver continuous products (e.g. SIF, PRI, NDVI, etc.) based on automated field spectrometers (e.g., FloX and RoX, etc.) and other optical systems. Several dozens of new towers already operational globally can be readily used for the proposed workflow. Over 500 active traditional flux towers can be updated to synchronize their data with remote sensing measurements. This presentation will show how the new tools are used by major networks, and describe how this approach can be utilized for matching remote sensing and tower data to aid in ground truthing, improve scientific interactions, and promote joint grant writing and other forms of collaboration between the flux and remote sensing communities.

Three-dimensional ocean sensor networks: A survey

NASA Astrophysics Data System (ADS)

Wang, Yu; Liu, Yingjian; Guo, Zhongwen

2012-12-01

The past decade has seen a growing interest in ocean sensor networks because of their wide applications in marine research, oceanography, ocean monitoring, offshore exploration, and defense or homeland security. Ocean sensor networks are generally formed with various ocean sensors, autonomous underwater vehicles, surface stations, and research vessels. To make ocean sensor network applications viable, efficient communication among all devices and components is crucial. Due to the unique characteristics of underwater acoustic channels and the complex deployment environment in three dimensional (3D) ocean spaces, new efficient and reliable communication and networking protocols are needed in design of ocean sensor networks. In this paper, we aim to provide an overview of the most recent advances in network design principles for 3D ocean sensor networks, with focuses on deployment, localization, topology design, and position-based routing in 3D ocean spaces.

Dynamic Hierarchical Sleep Scheduling for Wireless Ad-Hoc Sensor Networks

PubMed Central

Wen, Chih-Yu; Chen, Ying-Chih

2009-01-01

This paper presents two scheduling management schemes for wireless sensor networks, which manage the sensors by utilizing the hierarchical network structure and allocate network resources efficiently. A local criterion is used to simultaneously establish the sensing coverage and connectivity such that dynamic cluster-based sleep scheduling can be achieved. The proposed schemes are simulated and analyzed to abstract the network behaviors in a number of settings. The experimental results show that the proposed algorithms provide efficient network power control and can achieve high scalability in wireless sensor networks. PMID:22412343

Dynamic hierarchical sleep scheduling for wireless ad-hoc sensor networks.

PubMed

Wen, Chih-Yu; Chen, Ying-Chih

2009-01-01

This paper presents two scheduling management schemes for wireless sensor networks, which manage the sensors by utilizing the hierarchical network structure and allocate network resources efficiently. A local criterion is used to simultaneously establish the sensing coverage and connectivity such that dynamic cluster-based sleep scheduling can be achieved. The proposed schemes are simulated and analyzed to abstract the network behaviors in a number of settings. The experimental results show that the proposed algorithms provide efficient network power control and can achieve high scalability in wireless sensor networks.

Evaluating a New Homogeneous Total Ozone Climate Data Record from GOME/ERS-2, SCIAMACHY/Envisat, and GOME-2/MetOp-A

NASA Technical Reports Server (NTRS)

Koukouli, M.E.; Lerot, C.; Granville, J.; Goutail, F.; Lambert, J.-C.; Pommereau, J.-P.; Balis, D.; Zyrichidou, I.; Van Roozendael, M.; Coldewey-Egbers, M.;

Watchdog Sensor Network with Multi-Stage RF Signal Identification and Cooperative Intrusion Detection

DTIC Science & Technology

2012-03-01

detection and physical layer authentication in mobile Ad Hoc networks and wireless sensor networks (WSNs) have been investigated. Résume Le rapport...IEEE 802.16 d and e (WiMAX); (b) IEEE 802.11 (Wi-Fi) family of a, b, g, n, and s (c) Sensor networks based on IEEE 802.15.4: Wireless USB, Bluetooth... sensor network are investigated for standard compatible wireless signals. The proposed signal existence detection and identification process consists

Web-Based Interface for Command and Control of Network Sensors

NASA Technical Reports Server (NTRS)

Wallick, Michael N.; Doubleday, Joshua R.; Shams, Khawaja S.

2010-01-01

This software allows for the visualization and control of a network of sensors through a Web browser interface. It is currently being deployed for a network of sensors monitoring Mt. Saint Helen s volcano; however, this innovation is generic enough that it can be deployed for any type of sensor Web. From this interface, the user is able to fully control and monitor the sensor Web. This includes, but is not limited to, sending "test" commands to individual sensors in the network, monitoring for real-world events, and reacting to those events

Integrating wireless sensor network for monitoring subsidence phenomena

NASA Astrophysics Data System (ADS)

Marturià, Jordi; Lopez, Ferran; Gigli, Giovanni; Intrieri, Emanuele; Mucchi, Lorenzo; Fornaciai, Alessandro

2016-04-01

An innovative wireless sensor network (WSN) for the 3D superficial monitoring of deformations (such as landslides and subsidence) is being developed in the frame of the Wi-GIM project (Wireless sensor network for Ground Instability Monitoring - LIFE12 ENV/IT/001033). The surface movement is detected acquiring the position (x, y and z) by integrating large bandwidth technology able to detect the 3D coordinates of the sensor with a sub-meter error, with continuous wave radar, which allows decreasing the error down to sub-cm. The Estació neighborhood in Sallent is located over the old potassium mine Enrique. This zone has been affected by a subsidence process over more than twenty years. The implementation of a wide network for ground auscultation has allowed monitoring the process of subsidence since 1997. This network consists of: i) a high-precision topographic leveling network to control the subsidence in surface; ii) a rod extensometers network to monitor subsurface deformation; iii) an automatic Leica TCA Total Station to monitor building movements; iv) an inclinometers network to measure the horizontal displacements on subsurface and v) a piezometer to measure the water level. Those networks were implemented within an alert system for an organized an efficient response of the civil protection authorities in case of an emergency. On 23rd December 2008, an acceleration of subsoil movements (of approx. 12-18 cm/year) provoked the activation of the emergency plan by the Catalan Civil Protection. This implied the preventive and scheduled evacuation of the neighbours (January 2009) located in the area with a higher risk of collapse: around 120 residents of 43 homes. As a consequence, the administration implemented a compensation plan for the evacuation of the whole neighbourhood residents and the demolition of 405 properties. In this work, the adaptation and integration process of Wi-GIM system with those conventional monitoring network are presented for its testing and evaluation. The knowledge gained in the subsidence process, complemented by the huge availability of data from existing networks constitutes a solid foundation for achieving those objectives. New monitoring points have been identified, constructed, prepared to integrate the conventional monitoring system with Wi-GIM system to build a robust system compatible with WI-GIM requirements.

A range-based predictive localization algorithm for WSID networks

NASA Astrophysics Data System (ADS)

Liu, Yuan; Chen, Junjie; Li, Gang

2017-11-01

Most studies on localization algorithms are conducted on the sensor networks with densely distributed nodes. However, the non-localizable problems are prone to occur in the network with sparsely distributed sensor nodes. To solve this problem, a range-based predictive localization algorithm (RPLA) is proposed in this paper for the wireless sensor networks syncretizing the RFID (WSID) networks. The Gaussian mixture model is established to predict the trajectory of a mobile target. Then, the received signal strength indication is used to reduce the residence area of the target location based on the approximate point-in-triangulation test algorithm. In addition, collaborative localization schemes are introduced to locate the target in the non-localizable situations. Simulation results verify that the RPLA achieves accurate localization for the network with sparsely distributed sensor nodes. The localization accuracy of the RPLA is 48.7% higher than that of the APIT algorithm, 16.8% higher than that of the single Gaussian model-based algorithm and 10.5% higher than that of the Kalman filtering-based algorithm.

SCODE: A Secure Coordination-Based Data Dissemination to Mobile Sinks in Sensor Networks

NASA Astrophysics Data System (ADS)

Hung, Lexuan; Lee, Sungyoung; Lee, Young-Koo; Lee, Heejo

For many sensor network applications such as military, homeland security, it is necessary for users (sinks) to access sensor networks while they are moving. However, sink mobility brings new challenges to secure routing in large-scale sensor networks. Mobile sinks have to constantly propagate their current location to all nodes, and these nodes need to exchange messages with each other so that the sensor network can establish and maintain a secure multi-hop path between a source node and a mobile sink. This causes significant computation and communication overhead for sensor nodes. Previous studies on sink mobility have mainly focused on efficiency and effectiveness of data dissemination without security consideration. In this paper, we propose a secure and energy-efficient data dissemination protocol — Secure COodination-based Data dissEmination (SCODE) — for mobile sinks in sensor networks. We take advantages of coordination networks (grid structure) based on Geographical Adaptive Fidelity (GAF) protocol to construct a secure and efficient routing path between sources and sinks. Our security analysis demonstrates that the proposed protocol can defend against common attacks in sensor network routing such as replay attacks, selective forwarding attacks, sinkhole and wormhole, Sybil attacks, HELLO flood attacks. Our performance evaluation both in mathematical analysis and simulation shows that the SCODE significantly reduces communication overhead and energy consumption while the latency is similar compared with the existing routing protocols, and it always delivers more than 90 percentage of packets successfully.

Design and Analysis of a Data Fusion Scheme in Mobile Wireless Sensor Networks Based on Multi-Protocol Mobile Agents

PubMed Central

Wu, Chunxue; Wu, Wenliang; Wan, Caihua

2017-01-01

Sensors are increasingly used in mobile environments with wireless network connections. Multiple sensor types measure distinct aspects of the same event. Their measurements are then combined to produce integrated, reliable results. As the number of sensors in networks increases, low energy requirements and changing network connections complicate event detection and measurement. We present a data fusion scheme for use in mobile wireless sensor networks with high energy efficiency and low network delays, that still produces reliable results. In the first phase, we used a network simulation where mobile agents dynamically select the next hop migration node based on the stability parameter of the link, and perform the data fusion at the migration node. Agents use the fusion results to decide if it should return the fusion results to the processing center or continue to collect more data. In the second phase. The feasibility of data fusion at the node level is confirmed by an experimental design where fused data from color sensors show near-identical results to actual physical temperatures. These results are potentially important for new large-scale sensor network applications. PMID:29099793

An Embedded Multi-Agent Systems Based Industrial Wireless Sensor Network

PubMed Central

Brennan, Robert W.

2017-01-01

With the emergence of cyber-physical systems, there has been a growing interest in network-connected devices. One of the key requirements of a cyber-physical device is the ability to sense its environment. Wireless sensor networks are a widely-accepted solution for this requirement. In this study, an embedded multi-agent systems-managed wireless sensor network is presented. A novel architecture is proposed, along with a novel wireless sensor network architecture. Active and passive wireless sensor node types are defined, along with their communication protocols, and two application-specific examples are presented. A series of three experiments is conducted to evaluate the performance of the agent-embedded wireless sensor network. PMID:28906452

An Embedded Multi-Agent Systems Based Industrial Wireless Sensor Network.

PubMed

Taboun, Mohammed S; Brennan, Robert W

2017-09-14

With the emergence of cyber-physical systems, there has been a growing interest in network-connected devices. One of the key requirements of a cyber-physical device is the ability to sense its environment. Wireless sensor networks are a widely-accepted solution for this requirement. In this study, an embedded multi-agent systems-managed wireless sensor network is presented. A novel architecture is proposed, along with a novel wireless sensor network architecture. Active and passive wireless sensor node types are defined, along with their communication protocols, and two application-specific examples are presented. A series of three experiments is conducted to evaluate the performance of the agent-embedded wireless sensor network.

Development and Evaluation of a City-Wide Wireless Weather Sensor Network

ERIC Educational Resources Information Center

Chang, Ben; Wang, Hsue-Yie; Peng, Tian-Yin; Hsu, Ying-Shao

2010-01-01

This project analyzed the effectiveness of a city-wide wireless weather sensor network, the Taipei Weather Science Learning Network (TWIN), in facilitating elementary and junior high students' study of weather science. The network, composed of sixty school-based weather sensor nodes and a centralized weather data archive server, provides students…

A Novel Energy Efficient Topology Control Scheme Based on a Coverage-Preserving and Sleep Scheduling Model for Sensor Networks

PubMed Central

Shi, Binbin; Wei, Wei; Wang, Yihuai; Shu, Wanneng

2016-01-01

In high-density sensor networks, scheduling some sensor nodes to be in the sleep mode while other sensor nodes remain active for monitoring or forwarding packets is an effective control scheme to conserve energy. In this paper, a Coverage-Preserving Control Scheduling Scheme (CPCSS) based on a cloud model and redundancy degree in sensor networks is proposed. Firstly, the normal cloud model is adopted for calculating the similarity degree between the sensor nodes in terms of their historical data, and then all nodes in each grid of the target area can be classified into several categories. Secondly, the redundancy degree of a node is calculated according to its sensing area being covered by the neighboring sensors. Finally, a centralized approximation algorithm based on the partition of the target area is designed to obtain the approximate minimum set of nodes, which can retain the sufficient coverage of the target region and ensure the connectivity of the network at the same time. The simulation results show that the proposed CPCSS can balance the energy consumption and optimize the coverage performance of the sensor network. PMID:27754405

A Novel Energy Efficient Topology Control Scheme Based on a Coverage-Preserving and Sleep Scheduling Model for Sensor Networks.

PubMed

Shi, Binbin; Wei, Wei; Wang, Yihuai; Shu, Wanneng

2016-10-14

In high-density sensor networks, scheduling some sensor nodes to be in the sleep mode while other sensor nodes remain active for monitoring or forwarding packets is an effective control scheme to conserve energy. In this paper, a Coverage-Preserving Control Scheduling Scheme (CPCSS) based on a cloud model and redundancy degree in sensor networks is proposed. Firstly, the normal cloud model is adopted for calculating the similarity degree between the sensor nodes in terms of their historical data, and then all nodes in each grid of the target area can be classified into several categories. Secondly, the redundancy degree of a node is calculated according to its sensing area being covered by the neighboring sensors. Finally, a centralized approximation algorithm based on the partition of the target area is designed to obtain the approximate minimum set of nodes, which can retain the sufficient coverage of the target region and ensure the connectivity of the network at the same time. The simulation results show that the proposed CPCSS can balance the energy consumption and optimize the coverage performance of the sensor network.

A Study on Wireless Charging for Prolonging the Lifetime of Wireless Sensor Networks.

PubMed

Tu, Weijian; Xu, Xianghua; Ye, Tingcong; Cheng, Zongmao

2017-07-04

Wireless charging is an important issue in wireless sensor networks, since it can provide an emerging and effective solution in the absence of other power supplies. The state-of-the-art methods employ a mobile car and a predefined moving path to charge the sensor nodes in the network. Previous studies only consider a factor of the network (i.e., residual energy of sensor node) as a constraint to design the wireless charging strategy. However, other factors, such as the travelled distance of the mobile car, can also affect the effectiveness of wireless charging strategy. In this work, we study wireless charging strategy based on the analysis of a combination of two factors, including the residual energy of sensor nodes and the travelled distance of the charging car. Firstly, we theoretically analyze the limited size of the sensor network to match the capability of a charging car. Then, the networked factors are selected as the weights of traveling salesman problem (TSP) to design the moving path of the charging car. Thirdly, the charging time of each sensor node is computed based on the linear programming problem for the charging car. Finally, a charging period for the network is studied. The experimental results show that the proposed approach can significantly maximize the lifetime of the wireless sensor network.

Cryosphere Sensor Webs With The Autonomous Sciencecraft Experiment

NASA Astrophysics Data System (ADS)

Scharenbroich, L.; Doggett, T.; Kratz, T.; Castano, R.; Chien, S.; Davies, A. G.; Tran, D.; Mazzoni, D.

2006-12-01

Autonomous sensor-webs are being deployed as part of the Autonomous Sciencecraft Experiment [1], whereby observations using the Hyperion instrument [2] on-board Earth Observing-1 (EO-1 are triggered by either ground sensors or by near-real-time analysis of data from other space-based sensors. In the realm of cryosphere monitoring, one sensor-web has been set up pairing EO-1 with a sensor buoy [3] deployed in Sparkling Lake, one of several lakes in northern Wisconsin monitored by University of Wisconsin's Trout Lake Station. A Support Vector Machine (SVM) classifier was trained on historical thermistor chain data with manually recorded ice-in and ice-out times and used to trigger Hyperion observations of the Trout Lake area during spring thaw and winter freeze in 2005. A second sensor-web is being developed using near-real time sea ice data products, based on Department of Defense meteorological satellites, available from the National Snow and Ice Data Center (NSIDC) [4]. Once operational, this sensor web will trigger Hyperion observations of pre-defined targets in the Arctic and Antarctic where regional resolution data shows sea ice formation or break up. [1] Chien et al. (2005), An autonomous earth-observing sensor-web, IEEE Intelligent Systems, [2] Pearlman et al. (2003), Hyperion, a space-based imaging spectrometer, IEEE Trans. Geosci. Rem. Sens., 41(6), [3] Kratz, T. et al. (in press) Toward a Global Lake Ecological Observatory Network, Proceedings of the Karelian Institute, [4] Cavalieri et al. (1999) Near real-time DMSP SSM/I daily polar gridded sea ice concentrations, National Snow and Ice Data Center. Digital Media.

Ultra-low power high precision magnetotelluric receiver array based customized computer and wireless sensor network

NASA Astrophysics Data System (ADS)

Chen, R.; Xi, X.; Zhao, X.; He, L.; Yao, H.; Shen, R.

2016-12-01

Dense 3D magnetotelluric (MT) data acquisition owns the benefit of suppressing the static shift and topography effect, can achieve high precision and high resolution inversion for underground structure. This method may play an important role in mineral exploration, geothermal resources exploration, and hydrocarbon exploration. It's necessary to reduce the power consumption greatly of a MT signal receiver for large-scale 3D MT data acquisition while using sensor network to monitor data quality of deployed MT receivers. We adopted a series of technologies to realized above goal. At first, we designed an low-power embedded computer which can couple with other parts of MT receiver tightly and support wireless sensor network. The power consumption of our embedded computer is less than 1 watt. Then we designed 4-channel data acquisition subsystem which supports 24-bit analog-digital conversion, GPS synchronization, and real-time digital signal processing. Furthermore, we developed the power supply and power management subsystem for MT receiver. At last, a series of software, which support data acquisition, calibration, wireless sensor network, and testing, were developed. The software which runs on personal computer can monitor and control over 100 MT receivers on the field for data acquisition and quality control. The total power consumption of the receiver is about 2 watts at full operation. The standby power consumption is less than 0.1 watt. Our testing showed that the MT receiver can acquire good quality data at ground with electrical dipole length as 3 m. Over 100 MT receivers were made and used for large-scale geothermal exploration in China with great success.

Using Neural Networks for Sensor Validation

NASA Technical Reports Server (NTRS)

Mattern, Duane L.; Jaw, Link C.; Guo, Ten-Huei; Graham, Ronald; McCoy, William

1998-01-01

This paper presents the results of applying two different types of neural networks in two different approaches to the sensor validation problem. The first approach uses a functional approximation neural network as part of a nonlinear observer in a model-based approach to analytical redundancy. The second approach uses an auto-associative neural network to perform nonlinear principal component analysis on a set of redundant sensors to provide an estimate for a single failed sensor. The approaches are demonstrated using a nonlinear simulation of a turbofan engine. The fault detection and sensor estimation results are presented and the training of the auto-associative neural network to provide sensor estimates is discussed.

An Enhanced PSO-Based Clustering Energy Optimization Algorithm for Wireless Sensor Network.

PubMed

Vimalarani, C; Subramanian, R; Sivanandam, S N

2016-01-01

Wireless Sensor Network (WSN) is a network which formed with a maximum number of sensor nodes which are positioned in an application environment to monitor the physical entities in a target area, for example, temperature monitoring environment, water level, monitoring pressure, and health care, and various military applications. Mostly sensor nodes are equipped with self-supported battery power through which they can perform adequate operations and communication among neighboring nodes. Maximizing the lifetime of the Wireless Sensor networks, energy conservation measures are essential for improving the performance of WSNs. This paper proposes an Enhanced PSO-Based Clustering Energy Optimization (EPSO-CEO) algorithm for Wireless Sensor Network in which clustering and clustering head selection are done by using Particle Swarm Optimization (PSO) algorithm with respect to minimizing the power consumption in WSN. The performance metrics are evaluated and results are compared with competitive clustering algorithm to validate the reduction in energy consumption.

A Gossip-based Energy Efficient Protocol for Robust In-network Aggregation in Wireless Sensor Networks

NASA Astrophysics Data System (ADS)

Fauji, Shantanu

We consider the problem of energy efficient and fault tolerant in--network aggregation for wireless sensor networks (WSNs). In-network aggregation is the process of aggregation while collecting data from sensors to the base station. This process should be energy efficient due to the limited energy at the sensors and tolerant to the high failure rates common in sensor networks. Tree based in--network aggregation protocols, although energy efficient, are not robust to network failures. Multipath routing protocols are robust to failures to a certain degree but are not energy efficient due to the overhead in the maintenance of multiple paths. We propose a new protocol for in-network aggregation in WSNs, which is energy efficient, achieves high lifetime, and is robust to the changes in the network topology. Our protocol, gossip--based protocol for in-network aggregation (GPIA) is based on the spreading of information via gossip. GPIA is not only adaptive to failures and changes in the network topology, but is also energy efficient. Energy efficiency of GPIA comes from all the nodes being capable of selective message reception and detecting convergence of the aggregation early. We experimentally show that GPIA provides significant improvement over some other competitors like the Ridesharing, Synopsis Diffusion and the pure version of gossip. GPIA shows ten fold, five fold and two fold improvement over the pure gossip, the synopsis diffusion and Ridesharing protocols in terms of network lifetime, respectively. Further, GPIA retains gossip's robustness to failures and improves upon the accuracy of synopsis diffusion and Ridesharing.

High-fidelity simulation capability for virtual testing of seismic and acoustic sensors

NASA Astrophysics Data System (ADS)

Wilson, D. Keith; Moran, Mark L.; Ketcham, Stephen A.; Lacombe, James; Anderson, Thomas S.; Symons, Neill P.; Aldridge, David F.; Marlin, David H.; Collier, Sandra L.; Ostashev, Vladimir E.

2005-05-01

This paper describes development and application of a high-fidelity, seismic/acoustic simulation capability for battlefield sensors. The purpose is to provide simulated sensor data so realistic that they cannot be distinguished by experts from actual field data. This emerging capability provides rapid, low-cost trade studies of unattended ground sensor network configurations, data processing and fusion strategies, and signatures emitted by prototype vehicles. There are three essential components to the modeling: (1) detailed mechanical signature models for vehicles and walkers, (2) high-resolution characterization of the subsurface and atmospheric environments, and (3) state-of-the-art seismic/acoustic models for propagating moving-vehicle signatures through realistic, complex environments. With regard to the first of these components, dynamic models of wheeled and tracked vehicles have been developed to generate ground force inputs to seismic propagation models. Vehicle models range from simple, 2D representations to highly detailed, 3D representations of entire linked-track suspension systems. Similarly detailed models of acoustic emissions from vehicle engines are under development. The propagation calculations for both the seismics and acoustics are based on finite-difference, time-domain (FDTD) methodologies capable of handling complex environmental features such as heterogeneous geologies, urban structures, surface vegetation, and dynamic atmospheric turbulence. Any number of dynamic sources and virtual sensors may be incorporated into the FDTD model. The computational demands of 3D FDTD simulation over tactical distances require massively parallel computers. Several example calculations of seismic/acoustic wave propagation through complex atmospheric and terrain environments are shown.

The Lemur Conjecture

NASA Astrophysics Data System (ADS)

Lanzagorta, Marco; Jitrik, Oliverio; Uhlmann, Jeffrey; Venegas-Andraca, Salvador E.

2017-05-01

In previous research we designed an interferometric quantum seismograph that uses entangled photon states to enhance sensitivity in an optomechanic device. However, a spatially-distributed array of such sensors, with each sensor measuring only nm-vibrations, may not provide sufficient sensitivity for the prediction of major earthquakes because it fails to exploit potentially critical phase information. We conjecture that relative phase information can explain the anecdotal observations that animals such as lemurs exhibit sensitivity to impending earthquakes earlier than can be done confidently with traditional seismic technology. More specifically, we propose that lemurs use their limbs as ground motion sensors and that relative phase differences are fused in the brain in a manner similar to a phased-array or synthetic-aperture radar. In this paper we will describe a lemur-inspired quantum sensor network for early warning of earthquakes. The system uses 4 interferometric quantum seismographs (e.g., analogous to a lemurs limbs) and then conducts phase and data fusion of the seismic information. Although we discuss a quantum-based technology, the principles described can also be applied to classical sensor arrays

Spatial Distribution of Accuracy of Aerosol Retrievals from Multiple Satellite Sensors

NASA Technical Reports Server (NTRS)

Petrenko, Maksym; Ichoku, Charles

2012-01-01

Remote sensing of aerosols from space has been a subject of extensive research, with multiple sensors retrieving aerosol properties globally on a daily or weekly basis. The diverse algorithms used for these retrievals operate on different types of reflected signals based on different assumptions about the underlying physical phenomena. Depending on the actual retrieval conditions and especially on the geographical location of the sensed aerosol parcels, the combination of these factors might be advantageous for one or more of the sensors and unfavorable for others, resulting in disagreements between similar aerosol parameters retrieved from different sensors. In this presentation, we will demonstrate the use of the Multi-sensor Aerosol Products Sampling System (MAPSS) to analyze and intercompare aerosol retrievals from multiple spaceborne sensors, including MODIS (on Terra and Aqua), MISR, OMI, POLDER, CALIOP, and SeaWiFS. Based on this intercomparison, we are determining geographical locations where these products provide the greatest accuracy of the retrievals and identifying the products that are the most suitable for retrieval at these locations. The analyses are performed by comparing quality-screened satellite aerosol products to available collocated ground-based aerosol observations from the Aerosol Robotic Network (AERONET) stations, during the period of 2006-2010 when all the satellite sensors were operating concurrently. Furthermore, we will discuss results of a statistical approach that is applied to the collocated data to detect and remove potential data outliers that can bias the results of the analysis.

Use of the Delay-Tolerant Networking Bundle Protocol from Space

NASA Technical Reports Server (NTRS)

Wood, Lloyd; Ivancic, William D.; Eddy, Wesley M.; Stewart, Dave; Northam, James; Jackson, Chris; daSilvaCuriel, Alex

2009-01-01

The Disaster Monitoring Constellation (DMC), constructed by Survey Satellite Technology Ltd (SSTL), is a multisatellite Earth-imaging low-Earth-orbit sensor network where captured image swaths are stored onboard each satellite and later downloaded from the satellite payloads to a ground station. Store-and-forward of images with capture and later download gives each satellite the characteristics of a node in a Delay/Disruption Tolerant Network (DTN). Originally developed for the Interplanetary Internet, DTNs are now under investigation in an Internet Research Task Force (IRTF) DTN research group (RG), which has developed a bundle architecture and protocol. The DMC is currently unique in its adoption of the Internet Protocol (IP) for its imaging payloads and for satellite command and control, based around reuse of commercial networking and link protocols. These satellites use of IP has enabled earlier experiments with the Cisco router in Low Earth Orbit (CLEO) onboard the constellation's UK-DMC satellite. Earth images are downloaded from the satellites using a custom IPbased high-speed transfer protocol developed by SSTL, Saratoga, which tolerates unusual link environments. Saratoga has been documented in the Internet Engineering Task Force (IETF) for wider adoption. We experiment with use of DTNRG bundle concepts onboard the UKDMC satellite, by examining how Saratoga can be used as a DTN convergence layer to carry the DTNRG Bundle Protocol, so that sensor images can be delivered to ground stations and beyond as bundles. This is the first successful use of the DTNRG Bundle Protocol in a space environment. We use our practical experience to examine the strengths and weaknesses of the Bundle Protocol for DTN use, paying attention to fragmentation, custody transfer, and reliability issues.

Landslide and Flood Warning System Prototypes based on Wireless Sensor Networks

NASA Astrophysics Data System (ADS)

Hloupis, George; Stavrakas, Ilias; Triantis, Dimos

2010-05-01

Wireless sensor networks (WSNs) are one of the emerging areas that received great attention during the last few years. This is mainly due to the fact that WSNs have provided scientists with the capability of developing real-time monitoring systems equipped with sensors based on Micro-Electro-Mechanical Systems (MEMS). WSNs have great potential for many applications in environmental monitoring since the sensor nodes that comprised from can host several MEMS sensors (such as temperature, humidity, inertial, pressure, strain-gauge) and transducers (such as position, velocity, acceleration, vibration). The resulting devices are small and inexpensive but with limited memory and computing resources. Each sensor node contains a sensing module which along with an RF transceiver. The communication is broadcast-based since the network topology can change rapidly due to node failures [1]. Sensor nodes can transmit their measurements to central servers through gateway nodes without any processing or they make preliminary calculations locally in order to produce results that will be sent to central servers [2]. Based on the above characteristics, two prototypes using WSNs are presented in this paper: A Landslide detection system and a Flood warning system. Both systems sent their data to central processing server where the core of processing routines exists. Transmission is made using Zigbee and IEEE 802.11b protocol but is capable to use VSAT communication also. Landslide detection system uses structured network topology. Each measuring node comprises of a columnar module that is half buried to the area under investigation. Each sensing module contains a geophone, an inclinometer and a set of strain gauges. Data transmitted to central processing server where possible landslide evolution is monitored. Flood detection system uses unstructured network topology since the failure rate of sensor nodes is expected higher. Each sensing module contains a custom water level sensor (based on plastic optical fiber). Data transmitted directly to server where the early warning algorithms monitor the water level variations in real time. Both sensor nodes use power harvesting techniques in order to extend their battery life as much as possible. [1] Yick J.; Mukherjee, B.; Ghosal, D. Wireless sensor network survey. Comput. Netw. 2008, 52, 2292-2330. [2] Garcia, M.; Bri, D.; Boronat, F.; Lloret, J. A new neighbor selection strategy for group-based wireless sensor networks, In The Fourth International Conference on Networking and Services (ICNS 2008), Gosier, Guadalupe, March 16-21, 2008.

Reputation-Based Internet Protocol Security: A Multilayer Security Framework for Mobile Ad Hoc Networks

DTIC Science & Technology

2010-09-01

secure ad-hoc networks of mobile sensors deployed in a hostile environment . These sensors are normally small 86 and resource...Communications Magazine, 51, 2008. 45. Kumar, S.A. “Classification and Review of Security Schemes in Mobile Comput- ing”. Wireless Sensor Network , 2010... Networks ”. Wireless /Mobile Network Security , 2008. 85. Xiao, Y. “Accountability for Wireless LANs, Ad Hoc Networks , and Wireless

QPA-CLIPS: A language and representation for process control

NASA Technical Reports Server (NTRS)

Freund, Thomas G.

1994-01-01

QPA-CLIPS is an extension of CLIPS oriented towards process control applications. Its constructs define a dependency network of process actions driven by sensor information. The language consists of three basic constructs: TASK, SENSOR, and FILTER. TASK's define the dependency network describing alternative state transitions for a process. SENSOR's and FILTER's define sensor information sources used to activate state transitions within the network. Deftemplate's define these constructs and their run-time environment is an interpreter knowledge base, performing pattern matching on sensor information and so activating TASK's in the dependency network. The pattern matching technique is based on the repeatable occurrence of a sensor data pattern. QPA-CIPS has been successfully tested on a SPARCStation providing supervisory control to an Allen-Bradley PLC 5 controller driving molding equipment.

Economic Feasibility of Wireless Sensor Network-Based Service Provision in a Duopoly Setting with a Monopolist Operator.

PubMed

Sanchis-Cano, Angel; Romero, Julián; Sacoto-Cabrera, Erwin J; Guijarro, Luis

2017-11-25

We analyze the feasibility of providing Wireless Sensor Network-data-based services in an Internet of Things scenario from an economical point of view. The scenario has two competing service providers with their own private sensor networks, a network operator and final users. The scenario is analyzed as two games using game theory. In the first game, sensors decide to subscribe or not to the network operator to upload the collected sensing-data, based on a utility function related to the mean service time and the price charged by the operator. In the second game, users decide to subscribe or not to the sensor-data-based service of the service providers based on a Logit discrete choice model related to the quality of the data collected and the subscription price. The sinks and users subscription stages are analyzed using population games and discrete choice models, while network operator and service providers pricing stages are analyzed using optimization and Nash equilibrium concepts respectively. The model is shown feasible from an economic point of view for all the actors if there are enough interested final users and opens the possibility of developing more efficient models with different types of services.

Optimization of Self-Directed Target Coverage in Wireless Multimedia Sensor Network

PubMed Central

Yang, Yang; Wang, Yufei; Pi, Dechang; Wang, Ruchuan

2014-01-01

Video and image sensors in wireless multimedia sensor networks (WMSNs) have directed view and limited sensing angle. So the methods to solve target coverage problem for traditional sensor networks, which use circle sensing model, are not suitable for WMSNs. Based on the FoV (field of view) sensing model and FoV disk model proposed, how expected multimedia sensor covers the target is defined by the deflection angle between target and the sensor's current orientation and the distance between target and the sensor. Then target coverage optimization algorithms based on expected coverage value are presented for single-sensor single-target, multisensor single-target, and single-sensor multitargets problems distinguishingly. Selecting the orientation that sensor rotated to cover every target falling in the FoV disk of that sensor for candidate orientations and using genetic algorithm to multisensor multitargets problem, which has NP-complete complexity, then result in the approximated minimum subset of sensors which covers all the targets in networks. Simulation results show the algorithm's performance and the effect of number of targets on the resulting subset. PMID:25136667

The Spaceborne Imaging Radar program: SIR-C - The next step toward EOS

NASA Technical Reports Server (NTRS)

Evans, Diane; Elachi, Charles; Cimino, Jobea

1987-01-01

The NASA Shuttle Imaging Radar SIR-C experiments will investigate earth surface and environment phenomena to deepen understanding of terra firma, biosphere, hydrosphere, cryosphere, and atmosphere components of the earth system, capitalizing on the observational capabilities of orbiting multiparameter radar sensors alone or in combination with other sensors. The SIR-C sensor encompasses an antenna array, an exciter, receivers, a data-handling network, and the ground SAR processor. It will be possible to steer the antenna beam electronically, so that the radar look angle can be varied.

Converging Redundant Sensor Network Information for Improved Building Control

DOE Office of Scientific and Technical Information (OSTI.GOV)

Dale Tiller; D. Phil; Gregor Henze

2007-09-30

This project investigated the development and application of sensor networks to enhance building energy management and security. Commercial, industrial and residential buildings often incorporate systems used to determine occupancy, but current sensor technology and control algorithms limit the effectiveness of these systems. For example, most of these systems rely on single monitoring points to detect occupancy, when more than one monitoring point could improve system performance. Phase I of the project focused on instrumentation and data collection. During the initial project phase, a new occupancy detection system was developed, commissioned and installed in a sample of private offices and open-planmore » office workstations. Data acquisition systems were developed and deployed to collect data on space occupancy profiles. Phase II of the project demonstrated that a network of several sensors provides a more accurate measure of occupancy than is possible using systems based on single monitoring points. This phase also established that analysis algorithms could be applied to the sensor network data stream to improve the accuracy of system performance in energy management and security applications. In Phase III of the project, the sensor network from Phase I was complemented by a control strategy developed based on the results from the first two project phases: this controller was implemented in a small sample of work areas, and applied to lighting control. Two additional technologies were developed in the course of completing the project. A prototype web-based display that portrays the current status of each detector in a sensor network monitoring building occupancy was designed and implemented. A new capability that enables occupancy sensors in a sensor network to dynamically set the 'time delay' interval based on ongoing occupant behavior in the space was also designed and implemented.« less

Optimal placement of multiple types of communicating sensors with availability and coverage redundancy constraints

NASA Astrophysics Data System (ADS)

Vecherin, Sergey N.; Wilson, D. Keith; Pettit, Chris L.

2010-04-01

Determination of an optimal configuration (numbers, types, and locations) of a sensor network is an important practical problem. In most applications, complex signal propagation effects and inhomogeneous coverage preferences lead to an optimal solution that is highly irregular and nonintuitive. The general optimization problem can be strictly formulated as a binary linear programming problem. Due to the combinatorial nature of this problem, however, its strict solution requires significant computational resources (NP-complete class of complexity) and is unobtainable for large spatial grids of candidate sensor locations. For this reason, a greedy algorithm for approximate solution was recently introduced [S. N. Vecherin, D. K. Wilson, and C. L. Pettit, "Optimal sensor placement with terrain-based constraints and signal propagation effects," Unattended Ground, Sea, and Air Sensor Technologies and Applications XI, SPIE Proc. Vol. 7333, paper 73330S (2009)]. Here further extensions to the developed algorithm are presented to include such practical needs and constraints as sensor availability, coverage by multiple sensors, and wireless communication of the sensor information. Both communication and detection are considered in a probabilistic framework. Communication signal and signature propagation effects are taken into account when calculating probabilities of communication and detection. Comparison of approximate and strict solutions on reduced-size problems suggests that the approximate algorithm yields quick and good solutions, which thus justifies using that algorithm for full-size problems. Examples of three-dimensional outdoor sensor placement are provided using a terrain-based software analysis tool.

AEGIS: A Lightweight Firewall for Wireless Sensor Networks

NASA Astrophysics Data System (ADS)

Hossain, Mohammad Sajjad; Raghunathan, Vijay

Firewalls are an essential component in today's networked computing systems (desktops, laptops, and servers) and provide effective protection against a variety of over-the-network security attacks. With the development of technologies such as IPv6 and 6LoWPAN that pave the way for Internet-connected embedded systems and sensor networks, these devices will soon be subject to (and need to be defended against) similar security threats. As a first step, this paper presents Aegis, a lightweight, rule-based firewall for networked embedded systems such as wireless sensor networks. Aegis is based on a semantically rich, yet simple, rule definition language. In addition, Aegis is highly efficient during operation, runs in a transparent manner from running applications, and is easy to maintain. Experimental results obtained using real sensor nodes and cycle-accurate simulations demonstrate that Aegis successfully performs gatekeeping of a sensor node's communication traffic in a flexible manner with minimal overheads.

An energy-efficient data gathering protocol in large wireless sensor network

NASA Astrophysics Data System (ADS)

Wang, Yamin; Zhang, Ruihua; Tao, Shizhong

2006-11-01

Wireless sensor network consisting of a large number of small sensors with low-power transceiver can be an effective tool for gathering data in a variety of environment. The collected data must be transmitted to the base station for further processing. Since a network consists of sensors with limited battery energy, the method for data gathering and routing must be energy efficient in order to prolong the lifetime of the network. In this paper, we presented an energy-efficient data gathering protocol in wireless sensor network. The new protocol used data fusion technology clusters nodes into groups and builds a chain among the cluster heads according to a hybrid of the residual energy and distance to the base station. Results in stochastic geometry are used to derive the optimum parameter of our algorithm that minimizes the total energy spent in the network. Simulation results show performance superiority of the new protocol.

Collaboration of Miniature Multi-Modal Mobile Smart Robots over a Network

DTIC Science & Technology

2015-08-14

theoretical research on mathematics of failures in sensor-network-based miniature multimodal mobile robots and electromechanical systems. The views...theoretical research on mathematics of failures in sensor-network-based miniature multimodal mobile robots and electromechanical systems. The...independently evolving research directions based on physics-based models of mechanical, electromechanical and electronic devices, operational constraints

Using Public Network Infrastructures for UAV Remote Sensing in Civilian Security Operations

DTIC Science & Technology

2011-03-01

leveraging public wireless communication networks for UAV-based sensor networks with respect to existing constraints and user requirements...Detection with an Autonomous Micro UAV Mesh Network . In the near future police departments, fire brigades and other homeland security ...UAV-based sensor networks with respect to existing constraints and user requirements. 15. SUBJECT TERMS 16. SECURITY CLASSIFICATION OF: 17. LIMITATION

Features Extraction of Flotation Froth Images and BP Neural Network Soft-Sensor Model of Concentrate Grade Optimized by Shuffled Cuckoo Searching Algorithm

PubMed Central

Wang, Jie-sheng; Han, Shuang; Shen, Na-na; Li, Shu-xia

2014-01-01

For meeting the forecasting target of key technology indicators in the flotation process, a BP neural network soft-sensor model based on features extraction of flotation froth images and optimized by shuffled cuckoo search algorithm is proposed. Based on the digital image processing technique, the color features in HSI color space, the visual features based on the gray level cooccurrence matrix, and the shape characteristics based on the geometric theory of flotation froth images are extracted, respectively, as the input variables of the proposed soft-sensor model. Then the isometric mapping method is used to reduce the input dimension, the network size, and learning time of BP neural network. Finally, a shuffled cuckoo search algorithm is adopted to optimize the BP neural network soft-sensor model. Simulation results show that the model has better generalization results and prediction accuracy. PMID:25133210

Optimization of wireless sensor networks based on chicken swarm optimization algorithm

NASA Astrophysics Data System (ADS)

Wang, Qingxi; Zhu, Lihua

2017-05-01

In order to reduce the energy consumption of wireless sensor network and improve the survival time of network, the clustering routing protocol of wireless sensor networks based on chicken swarm optimization algorithm was proposed. On the basis of LEACH agreement, it was improved and perfected that the points on the cluster and the selection of cluster head using the chicken group optimization algorithm, and update the location of chicken which fall into the local optimum by Levy flight, enhance population diversity, ensure the global search capability of the algorithm. The new protocol avoided the die of partial node of intensive using by making balanced use of the network nodes, improved the survival time of wireless sensor network. The simulation experiments proved that the protocol is better than LEACH protocol on energy consumption, also is better than that of clustering routing protocol based on particle swarm optimization algorithm.

Embedded Electro-Optic Sensor Network for the On-Site Calibration and Real-Time Performance Monitoring of Large-Scale Phased Arrays

DTIC Science & Technology

2005-07-09

This final report summarizes the progress during the Phase I SBIR project entitled Embedded Electro - Optic Sensor Network for the On-Site Calibration...network based on an electro - optic field-detection technique (the Electro - optic Sensor Network, or ESN) for the performance evaluation of phased

An ANN-Based Smart Tomographic Reconstructor in a Dynamic Environment

PubMed Central

de Cos Juez, Francisco J.; Lasheras, Fernando Sánchez; Roqueñí, Nieves; Osborn, James

2012-01-01

In astronomy, the light emitted by an object travels through the vacuum of space and then the turbulent atmosphere before arriving at a ground based telescope. By passing through the atmosphere a series of turbulent layers modify the light's wave-front in such a way that Adaptive Optics reconstruction techniques are needed to improve the image quality. A novel reconstruction technique based in Artificial Neural Networks (ANN) is proposed. The network is designed to use the local tilts of the wave-front measured by a Shack Hartmann Wave-front Sensor (SHWFS) as inputs and estimate the turbulence in terms of Zernike coefficients. The ANN used is a Multi-Layer Perceptron (MLP) trained with simulated data with one turbulent layer changing in altitude. The reconstructor was tested using three different atmospheric profiles and compared with two existing reconstruction techniques: Least Squares type Matrix Vector Multiplication (LS) and Learn and Apply (L + A). PMID:23012524

A feedback-based secure path approach for wireless sensor network data collection.

PubMed

Mao, Yuxin; Wei, Guiyi

2010-01-01

The unattended nature of wireless sensor networks makes them very vulnerable to malicious attacks. Therefore, how to preserve secure data collection is an important issue to wireless sensor networks. In this paper, we propose a novel approach of secure data collection for wireless sensor networks. We explore secret sharing and multipath routing to achieve secure data collection in wireless sensor network with compromised nodes. We present a novel tracing-feedback mechanism, which makes full use of the routing functionality of wireless sensor networks, to improve the quality of data collection. The major advantage of the approach is that the secure paths are constructed as a by-product of data collection. The process of secure routing causes little overhead to the sensor nodes in the network. Compared with existing works, the algorithms of the proposed approach are easy to implement and execute in resource-constrained wireless sensor networks. According to the result of a simulation experiment, the performance of the approach is better than the recent approaches with a similar purpose.

Distributing flight dynamics products via the World Wide Web

NASA Technical Reports Server (NTRS)

Woodard, Mark; Matusow, David

1996-01-01

The NASA Flight Dynamics Products Center (FDPC), which make available selected operations products via the World Wide Web, is reported on. The FDPC can be accessed from any host machine connected to the Internet. It is a multi-mission service which provides Internet users with unrestricted access to the following standard products: antenna contact predictions; ground tracks; orbit ephemerides; mean and osculating orbital elements; earth sensor sun and moon interference predictions; space flight tracking data network summaries; and Shuttle transport system predictions. Several scientific data bases are available through the service.

Wireless sensor network for irrigation application in cotton

USDA-ARS?s Scientific Manuscript database

A wireless sensor network was deployed in a cotton field to monitor soil water status for irrigation. The network included two systems, a Decagon system and a microcontroller-based system. The Decagon system consists of soil volumetric water-content sensors, wireless data loggers, and a central data...

An Energy-Efficient and High-Quality Video Transmission Architecture in Wireless Video-Based Sensor Networks.

PubMed

Aghdasi, Hadi S; Abbaspour, Maghsoud; Moghadam, Mohsen Ebrahimi; Samei, Yasaman

2008-08-04

Technological progress in the fields of Micro Electro-Mechanical Systems (MEMS) and wireless communications and also the availability of CMOS cameras, microphones and small-scale array sensors, which may ubiquitously capture multimedia content from the field, have fostered the development of low-cost limited resources Wireless Video-based Sensor Networks (WVSN). With regards to the constraints of videobased sensor nodes and wireless sensor networks, a supporting video stream is not easy to implement with the present sensor network protocols. In this paper, a thorough architecture is presented for video transmission over WVSN called Energy-efficient and high-Quality Video transmission Architecture (EQV-Architecture). This architecture influences three layers of communication protocol stack and considers wireless video sensor nodes constraints like limited process and energy resources while video quality is preserved in the receiver side. Application, transport, and network layers are the layers in which the compression protocol, transport protocol, and routing protocol are proposed respectively, also a dropping scheme is presented in network layer. Simulation results over various environments with dissimilar conditions revealed the effectiveness of the architecture in improving the lifetime of the network as well as preserving the video quality.

Combine harvester monitor system based on wireless sensor network

USDA-ARS?s Scientific Manuscript database

A measurement method based on Wireless Sensor Network (WSN) was developed to monitor the working condition of combine harvester for remote application. Three JN5139 modules were chosen for sensor data acquisition and another two as a router and a coordinator, which could create a tree topology netwo...

Cluster Size Optimization in Sensor Networks with Decentralized Cluster-Based Protocols

PubMed Central

Amini, Navid; Vahdatpour, Alireza; Xu, Wenyao; Gerla, Mario; Sarrafzadeh, Majid

2011-01-01

Network lifetime and energy-efficiency are viewed as the dominating considerations in designing cluster-based communication protocols for wireless sensor networks. This paper analytically provides the optimal cluster size that minimizes the total energy expenditure in such networks, where all sensors communicate data through their elected cluster heads to the base station in a decentralized fashion. LEACH, LEACH-Coverage, and DBS comprise three cluster-based protocols investigated in this paper that do not require any centralized support from a certain node. The analytical outcomes are given in the form of closed-form expressions for various widely-used network configurations. Extensive simulations on different networks are used to confirm the expectations based on the analytical results. To obtain a thorough understanding of the results, cluster number variability problem is identified and inspected from the energy consumption point of view. PMID:22267882

A Survey of Wireless Sensor Network Based Air Pollution Monitoring Systems

PubMed Central

Yi, Wei Ying; Lo, Kin Ming; Mak, Terrence; Leung, Kwong Sak; Leung, Yee; Meng, Mei Ling

2015-01-01

The air quality in urban areas is a major concern in modern cities due to significant impacts of air pollution on public health, global environment, and worldwide economy. Recent studies reveal the importance of micro-level pollution information, including human personal exposure and acute exposure to air pollutants. A real-time system with high spatio-temporal resolution is essential because of the limited data availability and non-scalability of conventional air pollution monitoring systems. Currently, researchers focus on the concept of The Next Generation Air Pollution Monitoring System (TNGAPMS) and have achieved significant breakthroughs by utilizing the advance sensing technologies, MicroElectroMechanical Systems (MEMS) and Wireless Sensor Network (WSN). However, there exist potential problems of these newly proposed systems, namely the lack of 3D data acquisition ability and the flexibility of the sensor network. In this paper, we classify the existing works into three categories as Static Sensor Network (SSN), Community Sensor Network (CSN) and Vehicle Sensor Network (VSN) based on the carriers of the sensors. Comprehensive reviews and comparisons among these three types of sensor networks were also performed. Last but not least, we discuss the limitations of the existing works and conclude the objectives that we want to achieve in future systems. PMID:26703598

A Survey of Wireless Sensor Network Based Air Pollution Monitoring Systems.

PubMed

Yi, Wei Ying; Lo, Kin Ming; Mak, Terrence; Leung, Kwong Sak; Leung, Yee; Meng, Mei Ling

2015-12-12

The air quality in urban areas is a major concern in modern cities due to significant impacts of air pollution on public health, global environment, and worldwide economy. Recent studies reveal the importance of micro-level pollution information, including human personal exposure and acute exposure to air pollutants. A real-time system with high spatio-temporal resolution is essential because of the limited data availability and non-scalability of conventional air pollution monitoring systems. Currently, researchers focus on the concept of The Next Generation Air Pollution Monitoring System (TNGAPMS) and have achieved significant breakthroughs by utilizing the advance sensing technologies, MicroElectroMechanical Systems (MEMS) and Wireless Sensor Network (WSN). However, there exist potential problems of these newly proposed systems, namely the lack of 3D data acquisition ability and the flexibility of the sensor network. In this paper, we classify the existing works into three categories as Static Sensor Network (SSN), Community Sensor Network (CSN) and Vehicle Sensor Network (VSN) based on the carriers of the sensors. Comprehensive reviews and comparisons among these three types of sensor networks were also performed. Last but not least, we discuss the limitations of the existing works and conclude the objectives that we want to achieve in future systems.

Long-Term Large-Scale Bias-Adjusted Precipitation Estimates at High Spatial and Temporal Resolution Derived from the National Mosaic and Multi-Sensor QPE (NMQ/Q2) Precipitation Reanalysis over CONUS

NASA Astrophysics Data System (ADS)

Prat, O. P.; Nelson, B. R.; Stevens, S. E.; Seo, D. J.; Kim, B.

2014-12-01

The processing of radar-only precipitation via the reanalysis from the National Mosaic and Multi-Sensor Quantitative (NMQ/Q2) based on the WSR-88D Next-generation Radar (Nexrad) network over Continental United States (CONUS) is nearly completed for the period covering from 2000 to 2012. This important milestone constitutes a unique opportunity to study precipitation processes at a 1-km spatial resolution for a 5-min temporal resolution. However, in order to be suitable for hydrological, meteorological and climatological applications, the radar-only product needs to be bias-adjusted and merged with in-situ rain gauge information. Rain gauge networks such as the Hydrometeorological Automated Data System (HADS), the Automated Surface Observing Systems (ASOS), the Climate Reference Network (CRN), and the Global Historical Climatology Network - Daily (GHCN-D) are used to adjust for those biases and to merge with the radar only product to provide a multi-sensor estimate. The challenges related to incorporating non-homogeneous networks over a vast area and for a long-term record are enormous. Among the challenges we are facing are the difficulties incorporating differing resolution and quality surface measurements to adjust gridded estimates of precipitation. Another challenge is the type of adjustment technique. After assessing the bias and applying reduction or elimination techniques, we are investigating the kriging method and its variants such as simple kriging (SK), ordinary kriging (OK), and conditional bias-penalized Kriging (CBPK) among others. In addition we hope to generate estimates of uncertainty for the gridded estimate. In this work the methodology is presented as well as a comparison between the radar-only product and the final multi-sensor QPE product. The comparison is performed at various time scales from the sub-hourly, to annual. In addition, comparisons over the same period with a suite of lower resolution QPEs derived from ground based radar measurements (Stage IV) and satellite products (TMPA, CMORPH, PERSIANN) are provided in order to give a detailed picture of the improvements and remaining challenges.

Ground- and Space-based Observations of Horizontally-extensive Lightning Flashes

NASA Astrophysics Data System (ADS)

Zhang, D.; Cummins, K. L.; Bitzer, P. M.

2017-12-01

Horizontally-extensive lightning flashes occur frequently in association with mature and late phases of multicellular thunderstorms, both in trailing stratiform regions and horizontally-extensive anvils. The spatial relationship between these flashes and the parent cloud volume is of importance for space launch operational decision making, and is of broader scientific interest. Before this question can be accurately addressed, there is a need to understand the degree to which current lightning observation systems can depict the spatial extent of these long flashes. In this ongoing work, we will intercompare the depiction of horizontally-extensive flashes using several ground-based lightning locating systems (LLSs) located at Kennedy Space Center (KSC) with space-based observations observed by the recently-launched Geostationary Lightning Mapper (GLM) onboard the GOES-16 satellite. Ground-based datasets include the KSC Lightning Mapping Array (KSCLMA), the operational narrowband digital interferometer network MERLIN, and the combined cloud-to-ground and cloud lightning dataset produced by the U.S. National Lightning Detection Network (NLDN). The KSCLMA system is a network of VHF time-of-arrival sensors that preferentially report breakdown processes, and MERLIN is a network of VHF interferometers that point to the discharges in the horizontal plane. Observations to date indicate that MERLIN and the KSCSLMA provide similar overall descriptions of the spatial and temporal extent of these flashes, while the NLDN does not provide adequate spatial mapping of these flashes. The KSC LMA system has much better location accuracy, and provides excellent 3-dimensional representation within 100 km of KSC. It also has sufficient sensitivity to provide 2-dimensional flash mapping within 250 km of KSC. The MERLIN system provides a more-detailed representation of fast leader propagation (in 2 dimensions) with 100 km of KSC. Earlier work during the CHUVA campaign in Brazil with similar systems and the (orbital) Lightning Imaging System (LIS) has shown that the interferometric data correlated much better in space and time with the LIS optical observations. We are currently investigating this relationship at KSC, where both the LMA and interferometer perform much better than the systems used during CHUVA.

A Target Coverage Scheduling Scheme Based on Genetic Algorithms in Directional Sensor Networks

PubMed Central

Gil, Joon-Min; Han, Youn-Hee

2011-01-01

As a promising tool for monitoring the physical world, directional sensor networks (DSNs) consisting of a large number of directional sensors are attracting increasing attention. As directional sensors in DSNs have limited battery power and restricted angles of sensing range, maximizing the network lifetime while monitoring all the targets in a given area remains a challenge. A major technique to conserve the energy of directional sensors is to use a node wake-up scheduling protocol by which some sensors remain active to provide sensing services, while the others are inactive to conserve their energy. In this paper, we first address a Maximum Set Covers for DSNs (MSCD) problem, which is known to be NP-complete, and present a greedy algorithm-based target coverage scheduling scheme that can solve this problem by heuristics. This scheme is used as a baseline for comparison. We then propose a target coverage scheduling scheme based on a genetic algorithm that can find the optimal cover sets to extend the network lifetime while monitoring all targets by the evolutionary global search technique. To verify and evaluate these schemes, we conducted simulations and showed that the schemes can contribute to extending the network lifetime. Simulation results indicated that the genetic algorithm-based scheduling scheme had better performance than the greedy algorithm-based scheme in terms of maximizing network lifetime. PMID:22319387

Design of a sensor network for structural health monitoring of a full-scale composite horizontal tail

NASA Astrophysics Data System (ADS)

Gao, Dongyue; Wang, Yishou; Wu, Zhanjun; Rahim, Gorgin; Bai, Shengbao

2014-05-01

The detection capability of a given structural health monitoring (SHM) system strongly depends on its sensor network placement. In order to minimize the number of sensors while maximizing the detection capability, optimal design of the PZT sensor network placement is necessary for structural health monitoring (SHM) of a full-scale composite horizontal tail. In this study, the sensor network optimization was simplified as a problem of determining the sensor array placement between stiffeners to achieve the desired the coverage rate. First, an analysis of the structural layout and load distribution of a composite horizontal tail was performed. The constraint conditions of the optimal design were presented. Then, the SHM algorithm of the composite horizontal tail under static load was proposed. Based on the given SHM algorithm, a sensor network was designed for the full-scale composite horizontal tail structure. Effective profiles of cross-stiffener paths (CRPs) and uncross-stiffener paths (URPs) were estimated by a Lamb wave propagation experiment in a multi-stiffener composite specimen. Based on the coverage rate and the redundancy requirements, a seven-sensor array-network was chosen as the optimal sensor network for each airfoil. Finally, a preliminary SHM experiment was performed on a typical composite aircraft structure component. The reliability of the SHM result for a composite horizontal tail structure under static load was validated. In the result, the red zone represented the delamination damage. The detection capability of the optimized sensor network was verified by SHM of a full-scale composite horizontal tail; all the diagnosis results were obtained in two minutes. The result showed that all the damage in the monitoring region was covered by the sensor network.

If it walks like a duck: nanosensor threat assessment

NASA Astrophysics Data System (ADS)

Chachis, George C.

2003-09-01

A convergence of technologies is making deployment of unattended ground nanosensors operationally feasible in terms of energy, communications for both arbitrated and self-organizing distributed, collective behaviors. A number of nano communications technologies are already making network-centric systems possible for MicroElectrical Mechanical (MEM) sensor devices today. Similar technologies may make NanoElectrical Mechanical (NEM) sensor devices operationally feasible a few years from now. Just as organizational behaviors of large numbers of nanodevices can derive strategies from social insects and other group-oriented animals, bio-inspired heuristics for threat assessment provide a conceptual approach for successful integration of nanosensors into unattended smart sensor networks. Biological models such as the organization of social insects or the dynamics of immune systems show promise as biologically-inspired paradigms for protecting nanosensor networks for security scene analysis and battlespace awareness. The paradox of nanosensors is that the smaller the device is the more useful it is but the smaller it is the more vulnerable it is to a variety of threats. In other words simpler means networked nanosensors are more likely to fall prey to a wide-range of attacks including jamming, spoofing, Janisserian recruitment, Pied-Piper distraction, as well as typical attacks computer network security. Thus, unattended sensor technologies call for network architectures that include security and countermeasures to provide reliable scene analysis or battlespace awareness information. Such network centric architectures may well draw upon a variety of bio-inspired approaches to safeguard, validate and make sense of large quantities of information.

Energy-aware scheduling of surveillance in wireless multimedia sensor networks.

PubMed

Wang, Xue; Wang, Sheng; Ma, Junjie; Sun, Xinyao

2010-01-01

Wireless sensor networks involve a large number of sensor nodes with limited energy supply, which impacts the behavior of their application. In wireless multimedia sensor networks, sensor nodes are equipped with audio and visual information collection modules. Multimedia contents are ubiquitously retrieved in surveillance applications. To solve the energy problems during target surveillance with wireless multimedia sensor networks, an energy-aware sensor scheduling method is proposed in this paper. Sensor nodes which acquire acoustic signals are deployed randomly in the sensing fields. Target localization is based on the signal energy feature provided by multiple sensor nodes, employing particle swarm optimization (PSO). During the target surveillance procedure, sensor nodes are adaptively grouped in a totally distributed manner. Specially, the target motion information is extracted by a forecasting algorithm, which is based on the hidden Markov model (HMM). The forecasting results are utilized to awaken sensor node in the vicinity of future target position. According to the two properties, signal energy feature and residual energy, the sensor nodes decide whether to participate in target detection separately with a fuzzy control approach. Meanwhile, the local routing scheme of data transmission towards the observer is discussed. Experimental results demonstrate the efficiency of energy-aware scheduling of surveillance in wireless multimedia sensor network, where significant energy saving is achieved by the sensor awakening approach and data transmission paths are calculated with low computational complexity.

An Integrated Intrusion Detection Model of Cluster-Based Wireless Sensor Network

PubMed Central

Sun, Xuemei; Yan, Bo; Zhang, Xinzhong; Rong, Chuitian

2015-01-01

Considering wireless sensor network characteristics, this paper combines anomaly and mis-use detection and proposes an integrated detection model of cluster-based wireless sensor network, aiming at enhancing detection rate and reducing false rate. Adaboost algorithm with hierarchical structures is used for anomaly detection of sensor nodes, cluster-head nodes and Sink nodes. Cultural-Algorithm and Artificial-Fish–Swarm-Algorithm optimized Back Propagation is applied to mis-use detection of Sink node. Plenty of simulation demonstrates that this integrated model has a strong performance of intrusion detection. PMID:26447696

An Integrated Intrusion Detection Model of Cluster-Based Wireless Sensor Network.

PubMed

Sun, Xuemei; Yan, Bo; Zhang, Xinzhong; Rong, Chuitian

2015-01-01

Considering wireless sensor network characteristics, this paper combines anomaly and mis-use detection and proposes an integrated detection model of cluster-based wireless sensor network, aiming at enhancing detection rate and reducing false rate. Adaboost algorithm with hierarchical structures is used for anomaly detection of sensor nodes, cluster-head nodes and Sink nodes. Cultural-Algorithm and Artificial-Fish-Swarm-Algorithm optimized Back Propagation is applied to mis-use detection of Sink node. Plenty of simulation demonstrates that this integrated model has a strong performance of intrusion detection.

PIYAS-proceeding to intelligent service oriented memory allocation for flash based data centric sensor devices in wireless sensor networks.

PubMed

Rizvi, Sanam Shahla; Chung, Tae-Sun

2010-01-01

Flash memory has become a more widespread storage medium for modern wireless devices because of its effective characteristics like non-volatility, small size, light weight, fast access speed, shock resistance, high reliability and low power consumption. Sensor nodes are highly resource constrained in terms of limited processing speed, runtime memory, persistent storage, communication bandwidth and finite energy. Therefore, for wireless sensor networks supporting sense, store, merge and send schemes, an efficient and reliable file system is highly required with consideration of sensor node constraints. In this paper, we propose a novel log structured external NAND flash memory based file system, called Proceeding to Intelligent service oriented memorY Allocation for flash based data centric Sensor devices in wireless sensor networks (PIYAS). This is the extended version of our previously proposed PIYA [1]. The main goals of the PIYAS scheme are to achieve instant mounting and reduced SRAM space by keeping memory mapping information to a very low size of and to provide high query response throughput by allocation of memory to the sensor data by network business rules. The scheme intelligently samples and stores the raw data and provides high in-network data availability by keeping the aggregate data for a longer period of time than any other scheme has done before. We propose effective garbage collection and wear-leveling schemes as well. The experimental results show that PIYAS is an optimized memory management scheme allowing high performance for wireless sensor networks.

A 2.5D Map-Based Mobile Robot Localization via Cooperation of Aerial and Ground Robots

PubMed Central

Nam, Tae Hyeon; Shim, Jae Hong; Cho, Young Im

2017-01-01

Recently, there has been increasing interest in studying the task coordination of aerial and ground robots. When a robot begins navigation in an unknown area, it has no information about the surrounding environment. Accordingly, for robots to perform tasks based on location information, they need a simultaneous localization and mapping (SLAM) process that uses sensor information to draw a map of the environment, while simultaneously estimating the current location of the robot on the map. This paper aims to present a localization method based in cooperation between aerial and ground robots in an indoor environment. The proposed method allows a ground robot to reach accurate destination by using a 2.5D elevation map built by a low-cost RGB-D (Red Green and Blue-Depth) sensor and 2D Laser sensor attached onto an aerial robot. A 2.5D elevation map is formed by projecting height information of an obstacle using depth information obtained by the RGB-D sensor onto a grid map, which is generated by using the 2D Laser sensor and scan matching. Experimental results demonstrate the effectiveness of the proposed method for its accuracy in location recognition and computing speed. PMID:29186843

A 2.5D Map-Based Mobile Robot Localization via Cooperation of Aerial and Ground Robots.

PubMed

Nam, Tae Hyeon; Shim, Jae Hong; Cho, Young Im

2017-11-25

Recently, there has been increasing interest in studying the task coordination of aerial and ground robots. When a robot begins navigation in an unknown area, it has no information about the surrounding environment. Accordingly, for robots to perform tasks based on location information, they need a simultaneous localization and mapping (SLAM) process that uses sensor information to draw a map of the environment, while simultaneously estimating the current location of the robot on the map. This paper aims to present a localization method based in cooperation between aerial and ground robots in an indoor environment. The proposed method allows a ground robot to reach accurate destination by using a 2.5D elevation map built by a low-cost RGB-D (Red Green and Blue-Depth) sensor and 2D Laser sensor attached onto an aerial robot. A 2.5D elevation map is formed by projecting height information of an obstacle using depth information obtained by the RGB-D sensor onto a grid map, which is generated by using the 2D Laser sensor and scan matching. Experimental results demonstrate the effectiveness of the proposed method for its accuracy in location recognition and computing speed.

Sao Paulo Lightning Mapping Array (SP-LMA): Network Assessment and Analyses for Intercomparison Studies and GOES-R Proxy Activities

NASA Technical Reports Server (NTRS)

Bailey, J. C.; Blakeslee, R. J.; Carey, L. D.; Goodman, S. J.; Rudlosky, S. D.; Albrecht, R.; Morales, C. A.; Anselmo, E. M.; Neves, J. R.; Buechler, D. E.

2014-01-01

A 12 station Lightning Mapping Array (LMA) network was deployed during October 2011 in the vicinity of Sao Paulo, Brazil (SP-LMA) to contribute total lightning measurements to an international field campaign [CHUVA - Cloud processes of tHe main precipitation systems in Brazil: A contribUtion to cloud resolVing modeling and to the GPM (GlobAl Precipitation Measurement)]. The SP-LMA was operational from November 2011 through March 2012 during the Vale do Paraiba campaign. Sensor spacing was on the order of 15-30 km, with a network diameter on the order of 40-50km. The SP-LMA provides good 3-D lightning mapping out to 150 km from the network center, with 2-D coverage considerably farther. In addition to supporting CHUVA science/mission objectives, the SP-LMA is supporting the generation of unique proxy data for the Geostationary Lightning Mapper (GLM) and Advanced Baseline Imager (ABI), on NOAA's Geostationary Operational Environmental Satellite-R (GOES-R: scheduled for a 2015 launch). These proxy data will be used to develop and validate operational algorithms so that they will be ready to use on "day1" following the GOES-R launch. As the CHUVA Vale do Paraiba campaign opportunity was formulated, a broad community-based interest developed for a comprehensive Lightning Location System (LLS) intercomparison and assessment study, leading to the participation and/or deployment of eight other ground-based networks and the space-based Lightning Imaging Sensor (LIS). The SP-LMA data is being intercompared with lightning observations from other deployed lightning networks to advance our understanding of the capabilities/contributions of each of these networks toward GLM proxy and validation activities. This paper addresses the network assessment including noise reduction criteria, detection efficiency estimates, and statistical and climatological (both temporal and spatially) analyses for intercomparison studies and GOES-R proxy activities.

Research on dynamic routing mechanisms in wireless sensor networks.

PubMed

Zhao, A Q; Weng, Y N; Lu, Y; Liu, C Y

2014-01-01

WirelessHART is the most widely applied standard in wireless sensor networks nowadays. However, it does not provide any dynamic routing mechanism, which is important for the reliability and robustness of the wireless network applications. In this paper, a collection tree protocol based, dynamic routing mechanism was proposed for WirelessHART network. The dynamic routing mechanism was evaluated through several simulation experiments in three aspects: time for generating the topology, link quality, and stability of network. Besides, the data transmission efficiency of this routing mechanism was analyzed. The simulation and evaluation results show that this mechanism can act as a dynamic routing mechanism for the TDMA-based wireless sensor network.

Using Reputation Systems and Non-Deterministic Routing to Secure Wireless Sensor Networks

PubMed Central

Moya, José M.; Vallejo, Juan Carlos; Fraga, David; Araujo, Álvaro; Villanueva, Daniel; de Goyeneche, Juan-Mariano

2009-01-01

Security in wireless sensor networks is difficult to achieve because of the resource limitations of the sensor nodes. We propose a trust-based decision framework for wireless sensor networks coupled with a non-deterministic routing protocol. Both provide a mechanism to effectively detect and confine common attacks, and, unlike previous approaches, allow bad reputation feedback to the network. This approach has been extensively simulated, obtaining good results, even for unrealistically complex attack scenarios. PMID:22412345

Nonlinear Dynamic Model-Based Multiobjective Sensor Network Design Algorithm for a Plant with an Estimator-Based Control System

DOE Office of Scientific and Technical Information (OSTI.GOV)

Paul, Prokash; Bhattacharyya, Debangsu; Turton, Richard

Here, a novel sensor network design (SND) algorithm is developed for maximizing process efficiency while minimizing sensor network cost for a nonlinear dynamic process with an estimator-based control system. The multiobjective optimization problem is solved following a lexicographic approach where the process efficiency is maximized first followed by minimization of the sensor network cost. The partial net present value, which combines the capital cost due to the sensor network and the operating cost due to deviation from the optimal efficiency, is proposed as an alternative objective. The unscented Kalman filter is considered as the nonlinear estimator. The large-scale combinatorial optimizationmore » problem is solved using a genetic algorithm. The developed SND algorithm is applied to an acid gas removal (AGR) unit as part of an integrated gasification combined cycle (IGCC) power plant with CO 2 capture. Due to the computational expense, a reduced order nonlinear model of the AGR process is identified and parallel computation is performed during implementation.« less

Nonlinear Dynamic Model-Based Multiobjective Sensor Network Design Algorithm for a Plant with an Estimator-Based Control System

DOE PAGES

Paul, Prokash; Bhattacharyya, Debangsu; Turton, Richard; ...

2017-06-06

Here, a novel sensor network design (SND) algorithm is developed for maximizing process efficiency while minimizing sensor network cost for a nonlinear dynamic process with an estimator-based control system. The multiobjective optimization problem is solved following a lexicographic approach where the process efficiency is maximized first followed by minimization of the sensor network cost. The partial net present value, which combines the capital cost due to the sensor network and the operating cost due to deviation from the optimal efficiency, is proposed as an alternative objective. The unscented Kalman filter is considered as the nonlinear estimator. The large-scale combinatorial optimizationmore » problem is solved using a genetic algorithm. The developed SND algorithm is applied to an acid gas removal (AGR) unit as part of an integrated gasification combined cycle (IGCC) power plant with CO 2 capture. Due to the computational expense, a reduced order nonlinear model of the AGR process is identified and parallel computation is performed during implementation.« less

A Study on Wireless Charging for Prolonging the Lifetime of Wireless Sensor Networks

PubMed Central

Tu, Weijian; Xu, Xianghua; Ye, Tingcong; Cheng, Zongmao

2017-01-01

Wireless charging is an important issue in wireless sensor networks, since it can provide an emerging and effective solution in the absence of other power supplies. The state-of-the-art methods employ a mobile car and a predefined moving path to charge the sensor nodes in the network. Previous studies only consider a factor of the network (i.e., residual energy of sensor node) as a constraint to design the wireless charging strategy. However, other factors, such as the travelled distance of the mobile car, can also affect the effectiveness of wireless charging strategy. In this work, we study wireless charging strategy based on the analysis of a combination of two factors, including the residual energy of sensor nodes and the travelled distance of the charging car. Firstly, we theoretically analyze the limited size of the sensor network to match the capability of a charging car. Then, the networked factors are selected as the weights of traveling salesman problem (TSP) to design the moving path of the charging car. Thirdly, the charging time of each sensor node is computed based on the linear programming problem for the charging car. Finally, a charging period for the network is studied. The experimental results show that the proposed approach can significantly maximize the lifetime of the wireless sensor network. PMID:28677639

High throughput field plant phenotyping facility at University of Nebraska-Lincoln and the first year experience

NASA Astrophysics Data System (ADS)

Ge, Y.; Bai, G.; Irmak, S.; Awada, T.; Stoerger, V.; Graef, G.; Scoby, D.; Schnable, J.

2017-12-01

University of Nebraska - Lincoln's high throughput field plant phenotyping facility is a cable robot based system built on a 1-ac field. The sensor platform is tethered with eight cables via four poles at the corners of the field for its precise control and positioning. The sensor modules on the platform include a 4-band RGB-NIR camera, a thermal infrared camera, a 3D LiDAR, VNIR spectrometers, and environmental sensors. These sensors are used to collect multifaceted physiological, structural and chemical properties of plants from the field plots. A subsurface drip irrigation system is established in this field which allows a controlled amount of water and fertilizers to be delivered to individual plots. An extensive soil moisture sensor network is also established to monitor soil water status, and serve as a feedback loop for irrigation scheduling. In the first year of operation, the field is planted maize and soybean. Weekly ground truth data were collected from the plots to validate image and sensor data from the phenotyping system. This presentation will provide an overview of this state-of-the-art field plant phenotyping facility, and present preliminary data from the first year operation of the system.

A multi-sensor land mine detection system: hardware and architectural outline of the Australian RRAMNS CTD system

NASA Astrophysics Data System (ADS)

Abeynayake, Canicious; Chant, Ian; Kempinger, Siegfried; Rye, Alan

2005-06-01

The Rapid Route Area and Mine Neutralisation System (RRAMNS) Capability Technology Demonstrator (CTD) is a countermine detection project undertaken by DSTO and supported by the Australian Defence Force (ADF). The limited time and budget for this CTD resulted in some difficult strategic decisions with regard to hardware selection and system architecture. Although the delivered system has certain limitations arising from its experimental status, many lessons have been learned which illustrate a pragmatic path for future development. RRAMNS a similar sensor suite to other systems, in that three complementary sensors are included. These are Ground Probing Radar, Metal Detector Array, and multi-band electro-optic sensors. However, RRAMNS uses a unique imaging system and a network based real-time control and sensor fusion architecture. The relatively simple integration of each of these components could be the basis for a robust and cost-effective operational system. The RRAMNS imaging system consists of three cameras which cover the visible spectrum, the mid-wave and long-wave infrared region. This subsystem can be used separately as a scouting sensor. This paper describes the system at its mid-2004 status, when full integration of all detection components was achieved.

Highly stretchable strain sensor based on SWCNTs/CB synergistic conductive network for wearable human-activity monitoring and recognition

NASA Astrophysics Data System (ADS)

Guo, Xiaohui; Huang, Ying; Zhao, Yunong; Mao, Leidong; Gao, Le; Pan, Weidong; Zhang, Yugang; Liu, Ping

2017-09-01

Flexible, stretchable, and wearable strain sensors have attracted significant attention for their potential applications in human movement detection and recognition. Here, we report a highly stretchable and flexible strain sensor based on a single-walled carbon nanotube (SWCNTs)/carbon black (CB) synergistic conductive network. The fabrication, synergistic conductive mechanism, and characterization of the sandwich-structured strain sensor were investigated. The experimental results show that the device exhibits high stretchability (120%), excellent flexibility, fast response (˜60 ms), temperature independence, and superior stability and reproducibility during ˜1100 stretching/releasing cycles. Furthermore, human activities such as the bending of a finger or elbow and gestures were monitored and recognized based on the strain sensor, indicating that the stretchable strain sensor based on the SWCNTs/CB synergistic conductive network could have promising applications in flexible and wearable devices for human motion monitoring.

Distributed Similarity based Clustering and Compressed Forwarding for wireless sensor networks.

PubMed

Arunraja, Muruganantham; Malathi, Veluchamy; Sakthivel, Erulappan

2015-11-01

Wireless sensor networks are engaged in various data gathering applications. The major bottleneck in wireless data gathering systems is the finite energy of sensor nodes. By conserving the on board energy, the life span of wireless sensor network can be well extended. Data communication being the dominant energy consuming activity of wireless sensor network, data reduction can serve better in conserving the nodal energy. Spatial and temporal correlation among the sensor data is exploited to reduce the data communications. Data similar cluster formation is an effective way to exploit spatial correlation among the neighboring sensors. By sending only a subset of data and estimate the rest using this subset is the contemporary way of exploiting temporal correlation. In Distributed Similarity based Clustering and Compressed Forwarding for wireless sensor networks, we construct data similar iso-clusters with minimal communication overhead. The intra-cluster communication is reduced using adaptive-normalized least mean squares based dual prediction framework. The cluster head reduces the inter-cluster data payload using a lossless compressive forwarding technique. The proposed work achieves significant data reduction in both the intra-cluster and the inter-cluster communications, with the optimal data accuracy of collected data. Copyright © 2015 ISA. Published by Elsevier Ltd. All rights reserved.

Periodically Launched, Dedicated CubeSats/SmallSats for Space Situational Awareness Through NASA Communications Networks

NASA Astrophysics Data System (ADS)

Stromberg, E. M.; Shaw, H.; Estabrook, P.; Neilsen, T. L.; Gunther, J.; Swenson, C.; Fish, C. S.; Schaire, S. H.

2014-12-01

Space Situational Awareness (SSA) is an area where spaceflight activities and missions can directly influence the quality of life on earth. The combination of space weather, near earth orbiting objects, atmospheric conditions at the space boundary, and other phenomena can have significant short-term and long-term implications for the inhabitants of this planet. The importance of SSA has led to increased activity in this area from both space and ground based platforms. The emerging capability of CubeSats and SmallSats provides an opportunity for these low-cost, versatile platforms to augment the SSA infrastructure. The CubeSats and SmallSats can be launched opportunistically with shorter lead times than larger missions. They can be organized both as constellations or individual sensor elements. Combining CubeSats and SmallSats with the existing NASA communications networks (TDRS Space Network, Deep Space Network and the Near Earth Network) provide a backbone structure for SSA which can be tied to a SSA portal for data distribution and management. In this poster we will describe the instruments and sensors needed for CubeSat and SmallSat SSA missions. We will describe the architecture and concept of operations for a set of opportunistic, periodically launched, SSA CubeSats and SmallSats. We will also describe the integrated communications infrastructure to support end-to-end data delivery and management to a SSA portal.

An algorithm for monitoring the traffic on a less-travelled road using multi-modal sensor suite

NASA Astrophysics Data System (ADS)

Damarla, Thyagaraju; Chatters, Gary; Liss, Brian; Vu, Hao; Sabatier, James M.

2014-06-01

We conducted an experiment to correlate the information gathered by a suite of hard sensors with the information on social networks such as Twitter, Facebook, etc. The experiment consisting of monitoring traffic on a well- traveled road and on a road inside a facility. The sensors suite selected mainly consists of sensors that require low power for operation and last a longtime. The output of each sensor is analyzed to classify the targets as ground vehicles, humans, and airborne targets. The algorithm is also used to count the number of targets belonging to each type so the sensor can store the information for anomaly detection. In this paper, we describe the classifier algorithms used for acoustic, seismic, and passive infrared (PIR) sensor data.

Spatial aggregation query in dynamic geosensor networks

NASA Astrophysics Data System (ADS)

Yi, Baolin; Feng, Dayang; Xiao, Shisong; Zhao, Erdun

2007-11-01

Wireless sensor networks have been widely used for civilian and military applications, such as environmental monitoring and vehicle tracking. In many of these applications, the researches mainly aim at building sensor network based systems to leverage the sensed data to applications. However, the existing works seldom exploited spatial aggregation query considering the dynamic characteristics of sensor networks. In this paper, we investigate how to process spatial aggregation query over dynamic geosensor networks where both the sink node and sensor nodes are mobile and propose several novel improvements on enabling techniques. The mobility of sensors makes the existing routing protocol based on information of fixed framework or the neighborhood infeasible. We present an improved location-based stateless implicit geographic forwarding (IGF) protocol for routing a query toward the area specified by query window, a diameter-based window aggregation query (DWAQ) algorithm for query propagation and data aggregation in the query window, finally considering the location changing of the sink node, we present two schemes to forward the result to the sink node. Simulation results show that the proposed algorithms can improve query latency and query accuracy.

Self-deployable mobile sensor networks for on-demand surveillance

NASA Astrophysics Data System (ADS)

Miao, Lidan; Qi, Hairong; Wang, Feiyi

2005-05-01

This paper studies two interconnected problems in mobile sensor network deployment, the optimal placement of heterogeneous mobile sensor platforms for cost-efficient and reliable coverage purposes, and the self-organizable deployment. We first develop an optimal placement algorithm based on a "mosaicked technology" such that different types of mobile sensors form a mosaicked pattern uniquely determined by the popularity of different types of sensor nodes. The initial state is assumed to be random. In order to converge to the optimal state, we investigate the swarm intelligence (SI)-based sensor movement strategy, through which the randomly deployed sensors can self-organize themselves to reach the optimal placement state. The proposed algorithm is compared with the random movement and the centralized method using performance metrics such as network coverage, convergence time, and energy consumption. Simulation results are presented to demonstrate the effectiveness of the mosaic placement and the SI-based movement.

The Rover Environmental Monitoring Station Ground Temperature Sensor: a pyrometer for measuring ground temperature on Mars.

PubMed

Sebastián, Eduardo; Armiens, Carlos; Gómez-Elvira, Javier; Zorzano, María P; Martinez-Frias, Jesus; Esteban, Blanca; Ramos, Miguel

2010-01-01

We describe the parameters that drive the design and modeling of the Rover Environmental Monitoring Station (REMS) Ground Temperature Sensor (GTS), an instrument aboard NASA's Mars Science Laboratory, and report preliminary test results. REMS GTS is a lightweight, low-power, and low cost pyrometer for measuring the Martian surface kinematic temperature. The sensor's main feature is its innovative design, based on a simple mechanical structure with no moving parts. It includes an in-flight calibration system that permits sensor recalibration when sensor sensitivity has been degraded by deposition of dust over the optics. This paper provides the first results of a GTS engineering model working in a Martian-like, extreme environment.

NetMOD Version 2.0 Mathematical Framework

DOE Office of Scientific and Technical Information (OSTI.GOV)

Merchant, Bion J.; Young, Christopher J.; Chael, Eric P.

2015-08-01

NetMOD ( Net work M onitoring for O ptimal D etection) is a Java-based software package for conducting simulation of seismic, hydroacoustic and infrasonic networks. Network simulations have long been used to study network resilience to station outages and to determine where additional stations are needed to reduce monitoring thresholds. NetMOD makes use of geophysical models to determine the source characteristics, signal attenuation along the path between the source and station, and the performance and noise properties of the station. These geophysical models are combined to simulate the relative amplitudes of signal and noise that are observed at each ofmore » the stations. From these signal-to-noise ratios (SNR), the probabilities of signal detection at each station and event detection across the network of stations can be computed given a detection threshold. The purpose of this document is to clearly and comprehensively present the mathematical framework used by NetMOD, the software package developed by Sandia National Laboratories to assess the monitoring capability of ground-based sensor networks. Many of the NetMOD equations used for simulations are inherited from the NetSim network capability assessment package developed in the late 1980s by SAIC (Sereno et al., 1990).« less

Energy Aware Clustering Algorithms for Wireless Sensor Networks

NASA Astrophysics Data System (ADS)

Rakhshan, Noushin; Rafsanjani, Marjan Kuchaki; Liu, Chenglian

2011-09-01

The sensor nodes deployed in wireless sensor networks (WSNs) are extremely power constrained, so maximizing the lifetime of the entire networks is mainly considered in the design. In wireless sensor networks, hierarchical network structures have the advantage of providing scalable and energy efficient solutions. In this paper, we investigate different clustering algorithms for WSNs and also compare these clustering algorithms based on metrics such as clustering distribution, cluster's load balancing, Cluster Head's (CH) selection strategy, CH's role rotation, node mobility, clusters overlapping, intra-cluster communications, reliability, security and location awareness.

Development and Integration of a Solar Powered Unmanned Aerial Vehicle and a Wireless Sensor Network to Monitor Greenhouse Gases

PubMed Central

Malaver, Alexander; Motta, Nunzio; Corke, Peter; Gonzalez, Felipe

2015-01-01

Measuring gases for environmental monitoring is a demanding task that requires long periods of observation and large numbers of sensors. Wireless Sensor Networks (WSNs) and Unmanned Aerial Vehicles (UAVs) currently represent the best alternative to monitor large, remote, and difficult access areas, as these technologies have the possibility of carrying specialized gas sensing systems. This paper presents the development and integration of a WSN and an UAV powered by solar energy in order to enhance their functionality and broader their applications. A gas sensing system implementing nanostructured metal oxide (MOX) and non-dispersive infrared sensors was developed to measure concentrations of CH4 and CO2. Laboratory, bench and field testing results demonstrate the capability of UAV to capture, analyze and geo-locate a gas sample during flight operations. The field testing integrated ground sensor nodes and the UAV to measure CO2 concentration at ground and low aerial altitudes, simultaneously. Data collected during the mission was transmitted in real time to a central node for analysis and 3D mapping of the target gas. The results highlights the accomplishment of the first flight mission of a solar powered UAV equipped with a CO2 sensing system integrated with a WSN. The system provides an effective 3D monitoring and can be used in a wide range of environmental applications such as agriculture, bushfires, mining studies, zoology and botanical studies using a ubiquitous low cost technology. PMID:25679312

Development and integration of a solar powered unmanned aerial vehicle and a wireless sensor network to monitor greenhouse gases.

PubMed

Malaver, Alexander; Motta, Nunzio; Corke, Peter; Gonzalez, Felipe

2015-02-11

Measuring gases for environmental monitoring is a demanding task that requires long periods of observation and large numbers of sensors. Wireless Sensor Networks (WSNs) and Unmanned Aerial Vehicles (UAVs) currently represent the best alternative to monitor large, remote, and difficult access areas, as these technologies have the possibility of carrying specialized gas sensing systems. This paper presents the development and integration of a WSN and an UAV powered by solar energy in order to enhance their functionality and broader their applications. A gas sensing system implementing nanostructured metal oxide (MOX) and non-dispersive infrared sensors was developed to measure concentrations of CH4 and CO2. Laboratory, bench and field testing results demonstrate the capability of UAV to capture, analyze and geo-locate a gas sample during flight operations. The field testing integrated ground sensor nodes and the UAV to measure CO2 concentration at ground and low aerial altitudes, simultaneously. Data collected during the mission was transmitted in real time to a central node for analysis and 3D mapping of the target gas. The results highlights the accomplishment of the first flight mission of a solar powered UAV equipped with a CO2 sensing system integrated with a WSN. The system provides an effective 3D monitoring and can be used in a wide range of environmental applications such as agriculture, bushfires, mining studies, zoology and botanical studies using a ubiquitous low cost technology.

Estimation and Fusion for Tracking Over Long-Haul Links Using Artificial Neural Networks

DOE PAGES

Liu, Qiang; Brigham, Katharine; Rao, Nageswara S. V.

2017-02-01

In a long-haul sensor network, sensors are remotely deployed over a large geographical area to perform certain tasks, such as tracking and/or monitoring of one or more dynamic targets. A remote fusion center fuses the information provided by these sensors so that a final estimate of certain target characteristics – such as the position – is expected to possess much improved quality. In this paper, we pursue learning-based approaches for estimation and fusion of target states in longhaul sensor networks. In particular, we consider learning based on various implementations of artificial neural networks (ANNs). Finally, the joint effect of (i)more » imperfect communication condition, namely, link-level loss and delay, and (ii) computation constraints, in the form of low-quality sensor estimates, on ANN-based estimation and fusion, is investigated by means of analytical and simulation studies.« less

Estimation and Fusion for Tracking Over Long-Haul Links Using Artificial Neural Networks

DOE Office of Scientific and Technical Information (OSTI.GOV)

Liu, Qiang; Brigham, Katharine; Rao, Nageswara S. V.

In a long-haul sensor network, sensors are remotely deployed over a large geographical area to perform certain tasks, such as tracking and/or monitoring of one or more dynamic targets. A remote fusion center fuses the information provided by these sensors so that a final estimate of certain target characteristics – such as the position – is expected to possess much improved quality. In this paper, we pursue learning-based approaches for estimation and fusion of target states in longhaul sensor networks. In particular, we consider learning based on various implementations of artificial neural networks (ANNs). Finally, the joint effect of (i)more » imperfect communication condition, namely, link-level loss and delay, and (ii) computation constraints, in the form of low-quality sensor estimates, on ANN-based estimation and fusion, is investigated by means of analytical and simulation studies.« less

Early Forest Fire Detection Using Radio-Acoustic Sounding System

PubMed Central

Sahin, Yasar Guneri; Ince, Turker

2009-01-01

Automated early fire detection systems have recently received a significant amount of attention due to their importance in protecting the global environment. Some emergent technologies such as ground-based, satellite-based remote sensing and distributed sensor networks systems have been used to detect forest fires in the early stages. In this study, a radio-acoustic sounding system with fine space and time resolution capabilities for continuous monitoring and early detection of forest fires is proposed. Simulations show that remote thermal mapping of a particular forest region by the proposed system could be a potential solution to the problem of early detection of forest fires. PMID:22573967

A Tree Based Self-routing Scheme for Mobility Support in Wireless Sensor Networks

NASA Astrophysics Data System (ADS)

Kim, Young-Duk; Yang, Yeon-Mo; Kang, Won-Seok; Kim, Jin-Wook; An, Jinung

Recently, WSNs (Wireless Sensor Networks) with mobile robot is a growing technology that offer efficient communication services for anytime and anywhere applications. However, the tiny sensor node has very limited network resources due to its low battery power, low data rate, node mobility, and channel interference constraint between neighbors. Thus, in this paper, we proposed a tree based self-routing protocol for autonomous mobile robots based on beacon mode and implemented in real test-bed environments. The proposed scheme offers beacon based real-time scheduling for reliable association process between parent and child nodes. In addition, it supports smooth handover procedure by reducing flooding overhead of control packets. Throughout the performance evaluation by using a real test-bed system and simulation, we illustrate that our proposed scheme demonstrates promising performance for wireless sensor networks with mobile robots.

LinkMind: link optimization in swarming mobile sensor networks.

PubMed

Ngo, Trung Dung

2011-01-01

A swarming mobile sensor network is comprised of a swarm of wirelessly connected mobile robots equipped with various sensors. Such a network can be applied in an uncertain environment for services such as cooperative navigation and exploration, object identification and information gathering. One of the most advantageous properties of the swarming wireless sensor network is that mobile nodes can work cooperatively to organize an ad-hoc network and optimize the network link capacity to maximize the transmission of gathered data from a source to a target. This paper describes a new method of link optimization of swarming mobile sensor networks. The new method is based on combination of the artificial potential force guaranteeing connectivities of the mobile sensor nodes and the max-flow min-cut theorem of graph theory ensuring optimization of the network link capacity. The developed algorithm is demonstrated and evaluated in simulation.

LinkMind: Link Optimization in Swarming Mobile Sensor Networks

PubMed Central

Ngo, Trung Dung

2011-01-01

A swarming mobile sensor network is comprised of a swarm of wirelessly connected mobile robots equipped with various sensors. Such a network can be applied in an uncertain environment for services such as cooperative navigation and exploration, object identification and information gathering. One of the most advantageous properties of the swarming wireless sensor network is that mobile nodes can work cooperatively to organize an ad-hoc network and optimize the network link capacity to maximize the transmission of gathered data from a source to a target. This paper describes a new method of link optimization of swarming mobile sensor networks. The new method is based on combination of the artificial potential force guaranteeing connectivities of the mobile sensor nodes and the max-flow min-cut theorem of graph theory ensuring optimization of the network link capacity. The developed algorithm is demonstrated and evaluated in simulation. PMID:22164070

Evaluating detection and estimation capabilities of magnetometer-based vehicle sensors

NASA Astrophysics Data System (ADS)

Slater, David M.; Jacyna, Garry M.

2013-05-01

In an effort to secure the northern and southern United States borders, MITRE has been tasked with developing Modeling and Simulation (M&S) tools that accurately capture the mapping between algorithm-level Measures of Performance (MOP) and system-level Measures of Effectiveness (MOE) for current/future surveillance systems deployed by the the Customs and Border Protection Office of Technology Innovations and Acquisitions (OTIA). This analysis is part of a larger M&S undertaking. The focus is on two MOPs for magnetometer-based Unattended Ground Sensors (UGS). UGS are placed near roads to detect passing vehicles and estimate properties of the vehicle's trajectory such as bearing and speed. The first MOP considered is the probability of detection. We derive probabilities of detection for a network of sensors over an arbitrary number of observation periods and explore how the probability of detection changes when multiple sensors are employed. The performance of UGS is also evaluated based on the level of variance in the estimation of trajectory parameters. We derive the Cramer-Rao bounds for the variances of the estimated parameters in two cases: when no a priori information is known and when the parameters are assumed to be Gaussian with known variances. Sample results show that UGS perform significantly better in the latter case.

Chain-Based Communication in Cylindrical Underwater Wireless Sensor Networks

PubMed Central

Javaid, Nadeem; Jafri, Mohsin Raza; Khan, Zahoor Ali; Alrajeh, Nabil; Imran, Muhammad; Vasilakos, Athanasios

2015-01-01

Appropriate network design is very significant for Underwater Wireless Sensor Networks (UWSNs). Application-oriented UWSNs are planned to achieve certain objectives. Therefore, there is always a demand for efficient data routing schemes, which can fulfill certain requirements of application-oriented UWSNs. These networks can be of any shape, i.e., rectangular, cylindrical or square. In this paper, we propose chain-based routing schemes for application-oriented cylindrical networks and also formulate mathematical models to find a global optimum path for data transmission. In the first scheme, we devise four interconnected chains of sensor nodes to perform data communication. In the second scheme, we propose routing scheme in which two chains of sensor nodes are interconnected, whereas in third scheme single-chain based routing is done in cylindrical networks. After finding local optimum paths in separate chains, we find global optimum paths through their interconnection. Moreover, we develop a computational model for the analysis of end-to-end delay. We compare the performance of the above three proposed schemes with that of Power Efficient Gathering System in Sensor Information Systems (PEGASIS) and Congestion adjusted PEGASIS (C-PEGASIS). Simulation results show that our proposed 4-chain based scheme performs better than the other selected schemes in terms of network lifetime, end-to-end delay, path loss, transmission loss, and packet sending rate. PMID:25658394

A Neural Network Based Intelligent Predictive Sensor for Cloudiness, Solar Radiation and Air Temperature

PubMed Central

Ferreira, Pedro M.; Gomes, João M.; Martins, Igor A. C.; Ruano, António E.

2012-01-01

Accurate measurements of global solar radiation and atmospheric temperature, as well as the availability of the predictions of their evolution over time, are important for different areas of applications, such as agriculture, renewable energy and energy management, or thermal comfort in buildings. For this reason, an intelligent, light-weight and portable sensor was developed, using artificial neural network models as the time-series predictor mechanisms. These have been identified with the aid of a procedure based on the multi-objective genetic algorithm. As cloudiness is the most significant factor affecting the solar radiation reaching a particular location on the Earth surface, it has great impact on the performance of predictive solar radiation models for that location. This work also represents one step towards the improvement of such models by using ground-to-sky hemispherical colour digital images as a means to estimate cloudiness by the fraction of visible sky corresponding to clouds and to clear sky. The implementation of predictive models in the prototype has been validated and the system is able to function reliably, providing measurements and four-hour forecasts of cloudiness, solar radiation and air temperature. PMID:23202230

Crowd-Sourcing Seismic Data: Lessons Learned from the Quake-Catcher Network

NASA Astrophysics Data System (ADS)

Cochran, E. S.; Sumy, D. F.; DeGroot, R. M.; Clayton, R. W.

2015-12-01

The Quake Catcher Network (QCN; qcn.caltech.edu) uses low cost micro-electro-mechanical system (MEMS) sensors hosted by volunteers to collect seismic data. Volunteers use accelerometers internal to laptop computers, phones, tablets or small (the size of a matchbox) MEMS sensors plugged into desktop computers using a USB connector to collect scientifically useful data. Data are collected and sent to a central server using the Berkeley Open Infrastructure for Network Computing (BOINC) distributed computing software. Since 2008, when the first citizen scientists joined the QCN project, sensors installed in museums, schools, offices, and residences have collected thousands of earthquake records. We present and describe the rapid installations of very dense sensor networks that have been undertaken following several large earthquakes including the 2010 M8.8 Maule Chile, the 2010 M7.1 Darfield, New Zealand, and the 2015 M7.8 Gorkha, Nepal earthquake. These large data sets allowed seismologists to develop new rapid earthquake detection capabilities and closely examine source, path, and site properties that impact ground shaking at a site. We show how QCN has engaged a wide sector of the public in scientific data collection, providing the public with insights into how seismic data are collected and used. Furthermore, we describe how students use data recorded by QCN sensors installed in their classrooms to explore and investigate earthquakes that they felt, as part of 'teachable moment' exercises.

Ikhana: A NASA UAS Supporting Long Duration Earth Science Missions

NASA Technical Reports Server (NTRS)

Cobleigh, Brent R.

2006-01-01

NASA's Ikhana unmanned aerial vehicle (UAV) is a General Atomics MQ-9 Predator-B modified to support the conduct of Earth science missions for the NASA Science Mission Directorate through partnerships, other government agencies and universities. Ikhana, a Native American word meaning 'intelligence', can carry over 2000 lbs of atmospheric and remote sensing instruments in the payload bay and external pods. The aircraft is capable of mission durations in excess of 24 hours at altitudes above 40,000 ft. Redundant flight control, avionics, power, and network systems increase the system reliability and allow easier access to public airspace. The aircraft is remotely piloted from a mobile ground control station (GCS) using both C-band line-of-sight and Ku-band over-the-horizon satellite datalinks. NASA's GCS has been modified to support on-site science monitoring, or the downlink data can be networked to remote sites. All ground support systems are designed to be deployable to support global Eart science investigations. On-board support capabilities include an instrumentation system and an Airborne Research Test System (ARTS). The ARTS can host research algorithms that will autonomously command and control on-board sensors, perform sensor health monitoring, conduct data analysis, and request changes to the flight plan to maximize data collection. The ARTS also has the ability to host algorithms that will autonomously control the aircraft trajectory based on sensor needs, (e.g. precision trajectory for repeat pass interferometry) or to optimize mission objectives (e.g. search for specific atmospheric conditions). Standard on-board networks will collect science data for recording and for inclusion in the aircraft's high bandwidth downlink. The Ikhana project will complete GCS development, science support systems integration, external pod integration and flight clearance, and operations crew training in early 2007. A large-area remote sensing mission is currently scheduled for the Summer 2007.

Applying traditional signal processing techniques to social media exploitation for situational understanding

NASA Astrophysics Data System (ADS)

Abdelzaher, Tarek; Roy, Heather; Wang, Shiguang; Giridhar, Prasanna; Al Amin, Md. Tanvir; Bowman, Elizabeth K.; Kolodny, Michael A.

2016-05-01

Signal processing techniques such as filtering, detection, estimation and frequency domain analysis have long been applied to extract information from noisy sensor data. This paper describes the exploitation of these signal processing techniques to extract information from social networks, such as Twitter and Instagram. Specifically, we view social networks as noisy sensors that report events in the physical world. We then present a data processing stack for detection, localization, tracking, and veracity analysis of reported events using social network data. We show using a controlled experiment that the behavior of social sources as information relays varies dramatically depending on context. In benign contexts, there is general agreement on events, whereas in conflict scenarios, a significant amount of collective filtering is introduced by conflicted groups, creating a large data distortion. We describe signal processing techniques that mitigate such distortion, resulting in meaningful approximations of actual ground truth, given noisy reported observations. Finally, we briefly present an implementation of the aforementioned social network data processing stack in a sensor network analysis toolkit, called Apollo. Experiences with Apollo show that our techniques are successful at identifying and tracking credible events in the physical world.

Designing teams of unattended ground sensors using genetic algorithms

NASA Astrophysics Data System (ADS)

Yilmaz, Ayse S.; McQuay, Brian N.; Wu, Annie S.; Sciortino, John C., Jr.

2004-04-01

Improvements in sensor capabilities have driven the need for automated sensor allocation and management systems. Such systems provide a penalty-free test environment and valuable input to human operators by offering candidate solutions. These abilities lead, in turn, to savings in manpower and time. Determining an optimal team of cooperating sensors for military operations is a challenging task. There is a tradeoff between the desire to decrease the cost and the need to increase the sensing capabilities of a sensor suite. This work focuses on unattended ground sensor networks consisting of teams of small, inexpensive sensors. Given a possible configuration of enemy radar, our goal isto generate sensor suites that monitor as many enemy radar as possible while minimizing cost. In previous work, we have shown that genetic algorithms (GAs) can be used to evolve successful teams of sensors for this problem. This work extends our previous work in two ways: we use an improved simulator containing a more accurate model of radar and sensor capabilities for out fitness evaluations and we introduce two new genetic operators, insertion and deletion, that are expected to improve the GA's fine tuning abilities. Empirical results show that our GA approach produces near optimal results under a variety of enemy radar configurations using sensors with varying capabilities. Detection percentage remains stable regardless of changes in the enemy radar placements.

Economic Feasibility of Wireless Sensor Network-Based Service Provision in a Duopoly Setting with a Monopolist Operator

PubMed Central

Romero, Julián; Sacoto-Cabrera, Erwin J.

2017-01-01

We analyze the feasibility of providing Wireless Sensor Network-data-based services in an Internet of Things scenario from an economical point of view. The scenario has two competing service providers with their own private sensor networks, a network operator and final users. The scenario is analyzed as two games using game theory. In the first game, sensors decide to subscribe or not to the network operator to upload the collected sensing-data, based on a utility function related to the mean service time and the price charged by the operator. In the second game, users decide to subscribe or not to the sensor-data-based service of the service providers based on a Logit discrete choice model related to the quality of the data collected and the subscription price. The sinks and users subscription stages are analyzed using population games and discrete choice models, while network operator and service providers pricing stages are analyzed using optimization and Nash equilibrium concepts respectively. The model is shown feasible from an economic point of view for all the actors if there are enough interested final users and opens the possibility of developing more efficient models with different types of services. PMID:29186847

Prospects for infrasound bolide detections from balloon-borne platforms

NASA Astrophysics Data System (ADS)

Young, Eliot; Bowman, Daniel; Arrowsmith, Stephen; Boslough, Marc; Klein, Viliam; Ballard, Courtney; Lees, Jonathan

2017-04-01

We report on an experiment to assess whether balloon-borne instruments can improve sensitivities to bolides exploding in the Earth's atmosphere (essentially using the atmosphere as a witness plate to characterize the small end of the NEO (Near Earth Object) population). The CTBTO's infrasound network regularly detects infrasound disturbances caused by bolides, including the 15-FEB-2013 Chelybinsk impact. Balloon-borne infrasound sensors should have two important advantages over ground-based infrasound stations: there should be virtually no wind noise on a free-floating platform, and a sensor in the stratosphere should benefit from its location within the stratospheric duct. Balloon-borne sensors also have the disadvantage that the amplitude of infrasound waves will decrease as they ascend with altitude. To test the performance of balloon-borne sensors, we conducted an experiment on a NASA high altitude (35 km) balloon launched from Ft Sumner, NM on 28-SEP-2016. We were able to put two independent infrasound payloads on this flight. We arranged for three 3000-lb ANFO explosions to be detonated from Socorro, NM at 12:00, 14:00 and 16:29:59 MST. The first two explosions were detected from the NASA balloon, with the first explosion showing three separate waveforms arriving within a 25-s span. The peak-to-peak amplitude of the waveforms was about 0.06 Pa, and the cleanest microphone channel detected this waveform with an SNR greater than 20. A second balloon at 15 km altitude also detected the second explosion. We have signals from a dozen ground stations at various positions from Socorro to Ft Sumner. We will report on wave propagation models and how they compare with observations from the two balloons and the various ground-stations.

Storm-based Cloud-to-Ground Lightning Probabilities and Warnings

NASA Astrophysics Data System (ADS)

Calhoun, K. M.; Meyer, T.; Kingfield, D.

2017-12-01

A new cloud-to-ground (CG) lightning probability algorithm has been developed using machine-learning methods. With storm-based inputs of Earth Networks' in-cloud lightning, Vaisala's CG lightning, multi-radar/multi-sensor (MRMS) radar derived products including the Maximum Expected Size of Hail (MESH) and Vertically Integrated Liquid (VIL), and near storm environmental data including lapse rate and CAPE, a random forest algorithm was trained to produce probabilities of CG lightning up to one-hour in advance. As part of the Prototype Probabilistic Hazard Information experiment in the Hazardous Weather Testbed in 2016 and 2017, National Weather Service forecasters were asked to use this CG lightning probability guidance to create rapidly updating probability grids and warnings for the threat of CG lightning for 0-60 minutes. The output from forecasters was shared with end-users, including emergency managers and broadcast meteorologists, as part of an integrated warning team.

Exploration of Objective Functions for Optimal Placement of Weather Stations

NASA Astrophysics Data System (ADS)

Snyder, A.; Dietterich, T.; Selker, J. S.

2016-12-01

Many regions of Earth lack ground-based sensing of weather variables. For example, most countries in Sub-Saharan Africa do not have reliable weather station networks. This absence of sensor data has many consequences ranging from public safety (poor prediction and detection of severe weather events), to agriculture (lack of crop insurance), to science (reduced quality of world-wide weather forecasts, climate change measurement, etc.). The Trans-African Hydro-Meteorological Observatory (TAHMO.org) project seeks to address these problems by deploying and operating a large network of weather stations throughout Sub-Saharan Africa. To design the TAHMO network, we must determine where to locate each weather station. We can formulate this as the following optimization problem: Determine a set of N sites that jointly optimize the value of an objective function. The purpose of this poster is to propose and assess several objective functions. In addition to standard objectives (e.g., minimizing the summed squared error of interpolated values over the entire region), we consider objectives that minimize the maximum error over the region and objectives that optimize the detection of extreme events. An additional issue is that each station measures more than 10 variables—how should we balance the accuracy of our interpolated maps for each variable? Weather sensors inevitably drift out of calibration or fail altogether. How can we incorporate robustness to failed sensors into our network design? Another important requirement is that the network should make it possible to detect failed sensors by comparing their readings with those of other stations. How can this requirement be met? Finally, we provide an initial assessment of the computational cost of optimizing these various objective functions. We invite everyone to join the discussion at our poster by proposing additional objectives, identifying additional issues to consider, and expanding our bibliography of relevant papers. A prize (derived from grapes grown in Oregon) will be awarded for the most insightful contribution to the discussion!

A Coral Reef Algorithm Based on Learning Automata for the Coverage Control Problem of Heterogeneous Directional Sensor Networks

PubMed Central

Li, Ming; Miao, Chunyan; Leung, Cyril

2015-01-01

Coverage control is one of the most fundamental issues in directional sensor networks. In this paper, the coverage optimization problem in a directional sensor network is formulated as a multi-objective optimization problem. It takes into account the coverage rate of the network, the number of working sensor nodes and the connectivity of the network. The coverage problem considered in this paper is characterized by the geographical irregularity of the sensed events and heterogeneity of the sensor nodes in terms of sensing radius, field of angle and communication radius. To solve this multi-objective problem, we introduce a learning automata-based coral reef algorithm for adaptive parameter selection and use a novel Tchebycheff decomposition method to decompose the multi-objective problem into a single-objective problem. Simulation results show the consistent superiority of the proposed algorithm over alternative approaches. PMID:26690162

A Coral Reef Algorithm Based on Learning Automata for the Coverage Control Problem of Heterogeneous Directional Sensor Networks.

PubMed

Li, Ming; Miao, Chunyan; Leung, Cyril

2015-12-04

Coverage control is one of the most fundamental issues in directional sensor networks. In this paper, the coverage optimization problem in a directional sensor network is formulated as a multi-objective optimization problem. It takes into account the coverage rate of the network, the number of working sensor nodes and the connectivity of the network. The coverage problem considered in this paper is characterized by the geographical irregularity of the sensed events and heterogeneity of the sensor nodes in terms of sensing radius, field of angle and communication radius. To solve this multi-objective problem, we introduce a learning automata-based coral reef algorithm for adaptive parameter selection and use a novel Tchebycheff decomposition method to decompose the multi-objective problem into a single-objective problem. Simulation results show the consistent superiority of the proposed algorithm over alternative approaches.

SNM-DAT: Simulation of a heterogeneous network for nuclear border security

NASA Astrophysics Data System (ADS)

Nemzek, R.; Kenyon, G.; Koehler, A.; Lee, D. M.; Priedhorsky, W.; Raby, E. Y.

2007-08-01

We approach the problem of detecting Special Nuclear Material (SNM) smuggling across open borders by modeling a heterogeneous sensor network using an agent-based simulation. Our simulation SNM Data Analysis Tool (SNM-DAT) combines fixed seismic, metal, and radiation detectors with a mobile gamma spectrometer. Decision making within the simulation determines threat levels by combined signatures. The spectrometer is a limited-availability asset, and is only deployed for substantial threats. "Crossers" can be benign or carrying shielded SNM. Signatures and sensors are physics based, allowing us to model realistic sensor networks. The heterogeneous network provides great gains in detection efficiency compared to a radiation-only system. We can improve the simulation through better sensor and terrain models, additional signatures, and crossers that mimic actual trans-border traffic. We expect further gains in our ability to design sensor networks as we learn the emergent properties of heterogeneous detection, and potential adversary responses.

Lifetime Maximization via Hole Alleviation in IoT Enabling Heterogeneous Wireless Sensor Networks.

PubMed

Wadud, Zahid; Javaid, Nadeem; Khan, Muhammad Awais; Alrajeh, Nabil; Alabed, Mohamad Souheil; Guizani, Nadra

2017-07-21

In Internet of Things (IoT) enabled Wireless Sensor Networks (WSNs), there are two major factors which degrade the performance of the network. One is the void hole which occurs in a particular region due to unavailability of forwarder nodes. The other is the presence of energy hole which occurs due to imbalanced data traffic load on intermediate nodes. Therefore, an optimum transmission strategy is required to maximize the network lifespan via hole alleviation. In this regard, we propose a heterogeneous network solution that is capable to balance energy dissipation among network nodes. In addition, the divide and conquer approach is exploited to evenly distribute number of transmissions over various network areas. An efficient forwarder node selection is performed to alleviate coverage and energy holes. Linear optimization is performed to validate the effectiveness of our proposed work in term of energy minimization. Furthermore, simulations are conducted to show that our claims are well grounded. Results show the superiority of our work as compared to the baseline scheme in terms of energy consumption and network lifetime.

Lifetime Maximization via Hole Alleviation in IoT Enabling Heterogeneous Wireless Sensor Networks

PubMed Central

Wadud, Zahid; Khan, Muhammad Awais; Alrajeh, Nabil; Alabed, Mohamad Souheil; Guizani, Nadra

2017-01-01

In Internet of Things (IoT) enabled Wireless Sensor Networks (WSNs), there are two major factors which degrade the performance of the network. One is the void hole which occurs in a particular region due to unavailability of forwarder nodes. The other is the presence of energy hole which occurs due to imbalanced data traffic load on intermediate nodes. Therefore, an optimum transmission strategy is required to maximize the network lifespan via hole alleviation. In this regard, we propose a heterogeneous network solution that is capable to balance energy dissipation among network nodes. In addition, the divide and conquer approach is exploited to evenly distribute number of transmissions over various network areas. An efficient forwarder node selection is performed to alleviate coverage and energy holes. Linear optimization is performed to validate the effectiveness of our proposed work in term of energy minimization. Furthermore, simulations are conducted to show that our claims are well grounded. Results show the superiority of our work as compared to the baseline scheme in terms of energy consumption and network lifetime. PMID:28753990

The Rondonia Lightning Detection Network: Network Description, Science Objectives, Data Processing Archival/Methodology, and Results

NASA Technical Reports Server (NTRS)

Blakeslee, R. J.; Bailey, J. C.; Pinto, O.; Athayde, A.; Renno, N.; Weidman, C. D.

2003-01-01

A four station Advanced Lightning Direction Finder (ALDF) network was established in the state of Rondonia in western Brazil in 1999 through a collaboration of U.S. and Brazilian participants from NASA, INPE, INMET, and various universities. The network utilizes ALDF IMPACT (Improved Accuracy from Combined Technology) sensors to provide cloud-to-ground lightning observations (i.e., stroke/flash locations, signal amplitude, and polarity) using both time-of- arrival and magnetic direction finding techniques. The observations are collected, processed and archived at a central site in Brasilia and at the NASA/Marshall Space Flight Center in Huntsville, Alabama. Initial, non-quality assured quick-look results are made available in near real-time over the Internet. The network, which is still operational, was deployed to provide ground truth data for the Lightning Imaging Sensor (LIS) on the Tropical Rainfall Measuring Mission (TRMM) satellite that was launched in November 1997. The measurements are also being used to investigate the relationship between the electrical, microphysical and kinematic properties of tropical convection. In addition, the long-time series observations produced by this network will help establish a regional lightning climatological database, supplementing other databases in Brazil that already exist or may soon be implemented. Analytic inversion algorithms developed at the NASA/Marshall Space Flight Center have been applied to the Rondonian ALDF lightning observations to obtain site error corrections and improved location retrievals. The data will also be corrected for the network detection efficiency. The processing methodology and the results from the analysis of four years of network operations will be presented.

Calibration of Smartphone-Based Weather Measurements Using Pairwise Gossip.

PubMed

Zamora, Jane Louie Fresco; Kashihara, Shigeru; Yamaguchi, Suguru

2015-01-01

Accurate and reliable daily global weather reports are necessary for weather forecasting and climate analysis. However, the availability of these reports continues to decline due to the lack of economic support and policies in maintaining ground weather measurement systems from where these reports are obtained. Thus, to mitigate data scarcity, it is required to utilize weather information from existing sensors and built-in smartphone sensors. However, as smartphone usage often varies according to human activity, it is difficult to obtain accurate measurement data. In this paper, we present a heuristic-based pairwise gossip algorithm that will calibrate smartphone-based pressure sensors with respect to fixed weather stations as our referential ground truth. Based on actual measurements, we have verified that smartphone-based readings are unstable when observed during movement. Using our calibration algorithm on actual smartphone-based pressure readings, the updated values were significantly closer to the ground truth values.

Calibration of Smartphone-Based Weather Measurements Using Pairwise Gossip

PubMed Central

Yamaguchi, Suguru

2015-01-01

Accurate and reliable daily global weather reports are necessary for weather forecasting and climate analysis. However, the availability of these reports continues to decline due to the lack of economic support and policies in maintaining ground weather measurement systems from where these reports are obtained. Thus, to mitigate data scarcity, it is required to utilize weather information from existing sensors and built-in smartphone sensors. However, as smartphone usage often varies according to human activity, it is difficult to obtain accurate measurement data. In this paper, we present a heuristic-based pairwise gossip algorithm that will calibrate smartphone-based pressure sensors with respect to fixed weather stations as our referential ground truth. Based on actual measurements, we have verified that smartphone-based readings are unstable when observed during movement. Using our calibration algorithm on actual smartphone-based pressure readings, the updated values were significantly closer to the ground truth values. PMID:26421312

A Field Programmable Gate Array-Based Reconfigurable Smart-Sensor Network for Wireless Monitoring of New Generation Computer Numerically Controlled Machines

PubMed Central

Moreno-Tapia, Sandra Veronica; Vera-Salas, Luis Alberto; Osornio-Rios, Roque Alfredo; Dominguez-Gonzalez, Aurelio; Stiharu, Ion; de Jesus Romero-Troncoso, Rene

2010-01-01

Computer numerically controlled (CNC) machines have evolved to adapt to increasing technological and industrial requirements. To cover these needs, new generation machines have to perform monitoring strategies by incorporating multiple sensors. Since in most of applications the online Processing of the variables is essential, the use of smart sensors is necessary. The contribution of this work is the development of a wireless network platform of reconfigurable smart sensors for CNC machine applications complying with the measurement requirements of new generation CNC machines. Four different smart sensors are put under test in the network and their corresponding signal processing techniques are implemented in a Field Programmable Gate Array (FPGA)-based sensor node. PMID:22163602

A field programmable gate array-based reconfigurable smart-sensor network for wireless monitoring of new generation computer numerically controlled machines.

PubMed

Moreno-Tapia, Sandra Veronica; Vera-Salas, Luis Alberto; Osornio-Rios, Roque Alfredo; Dominguez-Gonzalez, Aurelio; Stiharu, Ion; Romero-Troncoso, Rene de Jesus

2010-01-01

Computer numerically controlled (CNC) machines have evolved to adapt to increasing technological and industrial requirements. To cover these needs, new generation machines have to perform monitoring strategies by incorporating multiple sensors. Since in most of applications the online Processing of the variables is essential, the use of smart sensors is necessary. The contribution of this work is the development of a wireless network platform of reconfigurable smart sensors for CNC machine applications complying with the measurement requirements of new generation CNC machines. Four different smart sensors are put under test in the network and their corresponding signal processing techniques are implemented in a Field Programmable Gate Array (FPGA)-based sensor node.

Intelligent Wireless Sensor Networks for System Health Monitoring

NASA Technical Reports Server (NTRS)

Alena, Rick

2011-01-01

Wireless sensor networks (WSN) based on the IEEE 802.15.4 Personal Area Network (PAN) standard are finding increasing use in the home automation and emerging smart energy markets. The network and application layers, based on the ZigBee 2007 Standard, provide a convenient framework for component-based software that supports customer solutions from multiple vendors. WSNs provide the inherent fault tolerance required for aerospace applications. The Discovery and Systems Health Group at NASA Ames Research Center has been developing WSN technology for use aboard aircraft and spacecraft for System Health Monitoring of structures and life support systems using funding from the NASA Engineering and Safety Center and Exploration Technology Development and Demonstration Program. This technology provides key advantages for low-power, low-cost ancillary sensing systems particularly across pressure interfaces and in areas where it is difficult to run wires. Intelligence for sensor networks could be defined as the capability of forming dynamic sensor networks, allowing high-level application software to identify and address any sensor that joined the network without the use of any centralized database defining the sensors characteristics. The IEEE 1451 Standard defines methods for the management of intelligent sensor systems and the IEEE 1451.4 section defines Transducer Electronic Datasheets (TEDS), which contain key information regarding the sensor characteristics such as name, description, serial number, calibration information and user information such as location within a vehicle. By locating the TEDS information on the wireless sensor itself and enabling access to this information base from the application software, the application can identify the sensor unambiguously and interpret and present the sensor data stream without reference to any other information. The application software is able to read the status of each sensor module, responding in real-time to changes of PAN configuration, providing the appropriate response for maintaining overall sensor system function, even when sensor modules fail or the WSN is reconfigured. The session will present the architecture and technical feasibility of creating fault-tolerant WSNs for aerospace applications based on our application of the technology to a Structural Health Monitoring testbed. The interim results of WSN development and testing including our software architecture for intelligent sensor management will be discussed in the context of the specific tradeoffs required for effective use. Initial certification measurement techniques and test results gauging WSN susceptibility to Radio Frequency interference are introduced as key challenges for technology adoption. A candidate Developmental and Flight Instrumentation implementation using intelligent sensor networks for wind tunnel and flight tests is developed as a guide to understanding key aspects of the aerospace vehicle design, test and operations life cycle.

A Feedback-Based Secure Path Approach for Wireless Sensor Network Data Collection

PubMed Central

Mao, Yuxin; Wei, Guiyi

2010-01-01

The unattended nature of wireless sensor networks makes them very vulnerable to malicious attacks. Therefore, how to preserve secure data collection is an important issue to wireless sensor networks. In this paper, we propose a novel approach of secure data collection for wireless sensor networks. We explore secret sharing and multipath routing to achieve secure data collection in wireless sensor network with compromised nodes. We present a novel tracing-feedback mechanism, which makes full use of the routing functionality of wireless sensor networks, to improve the quality of data collection. The major advantage of the approach is that the secure paths are constructed as a by-product of data collection. The process of secure routing causes little overhead to the sensor nodes in the network. Compared with existing works, the algorithms of the proposed approach are easy to implement and execute in resource-constrained wireless sensor networks. According to the result of a simulation experiment, the performance of the approach is better than the recent approaches with a similar purpose. PMID:22163424

Maintaining the Database for Information Object Analysis, Intent, Dissemination and Enhancement (IOAIDE) and the US Army Research Laboratory Campus Sensor Network (ARL CSN)

DTIC Science & Technology

2017-01-01

CII-B 2800 Powder Mill Road Adelphi, MD 20783-1138 8. PERFORMING ORGANIZATION REPORT NUMBER ARL-TR-7921 9. SPONSORING/MONITORING AGENCY NAME(S...server database, structured query language, information objects, instructions, maintenance , cursor on target events, unattended ground sensors...unlimited. iii Contents List of Figures iv 1. Introduction 1 2. Computer and Software Development Tools Requirements 1 3. Database Maintenance 2 3.1

Helmet-mounted acoustic array for hostile fire detection and localization in an urban environment

NASA Astrophysics Data System (ADS)

Scanlon, Michael V.

2008-04-01

The detection and localization of hostile weapons firing has been demonstrated successfully with acoustic sensor arrays on unattended ground sensors (UGS), ground-vehicles, and unmanned aerial vehicles (UAVs). Some of the more mature systems have demonstrated significant capabilities and provide direct support to ongoing counter-sniper operations. The Army Research Laboratory (ARL) is conducting research and development for a helmet-mounted system to acoustically detect and localize small arms firing, or other events such as RPG, mortars, and explosions, as well as other non-transient signatures. Since today's soldier is quickly being asked to take on more and more reconnaissance, surveillance, & target acquisition (RSTA) functions, sensor augmentation enables him to become a mobile and networked sensor node on the complex and dynamic battlefield. Having a body-worn threat detection and localization capability for events that pose an immediate danger to the soldiers around him can significantly enhance their survivability and lethality, as well as enable him to provide and use situational awareness clues on the networked battlefield. This paper addresses some of the difficulties encountered by an acoustic system in an urban environment. Complex reverberation, multipath, diffraction, and signature masking by building structures makes this a very harsh environment for robust detection and classification of shockwaves and muzzle blasts. Multifunctional acoustic detection arrays can provide persistent surveillance and enhanced situational awareness for every soldier.

Ground-based sensors for the SR-71 sonic boom propagation experiment

NASA Technical Reports Server (NTRS)

Norris, Stephen R.; Haering, Edward A., Jr.; Murray, James E.

1995-01-01

This paper describes ground-level measurements of sonic boom signatures made as part of the SR-71 sonic boom propagation experiment recently completed at NASA Dryden Flight Research Center, Edwards, California. Ground level measurements were the final stage of this experiment which also included airborne measurements at near and intermediate distances from an SR-71 research aircraft. Three types of sensors were deployed to three station locations near the aircraft ground track. Pressure data were collected for flight conditions from Mach 1.25 to Mach 1.60 at altitudes from 30,000 to 48,000 ft. Ground-level measurement techniques, comparisons of data sets from different ground sensors, and sensor system strengths and weaknesses are discussed. The well-known N-wave structure dominated the sonic boom signatures generated by the SR-71 aircraft at most of these conditions. Variations in boom shape caused by atmospheric turbulence, focusing effects, or both were observed for several flights. Peak pressure and boom event duration showed some dependence on aircraft gross weight. The sonic boom signatures collected in this experiment are being compiled in a data base for distribution in support of the High Speed Research Program.

Analytic Perturbation Method for Estimating Ground Flash Fraction from Satellite Lightning Observations

NASA Technical Reports Server (NTRS)

Koshak, William; Solakiewicz, Richard

2013-01-01

An analytic perturbation method is introduced for estimating the lightning ground flash fraction in a set of N lightning flashes observed by a satellite lightning mapper. The value of N is large, typically in the thousands, and the observations consist of the maximum optical group area produced by each flash. The method is tested using simulated observations that are based on Optical Transient Detector (OTD) and Lightning Imaging Sensor (LIS) data. National Lightning Detection NetworkTM (NLDN) data is used to determine the flash-type (ground or cloud) of the satellite-observed flashes, and provides the ground flash fraction truth for the simulation runs. It is found that the mean ground flash fraction retrieval errors are below 0.04 across the full range 0-1 under certain simulation conditions. In general, it is demonstrated that the retrieval errors depend on many factors (i.e., the number, N, of satellite observations, the magnitude of random and systematic measurement errors, and the number of samples used to form certain climate distributions employed in the model).

Improved Space Surveillance Network (SSN) Scheduling using Artificial Intelligence Techniques

NASA Astrophysics Data System (ADS)

Stottler, D.

There are close to 20,000 cataloged manmade objects in space, the large majority of which are not active, functioning satellites. These are tracked by phased array and mechanical radars and ground and space-based optical telescopes, collectively known as the Space Surveillance Network (SSN). A better SSN schedule of observations could, using exactly the same legacy sensor resources, improve space catalog accuracy through more complementary tracking, provide better responsiveness to real-time changes, better track small debris in low earth orbit (LEO) through efficient use of applicable sensors, efficiently track deep space (DS) frequent revisit objects, handle increased numbers of objects and new types of sensors, and take advantage of future improved communication and control to globally optimize the SSN schedule. We have developed a scheduling algorithm that takes as input the space catalog and the associated covariance matrices and produces a globally optimized schedule for each sensor site as to what objects to observe and when. This algorithm is able to schedule more observations with the same sensor resources and have those observations be more complementary, in terms of the precision with which each orbit metric is known, to produce a satellite observation schedule that, when executed, minimizes the covariances across the entire space object catalog. If used operationally, the results would be significantly increased accuracy of the space catalog with fewer lost objects with the same set of sensor resources. This approach inherently can also trade-off fewer high priority tasks against more lower-priority tasks, when there is benefit in doing so. Currently the project has completed a prototyping and feasibility study, using open source data on the SSN's sensors, that showed significant reduction in orbit metric covariances. The algorithm techniques and results will be discussed along with future directions for the research.

Lidar-based individual tree species classification using convolutional neural network

NASA Astrophysics Data System (ADS)

Mizoguchi, Tomohiro; Ishii, Akira; Nakamura, Hiroyuki; Inoue, Tsuyoshi; Takamatsu, Hisashi

2017-06-01

Terrestrial lidar is commonly used for detailed documentation in the field of forest inventory investigation. Recent improvements of point cloud processing techniques enabled efficient and precise computation of an individual tree shape parameters, such as breast-height diameter, height, and volume. However, tree species are manually specified by skilled workers to date. Previous works for automatic tree species classification mainly focused on aerial or satellite images, and few works have been reported for classification techniques using ground-based sensor data. Several candidate sensors can be considered for classification, such as RGB or multi/hyper spectral cameras. Above all candidates, we use terrestrial lidar because it can obtain high resolution point cloud in the dark forest. We selected bark texture for the classification criteria, since they clearly represent unique characteristics of each tree and do not change their appearance under seasonable variation and aged deterioration. In this paper, we propose a new method for automatic individual tree species classification based on terrestrial lidar using Convolutional Neural Network (CNN). The key component is the creation step of a depth image which well describe the characteristics of each species from a point cloud. We focus on Japanese cedar and cypress which cover the large part of domestic forest. Our experimental results demonstrate the effectiveness of our proposed method.

Statistical-QoS Guaranteed Energy Efficiency Optimization for Energy Harvesting Wireless Sensor Networks

PubMed Central

Cheng, Wenchi; Zhang, Hailin

2017-01-01

Energy harvesting, which offers a never-ending energy supply, has emerged as a prominent technology to prolong the lifetime and reduce costs for the battery-powered wireless sensor networks. However, how to improve the energy efficiency while guaranteeing the quality of service (QoS) for energy harvesting based wireless sensor networks is still an open problem. In this paper, we develop statistical delay-bounded QoS-driven power control policies to maximize the effective energy efficiency (EEE), which is defined as the spectrum efficiency under given specified QoS constraints per unit harvested energy, for energy harvesting based wireless sensor networks. For the battery-infinite wireless sensor networks, our developed QoS-driven power control policy converges to the Energy harvesting Water Filling (E-WF) scheme and the Energy harvesting Channel Inversion (E-CI) scheme under the very loose and stringent QoS constraints, respectively. For the battery-finite wireless sensor networks, our developed QoS-driven power control policy becomes the Truncated energy harvesting Water Filling (T-WF) scheme and the Truncated energy harvesting Channel Inversion (T-CI) scheme under the very loose and stringent QoS constraints, respectively. Furthermore, we evaluate the outage probabilities to theoretically analyze the performance of our developed QoS-driven power control policies. The obtained numerical results validate our analysis and show that our developed optimal power control policies can optimize the EEE over energy harvesting based wireless sensor networks. PMID:28832509

Statistical-QoS Guaranteed Energy Efficiency Optimization for Energy Harvesting Wireless Sensor Networks.

PubMed

Gao, Ya; Cheng, Wenchi; Zhang, Hailin

2017-08-23

Energy harvesting, which offers a never-ending energy supply, has emerged as a prominent technology to prolong the lifetime and reduce costs for the battery-powered wireless sensor networks. However, how to improve the energy efficiency while guaranteeing the quality of service (QoS) for energy harvesting based wireless sensor networks is still an open problem. In this paper, we develop statistical delay-bounded QoS-driven power control policies to maximize the effective energy efficiency (EEE), which is defined as the spectrum efficiency under given specified QoS constraints per unit harvested energy, for energy harvesting based wireless sensor networks. For the battery-infinite wireless sensor networks, our developed QoS-driven power control policy converges to the Energy harvesting Water Filling (E-WF) scheme and the Energy harvesting Channel Inversion (E-CI) scheme under the very loose and stringent QoS constraints, respectively. For the battery-finite wireless sensor networks, our developed QoS-driven power control policy becomes the Truncated energy harvesting Water Filling (T-WF) scheme and the Truncated energy harvesting Channel Inversion (T-CI) scheme under the very loose and stringent QoS constraints, respectively. Furthermore, we evaluate the outage probabilities to theoretically analyze the performance of our developed QoS-driven power control policies. The obtained numerical results validate our analysis and show that our developed optimal power control policies can optimize the EEE over energy harvesting based wireless sensor networks.

Experimental Modal Analysis and Dynaic Strain Fiber Bragg Gratings for Structural Health Monitoring of Composite Aerospace Structures

NASA Astrophysics Data System (ADS)

Panopoulou, A.; Fransen, S.; Gomez Molinero, V.; Kostopoulos, V.

2012-07-01

The objective of this work is to develop a new structural health monitoring system for composite aerospace structures based on dynamic response strain measurements and experimental modal analysis techniques. Fibre Bragg Grating (FBG) optical sensors were used for monitoring the dynamic response of the composite structure. The structural dynamic behaviour has been numerically simulated and experimentally verified by means of vibration testing. The hypothesis of all vibration tests was that actual damage in composites reduces their stiffness and produces the same result as mass increase produces. Thus, damage was simulated by slightly varying locally the mass of the structure at different zones. Experimental modal analysis based on the strain responses was conducted and the extracted strain mode shapes were the input for the damage detection expert system. A feed-forward back propagation neural network was the core of the damage detection system. The features-input to the neural network consisted of the strain mode shapes, extracted from the experimental modal analysis. Dedicated training and validation activities were carried out based on the experimental results. The system showed high reliability, confirmed by the ability of the neural network to recognize the size and the position of damage on the structure. The experiments were performed on a real structure i.e. a lightweight antenna sub- reflector, manufactured and tested at EADS CASA ESPACIO. An integrated FBG sensor network, based on the advantage of multiplexing, was mounted on the structure with optimum topology. Numerical simulation of both structures was used as a support tool at all the steps of the work. Potential applications for the proposed system are during ground qualification extensive tests of space structures and during the mission as modal analysis tool on board, being able via the FBG responses to identify a potential failure.

Autonomous distributed self-organization for mobile wireless sensor networks.

PubMed

Wen, Chih-Yu; Tang, Hung-Kai

2009-01-01

This paper presents an adaptive combined-metrics-based clustering scheme for mobile wireless sensor networks, which manages the mobile sensors by utilizing the hierarchical network structure and allocates network resources efficiently A local criteria is used to help mobile sensors form a new cluster or join a current cluster. The messages transmitted during hierarchical clustering are applied to choose distributed gateways such that communication for adjacent clusters and distributed topology control can be achieved. In order to balance the load among clusters and govern the topology change, a cluster reformation scheme using localized criterions is implemented. The proposed scheme is simulated and analyzed to abstract the network behaviors in a number of settings. The experimental results show that the proposed algorithm provides efficient network topology management and achieves high scalability in mobile sensor networks.

Distance-Based and Low Energy Adaptive Clustering Protocol for Wireless Sensor Networks

PubMed Central

Gani, Abdullah; Anisi, Mohammad Hossein; Ab Hamid, Siti Hafizah; Akhunzada, Adnan; Khan, Muhammad Khurram

2016-01-01

A wireless sensor network (WSN) comprises small sensor nodes with limited energy capabilities. The power constraints of WSNs necessitate efficient energy utilization to extend the overall network lifetime of these networks. We propose a distance-based and low-energy adaptive clustering (DISCPLN) protocol to streamline the green issue of efficient energy utilization in WSNs. We also enhance our proposed protocol into the multi-hop-DISCPLN protocol to increase the lifetime of the network in terms of high throughput with minimum delay time and packet loss. We also propose the mobile-DISCPLN protocol to maintain the stability of the network. The modelling and comparison of these protocols with their corresponding benchmarks exhibit promising results. PMID:27658194

Self-Tuning Method for Increased Obstacle Detection Reliability Based on Internet of Things LiDAR Sensor Models

PubMed Central

2018-01-01

On-chip LiDAR sensors for vehicle collision avoidance are a rapidly expanding area of research and development. The assessment of reliable obstacle detection using data collected by LiDAR sensors has become a key issue that the scientific community is actively exploring. The design of a self-tuning methodology and its implementation are presented in this paper, to maximize the reliability of LiDAR sensors network for obstacle detection in the ‘Internet of Things’ (IoT) mobility scenarios. The Webots Automobile 3D simulation tool for emulating sensor interaction in complex driving environments is selected in order to achieve that objective. Furthermore, a model-based framework is defined that employs a point-cloud clustering technique, and an error-based prediction model library that is composed of a multilayer perceptron neural network, and k-nearest neighbors and linear regression models. Finally, a reinforcement learning technique, specifically a Q-learning method, is implemented to determine the number of LiDAR sensors that are required to increase sensor reliability for obstacle localization tasks. In addition, a IoT driving assistance user scenario, connecting a five LiDAR sensor network is designed and implemented to validate the accuracy of the computational intelligence-based framework. The results demonstrated that the self-tuning method is an appropriate strategy to increase the reliability of the sensor network while minimizing detection thresholds. PMID:29748521

Self-Tuning Method for Increased Obstacle Detection Reliability Based on Internet of Things LiDAR Sensor Models.

PubMed

Castaño, Fernando; Beruvides, Gerardo; Villalonga, Alberto; Haber, Rodolfo E

2018-05-10

On-chip LiDAR sensors for vehicle collision avoidance are a rapidly expanding area of research and development. The assessment of reliable obstacle detection using data collected by LiDAR sensors has become a key issue that the scientific community is actively exploring. The design of a self-tuning methodology and its implementation are presented in this paper, to maximize the reliability of LiDAR sensors network for obstacle detection in the 'Internet of Things' (IoT) mobility scenarios. The Webots Automobile 3D simulation tool for emulating sensor interaction in complex driving environments is selected in order to achieve that objective. Furthermore, a model-based framework is defined that employs a point-cloud clustering technique, and an error-based prediction model library that is composed of a multilayer perceptron neural network, and k-nearest neighbors and linear regression models. Finally, a reinforcement learning technique, specifically a Q-learning method, is implemented to determine the number of LiDAR sensors that are required to increase sensor reliability for obstacle localization tasks. In addition, a IoT driving assistance user scenario, connecting a five LiDAR sensor network is designed and implemented to validate the accuracy of the computational intelligence-based framework. The results demonstrated that the self-tuning method is an appropriate strategy to increase the reliability of the sensor network while minimizing detection thresholds.

Intelligent route surveillance

NASA Astrophysics Data System (ADS)

Schoemaker, Robin; Sandbrink, Rody; van Voorthuijsen, Graeme

2009-05-01

Intelligence on abnormal and suspicious behaviour along roads in operational domains is extremely valuable for countering the IED (Improvised Explosive Device) threat. Local sensor networks at strategic spots can gather data for continuous monitoring of daily vehicle activity. Unattended intelligent ground sensor networks use simple sensing nodes, e.g. seismic, magnetic, radar, or acoustic, or combinations of these in one housing. The nodes deliver rudimentary data at any time to be processed with software that filters out the required information. At TNO (Netherlands Organisation for Applied Scientific Research) research has started on how to equip a sensor network with data analysis software to determine whether behaviour is suspicious or not. Furthermore, the nodes should be expendable, if necessary, and be small in size such that they are hard to detect by adversaries. The network should be self-configuring and self-sustaining and should be reliable, efficient, and effective during operational tasks - especially route surveillance - as well as robust in time and space. If data from these networks are combined with data from other remote sensing devices (e.g. UAVs (Unmanned Aerial Vehicles)/aerostats), an even more accurate assessment of the tactical situation is possible. This paper shall focus on the concepts of operation towards a working intelligent route surveillance (IRS) research demonstrator network for monitoring suspicious behaviour in IED sensitive domains.

Hail detection algorithm for the Global Precipitation Measuring mission core satellite sensors

NASA Astrophysics Data System (ADS)

Mroz, Kamil; Battaglia, Alessandro; Lang, Timothy J.; Tanelli, Simone; Cecil, Daniel J.; Tridon, Frederic

2017-04-01

By exploiting an abundant number of extreme storms observed simultaneously by the Global Precipitation Measurement (GPM) mission core satellite's suite of sensors and by the ground-based S-band Next-Generation Radar (NEXRAD) network over continental US, proxies for the identification of hail are developed based on the GPM core satellite observables. The full capabilities of the GPM observatory are tested by analyzing more than twenty observables and adopting the hydrometeor classification based on ground-based polarimetric measurements as truth. The proxies have been tested using the Critical Success Index (CSI) as a verification measure. The hail detection algorithm based on the mean Ku reflectivity in the mixed-phase layer performs the best, out of all considered proxies (CSI of 45%). Outside the Dual frequency Precipitation Radar (DPR) swath, the Polarization Corrected Temperature at 18.7 GHz shows the greatest potential for hail detection among all GMI channels (CSI of 26% at a threshold value of 261 K). When dual variable proxies are considered, the combination involving the mixed-phase reflectivity values at both Ku and Ka-bands outperforms all the other proxies, with a CSI of 49%. The best-performing radar-radiometer algorithm is based on the mixed-phase reflectivity at Ku-band and on the brightness temperature (TB) at 10.7 GHz (CSI of 46%). When only radiometric data are available, the algorithm based on the TBs at 36.6 and 166 GHz is the most efficient, with a CSI of 27.5%.

Connected Dominating Set Based Topology Control in Wireless Sensor Networks

ERIC Educational Resources Information Center

He, Jing

2012-01-01

Wireless Sensor Networks (WSNs) are now widely used for monitoring and controlling of systems where human intervention is not desirable or possible. Connected Dominating Sets (CDSs) based topology control in WSNs is one kind of hierarchical method to ensure sufficient coverage while reducing redundant connections in a relatively crowded network.…

A Mobile Sensor Network System for Monitoring of Unfriendly Environments.

PubMed

Song, Guangming; Zhou, Yaoxin; Ding, Fei; Song, Aiguo

2008-11-14

Observing microclimate changes is one of the most popular applications of wireless sensor networks. However, some target environments are often too dangerous or inaccessible to humans or large robots and there are many challenges for deploying and maintaining wireless sensor networks in those unfriendly environments. This paper presents a mobile sensor network system for solving this problem. The system architecture, the mobile node design, the basic behaviors and advanced network capabilities have been investigated respectively. A wheel-based robotic node architecture is proposed here that can add controlled mobility to wireless sensor networks. A testbed including some prototype nodes has also been created for validating the basic functions of the proposed mobile sensor network system. Motion performance tests have been done to get the positioning errors and power consumption model of the mobile nodes. Results of the autonomous deployment experiment show that the mobile nodes can be distributed evenly into the previously unknown environments. It provides powerful support for network deployment and maintenance and can ensure that the sensor network will work properly in unfriendly environments.

A Novel Dual Separate Paths (DSP) Algorithm Providing Fault-Tolerant Communication for Wireless Sensor Networks.

PubMed

Tien, Nguyen Xuan; Kim, Semog; Rhee, Jong Myung; Park, Sang Yoon

2017-07-25

Fault tolerance has long been a major concern for sensor communications in fault-tolerant cyber physical systems (CPSs). Network failure problems often occur in wireless sensor networks (WSNs) due to various factors such as the insufficient power of sensor nodes, the dislocation of sensor nodes, the unstable state of wireless links, and unpredictable environmental interference. Fault tolerance is thus one of the key requirements for data communications in WSN applications. This paper proposes a novel path redundancy-based algorithm, called dual separate paths (DSP), that provides fault-tolerant communication with the improvement of the network traffic performance for WSN applications, such as fault-tolerant CPSs. The proposed DSP algorithm establishes two separate paths between a source and a destination in a network based on the network topology information. These paths are node-disjoint paths and have optimal path distances. Unicast frames are delivered from the source to the destination in the network through the dual paths, providing fault-tolerant communication and reducing redundant unicast traffic for the network. The DSP algorithm can be applied to wired and wireless networks, such as WSNs, to provide seamless fault-tolerant communication for mission-critical and life-critical applications such as fault-tolerant CPSs. The analyzed and simulated results show that the DSP-based approach not only provides fault-tolerant communication, but also improves network traffic performance. For the case study in this paper, when the DSP algorithm was applied to high-availability seamless redundancy (HSR) networks, the proposed DSP-based approach reduced the network traffic by 80% to 88% compared with the standard HSR protocol, thus improving network traffic performance.

A miniature disposable radio (MiDR) for unattended ground sensor systems (UGSS) and munitions

NASA Astrophysics Data System (ADS)

Wells, Jeffrey S.; Wurth, Timothy J.

2004-09-01

Unattended and tactical sensors are used by the U.S. Army"s Future Combat Systems (FCS) and Objective Force Warrior (OFW) to detect and identify enemy targets on the battlefield. The radios being developed as part of the Networked Sensors for the Objective Force (NSOF) are too costly and too large to deploy in missions requiring throw-away hardware. A low-cost miniature radio is required to satisfy the communication needs for unmanned sensor and munitions systems that are deployed in a disposable manner. A low cost miniature disposable communications suite is leveraged using the commercial off-the-shelf market and employing a miniature universal frequency conversion architecture. Employing the technology of universal frequency architecture in a commercially available communication unit delivers a robust disposable transceiver that can operate at virtually any frequency. A low-cost RF communication radio has applicability in the commercial, homeland defense, military, and other government markets. Specific uses include perimeter monitoring, infrastructure defense, unattended ground sensors, tactical sensors, and border patrol. This paper describes a low-cost radio architecture to meet the requirements of throw-away radios that can be easily modified or tuned to virtually any operating frequency required for the specific mission.

Software Defined Networking for Improved Wireless Sensor Network Management: A Survey

PubMed Central

Ndiaye, Musa; Hancke, Gerhard P.; Abu-Mahfouz, Adnan M.

2017-01-01

Wireless sensor networks (WSNs) are becoming increasingly popular with the advent of the Internet of things (IoT). Various real-world applications of WSNs such as in smart grids, smart farming and smart health would require a potential deployment of thousands or maybe hundreds of thousands of sensor nodes/actuators. To ensure proper working order and network efficiency of such a network of sensor nodes, an effective WSN management system has to be integrated. However, the inherent challenges of WSNs such as sensor/actuator heterogeneity, application dependency and resource constraints have led to challenges in implementing effective traditional WSN management. This difficulty in management increases as the WSN becomes larger. Software Defined Networking (SDN) provides a promising solution in flexible management WSNs by allowing the separation of the control logic from the sensor nodes/actuators. The advantage with this SDN-based management in WSNs is that it enables centralized control of the entire WSN making it simpler to deploy network-wide management protocols and applications on demand. This paper highlights some of the recent work on traditional WSN management in brief and reviews SDN-based management techniques for WSNs in greater detail while drawing attention to the advantages that SDN brings to traditional WSN management. This paper also investigates open research challenges in coming up with mechanisms for flexible and easier SDN-based WSN configuration and management. PMID:28471390

Software Defined Networking for Improved Wireless Sensor Network Management: A Survey.

PubMed

Ndiaye, Musa; Hancke, Gerhard P; Abu-Mahfouz, Adnan M

2017-05-04

Wireless sensor networks (WSNs) are becoming increasingly popular with the advent of the Internet of things (IoT). Various real-world applications of WSNs such as in smart grids, smart farming and smart health would require a potential deployment of thousands or maybe hundreds of thousands of sensor nodes/actuators. To ensure proper working order and network efficiency of such a network of sensor nodes, an effective WSN management system has to be integrated. However, the inherent challenges of WSNs such as sensor/actuator heterogeneity, application dependency and resource constraints have led to challenges in implementing effective traditional WSN management. This difficulty in management increases as the WSN becomes larger. Software Defined Networking (SDN) provides a promising solution in flexible management WSNs by allowing the separation of the control logic from the sensor nodes/actuators. The advantage with this SDN-based management in WSNs is that it enables centralized control of the entire WSN making it simpler to deploy network-wide management protocols and applications on demand. This paper highlights some of the recent work on traditional WSN management in brief and reviews SDN-based management techniques for WSNs in greater detail while drawing attention to the advantages that SDN brings to traditional WSN management. This paper also investigates open research challenges in coming up with mechanisms for flexible and easier SDN-based WSN configuration and management.

Real-time synchronization of wireless sensor network by 1-PPS signal

NASA Astrophysics Data System (ADS)

Giammarini, Marco; Pieralisi, Marco; Isidori, Daniela; Concettoni, Enrico; Cristalli, Cristina; Fioravanti, Matteo

2015-05-01

The use of wireless sensor networks with different nodes is desirable in a smart environment, because the network setting up and installation on preexisting structures can be done without a fixed cabled infrastructure. The flexibility of the monitoring system is fundamental where the use of a considerable quantity of cables could compromise the normal exercise, could affect the quality of acquired signal and finally increase the cost of the materials and installation. The network is composed of several intelligent "nodes", which acquires data from different kind of sensors, and then store or transmit them to a central elaboration unit. The synchronization of data acquisition is the core of the real-time wireless sensor network (WSN). In this paper, we present a comparison between different methods proposed by literature for the real-time acquisition in a WSN and finally we present our solution based on 1-Pulse-Per-Second (1-PPS) signal generated by GPS systems. The sensor node developed is a small-embedded system based on ARM microcontroller that manages the acquisition, the timing and the post-processing of the data. The communications between the sensors and the master based on IEEE 802.15.4 protocol and managed by dedicated software. Finally, we present the preliminary results obtained on a 3 floor building simulator with the wireless sensors system developed.

A Novel Deployment Scheme Based on Three-Dimensional Coverage Model for Wireless Sensor Networks

PubMed Central

Xiao, Fu; Yang, Yang; Wang, Ruchuan; Sun, Lijuan

2014-01-01

Coverage pattern and deployment strategy are directly related to the optimum allocation of limited resources for wireless sensor networks, such as energy of nodes, communication bandwidth, and computing power, and quality improvement is largely determined by these for wireless sensor networks. A three-dimensional coverage pattern and deployment scheme are proposed in this paper. Firstly, by analyzing the regular polyhedron models in three-dimensional scene, a coverage pattern based on cuboids is proposed, and then relationship between coverage and sensor nodes' radius is deduced; also the minimum number of sensor nodes to maintain network area's full coverage is calculated. At last, sensor nodes are deployed according to the coverage pattern after the monitor area is subdivided into finite 3D grid. Experimental results show that, compared with traditional random method, sensor nodes number is reduced effectively while coverage rate of monitor area is ensured using our coverage pattern and deterministic deployment scheme. PMID:25045747

Simple Random Sampling-Based Probe Station Selection for Fault Detection in Wireless Sensor Networks

PubMed Central

Huang, Rimao; Qiu, Xuesong; Rui, Lanlan

2011-01-01

Fault detection for wireless sensor networks (WSNs) has been studied intensively in recent years. Most existing works statically choose the manager nodes as probe stations and probe the network at a fixed frequency. This straightforward solution leads however to several deficiencies. Firstly, by only assigning the fault detection task to the manager node the whole network is out of balance, and this quickly overloads the already heavily burdened manager node, which in turn ultimately shortens the lifetime of the whole network. Secondly, probing with a fixed frequency often generates too much useless network traffic, which results in a waste of the limited network energy. Thirdly, the traditional algorithm for choosing a probing node is too complicated to be used in energy-critical wireless sensor networks. In this paper, we study the distribution characters of the fault nodes in wireless sensor networks, validate the Pareto principle that a small number of clusters contain most of the faults. We then present a Simple Random Sampling-based algorithm to dynamic choose sensor nodes as probe stations. A dynamic adjusting rule for probing frequency is also proposed to reduce the number of useless probing packets. The simulation experiments demonstrate that the algorithm and adjusting rule we present can effectively prolong the lifetime of a wireless sensor network without decreasing the fault detected rate. PMID:22163789

Simple random sampling-based probe station selection for fault detection in wireless sensor networks.

PubMed

Huang, Rimao; Qiu, Xuesong; Rui, Lanlan

2011-01-01

Fault detection for wireless sensor networks (WSNs) has been studied intensively in recent years. Most existing works statically choose the manager nodes as probe stations and probe the network at a fixed frequency. This straightforward solution leads however to several deficiencies. Firstly, by only assigning the fault detection task to the manager node the whole network is out of balance, and this quickly overloads the already heavily burdened manager node, which in turn ultimately shortens the lifetime of the whole network. Secondly, probing with a fixed frequency often generates too much useless network traffic, which results in a waste of the limited network energy. Thirdly, the traditional algorithm for choosing a probing node is too complicated to be used in energy-critical wireless sensor networks. In this paper, we study the distribution characters of the fault nodes in wireless sensor networks, validate the Pareto principle that a small number of clusters contain most of the faults. We then present a Simple Random Sampling-based algorithm to dynamic choose sensor nodes as probe stations. A dynamic adjusting rule for probing frequency is also proposed to reduce the number of useless probing packets. The simulation experiments demonstrate that the algorithm and adjusting rule we present can effectively prolong the lifetime of a wireless sensor network without decreasing the fault detected rate.

VLF long-range lightning location using the arrival time difference technique (ATD)

NASA Technical Reports Server (NTRS)

Ierkic, H. Mario

1996-01-01

A new network of VLF receiving systems is currently being developed in the USA to support NASA's Tropical Rain Measuring Mission (TRMM). The new network will be deployed in the east coast of the US, including Puerto Rico, and will be operational in late 1995. The system should give affordable, near real-time, accurate lightning locating capabilities at long ranges and with extended coverage. It is based on the Arrival Time Difference (ATD) method of Lee (1986; 1990). The ATD technique is based on the estimation of the time of arrival of sferics detected over an 18 kHz bandwith. The ground system results will be compared and complemented with satellite optical measurements gathered with the already operational Optical Transient Detector (OTD) instrument and in due course with its successor the Lightning Imaging Sensor (LIS). Lightning observations are important to understand atmospheric electrification phenomena, discharge processes, associated phenomena on earth (e.g. whistlers, explosive Spread-F) and other planets. In addition, lightning is a conspicuous indicator of atmospheric activity whose potential is just beginning to be recognized and utilized. On more prosaic grounds, lightning observations are important for protection of life, property and services.

A neural network-based estimator for the mixture ratio of the Space Shuttle Main Engine

NASA Astrophysics Data System (ADS)

Guo, T. H.; Musgrave, J.

1992-11-01

In order to properly utilize the available fuel and oxidizer of a liquid propellant rocket engine, the mixture ratio is closed loop controlled during main stage (65 percent - 109 percent power) operation. However, because of the lack of flight-capable instrumentation for measuring mixture ratio, the value of mixture ratio in the control loop is estimated using available sensor measurements such as the combustion chamber pressure and the volumetric flow, and the temperature and pressure at the exit duct on the low pressure fuel pump. This estimation scheme has two limitations. First, the estimation formula is based on an empirical curve fitting which is accurate only within a narrow operating range. Second, the mixture ratio estimate relies on a few sensor measurements and loss of any of these measurements will make the estimate invalid. In this paper, we propose a neural network-based estimator for the mixture ratio of the Space Shuttle Main Engine. The estimator is an extension of a previously developed neural network based sensor failure detection and recovery algorithm (sensor validation). This neural network uses an auto associative structure which utilizes the redundant information of dissimilar sensors to detect inconsistent measurements. Two approaches have been identified for synthesizing mixture ratio from measurement data using a neural network. The first approach uses an auto associative neural network for sensor validation which is modified to include the mixture ratio as an additional output. The second uses a new network for the mixture ratio estimation in addition to the sensor validation network. Although mixture ratio is not directly measured in flight, it is generally available in simulation and in test bed firing data from facility measurements of fuel and oxidizer volumetric flows. The pros and cons of these two approaches will be discussed in terms of robustness to sensor failures and accuracy of the estimate during typical transients using simulation data.

A neural network-based estimator for the mixture ratio of the Space Shuttle Main Engine

NASA Technical Reports Server (NTRS)

Guo, T. H.; Musgrave, J.

1992-01-01

In order to properly utilize the available fuel and oxidizer of a liquid propellant rocket engine, the mixture ratio is closed loop controlled during main stage (65 percent - 109 percent power) operation. However, because of the lack of flight-capable instrumentation for measuring mixture ratio, the value of mixture ratio in the control loop is estimated using available sensor measurements such as the combustion chamber pressure and the volumetric flow, and the temperature and pressure at the exit duct on the low pressure fuel pump. This estimation scheme has two limitations. First, the estimation formula is based on an empirical curve fitting which is accurate only within a narrow operating range. Second, the mixture ratio estimate relies on a few sensor measurements and loss of any of these measurements will make the estimate invalid. In this paper, we propose a neural network-based estimator for the mixture ratio of the Space Shuttle Main Engine. The estimator is an extension of a previously developed neural network based sensor failure detection and recovery algorithm (sensor validation). This neural network uses an auto associative structure which utilizes the redundant information of dissimilar sensors to detect inconsistent measurements. Two approaches have been identified for synthesizing mixture ratio from measurement data using a neural network. The first approach uses an auto associative neural network for sensor validation which is modified to include the mixture ratio as an additional output. The second uses a new network for the mixture ratio estimation in addition to the sensor validation network. Although mixture ratio is not directly measured in flight, it is generally available in simulation and in test bed firing data from facility measurements of fuel and oxidizer volumetric flows. The pros and cons of these two approaches will be discussed in terms of robustness to sensor failures and accuracy of the estimate during typical transients using simulation data.

Development of Arduino based wireless control system

NASA Astrophysics Data System (ADS)

Sun, Zhuoxiong; Dyke, Shirley J.; Pena, Francisco; Wilbee, Alana

2015-03-01

Over the past few decades, considerable attention has been given to structural control systems to mitigate structural vibration under natural hazards such as earthquakes and extreme weather conditions. Traditional wired structural control systems often employ a large amount of cables for communication among sensors, controllers and actuators. In such systems, implementation of wired sensors is usually quite complicated and expensive, especially on large scale structures such as bridges and buildings. To reduce the laborious installation and maintenance cost, wireless control systems (WCSs) are considered as a novel approach for structural vibration control. In this work, a WCS is developed based on the open source Arduino platform. Low cost, low power wireless sensing and communication components are built on the Arduino platform. Structural control algorithms are embedded within the wireless sensor board for feedback control. The developed WCS is first validated through a series of tests. Next, numerical simulations are performed simulating wireless control of a 3-story shear structure equipped with a semi-active control device (MR damper). Finally, experimental studies are carried out implementing the WCS on the 3-story shear structure in the Intelligent Infrastructure Systems Lab (IISL). A hydraulic shake table is used to generate seismic ground motions. The control performance is evaluated with the impact of modeling uncertainties, measurement noises as well as time delay and data loss induced by the wireless network. The developed WCS is shown to be effective in controlling structural vibrations under several historical earthquake ground motions.

Performance and analysis of MAC protocols based on application

NASA Astrophysics Data System (ADS)

Yadav, Ravi; Daniel, A. K.

2018-04-01

Wireless Sensor Network is one of the rapid emerging technology in recent decades. It covers large application area as civilian and military. Wireless Sensor Network primary consists of sensor nodes having low-power, low cost and multifunctional activities to collaborates and communicates via wireless medium. The deployment of sensor nodes are adhoc in nature, so sensor nodes are auto organize themselves in such a way to communicate with each other. The characteristics make more challenging areas on WSNs. This paper gives overview about characteristics of WSNs, Architecture and Contention Based MAC protocol. The paper present analysis of various protocol based on performance.

Distributed estimation for adaptive sensor selection in wireless sensor networks

NASA Astrophysics Data System (ADS)

Mahmoud, Magdi S.; Hassan Hamid, Matasm M.

2014-05-01

Wireless sensor networks (WSNs) are usually deployed for monitoring systems with the distributed detection and estimation of sensors. Sensor selection in WSNs is considered for target tracking. A distributed estimation scenario is considered based on the extended information filter. A cost function using the geometrical dilution of precision measure is derived for active sensor selection. A consensus-based estimation method is proposed in this paper for heterogeneous WSNs with two types of sensors. The convergence properties of the proposed estimators are analyzed under time-varying inputs. Accordingly, a new adaptive sensor selection (ASS) algorithm is presented in which the number of active sensors is adaptively determined based on the absolute local innovations vector. Simulation results show that the tracking accuracy of the ASS is comparable to that of the other algorithms.

Wireless Networks under a Backoff Attack: A Game Theoretical Perspective.

PubMed

Parras, Juan; Zazo, Santiago

2018-01-30

We study a wireless sensor network using CSMA/CA in the MAC layer under a backoff attack: some of the sensors of the network are malicious and deviate from the defined contention mechanism. We use Bianchi's network model to study the impact of the malicious sensors on the total network throughput, showing that it causes the throughput to be unfairly distributed among sensors. We model this conflict using game theory tools, where each sensor is a player. We obtain analytical solutions and propose an algorithm, based on Regret Matching, to learn the equilibrium of the game with an arbitrary number of players. Our approach is validated via simulations, showing that our theoretical predictions adjust to reality.

Challenges in complementing data from ground-based sensors with satellite-derived products to measure ecological changes in relation to climate – lessons from temperate wetland-upland landscapes

USGS Publications Warehouse

Gallant, Alisa L.; Sadinski, Walter J.; Brown, Jesslyn F.; Senay, Gabriel B.; Roth, Mark F.

2018-01-01

Assessing climate-related ecological changes across spatiotemporal scales meaningful to resource managers is challenging because no one method reliably produces essential data at both fine and broad scales. We recently confronted such challenges while integrating data from ground- and satellite-based sensors for an assessment of four wetland-rich study areas in the U.S. Midwest. We examined relations between temperature and precipitation and a set of variables measured on the ground at individual wetlands and another set measured via satellite sensors within surrounding 4 km2 landscape blocks. At the block scale, we used evapotranspiration and vegetation greenness as remotely sensed proxies for water availability and to estimate seasonal photosynthetic activity. We used sensors on the ground to coincidentally measure surface-water availability and amphibian calling activity at individual wetlands within blocks. Responses of landscape blocks generally paralleled changes in conditions measured on the ground, but the latter were more dynamic, and changes in ecological conditions on the ground that were critical for biota were not always apparent in measurements of related parameters in blocks. Here, we evaluate the effectiveness of decisions and assumptions we made in applying the remotely sensed data for the assessment and the value of integrating observations across scales, sensors, and disciplines.

Challenges in Complementing Data from Ground-Based Sensors with Satellite-Derived Products to Measure Ecological Changes in Relation to Climate—Lessons from Temperate Wetland-Upland Landscapes

PubMed Central

Sadinski, Walt; Senay, Gabriel B.

2018-01-01

Assessing climate-related ecological changes across spatiotemporal scales meaningful to resource managers is challenging because no one method reliably produces essential data at both fine and broad scales. We recently confronted such challenges while integrating data from ground- and satellite-based sensors for an assessment of four wetland-rich study areas in the U.S. Midwest. We examined relations between temperature and precipitation and a set of variables measured on the ground at individual wetlands and another set measured via satellite sensors within surrounding 4 km2 landscape blocks. At the block scale, we used evapotranspiration and vegetation greenness as remotely sensed proxies for water availability and to estimate seasonal photosynthetic activity. We used sensors on the ground to coincidentally measure surface-water availability and amphibian calling activity at individual wetlands within blocks. Responses of landscape blocks generally paralleled changes in conditions measured on the ground, but the latter were more dynamic, and changes in ecological conditions on the ground that were critical for biota were not always apparent in measurements of related parameters in blocks. Here, we evaluate the effectiveness of decisions and assumptions we made in applying the remotely sensed data for the assessment and the value of integrating observations across scales, sensors, and disciplines. PMID:29547531

Research Trends in Wireless Visual Sensor Networks When Exploiting Prioritization

PubMed Central

Costa, Daniel G.; Guedes, Luiz Affonso; Vasques, Francisco; Portugal, Paulo

2015-01-01

The development of wireless sensor networks for control and monitoring functions has created a vibrant investigation scenario, where many critical topics, such as communication efficiency and energy consumption, have been investigated in the past few years. However, when sensors are endowed with low-power cameras for visual monitoring, a new scope of challenges is raised, demanding new research efforts. In this context, the resource-constrained nature of sensor nodes has demanded the use of prioritization approaches as a practical mechanism to lower the transmission burden of visual data over wireless sensor networks. Many works in recent years have considered local-level prioritization parameters to enhance the overall performance of those networks, but global-level policies can potentially achieve better results in terms of visual monitoring efficiency. In this paper, we make a broad review of some recent works on priority-based optimizations in wireless visual sensor networks. Moreover, we envisage some research trends when exploiting prioritization, potentially fostering the development of promising optimizations for wireless sensor networks composed of visual sensors. PMID:25599425

A uniform energy consumption algorithm for wireless sensor and actuator networks based on dynamic polling point selection.

PubMed

Li, Shuo; Peng, Jun; Liu, Weirong; Zhu, Zhengfa; Lin, Kuo-Chi

2013-12-19

Recent research has indicated that using the mobility of the actuator in wireless sensor and actuator networks (WSANs) to achieve mobile data collection can greatly increase the sensor network lifetime. However, mobile data collection may result in unacceptable collection delays in the network if the path of the actuator is too long. Because real-time network applications require meeting data collection delay constraints, planning the path of the actuator is a very important issue to balance the prolongation of the network lifetime and the reduction of the data collection delay. In this paper, a multi-hop routing mobile data collection algorithm is proposed based on dynamic polling point selection with delay constraints to address this issue. The algorithm can actively update the selection of the actuator's polling points according to the sensor nodes' residual energies and their locations while also considering the collection delay constraint. It also dynamically constructs the multi-hop routing trees rooted by these polling points to balance the sensor node energy consumption and the extension of the network lifetime. The effectiveness of the algorithm is validated by simulation.

Standards-Based Wireless Sensor Networking Protocols for Spaceflight Applications

NASA Technical Reports Server (NTRS)

Wagner, Raymond S.

2010-01-01

Wireless sensor networks (WSNs) have the capacity to revolutionize data gathering in both spaceflight and terrestrial applications. WSNs provide a huge advantage over traditional, wired instrumentation since they do not require wiring trunks to connect sensors to a central hub. This allows for easy sensor installation in hard to reach locations, easy expansion of the number of sensors or sensing modalities, and reduction in both system cost and weight. While this technology offers unprecedented flexibility and adaptability, implementing it in practice is not without its difficulties. Recent advances in standards-based WSN protocols for industrial control applications have come a long way to solving many of the challenges facing practical WSN deployments. In this paper, we will overview two of the more promising candidates - WirelessHART from the HART Communication Foundation and ISA100.11a from the International Society of Automation - and present the architecture for a new standards-based sensor node for networking and applications research.

An Optimized Autonomous Space In-situ Sensorweb (OASIS) for Volcano Monitoring

NASA Astrophysics Data System (ADS)

Song, W.; Shirazi, B.; Lahusen, R.; Chien, S.; Kedar, S.; Webb, F.

2006-12-01

In response to NASA's announced requirement for Earth hazard monitoring sensor-web technology, we are developing a prototype real-time Optimized Autonomous Space In-situ Sensorweb. The prototype will be focused on volcano hazard monitoring at Mount St. Helens, which has been in continuous eruption since October 2004. The system is designed to be flexible and easily configurable for many other applications as well. The primary goals of the project are: 1) integrating complementary space (i.e., Earth Observing One (EO- 1) satellite) and in-situ (ground-based) elements into an interactive, autonomous sensor-web; 2) advancing sensor-web power and communication resource management technology; and 3) enabling scalability for seamless infusion of future space and in-situ assets into the sensor-web. To meet these goals, we are developing: 1) a test-bed in-situ array with smart sensor nodes capable of making autonomous data acquisition decisions; 2) efficient self-organization algorithm of sensor-web topology to support efficient data communication and command control; 3) smart bandwidth allocation algorithms in which sensor nodes autonomously determine packet priorities based on mission needs and local bandwidth information in real- time; and 4) remote network management and reprogramming tools. The space and in-situ control components of the system will be integrated such that each element is capable of triggering the other. Sensor-web data acquisition and dissemination will be accomplished through the use of SensorML language standards for geospatial information. The three-year project will demonstrate end-to-end system performance with the in-situ test-bed at Mount St. Helens and NASA's EO-1 platform.

Energy optimization in mobile sensor networks

NASA Astrophysics Data System (ADS)

Yu, Shengwei

Mobile sensor networks are considered to consist of a network of mobile robots, each of which has computation, communication and sensing capabilities. Energy efficiency is a critical issue in mobile sensor networks, especially when mobility (i.e., locomotion control), routing (i.e., communications) and sensing are unique characteristics of mobile robots for energy optimization. This thesis focuses on the problem of energy optimization of mobile robotic sensor networks, and the research results can be extended to energy optimization of a network of mobile robots that monitors the environment, or a team of mobile robots that transports materials from stations to stations in a manufacturing environment. On the energy optimization of mobile robotic sensor networks, our research focuses on the investigation and development of distributed optimization algorithms to exploit the mobility of robotic sensor nodes for network lifetime maximization. In particular, the thesis studies these five problems: 1. Network-lifetime maximization by controlling positions of networked mobile sensor robots based on local information with distributed optimization algorithms; 2. Lifetime maximization of mobile sensor networks with energy harvesting modules; 3. Lifetime maximization using joint design of mobility and routing; 4. Optimal control for network energy minimization; 5. Network lifetime maximization in mobile visual sensor networks. In addressing the first problem, we consider only the mobility strategies of the robotic relay nodes in a mobile sensor network in order to maximize its network lifetime. By using variable substitutions, the original problem is converted into a convex problem, and a variant of the sub-gradient method for saddle-point computation is developed for solving this problem. An optimal solution is obtained by the method. Computer simulations show that mobility of robotic sensors can significantly prolong the lifetime of the whole robotic sensor network while consuming negligible amount of energy for mobility cost. For the second problem, the problem is extended to accommodate mobile robotic nodes with energy harvesting capability, which makes it a non-convex optimization problem. The non-convexity issue is tackled by using the existing sequential convex approximation method, based on which we propose a novel procedure of modified sequential convex approximation that has fast convergence speed. For the third problem, the proposed procedure is used to solve another challenging non-convex problem, which results in utilizing mobility and routing simultaneously in mobile robotic sensor networks to prolong the network lifetime. The results indicate that joint design of mobility and routing has an edge over other methods in prolonging network lifetime, which is also the justification for the use of mobility in mobile sensor networks for energy efficiency purpose. For the fourth problem, we include the dynamics of the robotic nodes in the problem by modeling the networked robotic system using hybrid systems theory. A novel distributed method for the networked hybrid system is used to solve the optimal moving trajectories for robotic nodes and optimal network links, which are not answered by previous approaches. Finally, the fact that mobility is more effective in prolonging network lifetime for a data-intensive network leads us to apply our methods to study mobile visual sensor networks, which are useful in many applications. We investigate the joint design of mobility, data routing, and encoding power to help improving the video quality while maximizing the network lifetime. This study leads to a better understanding of the role mobility can play in data-intensive surveillance sensor networks.

Two-layer wireless distributed sensor/control network based on RF

NASA Astrophysics Data System (ADS)

Feng, Li; Lin, Yuchi; Zhou, Jingjing; Dong, Guimei; Xia, Guisuo

2006-11-01

A project of embedded Wireless Distributed Sensor/Control Network (WDSCN) based on RF is presented after analyzing the disadvantages of traditional measure and control system. Because of high-cost and complexity, such wireless techniques as Bluetooth and WiFi can't meet the needs of WDSCN. The two-layer WDSCN is designed based on RF technique, which operates in the ISM free frequency channel with low power and high transmission speed. Also the network is low cost, portable and moveable, integrated with the technologies of computer network, sensor, microprocessor and wireless communications. The two-layer network topology is selected in the system; a simple but efficient self-organization net protocol is designed to fit the periodic data collection, event-driven and store-and-forward. Furthermore, adaptive frequency hopping technique is adopted for anti-jamming apparently. The problems about power reduction and synchronization of data in wireless system are solved efficiently. Based on the discussion above, a measure and control network is set up to control such typical instruments and sensors as temperature sensor and signal converter, collect data, and monitor environmental parameters around. This system works well in different rooms. Experiment results show that the system provides an efficient solution to WDSCN through wireless links, with high efficiency, low power, high stability, flexibility and wide working range.

Landsat 7 thermal-IR image sharpening using an artificial neural network and sensor model

USGS Publications Warehouse

Lemeshewsky, G.P.; Schowengerdt, R.A.; ,

2001-01-01

The enhanced thematic mapper (plus) (ETM+) instrument on Landsat 7 shares the same basic design as the TM sensors on Landsats 4 and 5, with some significant improvements. In common are six multispectral bands with a 30-m ground-projected instantaneous field of view (GIFOV). However, the thermaL-IR (TIR) band now has a 60-m GIFOV, instead of 120-m. Also, a 15-m panchromatic band has been added. The artificial neural network (NN) image sharpening method described here uses data from the higher spatial resolution ETM+ bands to enhance (sharpen) the spatial resolution of the TIR imagery. It is based on an assumed correlation over multiple scales of resolution, between image edge contrast patterns in the TIR band and several other spectral bands. A multilayer, feedforward NN is trained to approximate TIR data at 60m, given degraded (from 30-m to 60-m) spatial resolution input from spectral bands 7, 5, and 2. After training, the NN output for full-resolution input generates an approximation of a TIR image at 30-m resolution. Two methods are used to degrade the spatial resolution of the imagery used for NN training, and the corresponding sharpening results are compared. One degradation method uses a published sensor transfer function (TF) for Landsat 5 to simulate sensor coarser resolution imagery from higher resolution imagery. For comparison, the second degradation method is simply Gaussian low pass filtering and subsampling, wherein the Gaussian filter approximates the full width at half maximum amplitude characteristics of the TF-based spatial filter. Two fixed-size NNs (that is, number of weights and processing elements) were trained separately with the degraded resolution data, and the sharpening results compared. The comparison evaluates the relative influence of the degradation technique employed and whether or not it is desirable to incorporate a sensor TF model. Preliminary results indicate some improvements for the sensor model-based technique. Further evaluation using a higher resolution reference image and strict application of sensor model to data is recommended.

Performance Analysis of Receive Diversity in Wireless Sensor Networks over GBSBE Models

PubMed Central

Goel, Shivali; Abawajy, Jemal H.; Kim, Tai-hoon

2010-01-01

Wireless sensor networks have attracted a lot of attention recently. In this paper, we develop a channel model based on the elliptical model for multipath components involving randomly placed scatterers in the scattering region with sensors deployed on a field. We verify that in a sensor network, the use of receive diversity techniques improves the performance of the system. Extensive performance analysis of the system is carried out for both single and multiple antennas with the applied receive diversity techniques. Performance analyses based on variations in receiver height, maximum multipath delay and transmit power have been performed considering different numbers of antenna elements present in the receiver array, Our results show that increasing the number of antenna elements for a wireless sensor network does indeed improve the BER rates that can be obtained. PMID:22163510

Air Pollution Monitoring and Mining Based on Sensor Grid in London

PubMed Central

Ma, Yajie; Richards, Mark; Ghanem, Moustafa; Guo, Yike; Hassard, John

2008-01-01

In this paper, we present a distributed infrastructure based on wireless sensors network and Grid computing technology for air pollution monitoring and mining, which aims to develop low-cost and ubiquitous sensor networks to collect real-time, large scale and comprehensive environmental data from road traffic emissions for air pollution monitoring in urban environment. The main informatics challenges in respect to constructing the high-throughput sensor Grid are discussed in this paper. We present a two-layer network framework, a P2P e-Science Grid architecture, and the distributed data mining algorithm as the solutions to address the challenges. We simulated the system in TinyOS to examine the operation of each sensor as well as the networking performance. We also present the distributed data mining result to examine the effectiveness of the algorithm. PMID:27879895

Air Pollution Monitoring and Mining Based on Sensor Grid in London.

PubMed

Ma, Yajie; Richards, Mark; Ghanem, Moustafa; Guo, Yike; Hassard, John

2008-06-01

In this paper, we present a distributed infrastructure based on wireless sensors network and Grid computing technology for air pollution monitoring and mining, which aims to develop low-cost and ubiquitous sensor networks to collect real-time, large scale and comprehensive environmental data from road traffic emissions for air pollution monitoring in urban environment. The main informatics challenges in respect to constructing the high-throughput sensor Grid are discussed in this paper. We present a twolayer network framework, a P2P e-Science Grid architecture, and the distributed data mining algorithm as the solutions to address the challenges. We simulated the system in TinyOS to examine the operation of each sensor as well as the networking performance. We also present the distributed data mining result to examine the effectiveness of the algorithm.

Network resiliency through memory health monitoring and proactive management

DOEpatents

Andrade Costa, Carlos H.; Cher, Chen-Yong; Park, Yoonho; Rosenburg, Bryan S.; Ryu, Kyung D.

2017-11-21

A method for managing a network queue memory includes receiving sensor information about the network queue memory, predicting a memory failure in the network queue memory based on the sensor information, and outputting a notification through a plurality of nodes forming a network and using the network queue memory, the notification configuring communications between the nodes.

Display integration for ground combat vehicles

NASA Astrophysics Data System (ADS)

Busse, David J.

1998-09-01

The United States Army's requirement to employ high resolution target acquisition sensors and information warfare to increase its dominance over enemy forces has led to the need to integrate advanced display devices into ground combat vehicle crew stations. The Army's force structure require the integration of advanced displays on both existing and emerging ground combat vehicle systems. The fielding of second generation target acquisition sensors, color digital terrain maps and high volume digital command and control information networks on these platforms define display performance requirements. The greatest challenge facing the system integrator is the development and integration of advanced displays that meet operational, vehicle and human computer interface performance requirements for the ground combat vehicle fleet. The subject of this paper is to address those challenges: operational and vehicle performance, non-soldier centric crew station configurations, display performance limitations related to human computer interfaces and vehicle physical environments, display technology limitations and the Department of Defense (DOD) acquisition reform initiatives. How the ground combat vehicle Program Manager and system integrator are addressing these challenges are discussed through the integration of displays on fielded, current and future close combat vehicle applications.

An Electronic-Nose Sensor Node Based on a Polymer-Coated Surface Acoustic Wave Array for Wireless Sensor Network Applications

PubMed Central

Tang, Kea-Tiong; Li, Cheng-Han; Chiu, Shih-Wen

2011-01-01

This study developed an electronic-nose sensor node based on a polymer-coated surface acoustic wave (SAW) sensor array. The sensor node comprised an SAW sensor array, a frequency readout circuit, and an Octopus II wireless module. The sensor array was fabricated on a large K2 128° YX LiNbO3 sensing substrate. On the surface of this substrate, an interdigital transducer (IDT) was produced with a Cr/Au film as its metallic structure. A mixed-mode frequency readout application specific integrated circuit (ASIC) was fabricated using a TSMC 0.18 μm process. The ASIC output was connected to a wireless module to transmit sensor data to a base station for data storage and analysis. This sensor node is applicable for wireless sensor network (WSN) applications. PMID:22163865

An electronic-nose sensor node based on a polymer-coated surface acoustic wave array for wireless sensor network applications.

PubMed

Tang, Kea-Tiong; Li, Cheng-Han; Chiu, Shih-Wen

2011-01-01

This study developed an electronic-nose sensor node based on a polymer-coated surface acoustic wave (SAW) sensor array. The sensor node comprised an SAW sensor array, a frequency readout circuit, and an Octopus II wireless module. The sensor array was fabricated on a large K(2) 128° YX LiNbO3 sensing substrate. On the surface of this substrate, an interdigital transducer (IDT) was produced with a Cr/Au film as its metallic structure. A mixed-mode frequency readout application specific integrated circuit (ASIC) was fabricated using a TSMC 0.18 μm process. The ASIC output was connected to a wireless module to transmit sensor data to a base station for data storage and analysis. This sensor node is applicable for wireless sensor network (WSN) applications.

Developing a lower-cost atmospheric CO2 monitoring system using commercial NDIR sensor

NASA Astrophysics Data System (ADS)

Arzoumanian, E.; Bastos, A.; Gaynullin, B.; Laurent, O.; Vogel, F. R.

2017-12-01

Cities release to the atmosphere about 44 % of global energy-related CO2. It is clear that accurate estimates of the magnitude of anthropogenic and natural urban emissions are needed to assess their influence on the carbon balance. A dense ground-based CO2 monitoring network in cities would potentially allow retrieving sector specific CO2 emission estimates when combined with an atmospheric inversion framework using reasonably accurate observations (ca. 1 ppm for hourly means). One major barrier for denser observation networks can be the high cost of high precision instruments or high calibration cost of cheaper and unstable instruments. We have developed and tested a novel inexpensive NDIR sensors for CO2 measurements which fulfils cost and typical parameters requirements (i.e. signal stability, efficient handling, and connectivity) necessary for this task. Such sensors are essential in the market of emissions estimates in cities from continuous monitoring networks as well as for leak detection of MRV (monitoring, reporting, and verification) services for industrial sites. We conducted extensive laboratory tests (short and long-term repeatability, cross-sensitivities, etc.) on a series of prototypes and the final versions were also tested in a climatic chamber. On four final HPP prototypes the sensitivity to pressure and temperature were precisely quantified and correction&calibration strategies developed. Furthermore, we fully integrated these HPP sensors in a Raspberry PI platform containing the CO2 sensor and additional sensors (pressure, temperature and humidity sensors), gas supply pump and a fully automated data acquisition unit. This platform was deployed in parallel to Picarro G2401 instruments in the peri-urban site Saclay - next to Paris, and in the urban site Jussieu - Paris, France. These measurements were conducted over several months in order to characterize the long-term drift of our HPP instruments and the ability of the correction and calibration scheme to provide bias free observations. From the lessons learned in the laboratory tests and field measurements, we developed a specific correction and calibration strategy for our NDIR sensors. Latest results and calibration strategies will be shown.

Three-Dimensional Reconstruction from Single Image Base on Combination of CNN and Multi-Spectral Photometric Stereo.

PubMed

Lu, Liang; Qi, Lin; Luo, Yisong; Jiao, Hengchao; Dong, Junyu

2018-03-02

Multi-spectral photometric stereo can recover pixel-wise surface normal from a single RGB image. The difficulty lies in that the intensity in each channel is the tangle of illumination, albedo and camera response; thus, an initial estimate of the normal is required in optimization-based solutions. In this paper, we propose to make a rough depth estimation using the deep convolutional neural network (CNN) instead of using depth sensors or binocular stereo devices. Since high-resolution ground-truth data is expensive to obtain, we designed a network and trained it with rendered images of synthetic 3D objects. We use the model to predict initial normal of real-world objects and iteratively optimize the fine-scale geometry in the multi-spectral photometric stereo framework. The experimental results illustrate the improvement of the proposed method compared with existing methods.

Three-Dimensional Reconstruction from Single Image Base on Combination of CNN and Multi-Spectral Photometric Stereo

PubMed Central

Lu, Liang; Qi, Lin; Luo, Yisong; Jiao, Hengchao; Dong, Junyu

2018-01-01

Multi-spectral photometric stereo can recover pixel-wise surface normal from a single RGB image. The difficulty lies in that the intensity in each channel is the tangle of illumination, albedo and camera response; thus, an initial estimate of the normal is required in optimization-based solutions. In this paper, we propose to make a rough depth estimation using the deep convolutional neural network (CNN) instead of using depth sensors or binocular stereo devices. Since high-resolution ground-truth data is expensive to obtain, we designed a network and trained it with rendered images of synthetic 3D objects. We use the model to predict initial normal of real-world objects and iteratively optimize the fine-scale geometry in the multi-spectral photometric stereo framework. The experimental results illustrate the improvement of the proposed method compared with existing methods. PMID:29498703

Lightning: Nature's Probe of Severe Weather for Research and Operations

NASA Technical Reports Server (NTRS)

Blakeslee, R.J.

2007-01-01

Lightning, the energetic and broadband electrical discharge produced by thunderstorms, provides a natural remote sensing signal for the study of severe storms and related phenomena on global, regional and local scales. Using this strong signal- one of nature's own probes of severe weather -lightning measurements prove to be straightforward and take advantage of a variety of measurement techniques that have advanced considerably in recent years. We briefly review some of the leading lightning detection systems including satellite-based optical detectors such as the Lightning Imaging Sensor, and ground-based radio frequency systems such as Vaisala's National Lightning Detection Network (NLDN), long range lightning detection systems, and the Lightning Mapping Array (LMA) networks. In addition, we examine some of the exciting new research results and operational capabilities (e.g., shortened tornado warning lead times) derived from these observations. Finally we look forward to the next measurement advance - lightning observations from geostationary orbit.

Automated Construction of Node Software Using Attributes in a Ubiquitous Sensor Network Environment

PubMed Central

Lee, Woojin; Kim, Juil; Kang, JangMook

2010-01-01

In sensor networks, nodes must often operate in a demanding environment facing restrictions such as restricted computing resources, unreliable wireless communication and power shortages. Such factors make the development of ubiquitous sensor network (USN) applications challenging. To help developers construct a large amount of node software for sensor network applications easily and rapidly, this paper proposes an approach to the automated construction of node software for USN applications using attributes. In the proposed technique, application construction proceeds by first developing a model for the sensor network and then designing node software by setting the values of the predefined attributes. After that, the sensor network model and the design of node software are verified. The final source codes of the node software are automatically generated from the sensor network model. We illustrate the efficiency of the proposed technique by using a gas/light monitoring application through a case study of a Gas and Light Monitoring System based on the Nano-Qplus operating system. We evaluate the technique using a quantitative metric—the memory size of execution code for node software. Using the proposed approach, developers are able to easily construct sensor network applications and rapidly generate a large number of node softwares at a time in a ubiquitous sensor network environment. PMID:22163678

Automated construction of node software using attributes in a ubiquitous sensor network environment.

PubMed

Lee, Woojin; Kim, Juil; Kang, JangMook

2010-01-01

In sensor networks, nodes must often operate in a demanding environment facing restrictions such as restricted computing resources, unreliable wireless communication and power shortages. Such factors make the development of ubiquitous sensor network (USN) applications challenging. To help developers construct a large amount of node software for sensor network applications easily and rapidly, this paper proposes an approach to the automated construction of node software for USN applications using attributes. In the proposed technique, application construction proceeds by first developing a model for the sensor network and then designing node software by setting the values of the predefined attributes. After that, the sensor network model and the design of node software are verified. The final source codes of the node software are automatically generated from the sensor network model. We illustrate the efficiency of the proposed technique by using a gas/light monitoring application through a case study of a Gas and Light Monitoring System based on the Nano-Qplus operating system. We evaluate the technique using a quantitative metric-the memory size of execution code for node software. Using the proposed approach, developers are able to easily construct sensor network applications and rapidly generate a large number of node softwares at a time in a ubiquitous sensor network environment.

Intercomparison of Unmanned Aerial Vehicle and Ground-Based Narrow Band Spectrometers Applied to Crop Trait Monitoring in Organic Potato Production

PubMed Central

Domingues Franceschini, Marston Héracles; Bartholomeus, Harm; van Apeldoorn, Dirk; Suomalainen, Juha; Kooistra, Lammert

2017-01-01

Vegetation properties can be estimated using optical sensors, acquiring data on board of different platforms. For instance, ground-based and Unmanned Aerial Vehicle (UAV)-borne spectrometers can measure reflectance in narrow spectral bands, while different modelling approaches, like regressions fitted to vegetation indices, can relate spectra with crop traits. Although monitoring frameworks using multiple sensors can be more flexible, they may result in higher inaccuracy due to differences related to the sensors characteristics, which can affect information sampling. Also organic production systems can benefit from continuous monitoring focusing on crop management and stress detection, but few studies have evaluated applications with this objective. In this study, ground-based and UAV spectrometers were compared in the context of organic potato cultivation. Relatively accurate estimates were obtained for leaf chlorophyll (RMSE = 6.07 µg·cm−2), leaf area index (RMSE = 0.67 m2·m−2), canopy chlorophyll (RMSE = 0.24 g·m−2) and ground cover (RMSE = 5.5%) using five UAV-based data acquisitions, from 43 to 99 days after planting. These retrievals are slightly better than those derived from ground-based measurements (RMSE = 7.25 µg·cm−2, 0.85 m2·m−2, 0.28 g·m−2 and 6.8%, respectively), for the same period. Excluding observations corresponding to the first acquisition increased retrieval accuracy and made outputs more comparable between sensors, due to relatively low vegetation cover on this date. Intercomparison of vegetation indices indicated that indices based on the contrast between spectral bands in the visible and near-infrared, like OSAVI, MCARI2 and CIg provided, at certain extent, robust outputs that could be transferred between sensors. Information sampling at plot level by both sensing solutions resulted in comparable discriminative potential concerning advanced stages of late blight incidence. These results indicate that optical sensors, and their integration, have great potential for monitoring this specific organic cropping system. PMID:28629159

Intercomparison of Unmanned Aerial Vehicle and Ground-Based Narrow Band Spectrometers Applied to Crop Trait Monitoring in Organic Potato Production.

PubMed

Domingues Franceschini, Marston Héracles; Bartholomeus, Harm; van Apeldoorn, Dirk; Suomalainen, Juha; Kooistra, Lammert

2017-06-18

Vegetation properties can be estimated using optical sensors, acquiring data on board of different platforms. For instance, ground-based and Unmanned Aerial Vehicle (UAV)-borne spectrometers can measure reflectance in narrow spectral bands, while different modelling approaches, like regressions fitted to vegetation indices, can relate spectra with crop traits. Although monitoring frameworks using multiple sensors can be more flexible, they may result in higher inaccuracy due to differences related to the sensors characteristics, which can affect information sampling. Also organic production systems can benefit from continuous monitoring focusing on crop management and stress detection, but few studies have evaluated applications with this objective. In this study, ground-based and UAV spectrometers were compared in the context of organic potato cultivation. Relatively accurate estimates were obtained for leaf chlorophyll (RMSE = 6.07 µg·cm -2 ), leaf area index (RMSE = 0.67 m²·m -2 ), canopy chlorophyll (RMSE = 0.24 g·m -2 ) and ground cover (RMSE = 5.5%) using five UAV-based data acquisitions, from 43 to 99 days after planting. These retrievals are slightly better than those derived from ground-based measurements (RMSE = 7.25 µg·cm -2 , 0.85 m²·m -2 , 0.28 g·m -2 and 6.8%, respectively), for the same period. Excluding observations corresponding to the first acquisition increased retrieval accuracy and made outputs more comparable between sensors, due to relatively low vegetation cover on this date. Intercomparison of vegetation indices indicated that indices based on the contrast between spectral bands in the visible and near-infrared, like OSAVI, MCARI2 and CI g provided, at certain extent, robust outputs that could be transferred between sensors. Information sampling at plot level by both sensing solutions resulted in comparable discriminative potential concerning advanced stages of late blight incidence. These results indicate that optical sensors, and their integration, have great potential for monitoring this specific organic cropping system.

A self-optimizing scheme for energy balanced routing in Wireless Sensor Networks using SensorAnt.

PubMed

Shamsan Saleh, Ahmed M; Ali, Borhanuddin Mohd; Rasid, Mohd Fadlee A; Ismail, Alyani

2012-01-01

Planning of energy-efficient protocols is critical for Wireless Sensor Networks (WSNs) because of the constraints on the sensor nodes' energy. The routing protocol should be able to provide uniform power dissipation during transmission to the sink node. In this paper, we present a self-optimization scheme for WSNs which is able to utilize and optimize the sensor nodes' resources, especially the batteries, to achieve balanced energy consumption across all sensor nodes. This method is based on the Ant Colony Optimization (ACO) metaheuristic which is adopted to enhance the paths with the best quality function. The assessment of this function depends on multi-criteria metrics such as the minimum residual battery power, hop count and average energy of both route and network. This method also distributes the traffic load of sensor nodes throughout the WSN leading to reduced energy usage, extended network life time and reduced packet loss. Simulation results show that our scheme performs much better than the Energy Efficient Ant-Based Routing (EEABR) in terms of energy consumption, balancing and efficiency.

Atmospheric electricity/meteorology analysis

NASA Technical Reports Server (NTRS)

Goodman, Steven J.; Blakeslee, Richard; Buechler, Dennis

1993-01-01

This activity focuses on Lightning Imaging Sensor (LIS)/Lightning Mapper Sensor (LMS) algorithm development and applied research. Specifically we are exploring the relationships between (1) global and regional lightning activity and rainfall, and (2) storm electrical development, physics, and the role of the environment. U.S. composite radar-rainfall maps and ground strike lightning maps are used to understand lightning-rainfall relationships at the regional scale. These observations are then compared to SSM/I brightness temperatures to simulate LIS/TRMM multi-sensor algorithm data sets. These data sets are supplied to the WETNET project archive. WSR88-D (NEXRAD) data are also used as it becomes available. The results of this study allow us to examine the information content from lightning imaging sensors in low-earth and geostationary orbits. Analysis of tropical and U.S. data sets continues. A neural network/sensor fusion algorithm is being refined for objectively associating lightning and rainfall with their parent storm systems. Total lightning data from interferometers are being used in conjunction with data from the national lightning network. A 6-year lightning/rainfall climatology has been assembled for LIS sampling studies.

An adaptive distributed data aggregation based on RCPC for wireless sensor networks

NASA Astrophysics Data System (ADS)

Hua, Guogang; Chen, Chang Wen

2006-05-01

One of the most important design issues in wireless sensor networks is energy efficiency. Data aggregation has significant impact on the energy efficiency of the wireless sensor networks. With massive deployment of sensor nodes and limited energy supply, data aggregation has been considered as an essential paradigm for data collection in sensor networks. Recently, distributed source coding has been demonstrated to possess several advantages in data aggregation for wireless sensor networks. Distributed source coding is able to encode sensor data with lower bit rate without direct communication among sensor nodes. To ensure reliable and high throughput transmission with the aggregated data, we proposed in this research a progressive transmission and decoding of Rate-Compatible Punctured Convolutional (RCPC) coded data aggregation with distributed source coding. Our proposed 1/2 RSC codes with Viterbi algorithm for distributed source coding are able to guarantee that, even without any correlation between the data, the decoder can always decode the data correctly without wasting energy. The proposed approach achieves two aspects in adaptive data aggregation for wireless sensor networks. First, the RCPC coding facilitates adaptive compression corresponding to the correlation of the sensor data. When the data correlation is high, higher compression ration can be achieved. Otherwise, lower compression ratio will be achieved. Second, the data aggregation is adaptively accumulated. There is no waste of energy in the transmission; even there is no correlation among the data, the energy consumed is at the same level as raw data collection. Experimental results have shown that the proposed distributed data aggregation based on RCPC is able to achieve high throughput and low energy consumption data collection for wireless sensor networks

Real-Time Identification of Smoldering and Flaming Combustion Phases in Forest Using a Wireless Sensor Network-Based Multi-Sensor System and Artificial Neural Network

PubMed Central

Yan, Xiaofei; Cheng, Hong; Zhao, Yandong; Yu, Wenhua; Huang, Huan; Zheng, Xiaoliang

2016-01-01

Diverse sensing techniques have been developed and combined with machine learning method for forest fire detection, but none of them referred to identifying smoldering and flaming combustion phases. This study attempts to real-time identify different combustion phases using a developed wireless sensor network (WSN)-based multi-sensor system and artificial neural network (ANN). Sensors (CO, CO2, smoke, air temperature and relative humidity) were integrated into one node of WSN. An experiment was conducted using burning materials from residual of forest to test responses of each node under no, smoldering-dominated and flaming-dominated combustion conditions. The results showed that the five sensors have reasonable responses to artificial forest fire. To reduce cost of the nodes, smoke, CO2 and temperature sensors were chiefly selected through correlation analysis. For achieving higher identification rate, an ANN model was built and trained with inputs of four sensor groups: smoke; smoke and CO2; smoke and temperature; smoke, CO2 and temperature. The model test results showed that multi-sensor input yielded higher predicting accuracy (≥82.5%) than single-sensor input (50.9%–92.5%). Based on these, it is possible to reduce the cost with a relatively high fire identification rate and potential application of the system can be tested in future under real forest condition. PMID:27527175

Real-Time Identification of Smoldering and Flaming Combustion Phases in Forest Using a Wireless Sensor Network-Based Multi-Sensor System and Artificial Neural Network.

PubMed

Yan, Xiaofei; Cheng, Hong; Zhao, Yandong; Yu, Wenhua; Huang, Huan; Zheng, Xiaoliang

2016-08-04

Diverse sensing techniques have been developed and combined with machine learning method for forest fire detection, but none of them referred to identifying smoldering and flaming combustion phases. This study attempts to real-time identify different combustion phases using a developed wireless sensor network (WSN)-based multi-sensor system and artificial neural network (ANN). Sensors (CO, CO₂, smoke, air temperature and relative humidity) were integrated into one node of WSN. An experiment was conducted using burning materials from residual of forest to test responses of each node under no, smoldering-dominated and flaming-dominated combustion conditions. The results showed that the five sensors have reasonable responses to artificial forest fire. To reduce cost of the nodes, smoke, CO₂ and temperature sensors were chiefly selected through correlation analysis. For achieving higher identification rate, an ANN model was built and trained with inputs of four sensor groups: smoke; smoke and CO₂; smoke and temperature; smoke, CO₂ and temperature. The model test results showed that multi-sensor input yielded higher predicting accuracy (≥82.5%) than single-sensor input (50.9%-92.5%). Based on these, it is possible to reduce the cost with a relatively high fire identification rate and potential application of the system can be tested in future under real forest condition.

Improved Space Object Orbit Determination Using CMOS Detectors

NASA Astrophysics Data System (ADS)

Schildknecht, T.; Peltonen, J.; Sännti, T.; Silha, J.; Flohrer, T.

2014-09-01

CMOS-sensors, or in general Active Pixel Sensors (APS), are rapidly replacing CCDs in the consumer camera market. Due to significant technological advances during the past years these devices start to compete with CCDs also for demanding scientific imaging applications, in particular in the astronomy community. CMOS detectors offer a series of inherent advantages compared to CCDs, due to the structure of their basic pixel cells, which each contains their own amplifier and readout electronics. The most prominent advantages for space object observations are the extremely fast and flexible readout capabilities, feasibility for electronic shuttering and precise epoch registration, and the potential to perform image processing operations on-chip and in real-time. The major challenges and design drivers for ground-based and space-based optical observation strategies have been analyzed. CMOS detector characteristics were critically evaluated and compared with the established CCD technology, especially with respect to the above mentioned observations. Similarly, the desirable on-chip processing functionalities which would further enhance the object detection and image segmentation were identified. Finally, we simulated several observation scenarios for ground- and space-based sensor by assuming different observation and sensor properties. We will introduce the analyzed end-to-end simulations of the ground- and space-based strategies in order to investigate the orbit determination accuracy and its sensitivity which may result from different values for the frame-rate, pixel scale, astrometric and epoch registration accuracies. Two cases were simulated, a survey using a ground-based sensor to observe objects in LEO for surveillance applications, and a statistical survey with a space-based sensor orbiting in LEO observing small-size debris in LEO. The ground-based LEO survey uses a dynamical fence close to the Earth shadow a few hours after sunset. For the space-based scenario a sensor in a sun-synchronous LEO orbit, always pointing in the anti-sun direction to achieve optimum illumination conditions for small LEO debris, was simulated. For the space-based scenario the simulations showed a 20 130 % improvement of the accuracy of all orbital parameters when varying the frame rate from 1/3 fps, which is the fastest rate for a typical CCD detector, to 50 fps, which represents the highest rate of scientific CMOS cameras. Changing the epoch registration accuracy from a typical 20.0 ms for a mechanical shutter to 0.025 ms, the theoretical value for the electronic shutter of a CMOS camera, improved the orbit accuracy by 4 to 190 %. The ground-based scenario also benefit from the specific CMOS characteristics, but to a lesser extent.

A novel multi-scale adaptive sampling-based approach for energy saving in leak detection for WSN-based water pipelines

NASA Astrophysics Data System (ADS)

Saqib, Najam us; Faizan Mysorewala, Muhammad; Cheded, Lahouari

2017-12-01

In this paper, we propose a novel monitoring strategy for a wireless sensor networks (WSNs)-based water pipeline network. Our strategy uses a multi-pronged approach to reduce energy consumption based on the use of two types of vibration sensors and pressure sensors, all having different energy levels, and a hierarchical adaptive sampling mechanism to determine the sampling frequency. The sampling rate of the sensors is adjusted according to the bandwidth of the vibration signal being monitored by using a wavelet-based adaptive thresholding scheme that calculates the new sampling frequency for the following cycle. In this multimodal sensing scheme, the duty-cycling approach is used for all sensors to reduce the sampling instances, such that the high-energy, high-precision (HE-HP) vibration sensors have low duty cycles, and the low-energy, low-precision (LE-LP) vibration sensors have high duty cycles. The low duty-cycling (HE-HP) vibration sensor adjusts the sampling frequency of the high duty-cycling (LE-LP) vibration sensor. The simulated test bed considered here consists of a water pipeline network which uses pressure and vibration sensors, with the latter having different energy consumptions and precision levels, at various locations in the network. This is all the more useful for energy conservation for extended monitoring. It is shown that by using the novel features of our proposed scheme, a significant reduction in energy consumption is achieved and the leak is effectively detected by the sensor node that is closest to it. Finally, both the total energy consumed by monitoring as well as the time to detect the leak by a WSN node are computed, and show the superiority of our proposed hierarchical adaptive sampling algorithm over a non-adaptive sampling approach.

Lightning Sensors for Observing, Tracking and Nowcasting Severe Weather

PubMed Central

Price, Colin

2008-01-01

Severe and extreme weather is a major natural hazard all over the world, often resulting in major natural disasters such as hail storms, tornados, wind storms, flash floods, forest fires and lightning damages. While precipitation, wind, hail, tornados, turbulence, etc. can only be observed at close distances, lightning activity in these damaging storms can be monitored at all spatial scales, from local (using very high frequency [VHF] sensors), to regional (using very low frequency [VLF] sensors), and even global scales (using extremely low frequency [ELF] sensors). Using sensors that detect the radio waves emitted by each lightning discharge, it is now possible to observe and track continuously distant thunderstorms using ground networks of sensors. In addition to the number of lightning discharges, these sensors can also provide information on lightning characteristics such as the ratio between intra-cloud and cloud-to-ground lightning, the polarity of the lightning discharge, peak currents, charge removal, etc. It has been shown that changes in some of these lightning characteristics during thunderstorms are often related to changes in the severity of the storms. In this paper different lightning observing systems are described, and a few examples are provided showing how lightning may be used to monitor storm hazards around the globe, while also providing the possibility of supplying short term forecasts, called nowcasting. PMID:27879700

Next generation of space based sensor for application in the SSA space weather domain.

NASA Astrophysics Data System (ADS)

Jansen, Frank; Kudela, Karel; Behrens, Joerg

Next generation of space based sensor for application in the SSA space weather domain. F. Jansen1, K. Kudela2, J. Behrens1 and NESTEC consortium3 1DLR, Bremen, Germany 2IEP SAS Kosice, Slovakia 3NESTEC consortium members (DLR Bremen, DESY Hamburg, MPS Katlenburg-Lindau, CTU Prague, University of Twente, IEP-SAS Kosice, UCL/MSSL, University of Manchester, University of Surrey, Hermanus Magnetic Observatory, North-West University Potchefsroom, University of Montreal) High energy solar and galactic cosmic rays have twofold importance for the SSA space weather domain. Cosmic rays have dangerous effects for space, air and ground based assets, but on the other side cosmic rays are direct measure tools for real time space weather warning. A review of space weather related SSA results from operating global cosmic ray networks (especially those by neutron monitors and by muon directional telescopes), its limitations and main questions to be solved, is presented. Especially those recent results, received in real time and with high temporal resolution, are reviewed and discussed. In addition the relevance of these monitors and telescopes in forecasting geomagnetic disturbances are checked. Based on this study result, a next generation of highly miniaturized hybrid silicon pixel device (Medipix sensor) will be described for the following, beyond state-of-the-art application: a SSA satellite for high energy solar and galactic cosmic ray spectrum measurement, with a space plasma environment data package and CME real time imaging by means of cosmic rays. All data management and processing will be carried out on the satellite in real time. Insofar a high reduction of data and transmission to ground station of finalized space weather relevant data and images are foreseen.

Fieldservers and Sensor Service Grid as Real-time Monitoring Infrastructure for Ubiquitous Sensor Networks

PubMed Central

Honda, Kiyoshi; Shrestha, Aadit; Witayangkurn, Apichon; Chinnachodteeranun, Rassarin; Shimamura, Hiroshi

2009-01-01

The fieldserver is an Internet based observation robot that can provide an outdoor solution for monitoring environmental parameters in real-time. The data from its sensors can be collected to a central server infrastructure and published on the Internet. The information from the sensor network will contribute to monitoring and modeling on various environmental issues in Asia, including agriculture, food, pollution, disaster, climate change etc. An initiative called Sensor Asia is developing an infrastructure called Sensor Service Grid (SSG), which integrates fieldservers and Web GIS to realize easy and low cost installation and operation of ubiquitous field sensor networks. PMID:22574018

Biosensor system-on-a-chip including CMOS-based signal processing circuits and 64 carbon nanotube-based sensors for the detection of a neurotransmitter.

PubMed

Lee, Byung Yang; Seo, Sung Min; Lee, Dong Joon; Lee, Minbaek; Lee, Joohyung; Cheon, Jun-Ho; Cho, Eunju; Lee, Hyunjoong; Chung, In-Young; Park, Young June; Kim, Suhwan; Hong, Seunghun

2010-04-07

We developed a carbon nanotube (CNT)-based biosensor system-on-a-chip (SoC) for the detection of a neurotransmitter. Here, 64 CNT-based sensors were integrated with silicon-based signal processing circuits in a single chip, which was made possible by combining several technological breakthroughs such as efficient signal processing, uniform CNT networks, and biocompatible functionalization of CNT-based sensors. The chip was utilized to detect glutamate, a neurotransmitter, where ammonia, a byproduct of the enzymatic reaction of glutamate and glutamate oxidase on CNT-based sensors, modulated the conductance signals to the CNT-based sensors. This is a major technological advancement in the integration of CNT-based sensors with microelectronics, and this chip can be readily integrated with larger scale lab-on-a-chip (LoC) systems for various applications such as LoC systems for neural networks.

Consensus-based distributed estimation in multi-agent systems with time delay

NASA Astrophysics Data System (ADS)

Abdelmawgoud, Ahmed

During the last years, research in the field of cooperative control of swarm of robots, especially Unmanned Aerial Vehicles (UAV); have been improved due to the increase of UAV applications. The ability to track targets using UAVs has a wide range of applications not only civilian but also military as well. For civilian applications, UAVs can perform tasks including, but not limited to: map an unknown area, weather forecasting, land survey, and search and rescue missions. On the other hand, for military personnel, UAV can track and locate a variety of objects, including the movement of enemy vehicles. Consensus problems arise in a number of applications including coordination of UAVs, information processing in wireless sensor networks, and distributed multi-agent optimization. We consider a widely studied consensus algorithms for processing sensed data by different sensors in wireless sensor networks of dynamic agents. Every agent involved in the network forms a weighted average of its own estimated value of some state with the values received from its neighboring agents. We introduced a novelty of consensus-based distributed estimation algorithms. We propose a new algorithm to reach a consensus given time delay constraints. The proposed algorithm performance was observed in a scenario where a swarm of UAVs measuring the location of a ground maneuvering target. We assume that each UAV computes its state prediction and shares it with its neighbors only. However, the shared information applied to different agents with variant time delays. The entire group of UAVs must reach a consensus on target state. Different scenarios were also simulated to examine the effectiveness and performance in terms of overall estimation error, disagreement between delayed and non-delayed agents, and time to reach a consensus for each parameter contributing on the proposed algorithm.

A Cluster-Based Architecture to Structure the Topology of Parallel Wireless Sensor Networks

PubMed Central

Lloret, Jaime; Garcia, Miguel; Bri, Diana; Diaz, Juan R.

2009-01-01

A wireless sensor network is a self-configuring network of mobile nodes connected by wireless links where the nodes have limited capacity and energy. In many cases, the application environment requires the design of an exclusive network topology for a particular case. Cluster-based network developments and proposals in existence have been designed to build a network for just one type of node, where all nodes can communicate with any other nodes in their coverage area. Let us suppose a set of clusters of sensor nodes where each cluster is formed by different types of nodes (e.g., they could be classified by the sensed parameter using different transmitting interfaces, by the node profile or by the type of device: laptops, PDAs, sensor etc.) and exclusive networks, as virtual networks, are needed with the same type of sensed data, or the same type of devices, or even the same type of profiles. In this paper, we propose an algorithm that is able to structure the topology of different wireless sensor networks to coexist in the same environment. It allows control and management of the topology of each network. The architecture operation and the protocol messages will be described. Measurements from a real test-bench will show that the designed protocol has low bandwidth consumption and also demonstrates the viability and the scalability of the proposed architecture. Our ccluster-based algorithm is compared with other algorithms reported in the literature in terms of architecture and protocol measurements. PMID:22303185

Efficient sensor network vehicle classification using peak harmonics of acoustic emissions

NASA Astrophysics Data System (ADS)

William, Peter E.; Hoffman, Michael W.

2008-04-01

An application is proposed for detection and classification of battlefield ground vehicles using the emitted acoustic signal captured at individual sensor nodes of an ad hoc Wireless Sensor Network (WSN). We make use of the harmonic characteristics of the acoustic emissions of battlefield vehicles, in reducing both the computations carried on the sensor node and the transmitted data to the fusion center for reliable and effcient classification of targets. Previous approaches focus on the lower frequency band of the acoustic emissions up to 500Hz; however, we show in the proposed application how effcient discrimination between battlefield vehicles is performed using features extracted from higher frequency bands (50 - 1500Hz). The application shows that selective time domain acoustic features surpass equivalent spectral features. Collaborative signal processing is utilized, such that estimation of certain signal model parameters is carried by the sensor node, in order to reduce the communication between the sensor node and the fusion center, while the remaining model parameters are estimated at the fusion center. The transmitted data from the sensor node to the fusion center ranges from 1 ~ 5% of the sampled acoustic signal at the node. A variety of classification schemes were examined, such as maximum likelihood, vector quantization and artificial neural networks. Evaluation of the proposed application, through processing of an acoustic data set with comparison to previous results, shows that the improvement is not only in the number of computations but also in the detection and false alarm rate as well.

On Deployment of Multiple Base Stations for Energy-Efficient Communication in Wireless Sensor Networks

DOE PAGES

Lin, Yunyue; Wu, Qishi; Cai, Xiaoshan; ...

2010-01-01

Data transmission from sensor nodes to a base station or a sink node often incurs significant energy consumption, which critically affects network lifetime. We generalize and solve the problem of deploying multiple base stations to maximize network lifetime in terms of two different metrics under one-hop and multihop communication models. In the one-hop communication model, the sensors far away from base stations always deplete their energy much faster than others. We propose an optimal solution and a heuristic approach based on the minimal enclosing circle algorithm to deploy a base station at the geometric center of each cluster. In themore » multihop communication model, both base station location and data routing mechanism need to be considered in maximizing network lifetime. We propose an iterative algorithm based on rigorous mathematical derivations and use linear programming to compute the optimal routing paths for data transmission. Simulation results show the distinguished performance of the proposed deployment algorithms in maximizing network lifetime.« less

Abstracts for student symposium

DOE Office of Scientific and Technical Information (OSTI.GOV)

Goldman, B.

Lawrence Livermore National Laboratory Science and Engineering Research Semester (SERS) students are participants in a national program sponsored by the DOE Office of Energy Research. Presented topics from Fall 1993 include: Laser glass, wiring codes, lead in food and food containers, chromium removal from ground water, fiber optic sensors for ph measurement, CFC replacement, predator/prey simulation, detection of micronuclei in germ cells, DNA conformation, stimulated brillouin scattering, DNA sequencing, evaluation of education programs, neural network analysis of nuclear glass, lithium ion batteries, Indonesian snails, optical switching systems, and photoreceiver design. Individual papers are indexed separately on the Energy Data Base.

A Multi-Objective Partition Method for Marine Sensor Networks Based on Degree of Event Correlation.

PubMed

Huang, Dongmei; Xu, Chenyixuan; Zhao, Danfeng; Song, Wei; He, Qi

2017-09-21

Existing marine sensor networks acquire data from sea areas that are geographically divided, and store the data independently in their affiliated sea area data centers. In the case of marine events across multiple sea areas, the current network structure needs to retrieve data from multiple data centers, and thus severely affects real-time decision making. In this study, in order to provide a fast data retrieval service for a marine sensor network, we use all the marine sensors as the vertices, establish the edge based on marine events, and abstract the marine sensor network as a graph. Then, we construct a multi-objective balanced partition method to partition the abstract graph into multiple regions and store them in the cloud computing platform. This method effectively increases the correlation of the sensors and decreases the retrieval cost. On this basis, an incremental optimization strategy is designed to dynamically optimize existing partitions when new sensors are added into the network. Experimental results show that the proposed method can achieve the optimal layout for distributed storage in the process of disaster data retrieval in the China Sea area, and effectively optimize the result of partitions when new buoys are deployed, which eventually will provide efficient data access service for marine events.

Spatio-Temporal Constrained Human Trajectory Generation from the PIR Motion Detector Sensor Network Data: A Geometric Algebra Approach

PubMed Central

Yu, Zhaoyuan; Yuan, Linwang; Luo, Wen; Feng, Linyao; Lv, Guonian

2015-01-01

Passive infrared (PIR) motion detectors, which can support long-term continuous observation, are widely used for human motion analysis. Extracting all possible trajectories from the PIR sensor networks is important. Because the PIR sensor does not log location and individual information, none of the existing methods can generate all possible human motion trajectories that satisfy various spatio-temporal constraints from the sensor activation log data. In this paper, a geometric algebra (GA)-based approach is developed to generate all possible human trajectories from the PIR sensor network data. Firstly, the representation of the geographical network, sensor activation response sequences and the human motion are represented as algebraic elements using GA. The human motion status of each sensor activation are labeled using the GA-based trajectory tracking. Then, a matrix multiplication approach is developed to dynamically generate the human trajectories according to the sensor activation log and the spatio-temporal constraints. The method is tested with the MERL motion database. Experiments show that our method can flexibly extract the major statistical pattern of the human motion. Compared with direct statistical analysis and tracklet graph method, our method can effectively extract all possible trajectories of the human motion, which makes it more accurate. Our method is also likely to provides a new way to filter other passive sensor log data in sensor networks. PMID:26729123

Spatio-Temporal Constrained Human Trajectory Generation from the PIR Motion Detector Sensor Network Data: A Geometric Algebra Approach.

PubMed

Yu, Zhaoyuan; Yuan, Linwang; Luo, Wen; Feng, Linyao; Lv, Guonian

2015-12-30

Passive infrared (PIR) motion detectors, which can support long-term continuous observation, are widely used for human motion analysis. Extracting all possible trajectories from the PIR sensor networks is important. Because the PIR sensor does not log location and individual information, none of the existing methods can generate all possible human motion trajectories that satisfy various spatio-temporal constraints from the sensor activation log data. In this paper, a geometric algebra (GA)-based approach is developed to generate all possible human trajectories from the PIR sensor network data. Firstly, the representation of the geographical network, sensor activation response sequences and the human motion are represented as algebraic elements using GA. The human motion status of each sensor activation are labeled using the GA-based trajectory tracking. Then, a matrix multiplication approach is developed to dynamically generate the human trajectories according to the sensor activation log and the spatio-temporal constraints. The method is tested with the MERL motion database. Experiments show that our method can flexibly extract the major statistical pattern of the human motion. Compared with direct statistical analysis and tracklet graph method, our method can effectively extract all possible trajectories of the human motion, which makes it more accurate. Our method is also likely to provides a new way to filter other passive sensor log data in sensor networks.

FIRESTORM: a collaborative network suite application for rapid sensor data processing and precise decisive responses

NASA Astrophysics Data System (ADS)

Kaniyantethu, Shaji

2011-06-01

This paper discusses the many features and composed technologies in Firestorm™ - a Distributed Collaborative Fires and Effects software. Modern response management systems capitalize on the capabilities of a plethora of sensors and its output for situational awareness. Firestorm utilizes a unique networked lethality approach by integrating unmanned air and ground vehicles to provide target handoff and sharing of data between humans and sensors. The system employs Bayesian networks for track management of sensor data, and distributed auction algorithms for allocating targets and delivering the right effect without information overload to the Warfighter. Firestorm Networked Effects Component provides joint weapon-target pairing, attack guidance, target selection standards, and other fires and effects components. Moreover, the open and modular architecture allows for easy integration with new data sources. Versatility and adaptability of the application enable it to devise and dispense a suitable response to a wide variety of scenarios. Recently, this application was used for detecting and countering a vehicle intruder with the help of radio frequency spotter sensor, command driven cameras, remote weapon system, portable vehicle arresting barrier, and an unmanned aerial vehicle - which confirmed the presence of the intruder, as well as provided lethal/non-lethal response and battle damage assessment. The completed demonstrations have proved Firestorm's™ validity and feasibility to predict, detect, neutralize, and protect key assets and/or area against a variety of possible threats. The sensors and responding assets can be deployed with numerous configurations to cover the various terrain and environmental conditions, and can be integrated to a number of platforms.

An Ad-hoc Satellite Network to Measure Filamentary Current Structures in the Auroral Zone

NASA Astrophysics Data System (ADS)

Nabong, C.; Fritz, T. A.; Semeter, J. L.

2014-12-01

An ad-hoc cubesat-based satellite network project known as ANDESITE is under development at Boston University. It aims to develop a dense constellation of easy-to-use, rapidly-deployable low-cost wireless sensor nodes in space. The objectives of the project are threefold: 1) Demonstrate viability of satellite based sensor networks by deploying an 8-node miniature sensor network to study the filamentation of the field aligned currents in the auroral zones of the Earth's magnetosphere. 2) Test the scalability of proposed protocols, including localization techniques, tracking, data aggregation, and routing, for a 3 dimensional wireless sensor network using a "flock" of nodes. 3) Construct a 6U Cube-sat running the Android OS as an integrated constellation manager, data mule and sensor node deplorer. This small network of sensor nodes will resolve current densities at different spatial resolutions in the near-Earth magnetosphere using measurements from magnetometers with 1-nT sensitivities and 0.2 nT/√Hz self-noise. Mapping of these currents will provide new constraints for models of auroral particle acceleration, wave-particle interactions, ionospheric destabilization, and other kinetic processes operating in the low-beta plasma of the near Earth magnetosphere.

Location-Aware Dynamic Session-Key Management for Grid-Based Wireless Sensor Networks

PubMed Central

Chen, Chin-Ling; Lin, I-Hsien

2010-01-01

Security is a critical issue for sensor networks used in hostile environments. When wireless sensor nodes in a wireless sensor network are distributed in an insecure hostile environment, the sensor nodes must be protected: a secret key must be used to protect the nodes transmitting messages. If the nodes are not protected and become compromised, many types of attacks against the network may result. Such is the case with existing schemes, which are vulnerable to attacks because they mostly provide a hop-by-hop paradigm, which is insufficient to defend against known attacks. We propose a location-aware dynamic session-key management protocol for grid-based wireless sensor networks. The proposed protocol improves the security of a secret key. The proposed scheme also includes a key that is dynamically updated. This dynamic update can lower the probability of the key being guessed correctly. Thus currently known attacks can be defended. By utilizing the local information, the proposed scheme can also limit the flooding region in order to reduce the energy that is consumed in discovering routing paths. PMID:22163606

Location-aware dynamic session-key management for grid-based Wireless Sensor Networks.

PubMed

Chen, Chin-Ling; Lin, I-Hsien

2010-01-01

Security is a critical issue for sensor networks used in hostile environments. When wireless sensor nodes in a wireless sensor network are distributed in an insecure hostile environment, the sensor nodes must be protected: a secret key must be used to protect the nodes transmitting messages. If the nodes are not protected and become compromised, many types of attacks against the network may result. Such is the case with existing schemes, which are vulnerable to attacks because they mostly provide a hop-by-hop paradigm, which is insufficient to defend against known attacks. We propose a location-aware dynamic session-key management protocol for grid-based wireless sensor networks. The proposed protocol improves the security of a secret key. The proposed scheme also includes a key that is dynamically updated. This dynamic update can lower the probability of the key being guessed correctly. Thus currently known attacks can be defended. By utilizing the local information, the proposed scheme can also limit the flooding region in order to reduce the energy that is consumed in discovering routing paths.

SATELLITE REMOTE SENSING AND GROUND-BASED ESTIMATES OF FOREST BIOMASS AND CANOPY STRUCTURE

EPA Science Inventory

MODIS (Moderate Resolution Imaging Spectroradiometer) launched in 1999 is the first satellite sensor to provide the kind of data necessary to intensively probe the global landscape for LAl. Because it is a new sensor, its data products must be validated with ground data. This res...

Distributed Environment Control Using Wireless Sensor/Actuator Networks for Lighting Applications

PubMed Central

Nakamura, Masayuki; Sakurai, Atsushi; Nakamura, Jiro

2009-01-01

We propose a decentralized algorithm to calculate the control signals for lights in wireless sensor/actuator networks. This algorithm uses an appropriate step size in the iterative process used for quickly computing the control signals. We demonstrate the accuracy and efficiency of this approach compared with the penalty method by using Mote-based mesh sensor networks. The estimation error of the new approach is one-eighth as large as that of the penalty method with one-fifth of its computation time. In addition, we describe our sensor/actuator node for distributed lighting control based on the decentralized algorithm and demonstrate its practical efficacy. PMID:22291525

Wireless Networks under a Backoff Attack: A Game Theoretical Perspective

PubMed Central

Zazo, Santiago

2018-01-01

We study a wireless sensor network using CSMA/CA in the MAC layer under a backoff attack: some of the sensors of the network are malicious and deviate from the defined contention mechanism. We use Bianchi’s network model to study the impact of the malicious sensors on the total network throughput, showing that it causes the throughput to be unfairly distributed among sensors. We model this conflict using game theory tools, where each sensor is a player. We obtain analytical solutions and propose an algorithm, based on Regret Matching, to learn the equilibrium of the game with an arbitrary number of players. Our approach is validated via simulations, showing that our theoretical predictions adjust to reality. PMID:29385752

Ultra-low power wireless sensing for long-term structural health monitoring

NASA Astrophysics Data System (ADS)

Bilbao, Argenis; Hoover, Davis; Rice, Jennifer; Chapman, Jamie

2011-04-01

Researchers have made significant progress in recent years towards realizing long-term structural health monitoring (SHM) utilizing wireless smart sensor networks (WSSNs). These efforts have focused on improving the performance and robustness of such networks to achieve high quality data acquisition and in-network processing. One of the primary challenges still facing the use of smart sensors for long-term monitoring deployments is their limited power resources. Periodically accessing the sensor nodes to change batteries is not feasible or economical in many deployment cases. While energy harvesting techniques show promise for prolonging unattended network life, low-power design and operation are still critically important. This research presents a new, fully integrated ultra-low power wireless smart sensor node and a flexible base station, both designed for long-term SHM applications. The power consumption of the sensor nodes and base station has been minimized through careful hardware selection and the implementation of power-aware network software, without sacrificing flexibility and functionality.

Evaluating a Novel Cellular Automata-Based Distributed Power Management Approach for Mobile Wireless Sensor Networks

NASA Astrophysics Data System (ADS)

Adabi, Sepideh; Adabi, Sahar; Rezaee, Ali

According to the traditional definition of Wireless Sensor Networks (WSNs), static sensors have limited the feasibility of WSNs in some kind of approaches, so the mobility was introduced in WSN. Mobile nodes in a WSN come equipped with battery and from the point of deployment, this battery reserve becomes a valuable resource since it cannot be replenished. Hence, maximizing the network lifetime by minimizing the energy is an important challenge in Mobile WSN. Energy conservation can be accomplished by different approaches. In this paper, we presented an energy conservation solution based on Cellular Automata. The main objective of this solution is based on dynamically adjusting the transmission range and switching between operational states of the sensor nodes.

Landslide monitoring using Geocubes, a wireless network of low-cost GPS receivers

NASA Astrophysics Data System (ADS)

Benoit, Lionel; Thom, Christian; Martin, Olivier

2013-04-01

Many geophysical structures such as landslides, glaciers or even volcanoes are features characterized by small extend area and deformation rate in the order of 1 to 10cm per day. Their study needs ever more accurate positioning data with an increased space and time resolution. Using an ublox LEA-6T GPS receiver, the French national mapping agency IGN developed its own wireless multi-sensor geo-monitoring system named Geocube. The basic device is equipped with a GPS and a wireless communication media and can be completed with various sensor modules such as meteorological sensors, ground humidity and pressure or seismograph. Due to the low cost of each receiver, spatial dense surveying networks are deployed. Data are then continuously collected and transmitted to a processing computer in real-time as well as saved in situ on a Micro-SD card. Among them, raw GPS carrier phase data give access to real-time accurate relative positioning on all mesh nodes if small baselines are used. In order to achieve a high accuracy, a dedicated GPS data processing method based on a Kalman filter is proposed. It allows an epoch by epoch positioning providing a high time resolution. Special attention is paid on two points : adaptation to wireless networks of low-cost GPS and real-time ability. A first test of Geocubes usability under field conditions was carried out during summer 2012. A fifteen receivers network was deployed on the landslide of Super-Sauze (French Alps) for a two months trial. The experimental area, the deployed network and the acquisition protocol are presented. Position time series with a 30 seconds sampling rate are then derived from raw data for 10 mobile receivers on a forty days session. A sub-centimetric accuracy on an epoch by epoch positioning is reached despite difficult field conditions due to a 40° elevation mask in the south direction. Then, the measured deformations are compared with in situ rainfall measurements collected by a dedicated sensor added to a Geocube on a network's node.

Landslide monitoring using Geocubes, a wireless network of low-cost GPS receivers.

NASA Astrophysics Data System (ADS)

Benoit, Lionel; Thom, Christian; Martin, Olivier

2013-04-01

Many geophysical structures such as landslides, glaciers or even volcanoes are features characterized by small extend area and deformation rate in the order of 1 to 10cm per day. Their study needs ever more accurate positioning data with an increased space and time resolution. Using an Ublox LEA-6T GPS receiver, the French national mapping agency IGN developed its own wireless multi-sensor geo-monitoring system named Geocube. The basic device is equipped with a GPS and a wireless communication media and can be completed with various sensor modules such as meteorological sensors, ground humidity and pressure or seismograph. Due to the low cost of each receiver, spatial dense surveying networks are deployed. Data are then continuously collected and transmitted to a processing computer in real-time as well as saved in situ on a Micro-SD card. Among them, raw GPS carrier phase data give access to real-time accurate relative positioning on all mesh nodes if small baselines are used. In order to achieve a high accuracy, a dedicated GPS data processing method based on a Kalman filter is proposed. It allows an epoch by epoch positioning providing a high time resolution. Special attention is paid on two points : adaptation to wireless networks of low-cost GPS and real-time ability. A first test of Geocubes usability under field conditions was carried out during summer 2012. A fifteen receivers network was deployed on the landslide of Super-Sauze (French Alps) for a two months trial. The experimental area, the deployed network and the acquisition protocol are presented. Position time series with a 30 seconds sampling rate are then derived from raw data for 10 mobile receivers on a forty days session. A sub-centimetric accuracy on an epoch by epoch positioning is reached despite difficult field conditions due to a 40° elevation mask in the south direction. Then, the measured deformations are compared with in situ rainfall measurements collected by a dedicated sensor added to a Geocube on a network's node.

Resilient Sensor Networks with Spatiotemporal Interpolation of Missing Sensors: An Example of Space Weather Forecasting by Multiple Satellites

PubMed Central

Tokumitsu, Masahiro; Hasegawa, Keisuke; Ishida, Yoshiteru

2016-01-01

This paper attempts to construct a resilient sensor network model with an example of space weather forecasting. The proposed model is based on a dynamic relational network. Space weather forecasting is vital for a satellite operation because an operational team needs to make a decision for providing its satellite service. The proposed model is resilient to failures of sensors or missing data due to the satellite operation. In the proposed model, the missing data of a sensor is interpolated by other sensors associated. This paper demonstrates two examples of space weather forecasting that involves the missing observations in some test cases. In these examples, the sensor network for space weather forecasting continues a diagnosis by replacing faulted sensors with virtual ones. The demonstrations showed that the proposed model is resilient against sensor failures due to suspension of hardware failures or technical reasons. PMID:27092508

Resilient Sensor Networks with Spatiotemporal Interpolation of Missing Sensors: An Example of Space Weather Forecasting by Multiple Satellites.

PubMed

Tokumitsu, Masahiro; Hasegawa, Keisuke; Ishida, Yoshiteru

2016-04-15

This paper attempts to construct a resilient sensor network model with an example of space weather forecasting. The proposed model is based on a dynamic relational network. Space weather forecasting is vital for a satellite operation because an operational team needs to make a decision for providing its satellite service. The proposed model is resilient to failures of sensors or missing data due to the satellite operation. In the proposed model, the missing data of a sensor is interpolated by other sensors associated. This paper demonstrates two examples of space weather forecasting that involves the missing observations in some test cases. In these examples, the sensor network for space weather forecasting continues a diagnosis by replacing faulted sensors with virtual ones. The demonstrations showed that the proposed model is resilient against sensor failures due to suspension of hardware failures or technical reasons.

An energy-efficient and secure hybrid algorithm for wireless sensor networks using a mobile data collector

NASA Astrophysics Data System (ADS)

Dayananda, Karanam Ravichandran; Straub, Jeremy

2017-05-01

This paper proposes a new hybrid algorithm for security, which incorporates both distributed and hierarchal approaches. It uses a mobile data collector (MDC) to collect information in order to save energy of sensor nodes in a wireless sensor network (WSN) as, in most networks, these sensor nodes have limited energy. Wireless sensor networks are prone to security problems because, among other things, it is possible to use a rogue sensor node to eavesdrop on or alter the information being transmitted. To prevent this, this paper introduces a security algorithm for MDC-based WSNs. A key use of this algorithm is to protect the confidentiality of the information sent by the sensor nodes. The sensor nodes are deployed in a random fashion and form group structures called clusters. Each cluster has a cluster head. The cluster head collects data from the other nodes using the time-division multiple access protocol. The sensor nodes send their data to the cluster head for transmission to the base station node for further processing. The MDC acts as an intermediate node between the cluster head and base station. The MDC, using its dynamic acyclic graph path, collects the data from the cluster head and sends it to base station. This approach is useful for applications including warfighting, intelligent building and medicine. To assess the proposed system, the paper presents a comparison of its performance with other approaches and algorithms that can be used for similar purposes.

Moball-Buoy Network: A Near-Real-Time Ground-Truth Distributed Monitoring System to Map Ice, Weather, Chemical Species, and Radiations, in the Arctic

NASA Astrophysics Data System (ADS)

Davoodi, F.; Shahabi, C.; Burdick, J.; Rais-Zadeh, M.; Menemenlis, D.

2014-12-01

The work had been funded by NASA HQ's office of Cryospheric Sciences Program. Recent observations of the Arctic have shown that sea ice has diminished drastically, consequently impacting the environment in the Arctic and beyond. Certain factors such as atmospheric anomalies, wind forces, temperature increase, and change in the distribution of cold and warm waters contribute to the sea ice reduction. However current measurement capabilities lack the accuracy, temporal sampling, and spatial coverage required to effectively quantify each contributing factor and to identify other missing factors. Addressing the need for new measurement capabilities for the new Arctic regime, we propose a game-changing in-situ Arctic-wide Distributed Mobile Monitoring system called Moball-buoy Network. Moball-buoy Network consists of a number of wind-propelled self-powered inflatable spheres referred to as Moball-buoys. The Moball-buoys are self-powered. They use their novel mechanical control and energy harvesting system to use the abundance of wind in the Arctic for their controlled mobility and energy harvesting. They are equipped with an array of low-power low-mass sensors and micro devices able to measure a wide range of environmental factors such as the ice conditions, chemical species wind vector patterns, cloud coverage, air temperature and pressure, electromagnetic fields, surface and subsurface water conditions, short- and long-wave radiations, bathymetry, and anthropogenic factors such as pollutions. The stop-and-go motion capability, using their novel mechanics, and the heads up cooperation control strategy at the core of the proposed distributed system enable the sensor network to be reconfigured dynamically according to the priority of the parameters to be monitored. The large number of Moball-buoys with their ground-based, sea-based, satellite and peer-to-peer communication capabilities would constitute a wireless mesh network that provides an interface for a global control system. This control system will ensure arctic-wide coverage, will optimize Moball-buoys monitoring efforts according to their available resources and the priority of local areas of high scientific value within the Arctic region. Moball-buoy Network is expected to be the first robust and persistent Arctic-wide environment monitoring system capable of providing reliable readings in near real time

An Energy-Efficient Secure Routing and Key Management Scheme for Mobile Sinks in Wireless Sensor Networks Using Deployment Knowledge

PubMed Central

Hung, Le Xuan; Canh, Ngo Trong; Lee, Sungyoung; Lee, Young-Koo; Lee, Heejo

2008-01-01

For many sensor network applications such as military or homeland security, it is essential for users (sinks) to access the sensor network while they are moving. Sink mobility brings new challenges to secure routing in large-scale sensor networks. Previous studies on sink mobility have mainly focused on efficiency and effectiveness of data dissemination without security consideration. Also, studies and experiences have shown that considering security during design time is the best way to provide security for sensor network routing. This paper presents an energy-efficient secure routing and key management for mobile sinks in sensor networks, called SCODEplus. It is a significant extension of our previous study in five aspects: (1) Key management scheme and routing protocol are considered during design time to increase security and efficiency; (2) The network topology is organized in a hexagonal plane which supports more efficiency than previous square-grid topology; (3) The key management scheme can eliminate the impacts of node compromise attacks on links between non-compromised nodes; (4) Sensor node deployment is based on Gaussian distribution which is more realistic than uniform distribution; (5) No GPS or like is required to provide sensor node location information. Our security analysis demonstrates that the proposed scheme can defend against common attacks in sensor networks including node compromise attacks, replay attacks, selective forwarding attacks, sinkhole and wormhole, Sybil attacks, HELLO flood attacks. Both mathematical and simulation-based performance evaluation show that the SCODEplus significantly reduces the communication overhead, energy consumption, packet delivery latency while it always delivers more than 97 percent of packets successfully. PMID:27873956

An Energy-Efficient Secure Routing and Key Management Scheme for Mobile Sinks in Wireless Sensor Networks Using Deployment Knowledge.

PubMed

Hung, Le Xuan; Canh, Ngo Trong; Lee, Sungyoung; Lee, Young-Koo; Lee, Heejo

2008-12-03

For many sensor network applications such as military or homeland security, it is essential for users (sinks) to access the sensor network while they are moving. Sink mobility brings new challenges to secure routing in large-scale sensor networks. Previous studies on sink mobility have mainly focused on efficiency and effectiveness of data dissemination without security consideration. Also, studies and experiences have shown that considering security during design time is the best way to provide security for sensor network routing. This paper presents an energy-efficient secure routing and key management for mobile sinks in sensor networks, called SCODE plus . It is a significant extension of our previous study in five aspects: (1) Key management scheme and routing protocol are considered during design time to increase security and efficiency; (2) The network topology is organized in a hexagonal plane which supports more efficiency than previous square-grid topology; (3) The key management scheme can eliminate the impacts of node compromise attacks on links between non-compromised nodes; (4) Sensor node deployment is based on Gaussian distribution which is more realistic than uniform distribution; (5) No GPS or like is required to provide sensor node location information. Our security analysis demonstrates that the proposed scheme can defend against common attacks in sensor networks including node compromise attacks, replay attacks, selective forwarding attacks, sinkhole and wormhole, Sybil attacks, HELLO flood attacks. Both mathematical and simulation-based performance evaluation show that the SCODE plus significantly reduces the communication overhead, energy consumption, packet delivery latency while it always delivers more than 97 percent of packets successfully.

Monitoring the Environmental Impact of TiO2 Nanoparticles Using a Plant-Based Sensor Network

PubMed Central

Lenaghan, Scott C.; Li, Yuanyuan; Zhang, Hao; Burris, Jason N.; Stewart, C. Neal; Parker, Lynne E.; Zhang, Mingjun

2016-01-01

The increased manufacturing of nanoparticles for use in cosmetics, foods, and clothing necessitates the need for an effective system to monitor and evaluate the potential environmental impact of these nanoparticles. The goal of this research was to develop a plant-based sensor network for characterizing, monitoring, and understanding the environmental impact of TiO2 nanoparticles. The network consisted of potted Arabidopsis thaliana with a surrounding water supply, which was monitored by cameras attached to a laptop computer running a machine learning algorithm. Using the proposed plant sensor network, we were able to examine the toxicity of TiO2 nanoparticles in two systems: algae and terrestrial plants. Increased terrestrial plant growth was observed upon introduction of the nanoparticles, whereas algal growth decreased significantly. The proposed system can be further automated for high-throughput screening of nanoparticle toxicity in the environment at multiple trophic levels. The proposed plant-based sensor network could be used for more accurate characterization of the environmental impact of nanomaterials. PMID:28458617

A software sensor model based on hybrid fuzzy neural network for rapid estimation water quality in Guangzhou section of Pearl River, China.

PubMed

Zhou, Chunshan; Zhang, Chao; Tian, Di; Wang, Ke; Huang, Mingzhi; Liu, Yanbiao

2018-01-02

In order to manage water resources, a software sensor model was designed to estimate water quality using a hybrid fuzzy neural network (FNN) in Guangzhou section of Pearl River, China. The software sensor system was composed of data storage module, fuzzy decision-making module, neural network module and fuzzy reasoning generator module. Fuzzy subtractive clustering was employed to capture the character of model, and optimize network architecture for enhancing network performance. The results indicate that, on basis of available on-line measured variables, the software sensor model can accurately predict water quality according to the relationship between chemical oxygen demand (COD) and dissolved oxygen (DO), pH and NH 4 + -N. Owing to its ability in recognizing time series patterns and non-linear characteristics, the software sensor-based FNN is obviously superior to the traditional neural network model, and its R (correlation coefficient), MAPE (mean absolute percentage error) and RMSE (root mean square error) are 0.8931, 10.9051 and 0.4634, respectively.

Adaptive neural network/expert system that learns fault diagnosis for different structures

NASA Astrophysics Data System (ADS)

Simon, Solomon H.

1992-08-01

Corporations need better real-time monitoring and control systems to improve productivity by watching quality and increasing production flexibility. The innovative technology to achieve this goal is evolving in the form artificial intelligence and neural networks applied to sensor processing, fusion, and interpretation. By using these advanced Al techniques, we can leverage existing systems and add value to conventional techniques. Neural networks and knowledge-based expert systems can be combined into intelligent sensor systems which provide real-time monitoring, control, evaluation, and fault diagnosis for production systems. Neural network-based intelligent sensor systems are more reliable because they can provide continuous, non-destructive monitoring and inspection. Use of neural networks can result in sensor fusion and the ability to model highly, non-linear systems. Improved models can provide a foundation for more accurate performance parameters and predictions. We discuss a research software/hardware prototype which integrates neural networks, expert systems, and sensor technologies and which can adapt across a variety of structures to perform fault diagnosis. The flexibility and adaptability of the prototype in learning two structures is presented. Potential applications are discussed.

Fusion of remotely sensed data from airborne and ground-based sensors for cotton regrowth study

USDA-ARS?s Scientific Manuscript database

The study investigated the use of aerial multispectral imagery and ground-based hyperspectral data for the discrimination of different crop types and timely detection of cotton plants over large areas. Airborne multispectral imagery and ground-based spectral reflectance data were acquired at the sa...

A virtual remote sensing observation network for continuous, near-real-time monitoring of atmospheric instability

NASA Astrophysics Data System (ADS)

Toporov, Maria; Löhnert, Ulrich; Potthast, Roland; Cimini, Domenico; De Angelis, Francesco

2017-04-01

Short-term forecasts of current high-resolution numerical weather prediction models still have large deficits in forecasting the exact temporal and spatial location of severe, locally influenced weather such as summer-time convective storms or cool season lifted stratus or ground fog. Often, the thermodynamic instability - especially in the boundary layer - plays an essential role in the evolution of weather events. While the thermodynamic state of the atmosphere is well measured close to the surface (i.e. 2 m) by in-situ sensors and in the upper troposphere by satellite sounders, the planetary boundary layer remains a largely under-sampled region of the atmosphere where only sporadic information from radiosondes or aircraft observations is available. The major objective of the presented DWD-funded project ARON (Extramural Research Programme) is to overcome this observational gap and to design an optimized network of ground based microwave radiometers (MWR) and compact Differential Absorption Lidars (DIAL) for a continuous, near-real-time monitoring of temperature and humidity in the atmospheric boundary layer in order to monitor thermodynamic (in)stability. Previous studies showed, that microwave profilers are well suited for continuously monitoring the temporal development of atmospheric stability (i.e. Cimini et al., 2015) before the initiation of deep convection, especially in the atmospheric boundary layer. However, the vertical resolution of microwave temperature profiles is best in the lowest kilometer above the surface, decreasing rapidly with increasing height. In addition, humidity profile retrievals typically cannot be resolved with more than two degrees of freedom for signal, resulting in a rather poor vertical resolution throughout the troposphere. Typical stability indices used to assess the potential of convection rely on temperature and humidity values not only in the region of the boundary layer but also in the layers above. Therefore, satellite remote sensing (i.e. SEVIRI, AMSU) is used to complement observations from a virtual ground-based microwave radiometer network based on the reanalysis of the COSMO model for Europe. In this contribution, we present a synergetic retrieval algorithm of stability indices from satellite observations and ground-based microwave measurements based on the COSMO-DE reanalysis as truth. In order to make the approach feasible for data assimilation applications at national weather services, we simulate satellite observations with the standard RTTOV model and use the newly developed RTTOV-gb (ground-based) for the ground-based radiometers (De Angelis et al., 2016). For the detection of significant instabilities, we show the synergy benefit in terms of uncertainty reduction, probability of detection and other forecast skill scores. The overall goal of ARON is to quantify the impact of ground-based vertical profilers within an integrated forecasting system, which combines short-term and now-casting.

Analysis of lightning outliers in the EUCLID network

NASA Astrophysics Data System (ADS)

Poelman, Dieter R.; Schulz, Wolfgang; Kaltenboeck, Rudolf; Delobbe, Laurent

2017-11-01

Lightning data as observed by the European Cooperation for Lightning Detection (EUCLID) network are used in combination with radar data to retrieve the temporal and spatial behavior of lightning outliers, i.e., discharges located in a wrong place, over a 5-year period from 2011 to 2016. Cloud-to-ground (CG) stroke and intracloud (IC) pulse data are superimposed on corresponding 5 min radar precipitation fields in two topographically different areas, Belgium and Austria, in order to extract lightning outliers based on the distance between each lightning event and the nearest precipitation. It is shown that the percentage of outliers is sensitive to changes in the network and to the location algorithm itself. The total percentage of outliers for both regions varies over the years between 0.8 and 1.7 % for a distance to the nearest precipitation of 2 km, with an average of approximately 1.2 % in Belgium and Austria. Outside the European summer thunderstorm season, the percentage of outliers tends to increase somewhat. The majority of all the outliers are low peak current events with absolute values falling between 0 and 10 kA. More specifically, positive cloud-to-ground strokes are more likely to be classified as outliers compared to all other types of discharges. Furthermore, it turns out that the number of sensors participating in locating a lightning discharge is different for outliers versus correctly located events, with outliers having the lowest amount of sensors participating. In addition, it is shown that in most cases the semi-major axis (SMA) assigned to a lightning discharge as a confidence indicator in the location accuracy (LA) is smaller for correctly located events compared to the semi-major axis of outliers.

Design and simulation of sensor networks for tracking Wifi users in outdoor urban environments

NASA Astrophysics Data System (ADS)

Thron, Christopher; Tran, Khoi; Smith, Douglas; Benincasa, Daniel

2017-05-01

We present a proof-of-concept investigation into the use of sensor networks for tracking of WiFi users in outdoor urban environments. Sensors are fixed, and are capable of measuring signal power from users' WiFi devices. We derive a maximum likelihood estimate for user location based on instantaneous sensor power measurements. The algorithm takes into account the effects of power control, and is self-calibrating in that the signal power model used by the location algorithm is adjusted and improved as part of the operation of the network. Simulation results to verify the system's performance are presented. The simulation scenario is based on a 1.5 km2 area of lower Manhattan, The self-calibration mechanism was verified for initial rms (root mean square) errors of up to 12 dB in the channel power estimates: rms errors were reduced by over 60% in 300 track-hours, in systems with limited power control. Under typical operating conditions with (without) power control, location rms errors are about 8.5 (5) meters with 90% accuracy within 9 (13) meters, for both pedestrian and vehicular users. The distance error distributions for smaller distances (<30 m) are well-approximated by an exponential distribution, while the distributions for large distance errors have fat tails. The issue of optimal sensor placement in the sensor network is also addressed. We specify a linear programming algorithm for determining sensor placement for networks with reduced number of sensors. In our test case, the algorithm produces a network with 18.5% fewer sensors with comparable accuracy estimation performance. Finally, we discuss future research directions for improving the accuracy and capabilities of sensor network systems in urban environments.

On Prolonging Network Lifetime through Load-Similar Node Deployment in Wireless Sensor Networks

PubMed Central

Li, Qiao-Qin; Gong, Haigang; Liu, Ming; Yang, Mei; Zheng, Jun

2011-01-01

This paper is focused on the study of the energy hole problem in the Progressive Multi-hop Rotational Clustered (PMRC)-structure, a highly scalable wireless sensor network (WSN) architecture. Based on an analysis on the traffic load distribution in PMRC-based WSNs, we propose a novel load-similar node distribution strategy combined with the Minimum Overlapping Layers (MOL) scheme to address the energy hole problem in PMRC-based WSNs. In this strategy, sensor nodes are deployed in the network area according to the load distribution. That is, more nodes shall be deployed in the range where the average load is higher, and then the loads among different areas in the sensor network tend to be balanced. Simulation results demonstrate that the load-similar node distribution strategy prolongs network lifetime and reduces the average packet latency in comparison with existing nonuniform node distribution and uniform node distribution strategies. Note that, besides the PMRC structure, the analysis model and the proposed load-similar node distribution strategy are also applicable to other multi-hop WSN structures. PMID:22163809

A network coding based routing protocol for underwater sensor networks.

PubMed

Wu, Huayang; Chen, Min; Guan, Xin

2012-01-01

Due to the particularities of the underwater environment, some negative factors will seriously interfere with data transmission rates, reliability of data communication, communication range, and network throughput and energy consumption of underwater sensor networks (UWSNs). Thus, full consideration of node energy savings, while maintaining a quick, correct and effective data transmission, extending the network life cycle are essential when routing protocols for underwater sensor networks are studied. In this paper, we have proposed a novel routing algorithm for UWSNs. To increase energy consumption efficiency and extend network lifetime, we propose a time-slot based routing algorithm (TSR).We designed a probability balanced mechanism and applied it to TSR. The theory of network coding is introduced to TSBR to meet the requirement of further reducing node energy consumption and extending network lifetime. Hence, time-slot based balanced network coding (TSBNC) comes into being. We evaluated the proposed time-slot based balancing routing algorithm and compared it with other classical underwater routing protocols. The simulation results show that the proposed protocol can reduce the probability of node conflicts, shorten the process of routing construction, balance energy consumption of each node and effectively prolong the network lifetime.

A Network Coding Based Routing Protocol for Underwater Sensor Networks

PubMed Central

Wu, Huayang; Chen, Min; Guan, Xin

2012-01-01

Due to the particularities of the underwater environment, some negative factors will seriously interfere with data transmission rates, reliability of data communication, communication range, and network throughput and energy consumption of underwater sensor networks (UWSNs). Thus, full consideration of node energy savings, while maintaining a quick, correct and effective data transmission, extending the network life cycle are essential when routing protocols for underwater sensor networks are studied. In this paper, we have proposed a novel routing algorithm for UWSNs. To increase energy consumption efficiency and extend network lifetime, we propose a time-slot based routing algorithm (TSR).We designed a probability balanced mechanism and applied it to TSR. The theory of network coding is introduced to TSBR to meet the requirement of further reducing node energy consumption and extending network lifetime. Hence, time-slot based balanced network coding (TSBNC) comes into being. We evaluated the proposed time-slot based balancing routing algorithm and compared it with other classical underwater routing protocols. The simulation results show that the proposed protocol can reduce the probability of node conflicts, shorten the process of routing construction, balance energy consumption of each node and effectively prolong the network lifetime. PMID:22666045

Coordinated Ground- and Space-based Multispectral Campaign to Study Equatorial Spread-F Formation

NASA Astrophysics Data System (ADS)

Finn, S. C.; Geddes, G.; Aryal, S.; Stephan, A. W.; Budzien, S. A.; Duggirala, P. R.; Chakrabarti, S.; Valladares, C.

2016-12-01

We present a concept for a multispectral campaign using coordinated data from state-of-the-art instruments aboard the International Space Station (ISS) and multiple ground-based spectrometers and digisondes deployed at low-latitudes to study the formation and development of Equatorial Spread-F (ESF). This extended observational campaign utilizes ultraviolet, visible, and radio measurements to develop a predictive capability for ESF and to study the coupling of the ionosphere-thermosphere (I-T) system during geomagnetically quiet and disturbed times. The ground-based instruments will be deployed in carefully chosen locations in the American and Indian sectors while the space-based data will provide global coverage spanning all local times and longitudes within ±51° geographic latitudes. The campaign, over an extended period covering a range of geophysical conditions, will provide the extensive data base necessary to address the important science questions. The space-based instrument suite consists of the Limb-imaging Ionospheric and Thermospheric Extreme-ultraviolet Spectrograph (LITES) and the GPS Radio Occultation and Ultraviolet Photometry-Colocated (GROUP-C) instruments, scheduled to launch to the ISS in November 2016. LITES is a compact imaging spectrograph for remote sensing of the upper atmosphere and ionosphere from 60 to 140nm and GROUP-C has a nadir-viewing FUV photometer. The ground-based instruments to be deployed for this campaign are three high-resolution imaging spectrographs capable of continuous round-the-clock airglow observations: Multiwavelength Imaging Spectrograph using Echelle grating (MISE) in India and two High Throughput and Multi-slit Imaging Spectrographs (HiT&MIS) to be deployed in Colombia and Argentina, the Low-Latitude Ionosphere Sensor Network (LISN), and the Global Ionospheric Radio Observatory (GIRO) digisondes network. We present data from the ground-based instruments, initial results from the LITES and GROUP-C instruments on-orbit, and modeling and analysis methods for the campaign. This work was supported by NSF 1315354 and 1145166, and ONR N00014-13-1-0266 grants. LITES and GROUP-C are part of the STP-H5 Payload, integrated and flown under the direction of the DoD Space Test Program.

Rapid-response Sensor Networks Leveraging Open Standards and the Internet of Things

NASA Astrophysics Data System (ADS)

Bermudez, L. E.; Lieberman, J. E.; Lewis, L.; Botts, M.; Liang, S.

2016-12-01

New sensor technologies provide an unparalleled capability to collect large numbers of diverse observations about the world around us. Networks of such sensors are especially effective for capturing and analyzing unexpected, fast moving events if they can be deployed with a minimum of time, effort, and cost. A rapid-response sensing and processing capability is extremely important in quickly unfolding events not only to collect data for future research.but also to support response efforts that may be needed by providing up-to-date knowledge of the situation. A recent pilot activity coordinated by the Open Geospatial Consortium combined Sensor Web Enablement (SWE) standards with Internet of Things (IoT) practices to understand better how to set up rapid-response sensor networks in comparable event situations involving accidents or disasters. The networks included weather and environmental sensors, georeferenced UAV and PTZ imagery collectors, and observations from "citizen sensors", as well as virtual observations generated by predictive models. A key feature of each "SWE-IoT" network was one or more Sensor Hubs that connected local, often proprietary sensor device protocols to a common set of standard SWE data types and standard Web interfaces on an IP-based internetwork. This IoT approach provided direct, common, interoperable access to all sensor readings from anywhere on the internetwork of sensors, Hubs, and applications. Sensor Hubs also supported an automated discovery protocol in which activated Hubs registered themselves with a canonical catalog service. As each sensor (wireless or wired) was activated within range of an authorized Hub, it registered itself with that Hub, which in turn registered the sensor and its capabilities with the catalog. Sensor Hub functions were implemented in a range of component types, from personal devices such as smartphones and Raspberry Pi's to full cloud-based sensor services platforms. Connected into a network "constellation" the Hubs also enabled reliable exchange and persistence of sensor data in constrained communications environments. Pilot results are being documented in public OGC engineering reports and are feeding into improved standards to support SWE-IoT networks for a range of domains and applications.

Kestrel: force protection and Intelligence, Surveillance, and Reconnaissance (ISR) persistent surveillance on aerostats

NASA Astrophysics Data System (ADS)

Luber, David R.; Marion, John E.; Fields, David

2012-05-01

Logos Technologies has developed and fielded the Kestrel system, an aerostat-based, wide area persistent surveillance system dedicated to force protection and ISR mission execution operating over forward operating bases. Its development included novel imaging and stabilization capability for day/night operations on military aerostat systems. The Kestrel system's contribution is a substantial enhancement to aerostat-based, force protection systems which to date have relied on narrow field of view ball gimbal sensors to identify targets of interest. This inefficient mechanism to conduct wide area field of view surveillance is greatly enhanced by Kestrel's ability to maintain a constant motion imagery stare of the entire forward operating base (FOB) area. The Kestrel airborne sensor enables 360° coverage out to extended ranges which covers a city sized area at moderate resolution, while cueing a narrow field of view sensor to provide high resolution imagery of targets of interest. The ground station exploitation system enables operators to autonomously monitor multiple regions of interest in real time, and allows for backtracking through the recorded imagery, while continuing to monitor ongoing activity. Backtracking capability allows operators to detect threat networks, their CONOPS, and locations of interest. Kestrel's unique advancement has already been utilized successfully in OEF operations.

CMOS: Efficient Clustered Data Monitoring in Sensor Networks

PubMed Central

2013-01-01

Tiny and smart sensors enable applications that access a network of hundreds or thousands of sensors. Thus, recently, many researchers have paid attention to wireless sensor networks (WSNs). The limitation of energy is critical since most sensors are battery-powered and it is very difficult to replace batteries in cases that sensor networks are utilized outdoors. Data transmission between sensor nodes needs more energy than computation in a sensor node. In order to reduce the energy consumption of sensors, we present an approximate data gathering technique, called CMOS, based on the Kalman filter. The goal of CMOS is to efficiently obtain the sensor readings within a certain error bound. In our approach, spatially close sensors are grouped as a cluster. Since a cluster header generates approximate readings of member nodes, a user query can be answered efficiently using the cluster headers. In addition, we suggest an energy efficient clustering method to distribute the energy consumption of cluster headers. Our simulation results with synthetic data demonstrate the efficiency and accuracy of our proposed technique. PMID:24459444

CMOS: efficient clustered data monitoring in sensor networks.

PubMed

Min, Jun-Ki

2013-01-01

Tiny and smart sensors enable applications that access a network of hundreds or thousands of sensors. Thus, recently, many researchers have paid attention to wireless sensor networks (WSNs). The limitation of energy is critical since most sensors are battery-powered and it is very difficult to replace batteries in cases that sensor networks are utilized outdoors. Data transmission between sensor nodes needs more energy than computation in a sensor node. In order to reduce the energy consumption of sensors, we present an approximate data gathering technique, called CMOS, based on the Kalman filter. The goal of CMOS is to efficiently obtain the sensor readings within a certain error bound. In our approach, spatially close sensors are grouped as a cluster. Since a cluster header generates approximate readings of member nodes, a user query can be answered efficiently using the cluster headers. In addition, we suggest an energy efficient clustering method to distribute the energy consumption of cluster headers. Our simulation results with synthetic data demonstrate the efficiency and accuracy of our proposed technique.

Sensor network based vehicle classification and license plate identification system

DOE Office of Scientific and Technical Information (OSTI.GOV)

Frigo, Janette Rose; Brennan, Sean M; Rosten, Edward J

Typically, for energy efficiency and scalability purposes, sensor networks have been used in the context of environmental and traffic monitoring applications in which operations at the sensor level are not computationally intensive. But increasingly, sensor network applications require data and compute intensive sensors such video cameras and microphones. In this paper, we describe the design and implementation of two such systems: a vehicle classifier based on acoustic signals and a license plate identification system using a camera. The systems are implemented in an energy-efficient manner to the extent possible using commercially available hardware, the Mica motes and the Stargate platform.more » Our experience in designing these systems leads us to consider an alternate more flexible, modular, low-power mote architecture that uses a combination of FPGAs, specialized embedded processing units and sensor data acquisition systems.« less

An evaluation of commercial NDIR sensors for a potential use in future urban GHG monitoring systems

NASA Astrophysics Data System (ADS)

Arzoumanian, E.; Bastos, A.; Gaynullin, B.; Martin, H.; Hjern, L.; Laurent, O.; Vogel, F. R.

2016-12-01

Cities are a key contributor to climate change, as urban activities are major sources of GHG emissions. It is clear that accurate estimates of the magnitude of anthropogenic and natural urban emissions are needed to assess their influence on the carbon balance. Recently Wu et al. (2016) suggested that a denser ground-based GHG monitoring network in Paris would have the potential allow retrieving sector specific GHG emission estimates (and potentially in certain other cities) when combined with an atmospheric inversion framework using reasonably accurate observations (ca. 1 ppm for hourly means). One major barrier for such denser observations can be the high cost of high-precision instruments or high calibration cost of cheaper, unstable instrumentation. Within a recent climate KIC project, LSCE and SenseAir AB have worked on novel inexpensive NDIR sensors for CO2 measurements for site and city-scale applications that fulfil typical repeatability and reproducibility requirements necessary for this task. We conducted laboratory tests on six prototypes and determined the sensitivity of the sensors to multiple parameters, e.g. changing pressure, temperature and water vapor. Also, we developed a correction and calibration strategy for our NDIR sensors. Furthermore, we fully integrated these NDIR sensors in a platform containing the CO2sensor, pressure and temperature sensors, gas supply pump and a fully automated data acquisition unit. This platform was deployed in parallel to Picarro G2401 instruments in the urban network of LSCE. In this field experiment, using weekly calibration, we find a root-mean-square difference of less than 1 ppm for hourly mean concentrations at the semi-urban site in Saclay and the urban site of Jussieu, Paris, France. Our recent results concerning sensor testing and CO2monitoring from the two sites sited above also guide our recommendations for a low cost urban environmental monitoring system based on open source hardware (Raspberry Pi) and software. Wu, L., Broquet, G., Ciais, P., Bellassen, V., Vogel, F., Chevallier, F., Xueref-Remy, I. and Wang, Y., 2015. Atmospheric inversion for cost effective quantification of city CO 2 emissions. Atmospheric Chemistry and Physics Discussions, 15(21), pp.30693-30756, accepted for publication in AMT.

Recent progress in distributed optical fiber Raman photon sensors at China Jiliang University

NASA Astrophysics Data System (ADS)

Zhang, Zaixuan; Wang, Jianfeng; Li, Yi; Gong, Huaping; Yu, Xiangdong; Liu, Honglin; Jin, Yongxing; Kang, Juan; Li, Chenxia; Zhang, Wensheng; Zhang, Wenping; Niu, Xiaohui; Sun, Zhongzhou; Zhao, Chunliu; Dong, Xinyong; Jin, Shangzhong

2012-06-01

A brief review of recent progress in researches, productions and applications of full distributed fiber Raman photon sensors at China Jiliang University (CJLU) is presented. In order to improve the measurement distance, the accuracy, the space resolution, the ability of multi-parameter measurements, and the intelligence of full distributed fiber sensor systems, a new generation fiber sensor technology based on the optical fiber nonlinear scattering fusion principle is proposed. A series of new generation full distributed fiber sensors are investigated and designed, which consist of new generation ultra-long distance full distributed fiber Raman and Rayleigh scattering photon sensors integrated with a fiber Raman amplifier, auto-correction full distributed fiber Raman photon temperature sensors based on Raman correlation dual sources, full distributed fiber Raman photon temperature sensors based on a pulse coding source, full distributed fiber Raman photon temperature sensors using a fiber Raman wavelength shifter, a new type of Brillouin optical time domain analyzers (BOTDAs) integrated with a fiber Raman amplifier for replacing a fiber Brillouin amplifier, full distributed fiber Raman and Brillouin photon sensors integrated with a fiber Raman amplifier, and full distributed fiber Brillouin photon sensors integrated with a fiber Brillouin frequency shifter. The Internet of things is believed as one of candidates of the next technological revolution, which has driven hundreds of millions of class markets. Sensor networks are important components of the Internet of things. The full distributed optical fiber sensor network (Rayleigh, Raman, and Brillouin scattering) is a 3S (smart materials, smart structure, and smart skill) system, which is easy to construct smart fiber sensor networks. The distributed optical fiber sensor can be embedded in the power grids, railways, bridges, tunnels, roads, constructions, water supply systems, dams, oil and gas pipelines and other facilities, and can be integrated with wireless networks.

Fuzzy Logic Based Anomaly Detection for Embedded Network Security Cyber Sensor

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ondrej Linda; Todd Vollmer; Jason Wright

Resiliency and security in critical infrastructure control systems in the modern world of cyber terrorism constitute a relevant concern. Developing a network security system specifically tailored to the requirements of such critical assets is of a primary importance. This paper proposes a novel learning algorithm for anomaly based network security cyber sensor together with its hardware implementation. The presented learning algorithm constructs a fuzzy logic rule based model of normal network behavior. Individual fuzzy rules are extracted directly from the stream of incoming packets using an online clustering algorithm. This learning algorithm was specifically developed to comply with the constrainedmore » computational requirements of low-cost embedded network security cyber sensors. The performance of the system was evaluated on a set of network data recorded from an experimental test-bed mimicking the environment of a critical infrastructure control system.« less

Providing Self-Healing Ability for Wireless Sensor Node by Using Reconfigurable Hardware

PubMed Central

Yuan, Shenfang; Qiu, Lei; Gao, Shang; Tong, Yao; Yang, Weiwei

2012-01-01

Wireless sensor networks (WSNs) have received tremendous attention over the past ten years. In engineering applications of WSNs, a number of sensor nodes are usually spread across some specific geographical area. Some of these nodes have to work in harsh environments. Dependability of the Wireless Sensor Network (WSN) is very important for its successful applications in the engineering area. In ordinary research, when a node has a failure, it is usually discarded and the network is reorganized to ensure the normal operation of the WSN. Using appropriate WSN re-organization methods, though the sensor networks can be reorganized, this causes additional maintenance costs and sometimes still decreases the function of the networks. In those situations where the sensor networks cannot be reorganized, the performance of the whole WSN will surely be degraded. In order to ensure the reliable and low cost operation of WSNs, a method to develop a wireless sensor node with self-healing ability based on reconfigurable hardware is proposed in this paper. Two self-healing WSN node realization paradigms based on reconfigurable hardware are presented, including a redundancy-based self-healing paradigm and a whole FPAA/FPGA based self-healing paradigm. The nodes designed with the self-healing ability can dynamically change their node configurations to repair the nodes' hardware failures. To demonstrate these two paradigms, a strain sensor node is adopted as an illustration to show the concepts. Two strain WSN sensor nodes with self-healing ability are developed respectively according to the proposed self-healing paradigms. Evaluation experiments on self-healing ability and power consumption are performed. Experimental results show that the developed nodes can self-diagnose the failures and recover to a normal state automatically. The research presented can improve the robustness of WSNs and reduce the maintenance cost of WSNs in engineering applications. PMID:23202176

Design and implementation of a secure wireless mote-based medical sensor network.

PubMed

Malasri, Kriangsiri; Wang, Lan

2009-01-01

A medical sensor network can wirelessly monitor vital signs of humans, making it useful for long-term health care without sacrificing patient comfort and mobility. For such a network to be viable, its design must protect data privacy and authenticity given that medical data are highly sensitive. We identify the unique security challenges of such a sensor network and propose a set of resource-efficient mechanisms to address these challenges. Our solution includes (1) a novel two-tier scheme for verifying the authenticity of patient data, (2) a secure key agreement protocol to set up shared keys between sensor nodes and base stations, and (3) symmetric encryption/decryption for protecting data confidentiality and integrity. We have implemented the proposed mechanisms on a wireless mote platform, and our results confirm their feasibility.

Citizen-sensor-networks to confront government decision-makers: Two lessons from the Netherlands.

PubMed

Carton, Linda; Ache, Peter

2017-07-01

This paper presents one emerging social-technical innovation: The evolution of citizen-sensor-networks where citizens organize themselves from the 'bottom up', for the sake of confronting governance officials with measured information about environmental qualities. We have observed how citizen-sensor-networks have been initiated in the Netherlands in cases where official government monitoring and business organizations leave gaps. The formed citizen-sensor-networks collect information about issues that affect the local community in their quality-of-living. In particular, two community initiatives are described where the sensed environmental information, on noise pollution and gas-extraction induced earthquakes respectively, is published through networked geographic information methods. Both community initiatives pioneered in developing an approach that comprises the combined setting-up of sensor data flows, real-time map portals and community organization. Two particular cases are analyzed to trace the emergence and network operation of such 'networked geo-information tools' in practice: (1) The Groningen earthquake monitor, and (2) The Airplane Monitor Schiphol. In both cases, environmental 'externalities' of spatial-economic activities play an important role, having economic dimensions of national importance (e.g. gas extraction and national airport development) while simultaneously affecting the regional community with environmental consequences. The monitoring systems analyzed in this paper are established bottom-up, by citizens for citizens, to serve as 'information power' in dialogue with government institutions. The goal of this paper is to gain insight in how these citizen-sensor-networks come about: how the idea for establishing a sensor network originated, how their value gets recognized and adopted in the overall 'system of governance'; to what extent they bring countervailing power against vested interests and established discourses to the table and influence power-laden conflicts over environmental pressures; and whether or not they achieve (some form of) institutionalization and, ultimately, policy change. We find that the studied-citizen-sensor networks gain strength by uniting efforts and activities in crowdsourcing data, providing factual, 'objectivized data' or 'evidence' of the situation 'on the ground' on a matter of local community-wide concern. By filling an information need of the local community, a process of 'collective sense-making' combined with citizen empowerment could grow, which influenced societal discourse and challenged prevailing truth-claims of public institutions. In both cases similar, 'competing' web-portals were developed in response, both by the gas-extraction company and the airport. But with the citizen-sensor-networks alongside, we conclude there is a shift in power balance involved between government and affected communities, as the government no longer has information monopoly on environmental measurements. Copyright © 2017 Elsevier Ltd. All rights reserved.

A Uniform Energy Consumption Algorithm for Wireless Sensor and Actuator Networks Based on Dynamic Polling Point Selection

PubMed Central

Li, Shuo; Peng, Jun; Liu, Weirong; Zhu, Zhengfa; Lin, Kuo-Chi

2014-01-01

Recent research has indicated that using the mobility of the actuator in wireless sensor and actuator networks (WSANs) to achieve mobile data collection can greatly increase the sensor network lifetime. However, mobile data collection may result in unacceptable collection delays in the network if the path of the actuator is too long. Because real-time network applications require meeting data collection delay constraints, planning the path of the actuator is a very important issue to balance the prolongation of the network lifetime and the reduction of the data collection delay. In this paper, a multi-hop routing mobile data collection algorithm is proposed based on dynamic polling point selection with delay constraints to address this issue. The algorithm can actively update the selection of the actuator's polling points according to the sensor nodes' residual energies and their locations while also considering the collection delay constraint. It also dynamically constructs the multi-hop routing trees rooted by these polling points to balance the sensor node energy consumption and the extension of the network lifetime. The effectiveness of the algorithm is validated by simulation. PMID:24451455

The Red Atrapa Sismos (Quake Catcher Network in Mexico): assessing performance during large and damaging earthquakes.

USGS Publications Warehouse

Dominguez, Luis A.; Yildirim, Battalgazi; Husker, Allen L.; Cochran, Elizabeth S.; Christensen, Carl; Cruz-Atienza, Victor M.

2015-01-01

Each volunteer computer monitors ground motion and communicates using the Berkeley Open Infrastructure for Network Computing (BOINC, Anderson, 2004). Using a standard short‐term average, long‐term average (STLA) algorithm (Earle and Shearer, 1994; Cochran, Lawrence, Christensen, Chung, 2009; Cochran, Lawrence, Christensen, and Jakka, 2009), volunteer computer and sensor systems detect abrupt changes in the acceleration recordings. Each time a possible trigger signal is declared, a small package of information containing sensor and ground‐motion information is streamed to one of the QCN servers (Chung et al., 2011). Trigger signals, correlated in space and time, are then processed by the QCN server to look for potential earthquakes.

Improving the Forecast Accuracy of an Ocean Observation and Prediction System by Adaptive Control of the Sensor Network

NASA Astrophysics Data System (ADS)

Talukder, A.; Panangadan, A. V.; Blumberg, A. F.; Herrington, T.; Georgas, N.

2008-12-01

The New York Harbor Observation and Prediction System (NYHOPS) is a real-time, estuarine and coastal ocean observing and modeling system for the New York Harbor and surrounding waters. Real-time measurements from in-situ mobile and stationary sensors in the NYHOPS networks are assimilated into marine forecasts in order to reduce the discrepancy with ground truth. The forecasts are obtained from the ECOMSED hydrodynamic model, a shallow water derivative of the Princeton Ocean Model. Currently, all sensors in the NYHOPS system are operated in a fixed mode with uniform sampling rates. This technology infusion effort demonstrates the use of Model Predictive Control (MPC) to autonomously adapt the operation of both mobile and stationary sensors in response to changing events that are -automatically detected from the ECOMSED forecasts. The controller focuses sensing resources on those regions that are expected to be impacted by the detected events. The MPC approach involves formulating the problem of calculating the optimal sensor parameters as a constrained multi-objective optimization problem. We have developed an objective function that takes into account the spatiotemporal relationship of the in-situ sensor locations and the locations of events detected by the model. Experiments in simulation were carried out using data collected during a freshwater flooding event. The location of the resulting freshwater plume was calculated from the corresponding model forecasts and was used by the MPC controller to derive control parameters for the sensing assets. The operational parameters that are controlled include the sampling rates of stationary sensors, paths of unmanned underwater vehicles (UUVs), and data transfer routes between sensors and the central modeling computer. The simulation experiments show that MPC-based sensor control reduces the RMS error in the forecast by a factor of 380% as compared to uniform sampling. The paths of multiple UUVs were simultaneously calculated such that measurements from on-board sensors would lead to maximal reduction in the forecast error after data assimilation. The MPC controller also reduces the consumption of system resources such as energy expended in sampling and wireless communication. The MPC-based control approach can be generalized to accept data from remote sensing satellites. This will enable in-situ sensors to be regulated using forecasts generated by assimilating local high resolution in-situ measurements with wide-area observations from remote sensing satellites.

Long-Term Quantitative Precipitation Estimates (QPE) at High Spatial and Temporal Resolution over CONUS: Bias-Adjustment of the Radar-Only National Mosaic and Multi-sensor QPE (NMQ/Q2) Precipitation Reanalysis (2001-2012)

NASA Astrophysics Data System (ADS)

Prat, Olivier; Nelson, Brian; Stevens, Scott; Seo, Dong-Jun; Kim, Beomgeun

2015-04-01

The processing of radar-only precipitation via the reanalysis from the National Mosaic and Multi-Sensor Quantitative (NMQ/Q2) based on the WSR-88D Next-generation Radar (NEXRAD) network over Continental United States (CONUS) is completed for the period covering from 2001 to 2012. This important milestone constitutes a unique opportunity to study precipitation processes at a 1-km spatial resolution for a 5-min temporal resolution. However, in order to be suitable for hydrological, meteorological and climatological applications, the radar-only product needs to be bias-adjusted and merged with in-situ rain gauge information. Several in-situ datasets are available to assess the biases of the radar-only product and to adjust for those biases to provide a multi-sensor QPE. The rain gauge networks that are used such as the Global Historical Climatology Network-Daily (GHCN-D), the Hydrometeorological Automated Data System (HADS), the Automated Surface Observing Systems (ASOS), and the Climate Reference Network (CRN), have different spatial density and temporal resolution. The challenges related to incorporating non-homogeneous networks over a vast area and for a long-term record are enormous. Among the challenges we are facing are the difficulties incorporating differing resolution and quality surface measurements to adjust gridded estimates of precipitation. Another challenge is the type of adjustment technique. The objective of this work is threefold. First, we investigate how the different in-situ networks can impact the precipitation estimates as a function of the spatial density, sensor type, and temporal resolution. Second, we assess conditional and un-conditional biases of the radar-only QPE for various time scales (daily, hourly, 5-min) using in-situ precipitation observations. Finally, after assessing the bias and applying reduction or elimination techniques, we are using a unique in-situ dataset merging the different RG networks (CRN, ASOS, HADS, GHCN-D) to adjust the radar-only QPE product via an Inverse Distance Weighting (IDW) approach. In addition, we also investigate alternate adjustment techniques such as the kriging method and its variants (Simple Kriging: SK; Ordinary Kriging: OK; Conditional Bias-Penalized Kriging: CBPK). From this approach, we also hope to generate estimates of uncertainty for the gridded bias-adjusted QPE. Further comparison with a suite of lower resolution QPEs derived from ground based radar measurements (Stage IV) and satellite products (TMPA, CMORPH, PERSIANN) is also provided in order to give a detailed picture of the improvements and remaining challenges.

Tilt performance of the ground settlement sensor configured in a fiber-optic low-coherent interferometer.

PubMed

Zhang, Pinglei; Wei, Heming; Guo, Jingjing; Sun, Changsen

2016-10-01

Ground settlement (GS) is one of the causes that destroy the durability of reinforced concrete structures. It could lead to a deterioration in the structural basement and increase the risk of collapse. The methods used for GS monitoring were mostly electronic-based sensors for reading the changes in resistance, resonant frequencies, etc. These sensors often bear low accuracy in the long term. Our published work demonstrated that a fiber-optic low-coherent interferometer configured in a Michelson interferometer was designed as a GS sensor, and a micro-meter resolution in the room environment was approached. However, the designed GS sensor, which in principle is based on a hydraulic connecting vessel, has to suffer from a tilt degeneration problem due to a strictly vertical requirement in practical installment. Here, we made a design for the GS sensor based on its robust tilt performance. The experimental tests show that the sensor can work well within a ±5° tilt. This could meet the requirements in most designed GS sensor installment applications.

Analysis of a commercial small unmanned airborne system (sUAS) in support of the Radiometric Calibration Test Site (RadCaTS) at Railroad Valley

NASA Astrophysics Data System (ADS)

Czapla-Myers, Jeffrey S.; Anderson, Nikolaus J.

2017-09-01

The Radiometric Calibration Test Site (RadCaTS) is an automated facility developed by the Remote Sensing Group (RSG) at the University of Arizona to provide radiometric calibration data for airborne and satellite sensors. RadCaTS uses stationary ground-viewing radiometers (GVRs) to spatially sample the surface reflectance of the site. The number and location of the GVRs is based on previous spatial, spectral, and temporal analyses of Railroad Valley. With the increase in high-resolution satellite sensors, there is renewed interest in examining the spatial uniformity the 1-km2 RadCaTS area at scales smaller than a typical 30-m sensor. RadCaTS is one of the four instrumented sites currently in the CEOS WGCV Radiometric Calibration Network (RadCalNet), which aims to harmonize the post-launch radiometric calibration of satellite sensors through the use of a global network of automated calibration sites. A better understanding of the RadCaTS spatial uniformity as a function of pixel size will also benefit the RadCalNet work. RSG has recently acquired a commercially-available small unmanned airborne system (sUAS) system, with which preliminary spatial homogeneity measurements of the 1-km2 RadCaTS area were made. This work describes an initial assessment of the airborne platform and integrated camera for spatial studies of RadCaTS using data that were collected in 2016 and 2017.

A Time Tree Medium Access Control for Energy Efficiency and Collision Avoidance in Wireless Sensor Networks

PubMed Central

Lee, Kilhung

2010-01-01

This paper presents a medium access control and scheduling scheme for wireless sensor networks. It uses time trees for sending data from the sensor node to the base station. For an energy efficient operation of the sensor networks in a distributed manner, time trees are built in order to reduce the collision probability and to minimize the total energy required to send data to the base station. A time tree is a data gathering tree where the base station is the root and each sensor node is either a relaying or a leaf node of the tree. Each tree operates in a different time schedule with possibly different activation rates. Through the simulation, the proposed scheme that uses time trees shows better characteristics toward burst traffic than the previous energy and data arrival rate scheme. PMID:22319270

The Robustness Analysis of Wireless Sensor Networks under Uncertain Interference

PubMed Central

Deng, Changjian

2013-01-01

Based on the complex network theory, robustness analysis of condition monitoring wireless sensor network under uncertain interference is present. In the evolution of the topology of sensor networks, the density weighted algebraic connectivity is taken into account, and the phenomenon of removing and repairing the link and node in the network is discussed. Numerical simulation is conducted to explore algebraic connectivity characteristics and network robustness performance. It is found that nodes density has the effect on algebraic connectivity distribution in the random graph model; high density nodes carry more connections, use more throughputs, and may be more unreliable. Moreover, the results show that, when network should be more error tolerant or robust by repairing nodes or adding new nodes, the network should be better clustered in median and high scale wireless sensor networks and be meshing topology in small scale networks. PMID:24363613

Wearable sensors for health monitoring

NASA Astrophysics Data System (ADS)

Suciu, George; Butca, Cristina; Ochian, Adelina; Halunga, Simona

2015-02-01

In this paper we describe several wearable sensors, designed for monitoring the health condition of the patients, based on an experimental model. Wearable sensors enable long-term continuous physiological monitoring, which is important for the treatment and management of many chronic illnesses, neurological disorders, and mental health issues. The system is based on a wearable sensors network, which is connected to a computer or smartphone. The wearable sensor network integrates several wearable sensors that can measure different parameters such as body temperature, heart rate and carbon monoxide quantity from the air. After the portable sensors measuring parameter values, they are transmitted by microprocessor through the Bluetooth to the application developed on computer or smartphone, to be interpreted.

Model Based Optimal Sensor Network Design for Condition Monitoring in an IGCC Plant

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kumar, Rajeeva; Kumar, Aditya; Dai, Dan

2012-12-31

This report summarizes the achievements and final results of this program. The objective of this program is to develop a general model-based sensor network design methodology and tools to address key issues in the design of an optimal sensor network configuration: the type, location and number of sensors used in a network, for online condition monitoring. In particular, the focus in this work is to develop software tools for optimal sensor placement (OSP) and use these tools to design optimal sensor network configuration for online condition monitoring of gasifier refractory wear and radiant syngas cooler (RSC) fouling. The methodology developedmore » will be applicable to sensing system design for online condition monitoring for broad range of applications. The overall approach consists of (i) defining condition monitoring requirement in terms of OSP and mapping these requirements in mathematical terms for OSP algorithm, (ii) analyzing trade-off of alternate OSP algorithms, down selecting the most relevant ones and developing them for IGCC applications (iii) enhancing the gasifier and RSC models as required by OSP algorithms, (iv) applying the developed OSP algorithm to design the optimal sensor network required for the condition monitoring of an IGCC gasifier refractory and RSC fouling. Two key requirements for OSP for condition monitoring are desired precision for the monitoring variables (e.g. refractory wear) and reliability of the proposed sensor network in the presence of expected sensor failures. The OSP problem is naturally posed within a Kalman filtering approach as an integer programming problem where the key requirements of precision and reliability are imposed as constraints. The optimization is performed over the overall network cost. Based on extensive literature survey two formulations were identified as being relevant to OSP for condition monitoring; one based on LMI formulation and the other being standard INLP formulation. Various algorithms to solve these two formulations were developed and validated. For a given OSP problem the computation efficiency largely depends on the “size” of the problem. Initially a simplified 1-D gasifier model assuming axial and azimuthal symmetry was used to test out various OSP algorithms. Finally these algorithms were used to design the optimal sensor network for condition monitoring of IGCC gasifier refractory wear and RSC fouling. The sensors type and locations obtained as solution to the OSP problem were validated using model based sensing approach. The OSP algorithm has been developed in a modular form and has been packaged as a software tool for OSP design where a designer can explore various OSP design algorithm is a user friendly way. The OSP software tool is implemented in Matlab/Simulink© in-house. The tool also uses few optimization routines that are freely available on World Wide Web. In addition a modular Extended Kalman Filter (EKF) block has also been developed in Matlab/Simulink© which can be utilized for model based sensing of important process variables that are not directly measured through combining the online sensors with model based estimation once the hardware sensor and their locations has been finalized. The OSP algorithm details and the results of applying these algorithms to obtain optimal sensor location for condition monitoring of gasifier refractory wear and RSC fouling profile are summarized in this final report.« less

Bayes Node Energy Polynomial Distribution to Improve Routing in Wireless Sensor Network

PubMed Central

Palanisamy, Thirumoorthy; Krishnasamy, Karthikeyan N.

2015-01-01

Wireless Sensor Network monitor and control the physical world via large number of small, low-priced sensor nodes. Existing method on Wireless Sensor Network (WSN) presented sensed data communication through continuous data collection resulting in higher delay and energy consumption. To conquer the routing issue and reduce energy drain rate, Bayes Node Energy and Polynomial Distribution (BNEPD) technique is introduced with energy aware routing in the wireless sensor network. The Bayes Node Energy Distribution initially distributes the sensor nodes that detect an object of similar event (i.e., temperature, pressure, flow) into specific regions with the application of Bayes rule. The object detection of similar events is accomplished based on the bayes probabilities and is sent to the sink node resulting in minimizing the energy consumption. Next, the Polynomial Regression Function is applied to the target object of similar events considered for different sensors are combined. They are based on the minimum and maximum value of object events and are transferred to the sink node. Finally, the Poly Distribute algorithm effectively distributes the sensor nodes. The energy efficient routing path for each sensor nodes are created by data aggregation at the sink based on polynomial regression function which reduces the energy drain rate with minimum communication overhead. Experimental performance is evaluated using Dodgers Loop Sensor Data Set from UCI repository. Simulation results show that the proposed distribution algorithm significantly reduce the node energy drain rate and ensure fairness among different users reducing the communication overhead. PMID:26426701

Bayes Node Energy Polynomial Distribution to Improve Routing in Wireless Sensor Network.

PubMed

Palanisamy, Thirumoorthy; Krishnasamy, Karthikeyan N

2015-01-01

Wireless Sensor Network monitor and control the physical world via large number of small, low-priced sensor nodes. Existing method on Wireless Sensor Network (WSN) presented sensed data communication through continuous data collection resulting in higher delay and energy consumption. To conquer the routing issue and reduce energy drain rate, Bayes Node Energy and Polynomial Distribution (BNEPD) technique is introduced with energy aware routing in the wireless sensor network. The Bayes Node Energy Distribution initially distributes the sensor nodes that detect an object of similar event (i.e., temperature, pressure, flow) into specific regions with the application of Bayes rule. The object detection of similar events is accomplished based on the bayes probabilities and is sent to the sink node resulting in minimizing the energy consumption. Next, the Polynomial Regression Function is applied to the target object of similar events considered for different sensors are combined. They are based on the minimum and maximum value of object events and are transferred to the sink node. Finally, the Poly Distribute algorithm effectively distributes the sensor nodes. The energy efficient routing path for each sensor nodes are created by data aggregation at the sink based on polynomial regression function which reduces the energy drain rate with minimum communication overhead. Experimental performance is evaluated using Dodgers Loop Sensor Data Set from UCI repository. Simulation results show that the proposed distribution algorithm significantly reduce the node energy drain rate and ensure fairness among different users reducing the communication overhead.

IMHRP: Improved Multi-Hop Routing Protocol for Wireless Sensor Networks

NASA Astrophysics Data System (ADS)

Huang, Jianhua; Ruan, Danwei; Hong, Yadong; Zhao, Ziming; Zheng, Hong

2017-10-01

Wireless sensor network (WSN) is a self-organizing system formed by a large number of low-cost sensor nodes through wireless communication. Sensor nodes collect environmental information and transmit it to the base station (BS). Sensor nodes usually have very limited battery energy. The batteries cannot be charged or replaced. Therefore, it is necessary to design an energy efficient routing protocol to maximize the network lifetime. This paper presents an improved multi-hop routing protocol (IMHRP) for homogeneous networks. In the IMHRP protocol, based on the distances to the BS, the CH nodes are divided into internal CH nodes and external CH nodes. The set-up phase of the protocol is based on the LEACH protocol and the minimum distance between CH nodes are limited to a special constant distance, so a more uniform distribution of CH nodes is achieved. In the steady-state phase, the routes of different CH nodes are created on the basis of the distances between the CH nodes. The energy efficiency of communication can be maximized. The simulation results show that the proposed algorithm can more effectively reduce the energy consumption of each round and prolong the network lifetime compared with LEACH protocol and MHT protocol.

A Novel Dynamic Spectrum Access Framework Based on Reinforcement Learning for Cognitive Radio Sensor Networks.

PubMed

Lin, Yun; Wang, Chao; Wang, Jiaxing; Dou, Zheng

2016-10-12

Cognitive radio sensor networks are one of the kinds of application where cognitive techniques can be adopted and have many potential applications, challenges and future research trends. According to the research surveys, dynamic spectrum access is an important and necessary technology for future cognitive sensor networks. Traditional methods of dynamic spectrum access are based on spectrum holes and they have some drawbacks, such as low accessibility and high interruptibility, which negatively affect the transmission performance of the sensor networks. To address this problem, in this paper a new initialization mechanism is proposed to establish a communication link and set up a sensor network without adopting spectrum holes to convey control information. Specifically, firstly a transmission channel model for analyzing the maximum accessible capacity for three different polices in a fading environment is discussed. Secondly, a hybrid spectrum access algorithm based on a reinforcement learning model is proposed for the power allocation problem of both the transmission channel and the control channel. Finally, extensive simulations have been conducted and simulation results show that this new algorithm provides a significant improvement in terms of the tradeoff between the control channel reliability and the efficiency of the transmission channel.

Improving Biometric-Based Authentication Schemes with Smart Card Revocation/Reissue for Wireless Sensor Networks.

PubMed

Moon, Jongho; Lee, Donghoon; Lee, Youngsook; Won, Dongho

2017-04-25

User authentication in wireless sensor networks is more difficult than in traditional networks owing to sensor network characteristics such as unreliable communication, limited resources, and unattended operation. For these reasons, various authentication schemes have been proposed to provide secure and efficient communication. In 2016, Park et al. proposed a secure biometric-based authentication scheme with smart card revocation/reissue for wireless sensor networks. However, we found that their scheme was still insecure against impersonation attack, and had a problem in the smart card revocation/reissue phase. In this paper, we show how an adversary can impersonate a legitimate user or sensor node, illegal smart card revocation/reissue and prove that Park et al.'s scheme fails to provide revocation/reissue. In addition, we propose an enhanced scheme that provides efficiency, as well as anonymity and security. Finally, we provide security and performance analysis between previous schemes and the proposed scheme, and provide formal analysis based on the random oracle model. The results prove that the proposed scheme can solve the weaknesses of impersonation attack and other security flaws in the security analysis section. Furthermore, performance analysis shows that the computational cost is lower than the previous scheme.

A Novel Dynamic Spectrum Access Framework Based on Reinforcement Learning for Cognitive Radio Sensor Networks

PubMed Central

Lin, Yun; Wang, Chao; Wang, Jiaxing; Dou, Zheng

2016-01-01

Cognitive radio sensor networks are one of the kinds of application where cognitive techniques can be adopted and have many potential applications, challenges and future research trends. According to the research surveys, dynamic spectrum access is an important and necessary technology for future cognitive sensor networks. Traditional methods of dynamic spectrum access are based on spectrum holes and they have some drawbacks, such as low accessibility and high interruptibility, which negatively affect the transmission performance of the sensor networks. To address this problem, in this paper a new initialization mechanism is proposed to establish a communication link and set up a sensor network without adopting spectrum holes to convey control information. Specifically, firstly a transmission channel model for analyzing the maximum accessible capacity for three different polices in a fading environment is discussed. Secondly, a hybrid spectrum access algorithm based on a reinforcement learning model is proposed for the power allocation problem of both the transmission channel and the control channel. Finally, extensive simulations have been conducted and simulation results show that this new algorithm provides a significant improvement in terms of the tradeoff between the control channel reliability and the efficiency of the transmission channel. PMID:27754316

Improving Biometric-Based Authentication Schemes with Smart Card Revocation/Reissue for Wireless Sensor Networks

PubMed Central

Moon, Jongho; Lee, Donghoon; Lee, Youngsook; Won, Dongho

2017-01-01

User authentication in wireless sensor networks is more difficult than in traditional networks owing to sensor network characteristics such as unreliable communication, limited resources, and unattended operation. For these reasons, various authentication schemes have been proposed to provide secure and efficient communication. In 2016, Park et al. proposed a secure biometric-based authentication scheme with smart card revocation/reissue for wireless sensor networks. However, we found that their scheme was still insecure against impersonation attack, and had a problem in the smart card revocation/reissue phase. In this paper, we show how an adversary can impersonate a legitimate user or sensor node, illegal smart card revocation/reissue and prove that Park et al.’s scheme fails to provide revocation/reissue. In addition, we propose an enhanced scheme that provides efficiency, as well as anonymity and security. Finally, we provide security and performance analysis between previous schemes and the proposed scheme, and provide formal analysis based on the random oracle model. The results prove that the proposed scheme can solve the weaknesses of impersonation attack and other security flaws in the security analysis section. Furthermore, performance analysis shows that the computational cost is lower than the previous scheme. PMID:28441331

A Distance-based Energy Aware Routing algorithm for wireless sensor networks.

PubMed

Wang, Jin; Kim, Jeong-Uk; Shu, Lei; Niu, Yu; Lee, Sungyoung

2010-01-01

Energy efficiency and balancing is one of the primary challenges for wireless sensor networks (WSNs) since the tiny sensor nodes cannot be easily recharged once they are deployed. Up to now, many energy efficient routing algorithms or protocols have been proposed with techniques like clustering, data aggregation and location tracking etc. However, many of them aim to minimize parameters like total energy consumption, latency etc., which cause hotspot nodes and partitioned network due to the overuse of certain nodes. In this paper, a Distance-based Energy Aware Routing (DEAR) algorithm is proposed to ensure energy efficiency and energy balancing based on theoretical analysis of different energy and traffic models. During the routing process, we consider individual distance as the primary parameter in order to adjust and equalize the energy consumption among involved sensors. The residual energy is also considered as a secondary factor. In this way, all the intermediate nodes will consume their energy at similar rate, which maximizes network lifetime. Simulation results show that the DEAR algorithm can reduce and balance the energy consumption for all sensor nodes so network lifetime is greatly prolonged compared to other routing algorithms.

Pervasive Monitoring—An Intelligent Sensor Pod Approach for Standardised Measurement Infrastructures

PubMed Central

Resch, Bernd; Mittlboeck, Manfred; Lippautz, Michael

2010-01-01

Geo-sensor networks have traditionally been built up in closed monolithic systems, thus limiting trans-domain usage of real-time measurements. This paper presents the technical infrastructure of a standardised embedded sensing device, which has been developed in the course of the Live Geography approach. The sensor pod implements data provision standards of the Sensor Web Enablement initiative, including an event-based alerting mechanism and location-aware Complex Event Processing functionality for detection of threshold transgression and quality assurance. The goal of this research is that the resultant highly flexible sensing architecture will bring sensor network applications one step further towards the realisation of the vision of a “digital skin for planet earth”. The developed infrastructure can potentially have far-reaching impacts on sensor-based monitoring systems through the deployment of ubiquitous and fine-grained sensor networks. This in turn allows for the straight-forward use of live sensor data in existing spatial decision support systems to enable better-informed decision-making. PMID:22163537

Pervasive monitoring--an intelligent sensor pod approach for standardised measurement infrastructures.

PubMed

Resch, Bernd; Mittlboeck, Manfred; Lippautz, Michael

2010-01-01

Geo-sensor networks have traditionally been built up in closed monolithic systems, thus limiting trans-domain usage of real-time measurements. This paper presents the technical infrastructure of a standardised embedded sensing device, which has been developed in the course of the Live Geography approach. The sensor pod implements data provision standards of the Sensor Web Enablement initiative, including an event-based alerting mechanism and location-aware Complex Event Processing functionality for detection of threshold transgression and quality assurance. The goal of this research is that the resultant highly flexible sensing architecture will bring sensor network applications one step further towards the realisation of the vision of a "digital skin for planet earth". The developed infrastructure can potentially have far-reaching impacts on sensor-based monitoring systems through the deployment of ubiquitous and fine-grained sensor networks. This in turn allows for the straight-forward use of live sensor data in existing spatial decision support systems to enable better-informed decision-making.

Non-contact plant growth measurement method and system based on ubiquitous sensor network technologies.

PubMed

Suk, Jinweon; Kim, Seokhoon; Ryoo, Intae

2011-01-01

This paper proposes a non-contact plant growth measurement system using infrared sensors based on the ubiquitous sensor network (USN) technology. The proposed system measures plant growth parameters such as the stem radius of plants using real-time non-contact methods, and generates diameter, cross-sectional area and thickening form of plant stems using this measured data. Non-contact sensors have been used not to cause any damage to plants during measurement of the growth parameters. Once the growth parameters are measured, they are transmitted to a remote server using the sensor network technology and analyzed in the application program server. The analyzed data are then provided for administrators and a group of interested users. The proposed plant growth measurement system has been designed and implemented using fixed-type and rotary-type infrared sensor based measurement methods and devices. Finally, the system performance is compared and verified with the measurement data that have been obtained by practical field experiments.

Comparison of the plenoptic sensor and the Shack-Hartmann sensor.

PubMed

Ko, Jonathan; Davis, Christopher C

2017-05-01

Adaptive optics has been successfully used for decades in the field of astronomy to correct for atmospheric turbulence. A well-developed example involves sensing the slightly distorted wavefronts with a Shack-Hartmann sensor and then correcting them with a phase conjugate device. While the Shack-Hartmann sensor has proven effective for astronomical purposes, it has been less successful for use in deep turbulence conditions often found in ground-to-ground-based optical systems. We have studied an alternative way to sense and correct distorted wavefronts using a plenoptic sensor. We review the design of the plenoptic sensor and directly compare it with the well-known Shack-Hartmann sensor. An experimental comparison of the plenoptic sensor and the Shack-Hartmann sensor is performed to highlight their differences in real-world atmospheric turbulence conditions.

On securing wireless sensor network--novel authentication scheme against DOS attacks.

PubMed

Raja, K Nirmal; Beno, M Marsaline

2014-10-01

Wireless sensor networks are generally deployed for collecting data from various environments. Several applications specific sensor network cryptography algorithms have been proposed in research. However WSN's has many constrictions, including low computation capability, less memory, limited energy resources, vulnerability to physical capture, which enforce unique security challenges needs to make a lot of improvements. This paper presents a novel security mechanism and algorithm for wireless sensor network security and also an application of this algorithm. The proposed scheme is given to strong authentication against Denial of Service Attacks (DOS). The scheme is simulated using network simulator2 (NS2). Then this scheme is analyzed based on the network packet delivery ratio and found that throughput has improved.

High capacity fiber optic sensor networks using hybrid multiplexing techniques and their applications

NASA Astrophysics Data System (ADS)

Sun, Qizhen; Li, Xiaolei; Zhang, Manliang; Liu, Qi; Liu, Hai; Liu, Deming

2013-12-01

Fiber optic sensor network is the development trend of fiber senor technologies and industries. In this paper, I will discuss recent research progress on high capacity fiber sensor networks with hybrid multiplexing techniques and their applications in the fields of security monitoring, environment monitoring, Smart eHome, etc. Firstly, I will present the architecture of hybrid multiplexing sensor passive optical network (HSPON), and the key technologies for integrated access and intelligent management of massive fiber sensor units. Two typical hybrid WDM/TDM fiber sensor networks for perimeter intrusion monitor and cultural relics security are introduced. Secondly, we propose the concept of "Microstructure－Optical X Domin Refecltor (M-OXDR)" for fiber sensor network expansion. By fabricating smart micro-structures with the ability of multidimensional encoded and low insertion loss along the fiber, the fiber sensor network of simple structure and huge capacity more than one thousand could be achieved. Assisted by the WDM/TDM and WDM/FDM decoding methods respectively, we built the verification systems for long-haul and real-time temperature sensing. Finally, I will show the high capacity and flexible fiber sensor network with IPv6 protocol based hybrid fiber/wireless access. By developing the fiber optic sensor with embedded IPv6 protocol conversion module and IPv6 router, huge amounts of fiber optic sensor nodes can be uniquely addressed. Meanwhile, various sensing information could be integrated and accessed to the Next Generation Internet.

Multi-mode Observations of Cloud-to-Ground Lightning Strokes

NASA Astrophysics Data System (ADS)

Smith, M. W.; Smith, B. J.; Clemenson, M. D.; Zollweg, J. D.

2015-12-01

We present hyper-temporal and hyper-spectral data collected using a suite of three Phantom high-speed cameras configured to observe cloud-to-ground lightning strokes. The first camera functioned as a contextual imager to show the location and structure of the strokes. The other two cameras were operated as slit-less spectrometers, with resolutions of 0.2 to 1.0 nm. The imaging camera was operated at a readout rate of 48,000 frames per second and provided an image-based trigger mechanism for the spectrometers. Each spectrometer operated at a readout rate of 400,000 frames per second. The sensors were deployed on the southern edge of Albuquerque, New Mexico and collected data over a 4 week period during the thunderstorm season in the summer of 2015. Strikes observed by the sensor suite were correlated to specific strikes recorded by the National Lightning Data Network (NLDN) and thereby geo-located. Sensor calibration factors, distance to each strike, and calculated values of atmospheric transmission were used to estimate absolute radiometric intensities for the spectral-temporal data. The data that we present show the intensity and time evolution of broadband and line emission features for both leader and return strokes. We highlight several key features and overall statistics of the observations. A companion poster describes a lightning model that is being developed at Sandia National Laboratories.

Overview of IMS infrasound station and engineering projects

NASA Astrophysics Data System (ADS)

Marty, J.; Doury, B.; Kramer, A.; Martysevich, P.

2015-12-01

The Provisional Technical Secretariat (PTS) of the Comprehensive Nuclear-Test-Ban Treaty (CTBTO) has a continuous interest in enhancing its capability in acoustic source detection, localization and characterization. The infrasound component of the International Monitoring System (IMS) constitutes the only worldwide ground-based infrasound network. It consists of sixty stations, among which forty-eight are already certified and continuously transmit data to the International Data Centre (IDC) in Vienna, Austria. Each infrasound station is composed of an array of infrasound sensors capable of measuring micro-pressure changes produced at ground level by infrasonic waves. The characteristics of infrasonic waves are computed in near real-time by IDC automatic detection software and are used as an input to IDC source categorization and localization algorithms. The PTS is continuously working towards the completion and sustainment of the IMS infrasound network. The objective of this presentation is to review the main activities performed in the IMS infrasound network over the last five years. This includes construction, installation, certification, major upgrade and revalidation activities. Major technology development projects to improve the reliability and robustness of IMS infrasound stations as well as their compliance with IMS Operational Manual requirements will also be presented. This includes advances in array geometry, wind noise reduction, system calibration, meteorological data as well as power and communication infrastructures. Finally the impact of all these changes on the overall detection capability of the IMS infrasound network will be highlighted.

A Formal Approach to the Selection by Minimum Error and Pattern Method for Sensor Data Loss Reduction in Unstable Wireless Sensor Network Communications

PubMed Central

Kim, Changhwa; Shin, DongHyun

2017-01-01

There are wireless networks in which typically communications are unsafe. Most terrestrial wireless sensor networks belong to this category of networks. Another example of an unsafe communication network is an underwater acoustic sensor network (UWASN). In UWASNs in particular, communication failures occur frequently and the failure durations can range from seconds up to a few hours, days, or even weeks. These communication failures can cause data losses significant enough to seriously damage human life or property, depending on their application areas. In this paper, we propose a framework to reduce sensor data loss during communication failures and we present a formal approach to the Selection by Minimum Error and Pattern (SMEP) method that plays the most important role for the reduction in sensor data loss under the proposed framework. The SMEP method is compared with other methods to validate its effectiveness through experiments using real-field sensor data sets. Moreover, based on our experimental results and performance comparisons, the SMEP method has been validated to be better than others in terms of the average sensor data value error rate caused by sensor data loss. PMID:28498312

A Formal Approach to the Selection by Minimum Error and Pattern Method for Sensor Data Loss Reduction in Unstable Wireless Sensor Network Communications.

PubMed

Kim, Changhwa; Shin, DongHyun

2017-05-12

There are wireless networks in which typically communications are unsafe. Most terrestrial wireless sensor networks belong to this category of networks. Another example of an unsafe communication network is an underwater acoustic sensor network (UWASN). In UWASNs in particular, communication failures occur frequently and the failure durations can range from seconds up to a few hours, days, or even weeks. These communication failures can cause data losses significant enough to seriously damage human life or property, depending on their application areas. In this paper, we propose a framework to reduce sensor data loss during communication failures and we present a formal approach to the Selection by Minimum Error and Pattern (SMEP) method that plays the most important role for the reduction in sensor data loss under the proposed framework. The SMEP method is compared with other methods to validate its effectiveness through experiments using real-field sensor data sets. Moreover, based on our experimental results and performance comparisons, the SMEP method has been validated to be better than others in terms of the average sensor data value error rate caused by sensor data loss.

Experiments on Adaptive Techniques for Host-Based Intrusion Detection

DOE Office of Scientific and Technical Information (OSTI.GOV)

DRAELOS, TIMOTHY J.; COLLINS, MICHAEL J.; DUGGAN, DAVID P.

2001-09-01

This research explores four experiments of adaptive host-based intrusion detection (ID) techniques in an attempt to develop systems that can detect novel exploits. The technique considered to have the most potential is adaptive critic designs (ACDs) because of their utilization of reinforcement learning, which allows learning exploits that are difficult to pinpoint in sensor data. Preliminary results of ID using an ACD, an Elman recurrent neural network, and a statistical anomaly detection technique demonstrate an ability to learn to distinguish between clean and exploit data. We used the Solaris Basic Security Module (BSM) as a data source and performed considerablemore » preprocessing on the raw data. A detection approach called generalized signature-based ID is recommended as a middle ground between signature-based ID, which has an inability to detect novel exploits, and anomaly detection, which detects too many events including events that are not exploits. The primary results of the ID experiments demonstrate the use of custom data for generalized signature-based intrusion detection and the ability of neural network-based systems to learn in this application environment.« less

An agenda-based routing protocol in delay tolerant mobile sensor networks.

PubMed

Wang, Xiao-Min; Zhu, Jin-Qi; Liu, Ming; Gong, Hai-Gang

2010-01-01

Routing in delay tolerant mobile sensor networks (DTMSNs) is challenging due to the networks' intermittent connectivity. Most existing routing protocols for DTMSNs use simplistic random mobility models for algorithm design and performance evaluation. In the real world, however, due to the unique characteristics of human mobility, currently existing random mobility models may not work well in environments where mobile sensor units are carried (such as DTMSNs). Taking a person's social activities into consideration, in this paper, we seek to improve DTMSN routing in terms of social structure and propose an agenda based routing protocol (ARP). In ARP, humans are classified based on their agendas and data transmission is made according to sensor nodes' transmission rankings. The effectiveness of ARP is demonstrated through comprehensive simulation studies.

Prediction-based Dynamic Energy Management in Wireless Sensor Networks

PubMed Central

Wang, Xue; Ma, Jun-Jie; Wang, Sheng; Bi, Dao-Wei

2007-01-01

Energy consumption is a critical constraint in wireless sensor networks. Focusing on the energy efficiency problem of wireless sensor networks, this paper proposes a method of prediction-based dynamic energy management. A particle filter was introduced to predict a target state, which was adopted to awaken wireless sensor nodes so that their sleep time was prolonged. With the distributed computing capability of nodes, an optimization approach of distributed genetic algorithm and simulated annealing was proposed to minimize the energy consumption of measurement. Considering the application of target tracking, we implemented target position prediction, node sleep scheduling and optimal sensing node selection. Moreover, a routing scheme of forwarding nodes was presented to achieve extra energy conservation. Experimental results of target tracking verified that energy-efficiency is enhanced by prediction-based dynamic energy management.

Hybrid Optimal Design of the Eco-Hydrological Wireless Sensor Network in the Middle Reach of the Heihe River Basin, China

PubMed Central

Kang, Jian; Li, Xin; Jin, Rui; Ge, Yong; Wang, Jinfeng; Wang, Jianghao

2014-01-01

The eco-hydrological wireless sensor network (EHWSN) in the middle reaches of the Heihe River Basin in China is designed to capture the spatial and temporal variability and to estimate the ground truth for validating the remote sensing productions. However, there is no available prior information about a target variable. To meet both requirements, a hybrid model-based sampling method without any spatial autocorrelation assumptions is developed to optimize the distribution of EHWSN nodes based on geostatistics. This hybrid model incorporates two sub-criteria: one for the variogram modeling to represent the variability, another for improving the spatial prediction to evaluate remote sensing productions. The reasonability of the optimized EHWSN is validated from representativeness, the variogram modeling and the spatial accuracy through using 15 types of simulation fields generated with the unconditional geostatistical stochastic simulation. The sampling design shows good representativeness; variograms estimated by samples have less than 3% mean error relative to true variograms. Then, fields at multiple scales are predicted. As the scale increases, estimated fields have higher similarities to simulation fields at block sizes exceeding 240 m. The validations prove that this hybrid sampling method is effective for both objectives when we do not know the characteristics of an optimized variables. PMID:25317762

Hybrid optimal design of the eco-hydrological wireless sensor network in the middle reach of the Heihe River Basin, China.

PubMed

Kang, Jian; Li, Xin; Jin, Rui; Ge, Yong; Wang, Jinfeng; Wang, Jianghao

2014-10-14

The eco-hydrological wireless sensor network (EHWSN) in the middle reaches of the Heihe River Basin in China is designed to capture the spatial and temporal variability and to estimate the ground truth for validating the remote sensing productions. However, there is no available prior information about a target variable. To meet both requirements, a hybrid model-based sampling method without any spatial autocorrelation assumptions is developed to optimize the distribution of EHWSN nodes based on geostatistics. This hybrid model incorporates two sub-criteria: one for the variogram modeling to represent the variability, another for improving the spatial prediction to evaluate remote sensing productions. The reasonability of the optimized EHWSN is validated from representativeness, the variogram modeling and the spatial accuracy through using 15 types of simulation fields generated with the unconditional geostatistical stochastic simulation. The sampling design shows good representativeness; variograms estimated by samples have less than 3% mean error relative to true variograms. Then, fields at multiple scales are predicted. As the scale increases, estimated fields have higher similarities to simulation fields at block sizes exceeding 240 m. The validations prove that this hybrid sampling method is effective for both objectives when we do not know the characteristics of an optimized variables.

An Outline of Data Aggregation Security in Heterogeneous Wireless Sensor Networks.

PubMed

Boubiche, Sabrina; Boubiche, Djallel Eddine; Bilami, Azzedine; Toral-Cruz, Homero

2016-04-12

Data aggregation processes aim to reduce the amount of exchanged data in wireless sensor networks and consequently minimize the packet overhead and optimize energy efficiency. Securing the data aggregation process is a real challenge since the aggregation nodes must access the relayed data to apply the aggregation functions. The data aggregation security problem has been widely addressed in classical homogeneous wireless sensor networks, however, most of the proposed security protocols cannot guarantee a high level of security since the sensor node resources are limited. Heterogeneous wireless sensor networks have recently emerged as a new wireless sensor network category which expands the sensor nodes' resources and capabilities. These new kinds of WSNs have opened new research opportunities where security represents a most attractive area. Indeed, robust and high security level algorithms can be used to secure the data aggregation at the heterogeneous aggregation nodes which is impossible in classical homogeneous WSNs. Contrary to the homogeneous sensor networks, the data aggregation security problem is still not sufficiently covered and the proposed data aggregation security protocols are numberless. To address this recent research area, this paper describes the data aggregation security problem in heterogeneous wireless sensor networks and surveys a few proposed security protocols. A classification and evaluation of the existing protocols is also introduced based on the adopted data aggregation security approach.

Tethered Vehicle Control and Tracking System

NASA Technical Reports Server (NTRS)

North, David D. (Inventor); Aull, Mark J. (Inventor)

2017-01-01

A kite system includes a kite and a ground station. The ground station includes a sensor that can be utilized to determine an angular position and velocity of the kite relative to the ground station. A controller utilizes a fuzzy logic control system to autonomously fly the kite. The system may include a ground station having powered winding units that generate power as the lines to the kite are unreeled. The control system may be configured to fly the kite in a crosswind trajectory to increase line tension for power generation. The sensors for determining the position of the kite are preferably ground-based.

Tethered Vehicle Control and Tracking System

NASA Technical Reports Server (NTRS)

North, David D. (Inventor); Aull, Mark J. (Inventor)

2014-01-01

A kite system includes a kite and a ground station. The ground station includes a sensor that can be utilized to determine an angular position and velocity of the kite relative to the ground station. A controller utilizes a fuzzy logic control system to autonomously fly the kite. The system may include a ground station having powered winding units that generate power as the lines to the kite are unreeled. The control system may be configured to fly the kite in a crosswind trajectory to increase line tension for power generation. The sensors for determining the position of the kite are preferably ground-based.

Information-based self-organization of sensor nodes of a sensor network

DOEpatents

Ko, Teresa H [Castro Valley, CA; Berry, Nina M [Tracy, CA

2011-09-20

A sensor node detects a plurality of information-based events. The sensor node determines whether at least one other sensor node is an information neighbor of the sensor node based on at least a portion of the plurality of information-based events. The information neighbor has an overlapping field of view with the sensor node. The sensor node sends at least one communication to the at least one other sensor node that is an information neighbor of the sensor node in response to at least one information-based event of the plurality of information-based events.