Experimental study of thin film sensor networks for wind turbine blade damage detection
NASA Astrophysics Data System (ADS)
Downey, A.; Laflamme, S.; Ubertini, F.; Sauder, H.; Sarkar, P.
2017-02-01
Damage detection of wind turbine blades is difficult due to their complex geometry and large size, for which large deployment of sensing systems is typically not economical. A solution is to develop and deploy dedicated sensor networks fabricated from inexpensive materials and electronics. The authors have recently developed a novel skin-type strain gauge for measuring strain over very large surfaces. The skin, a type of large-area electronics, is constituted from a network of soft elastomeric capacitors. The sensing system is analogous to a biological skin, where local strain can be monitored over a global area. In this paper, we propose the utilization of a dense network of soft elastomeric capacitors to detect, localize, and quantify damage on wind turbine blades. We also leverage mature off-the-shelf technologies, in particular resistive strain gauges, to augment such dense sensor network with high accuracy data at key locations, therefore constituting a hybrid dense sensor network. The proposed hybrid dense sensor network is installed inside a wind turbine blade model, and tested in a wind tunnel to simulate an operational environment. Results demonstrate the ability of the hybrid dense sensor network to detect, localize, and quantify damage.
Experimental damage detection of wind turbine blade using thin film sensor array
NASA Astrophysics Data System (ADS)
Downey, Austin; Laflamme, Simon; Ubertini, Filippo; Sarkar, Partha
2017-04-01
Damage detection of wind turbine blades is difficult due to their large sizes and complex geometries. Additionally, economic restraints limit the viability of high-cost monitoring methods. While it is possible to monitor certain global signatures through modal analysis, obtaining useful measurements over a blade's surface using off-the-shelf sensing technologies is difficult and typically not economical. A solution is to deploy dedicated sensor networks fabricated from inexpensive materials and electronics. The authors have recently developed a novel large-area electronic sensor measuring strain over very large surfaces. The sensing system is analogous to a biological skin, where local strain can be monitored over a global area. In this paper, we propose the utilization of a hybrid dense sensor network of soft elastomeric capacitors to detect, localize, and quantify damage, and resistive strain gauges to augment such dense sensor network with high accuracy data at key locations. The proposed hybrid dense sensor network is installed inside a wind turbine blade model and tested in a wind tunnel to simulate an operational environment. Damage in the form of changing boundary conditions is introduced into the monitored section of the blade. Results demonstrate the ability of the hybrid dense sensor network, and associated algorithms, to detect, localize, and quantify damage.
Reconstruction of in-plane strain maps using hybrid dense sensor network composed of sensing skin
NASA Astrophysics Data System (ADS)
Downey, Austin; Laflamme, Simon; Ubertini, Filippo
2016-12-01
The authors have recently developed a soft-elastomeric capacitive (SEC)-based thin film sensor for monitoring strain on mesosurfaces. Arranged in a network configuration, the sensing system is analogous to a biological skin, where local strain can be monitored over a global area. Under plane stress conditions, the sensor output contains the additive measurement of the two principal strain components over the monitored surface. In applications where the evaluation of strain maps is useful, in structural health monitoring for instance, such signal must be decomposed into linear strain components along orthogonal directions. Previous work has led to an algorithm that enabled such decomposition by leveraging a dense sensor network configuration with the addition of assumed boundary conditions. Here, we significantly improve the algorithm’s accuracy by leveraging mature off-the-shelf solutions to create a hybrid dense sensor network (HDSN) to improve on the boundary condition assumptions. The system’s boundary conditions are enforced using unidirectional RSGs and assumed virtual sensors. Results from an extensive experimental investigation demonstrate the good performance of the proposed algorithm and its robustness with respect to sensors’ layout. Overall, the proposed algorithm is seen to effectively leverage the advantages of a hybrid dense network for application of the thin film sensor to reconstruct surface strain fields over large surfaces.
Mechanisms for Prolonging Network Lifetime in Wireless Sensor Networks
ERIC Educational Resources Information Center
Yang, Yinying
2010-01-01
Sensors are used to monitor and control the physical environment. A Wireless Sensor Network (WSN) is composed of a large number of sensor nodes that are densely deployed either inside the phenomenon or very close to it [18][5]. Sensor nodes measure various parameters of the environment and transmit data collected to one or more sinks, using…
Radi, Marjan; Dezfouli, Behnam; Abu Bakar, Kamalrulnizam; Abd Razak, Shukor
2014-01-01
Network connectivity and link quality information are the fundamental requirements of wireless sensor network protocols to perform their desired functionality. Most of the existing discovery protocols have only focused on the neighbor discovery problem, while a few number of them provide an integrated neighbor search and link estimation. As these protocols require a careful parameter adjustment before network deployment, they cannot provide scalable and accurate network initialization in large-scale dense wireless sensor networks with random topology. Furthermore, performance of these protocols has not entirely been evaluated yet. In this paper, we perform a comprehensive simulation study on the efficiency of employing adaptive protocols compared to the existing nonadaptive protocols for initializing sensor networks with random topology. In this regard, we propose adaptive network initialization protocols which integrate the initial neighbor discovery with link quality estimation process to initialize large-scale dense wireless sensor networks without requiring any parameter adjustment before network deployment. To the best of our knowledge, this work is the first attempt to provide a detailed simulation study on the performance of integrated neighbor discovery and link quality estimation protocols for initializing sensor networks. This study can help system designers to determine the most appropriate approach for different applications. PMID:24678277
NASA Astrophysics Data System (ADS)
Asadollahi, Parisa; Li, Jian
2016-04-01
Understanding the dynamic behavior of complex structures such as long-span bridges requires dense deployment of sensors. Traditional wired sensor systems are generally expensive and time-consuming to install due to cabling. With wireless communication and on-board computation capabilities, wireless smart sensor networks have the advantages of being low cost, easy to deploy and maintain and therefore facilitate dense instrumentation for structural health monitoring. A long-term monitoring project was recently carried out for a cable-stayed bridge in South Korea with a dense array of 113 smart sensors, which feature the world's largest wireless smart sensor network for civil structural monitoring. This paper presents a comprehensive statistical analysis of the modal properties including natural frequencies, damping ratios and mode shapes of the monitored cable-stayed bridge. Data analyzed in this paper is composed of structural vibration signals monitored during a 12-month period under ambient excitations. The correlation between environmental temperature and the modal frequencies is also investigated. The results showed the long-term statistical structural behavior of the bridge, which serves as the basis for Bayesian statistical updating for the numerical model.
Lei, Chunyang; Bie, Hongxia; Fang, Gengfa; Gaura, Elena; Brusey, James; Zhang, Xuekun; Dutkiewicz, Eryk
2016-07-18
Super dense wireless sensor networks (WSNs) have become popular with the development of Internet of Things (IoT), Machine-to-Machine (M2M) communications and Vehicular-to-Vehicular (V2V) networks. While highly-dense wireless networks provide efficient and sustainable solutions to collect precise environmental information, a new channel access scheme is needed to solve the channel collision problem caused by the large number of competing nodes accessing the channel simultaneously. In this paper, we propose a space-time random access method based on a directional data transmission strategy, by which collisions in the wireless channel are significantly decreased and channel utility efficiency is greatly enhanced. Simulation results show that our proposed method can decrease the packet loss rate to less than 2 % in large scale WSNs and in comparison with other channel access schemes for WSNs, the average network throughput can be doubled.
Zanimonskiy, Yevgen M.; Yampolski, Yuri M.; Figurski, Mariusz
2017-01-01
The technique of the orthogonal projection of ionosphere electronic content variations for mapping total electron content (TEC) allows us to visualize ionospheric irregularities. For the reconstruction of global ionospheric characteristics, numerous global navigation satellite system (GNSS) receivers located in different regions of the Earth are used as sensors. We used dense GNSS networks in central Europe to detect and investigate a special type of plasma inhomogeneities, called travelling ionospheric disturbances (TID). Such use of GNSS sensors allows us to reconstruct the main TID parameters, such as spatial dimensions, velocities, and directions of their movement. The paper gives examples of the restoration of dynamic characteristics of ionospheric irregularities for quiet and disturbed geophysical conditions. Special attention is paid to the dynamics of ionospheric disturbances stimulated by the magnetic storms of two St. Patrick’s Days (17 March 2013 and 2015). Additional opportunities for the remote sensing of the ionosphere with the use of dense regional networks of GNSS receiving sensors have been noted too. PMID:28994718
Nykiel, Grzegorz; Zanimonskiy, Yevgen M; Yampolski, Yuri M; Figurski, Mariusz
2017-10-10
The technique of the orthogonal projection of ionosphere electronic content variations for mapping total electron content (TEC) allows us to visualize ionospheric irregularities. For the reconstruction of global ionospheric characteristics, numerous global navigation satellite system (GNSS) receivers located in different regions of the Earth are used as sensors. We used dense GNSS networks in central Europe to detect and investigate a special type of plasma inhomogeneities, called travelling ionospheric disturbances (TID). Such use of GNSS sensors allows us to reconstruct the main TID parameters, such as spatial dimensions, velocities, and directions of their movement. The paper gives examples of the restoration of dynamic characteristics of ionospheric irregularities for quiet and disturbed geophysical conditions. Special attention is paid to the dynamics of ionospheric disturbances stimulated by the magnetic storms of two St. Patrick's Days (17 March 2013 and 2015). Additional opportunities for the remote sensing of the ionosphere with the use of dense regional networks of GNSS receiving sensors have been noted too.
On the reliability of Quake-Catcher Network earthquake detections
Yildirim, Battalgazi; Cochran, Elizabeth S.; Chung, Angela I.; Christensen, Carl M.; Lawrence, Jesse F.
2015-01-01
Over the past two decades, there have been several initiatives to create volunteer‐based seismic networks. The Personal Seismic Network, proposed around 1990, used a short‐period seismograph to record earthquake waveforms using existing phone lines (Cranswick and Banfill, 1990; Cranswicket al., 1993). NetQuakes (Luetgert et al., 2010) deploys triaxial Micro‐Electromechanical Systems (MEMS) sensors in private homes, businesses, and public buildings where there is an Internet connection. Other seismic networks using a dense array of low‐cost MEMS sensors are the Community Seismic Network (Clayton et al., 2012; Kohler et al., 2013) and the Home Seismometer Network (Horiuchi et al., 2009). One main advantage of combining low‐cost MEMS sensors and existing Internet connection in public and private buildings over the traditional networks is the reduction in installation and maintenance costs (Koide et al., 2006). In doing so, it is possible to create a dense seismic network for a fraction of the cost of traditional seismic networks (D’Alessandro and D’Anna, 2013; D’Alessandro, 2014; D’Alessandro et al., 2014).
An Adaptive Channel Access Method for Dynamic Super Dense Wireless Sensor Networks.
Lei, Chunyang; Bie, Hongxia; Fang, Gengfa; Zhang, Xuekun
2015-12-03
Super dense and distributed wireless sensor networks have become very popular with the development of small cell technology, Internet of Things (IoT), Machine-to-Machine (M2M) communications, Vehicular-to-Vehicular (V2V) communications and public safety networks. While densely deployed wireless networks provide one of the most important and sustainable solutions to improve the accuracy of sensing and spectral efficiency, a new channel access scheme needs to be designed to solve the channel congestion problem introduced by the high dynamics of competing nodes accessing the channel simultaneously. In this paper, we firstly analyzed the channel contention problem using a novel normalized channel contention analysis model which provides information on how to tune the contention window according to the state of channel contention. We then proposed an adaptive channel contention window tuning algorithm in which the contention window tuning rate is set dynamically based on the estimated channel contention level. Simulation results show that our proposed adaptive channel access algorithm based on fast contention window tuning can achieve more than 95 % of the theoretical optimal throughput and 0 . 97 of fairness index especially in dynamic and dense networks.
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.
NASA Astrophysics Data System (ADS)
Coogan, A.; Avanzi, F.; Akella, R.; Conklin, M. H.; Bales, R. C.; Glaser, S. D.
2017-12-01
Automatic meteorological and snow stations provide large amounts of information at dense temporal resolution, but data quality is often compromised by noise and missing values. We present a new gap-filling and cleaning procedure for networks of these stations based on Kalman filtering and expectation maximization. Our method utilizes a multi-sensor, regime-switching Kalman filter to learn a latent process that captures dependencies between nearby stations and handles sharp changes in snowfall rate. Since the latent process is inferred using observations across working stations in the network, it can be used to fill in large data gaps for a malfunctioning station. The procedure was tested on meteorological and snow data from Wireless Sensor Networks (WSN) in the American River basin of the Sierra Nevada. Data include air temperature, relative humidity, and snow depth from dense networks of 10 to 12 stations within 1 km2 swaths. Both wet and dry water years have similar data issues. Data with artificially created gaps was used to quantify the method's performance. Our multi-sensor approach performs better than a single-sensor one, especially with large data gaps, as it learns and exploits the dominant underlying processes in snowpack at each site.
Water Catchment and Storage Monitoring
NASA Astrophysics Data System (ADS)
Bruenig, Michael; Dunbabin, Matt; Moore, Darren
2010-05-01
Sensors and Sensor Networks technologies provide the means for comprehensive understanding of natural processes in the environment by radically increasing the availability of empirical data about the natural world. This step change is achieved through a dramatic reduction in the cost of data acquisition and many orders of magnitude increase in the spatial and temporal granularity of measurements. Australia's Commonwealth Scientific and Industrial Research Organisation (CSIRO) is undertaking a strategic research program developing wireless sensor network technology for environmental monitoring. As part of this research initiative, we are engaging with government agencies to densely monitor water catchments and storages, thereby enhancing understanding of the environmental processes that affect water quality. In the Gold Coast hinterland in Queensland, Australia, we are building sensor networks to monitor restoration of rainforest within the catchment, and to monitor methane flux release and water quality in the water storages. This poster will present our ongoing work in this region of eastern Australia. The Springbrook plateau in the Gold Coast hinterland lies within a World Heritage listed area, has uniquely high rainfall, hosts a wide range of environmental gradients, and forms part of the catchment for Gold Coast's water storages. Parts of the plateau are being restored from agricultural grassland to native rainforest vegetation. Since April 2008, we have had a 10-node, multi-hop sensor network deployed there to monitor microclimate variables. This network will be expanded to 50-nodes in February 2010, and to around 200-nodes and 1000 sensors by mid-2011, spread over an area of approximately 0.8 square kilometers. The extremely dense microclimate sensing will enhance knowledge of the environmental factors that enhance or inhibit the regeneration of native rainforest. The final network will also include nodes with acoustic and image sensing capability for monitoring higher level parameters such as fauna diversity. The regenerating rainforest environment presents a number of interesting challenges for wireless sensor networks related to energy harvesting and to reliable low-power wireless communications through dense and wet vegetation. Located downstream from the Springbrook plateau, the Little Nerang and Hinze dams are the two major water supply storages for the Gold Coast region. In September 2009 we fitted methane, light, wind, and sonar sensors to our autonomous electric boat platform and successfully demonstrated autonomous collection of methane flux release data on Little Nerang Dam. Sensor and boat status data were relayed back to a human operator on the shore of the dam via a small network of our Fleck™ nodes. The network also included 4 floating nodes each fitted with a string of 6 temperature sensors for profiling temperature at different water depths. We plan to expand the network further during 2010 to incorporate floating methane nodes, additional temperature sensing nodes, as well as land-based microclimate nodes. The overall monitoring system will provide significant data to understand the connected catchment-to-storage system and will provide continuous data to monitor and understand change trends within this world heritage area.
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.
An intelligent surveillance platform for large metropolitan areas with dense sensor deployment.
Fernández, Jorge; Calavia, Lorena; Baladrón, Carlos; Aguiar, Javier M; Carro, Belén; Sánchez-Esguevillas, Antonio; Alonso-López, Jesus A; Smilansky, Zeev
2013-06-07
This paper presents an intelligent surveillance platform based on the usage of large numbers of inexpensive sensors designed and developed inside the European Eureka Celtic project HuSIMS. With the aim of maximizing the number of deployable units while keeping monetary and resource/bandwidth costs at a minimum, the surveillance platform is based on the usage of inexpensive visual sensors which apply efficient motion detection and tracking algorithms to transform the video signal in a set of motion parameters. In order to automate the analysis of the myriad of data streams generated by the visual sensors, the platform's control center includes an alarm detection engine which comprises three components applying three different Artificial Intelligence strategies in parallel. These strategies are generic, domain-independent approaches which are able to operate in several domains (traffic surveillance, vandalism prevention, perimeter security, etc.). The architecture is completed with a versatile communication network which facilitates data collection from the visual sensors and alarm and video stream distribution towards the emergency teams. The resulting surveillance system is extremely suitable for its deployment in metropolitan areas, smart cities, and large facilities, mainly because cheap visual sensors and autonomous alarm detection facilitate dense sensor network deployments for wide and detailed coverage.
Measuring NO, NO2, CO2 and O3 with low-cost sensors
NASA Astrophysics Data System (ADS)
Müller, Michael; Graf, Peter; Hüglin, Christoph
2017-04-01
Inexpensive sensors measuring ambient gas concentrations can be integrated in sensor units forming dense sensor networks. The utilized sensors have to be sufficiently accurate as the value of such networks directly depends on the information they provide. Thus, thorough testing of sensors before bringing them into service and the application of effective strategies for performance monitoring and adjustments during service are key elements for operating the low-cost sensors that are currently available on the market. We integrated several types of low-cost sensors into sensor units (Alphasense NO2 B4/B42F/B43F, Alphasense NO B4, SensAir CO2 LP8, Aeroqual O3 SM50), run them in the field next to instruments of air quality monitoring stations and performed tests in the laboratory. The poster summarizes our findings regarding the achieved sensor accuracy, methods to improve sensor performance as well as strategies to monitor the current state of the sensor (drifts, sensitivity) within a sensor network.
Mian, Adnan Noor; Fatima, Mehwish; Khan, Raees; Prakash, Ravi
2014-01-01
Energy efficiency is an important design paradigm in Wireless Sensor Networks (WSNs) and its consumption in dynamic environment is even more critical. Duty cycling of sensor nodes is used to address the energy consumption problem. However, along with advantages, duty cycle aware networks introduce some complexities like synchronization and latency. Due to their inherent characteristics, many traditional routing protocols show low performance in densely deployed WSNs with duty cycle awareness, when sensor nodes are supposed to have high mobility. In this paper we first present a three messages exchange Lightweight Random Walk Routing (LRWR) protocol and then evaluate its performance in WSNs for routing low data rate packets. Through NS-2 based simulations, we examine the LRWR protocol by comparing it with DYMO, a widely used WSN protocol, in both static and dynamic environments with varying duty cycles, assuming the standard IEEE 802.15.4 in lower layers. Results for the three metrics, that is, reliability, end-to-end delay, and energy consumption, show that LRWR protocol outperforms DYMO in scalability, mobility, and robustness, showing this protocol as a suitable choice in low duty cycle and dense WSNs.
Wang, Lusheng; Wang, Yamei; Ding, Zhizhong; Wang, Xiumin
2015-09-18
With the rapid development of wireless networking technologies, the Internet of Things and heterogeneous cellular networks (HCNs) tend to be integrated to form a promising wireless network paradigm for 5G. Hyper-dense sensor and mobile devices will be deployed under the coverage of heterogeneous cells, so that each of them could freely select any available cell covering it and compete for resource with others selecting the same cell, forming a cell selection (CS) game between these devices. Since different types of cells usually share the same portion of the spectrum, devices selecting overlapped cells can experience severe inter-cell interference (ICI). In this article, we study the CS game among a large amount of densely-deployed sensor and mobile devices for their uplink transmissions in a two-tier HCN. ICI is embedded with the traditional congestion game (TCG), forming a congestion game with ICI (CGI) and a congestion game with capacity (CGC). For the three games above, we theoretically find the circular boundaries between the devices selecting the macrocell and those selecting the picocells, indicated by the pure strategy Nash equilibria (PSNE). Meanwhile, through a number of simulations with different picocell radii and different path loss exponents, the collapse of the PSNE impacted by severe ICI (i.e., a large number of picocell devices change their CS preferences to the macrocell) is profoundly revealed, and the collapse points are identified.
Wang, Lusheng; Wang, Yamei; Ding, Zhizhong; Wang, Xiumin
2015-01-01
With the rapid development of wireless networking technologies, the Internet of Things and heterogeneous cellular networks (HCNs) tend to be integrated to form a promising wireless network paradigm for 5G. Hyper-dense sensor and mobile devices will be deployed under the coverage of heterogeneous cells, so that each of them could freely select any available cell covering it and compete for resource with others selecting the same cell, forming a cell selection (CS) game between these devices. Since different types of cells usually share the same portion of the spectrum, devices selecting overlapped cells can experience severe inter-cell interference (ICI). In this article, we study the CS game among a large amount of densely-deployed sensor and mobile devices for their uplink transmissions in a two-tier HCN. ICI is embedded with the traditional congestion game (TCG), forming a congestion game with ICI (CGI) and a congestion game with capacity (CGC). For the three games above, we theoretically find the circular boundaries between the devices selecting the macrocell and those selecting the picocells, indicated by the pure strategy Nash equilibria (PSNE). Meanwhile, through a number of simulations with different picocell radii and different path loss exponents, the collapse of the PSNE impacted by severe ICI (i.e., a large number of picocell devices change their CS preferences to the macrocell) is profoundly revealed, and the collapse points are identified. PMID:26393617
Arsalan, Muhammad; Naqvi, Rizwan Ali; Kim, Dong Seop; Nguyen, Phong Ha; Owais, Muhammad; Park, Kang Ryoung
2018-01-01
The recent advancements in computer vision have opened new horizons for deploying biometric recognition algorithms in mobile and handheld devices. Similarly, iris recognition is now much needed in unconstraint scenarios with accuracy. These environments make the acquired iris image exhibit occlusion, low resolution, blur, unusual glint, ghost effect, and off-angles. The prevailing segmentation algorithms cannot cope with these constraints. In addition, owing to the unavailability of near-infrared (NIR) light, iris recognition in visible light environment makes the iris segmentation challenging with the noise of visible light. Deep learning with convolutional neural networks (CNN) has brought a considerable breakthrough in various applications. To address the iris segmentation issues in challenging situations by visible light and near-infrared light camera sensors, this paper proposes a densely connected fully convolutional network (IrisDenseNet), which can determine the true iris boundary even with inferior-quality images by using better information gradient flow between the dense blocks. In the experiments conducted, five datasets of visible light and NIR environments were used. For visible light environment, noisy iris challenge evaluation part-II (NICE-II selected from UBIRIS.v2 database) and mobile iris challenge evaluation (MICHE-I) datasets were used. For NIR environment, the institute of automation, Chinese academy of sciences (CASIA) v4.0 interval, CASIA v4.0 distance, and IIT Delhi v1.0 iris datasets were used. Experimental results showed the optimal segmentation of the proposed IrisDenseNet and its excellent performance over existing algorithms for all five datasets. PMID:29748495
Arsalan, Muhammad; Naqvi, Rizwan Ali; Kim, Dong Seop; Nguyen, Phong Ha; Owais, Muhammad; Park, Kang Ryoung
2018-05-10
The recent advancements in computer vision have opened new horizons for deploying biometric recognition algorithms in mobile and handheld devices. Similarly, iris recognition is now much needed in unconstraint scenarios with accuracy. These environments make the acquired iris image exhibit occlusion, low resolution, blur, unusual glint, ghost effect, and off-angles. The prevailing segmentation algorithms cannot cope with these constraints. In addition, owing to the unavailability of near-infrared (NIR) light, iris recognition in visible light environment makes the iris segmentation challenging with the noise of visible light. Deep learning with convolutional neural networks (CNN) has brought a considerable breakthrough in various applications. To address the iris segmentation issues in challenging situations by visible light and near-infrared light camera sensors, this paper proposes a densely connected fully convolutional network (IrisDenseNet), which can determine the true iris boundary even with inferior-quality images by using better information gradient flow between the dense blocks. In the experiments conducted, five datasets of visible light and NIR environments were used. For visible light environment, noisy iris challenge evaluation part-II (NICE-II selected from UBIRIS.v2 database) and mobile iris challenge evaluation (MICHE-I) datasets were used. For NIR environment, the institute of automation, Chinese academy of sciences (CASIA) v4.0 interval, CASIA v4.0 distance, and IIT Delhi v1.0 iris datasets were used. Experimental results showed the optimal segmentation of the proposed IrisDenseNet and its excellent performance over existing algorithms for all five datasets.
On the feasibility of measuring urban air pollution by wireless distributed sensor networks.
Moltchanov, Sharon; Levy, Ilan; Etzion, Yael; Lerner, Uri; Broday, David M; Fishbain, Barak
2015-01-01
Accurate evaluation of air pollution on human-wellbeing requires high-resolution measurements. Standard air quality monitoring stations provide accurate pollution levels but due to their sparse distribution they cannot capture the highly resolved spatial variations within cities. Similarly, dedicated field campaigns can use tens of measurement devices and obtain highly dense spatial coverage but normally deployment has been limited to short periods of no more than few weeks. Nowadays, advances in communication and sensory technologies enable the deployment of dense grids of wireless distributed air monitoring nodes, yet their sensor ability to capture the spatiotemporal pollutant variability at the sub-neighborhood scale has never been thoroughly tested. This study reports ambient measurements of gaseous air pollutants by a network of six wireless multi-sensor miniature nodes that have been deployed in three urban sites, about 150 m apart. We demonstrate the network's capability to capture spatiotemporal concentration variations at an exceptional fine resolution but highlight the need for a frequent in-situ calibration to maintain the consistency of some sensors. Accordingly, a procedure for a field calibration is proposed and shown to improve the system's performance. Overall, our results support the compatibility of wireless distributed sensor networks for measuring urban air pollution at a sub-neighborhood spatial resolution, which suits the requirement for highly spatiotemporal resolved measurements at the breathing-height when assessing exposure to urban air pollution. Copyright © 2014 Elsevier B.V. All rights reserved.
An Intelligent Surveillance Platform for Large Metropolitan Areas with Dense Sensor Deployment
Fernández, Jorge; Calavia, Lorena; Baladrón, Carlos; Aguiar, Javier M.; Carro, Belén; Sánchez-Esguevillas, Antonio; Alonso-López, Jesus A.; Smilansky, Zeev
2013-01-01
This paper presents an intelligent surveillance platform based on the usage of large numbers of inexpensive sensors designed and developed inside the European Eureka Celtic project HuSIMS. With the aim of maximizing the number of deployable units while keeping monetary and resource/bandwidth costs at a minimum, the surveillance platform is based on the usage of inexpensive visual sensors which apply efficient motion detection and tracking algorithms to transform the video signal in a set of motion parameters. In order to automate the analysis of the myriad of data streams generated by the visual sensors, the platform's control center includes an alarm detection engine which comprises three components applying three different Artificial Intelligence strategies in parallel. These strategies are generic, domain-independent approaches which are able to operate in several domains (traffic surveillance, vandalism prevention, perimeter security, etc.). The architecture is completed with a versatile communication network which facilitates data collection from the visual sensors and alarm and video stream distribution towards the emergency teams. The resulting surveillance system is extremely suitable for its deployment in metropolitan areas, smart cities, and large facilities, mainly because cheap visual sensors and autonomous alarm detection facilitate dense sensor network deployments for wide and detailed coverage. PMID:23748169
A mobile sensing system for structural health monitoring: design and validation
NASA Astrophysics Data System (ADS)
Zhu, Dapeng; Yi, Xiaohua; Wang, Yang; Lee, Kok-Meng; Guo, Jiajie
2010-05-01
This paper describes a new approach using mobile sensor networks for structural health monitoring. Compared with static sensors, mobile sensor networks offer flexible system architectures with adaptive spatial resolutions. The paper first describes the design of a mobile sensing node that is capable of maneuvering on structures built with ferromagnetic materials. The mobile sensing node can also attach/detach an accelerometer onto/from the structural surface. The performance of the prototype mobile sensor network has been validated through laboratory experiments. Two mobile sensing nodes are adopted for navigating on a steel portal frame and providing dense acceleration measurements. Transmissibility function analysis is conducted to identify structural damage using data collected by the mobile sensing nodes. This preliminary work is expected to spawn transformative changes in the use of mobile sensors for future structural health monitoring.
NY-uHMT: A dense hydro-meteorological network to characterize urban land-atmosphere interactions
NASA Astrophysics Data System (ADS)
Ramamurthy, P.; Lakhankar, T.; Khanbilvardi, R.; Devineni, N.
2016-12-01
Most people in the US live in large Metropolitan areas that have a dense urban core in the center, dominated by built surfaces and surrounded by residential/suburban areas that consist a mix of built, vegetated and permeable surfaces. This creates a gradient in the hydro-meteorological environment giving rise to complex land-atmosphere interactions. Current modeling platforms and observational techniques like tower measurements do not adequately account for the underlying heterogeneity. To address this critical gap in our understanding we have instituted a dense network of sensors in the New York Metropolitan area. This unique urban sensor network consists of instrumentation to monitor soil moisture at multiple depths along with air temperature, relative humidity and precipitation, with room to add additional sensors in the future. The network is autonomous and connected to a centralized server using cellular towers. Apart from describing the spatial variability in hydro-meteorological quantities the network will also aid in conducting high-resolution numerical simulations to study and forecast urban weather and climate. In one such simulation conducted to partition the influence of storage flux, wind pattern and circulation and soil moisture deficit on urban heat island intensity (UHI), we found that the daily variability in UHI in NYC was sensitive to available energy and wind pattern. The long-term trend in UHI was however related to soil moisture deficit. In fact a prolonged heat wave period witnessed during summer 2006 correlated well with an extended dry period and the daily UHI in NYC almost doubled. Moreover, the urban soils also suffered from high degree of dessication, owing to drier urban boundary layer.
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.
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.
Bao, Xu; Li, Haijian; Qin, Lingqiao; Xu, Dongwei; Ran, Bin; Rong, Jian
2016-10-27
To obtain adequate traffic information, the density of traffic sensors should be sufficiently high to cover the entire transportation network. However, deploying sensors densely over the entire network may not be realistic for practical applications due to the budgetary constraints of traffic management agencies. This paper describes several possible spatial distributions of traffic information credibility and proposes corresponding different sensor information credibility functions to describe these spatial distribution properties. A maximum benefit model and its simplified model are proposed to solve the traffic sensor location problem. The relationships between the benefit and the number of sensors are formulated with different sensor information credibility functions. Next, expanding models and algorithms in analytic results are performed. For each case, the maximum benefit, the optimal number and spacing of sensors are obtained and the analytic formulations of the optimal sensor locations are derived as well. Finally, a numerical example is proposed to verify the validity and availability of the proposed models for solving a network sensor location problem. The results show that the optimal number of sensors of segments with different model parameters in an entire freeway network can be calculated. Besides, it can also be concluded that the optimal sensor spacing is independent of end restrictions but dependent on the values of model parameters that represent the physical conditions of sensors and roads.
Bao, Xu; Li, Haijian; Qin, Lingqiao; Xu, Dongwei; Ran, Bin; Rong, Jian
2016-01-01
To obtain adequate traffic information, the density of traffic sensors should be sufficiently high to cover the entire transportation network. However, deploying sensors densely over the entire network may not be realistic for practical applications due to the budgetary constraints of traffic management agencies. This paper describes several possible spatial distributions of traffic information credibility and proposes corresponding different sensor information credibility functions to describe these spatial distribution properties. A maximum benefit model and its simplified model are proposed to solve the traffic sensor location problem. The relationships between the benefit and the number of sensors are formulated with different sensor information credibility functions. Next, expanding models and algorithms in analytic results are performed. For each case, the maximum benefit, the optimal number and spacing of sensors are obtained and the analytic formulations of the optimal sensor locations are derived as well. Finally, a numerical example is proposed to verify the validity and availability of the proposed models for solving a network sensor location problem. The results show that the optimal number of sensors of segments with different model parameters in an entire freeway network can be calculated. Besides, it can also be concluded that the optimal sensor spacing is independent of end restrictions but dependent on the values of model parameters that represent the physical conditions of sensors and roads. PMID:27801794
Locating sources within a dense sensor array using graph clustering
NASA Astrophysics Data System (ADS)
Gerstoft, P.; Riahi, N.
2017-12-01
We develop a model-free technique to identify weak sources within dense sensor arrays using graph clustering. No knowledge about the propagation medium is needed except that signal strengths decay to insignificant levels within a scale that is shorter than the aperture. We then reinterpret the spatial coherence matrix of a wave field as a matrix whose support is a connectivity matrix of a graph with sensors as vertices. In a dense network, well-separated sources induce clusters in this graph. The geographic spread of these clusters can serve to localize the sources. The support of the covariance matrix is estimated from limited-time data using a hypothesis test with a robust phase-only coherence test statistic combined with a physical distance criterion. The latter criterion ensures graph sparsity and thus prevents clusters from forming by chance. We verify the approach and quantify its reliability on a simulated dataset. The method is then applied to data from a dense 5200 element geophone array that blanketed of the city of Long Beach (CA). The analysis exposes a helicopter traversing the array and oil production facilities.
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.
A Framework for Real-Time Collection, Analysis, and Classification of Ubiquitous Infrasound Data
NASA Astrophysics Data System (ADS)
Christe, A.; Garces, M. A.; Magana-Zook, S. A.; Schnurr, J. M.
2015-12-01
Traditional infrasound arrays are generally expensive to install and maintain. There are ~10^3 infrasound channels on Earth today. The amount of data currently provided by legacy architectures can be processed on a modest server. However, the growing availability of low-cost, ubiquitous, and dense infrasonic sensor networks presents a substantial increase in the volume, velocity, and variety of data flow. Initial data from a prototype ubiquitous global infrasound network is already pushing the boundaries of traditional research server and communication systems, in particular when serving data products over heterogeneous, international network topologies. We present a scalable, cloud-based approach for capturing and analyzing large amounts of dense infrasonic data (>10^6 channels). We utilize Akka actors with WebSockets to maintain data connections with infrasound sensors. Apache Spark provides streaming, batch, machine learning, and graph processing libraries which will permit signature classification, cross-correlation, and other analytics in near real time. This new framework and approach provide significant advantages in scalability and cost.
Cho, Soojin; Park, Jong-Woong; Sim, Sung-Han
2015-01-01
Wireless sensor networks (WSNs) facilitate a new paradigm to structural identification and monitoring for civil infrastructure. Conventional structural monitoring systems based on wired sensors and centralized data acquisition systems are costly for installation as well as maintenance. WSNs have emerged as a technology that can overcome such difficulties, making deployment of a dense array of sensors on large civil structures both feasible and economical. However, as opposed to wired sensor networks in which centralized data acquisition and processing is common practice, WSNs require decentralized computing algorithms to reduce data transmission due to the limitation associated with wireless communication. In this paper, the stochastic subspace identification (SSI) technique is selected for system identification, and SSI-based decentralized system identification (SDSI) is proposed to be implemented in a WSN composed of Imote2 wireless sensors that measure acceleration. The SDSI is tightly scheduled in the hierarchical WSN, and its performance is experimentally verified in a laboratory test using a 5-story shear building model. PMID:25856325
Real-time indoor monitoring system based on wireless sensor networks
NASA Astrophysics Data System (ADS)
Wu, Zhengzhong; Liu, Zilin; Huang, Xiaowei; Liu, Jun
2008-10-01
Wireless sensor networks (WSN) greatly extend our ability to monitor and control the physical world. It can collaborate and aggregate a huge amount of sensed data to provide continuous and spatially dense observation of environment. The control and monitoring of indoor atmosphere conditions represents an important task with the aim of ensuring suitable working and living spaces to people. However, the comprehensive air quality, which includes monitoring of humidity, temperature, gas concentrations, etc., is not so easy to be monitored and controlled. In this paper an indoor WSN monitoring system was developed. In the system several sensors such as temperature sensor, humidity sensor, gases sensor, were built in a RF transceiver board for monitoring indoor environment conditions. The indoor environmental monitoring parameters can be transmitted by wireless to database server and then viewed throw PC or PDA accessed to the local area networks by administrators. The system, which was also field-tested and showed a reliable and robust characteristic, is significant and valuable to people.
Distributed cyberinfrastructure tools for automated data processing of structural monitoring data
NASA Astrophysics Data System (ADS)
Zhang, Yilan; Kurata, Masahiro; Lynch, Jerome P.; van der Linden, Gwendolyn; Sederat, Hassan; Prakash, Atul
2012-04-01
The emergence of cost-effective sensing technologies has now enabled the use of dense arrays of sensors to monitor the behavior and condition of large-scale bridges. The continuous operation of dense networks of sensors presents a number of new challenges including how to manage such massive amounts of data that can be created by the system. This paper reports on the progress of the creation of cyberinfrastructure tools which hierarchically control networks of wireless sensors deployed in a long-span bridge. The internet-enabled cyberinfrastructure is centrally managed by a powerful database which controls the flow of data in the entire monitoring system architecture. A client-server model built upon the database provides both data-provider and system end-users with secured access to various levels of information of a bridge. In the system, information on bridge behavior (e.g., acceleration, strain, displacement) and environmental condition (e.g., wind speed, wind direction, temperature, humidity) are uploaded to the database from sensor networks installed in the bridge. Then, data interrogation services interface with the database via client APIs to autonomously process data. The current research effort focuses on an assessment of the scalability and long-term robustness of the proposed cyberinfrastructure framework that has been implemented along with a permanent wireless monitoring system on the New Carquinez (Alfred Zampa Memorial) Suspension Bridge in Vallejo, CA. Many data interrogation tools are under development using sensor data and bridge metadata (e.g., geometric details, material properties, etc.) Sample data interrogation clients including those for the detection of faulty sensors, automated modal parameter extraction.
Nguyen, Phong Ha; Arsalan, Muhammad; Koo, Ja Hyung; Naqvi, Rizwan Ali; Truong, Noi Quang; Park, Kang Ryoung
2018-05-24
Autonomous landing of an unmanned aerial vehicle or a drone is a challenging problem for the robotics research community. Previous researchers have attempted to solve this problem by combining multiple sensors such as global positioning system (GPS) receivers, inertial measurement unit, and multiple camera systems. Although these approaches successfully estimate an unmanned aerial vehicle location during landing, many calibration processes are required to achieve good detection accuracy. In addition, cases where drones operate in heterogeneous areas with no GPS signal should be considered. To overcome these problems, we determined how to safely land a drone in a GPS-denied environment using our remote-marker-based tracking algorithm based on a single visible-light-camera sensor. Instead of using hand-crafted features, our algorithm includes a convolutional neural network named lightDenseYOLO to extract trained features from an input image to predict a marker's location by visible light camera sensor on drone. Experimental results show that our method significantly outperforms state-of-the-art object trackers both using and not using convolutional neural network in terms of both accuracy and processing time.
A distributed geo-routing algorithm for wireless sensor networks.
Joshi, Gyanendra Prasad; Kim, Sung Won
2009-01-01
Geographic wireless sensor networks use position information for greedy routing. Greedy routing works well in dense networks, whereas in sparse networks it may fail and require a recovery algorithm. Recovery algorithms help the packet to get out of the communication void. However, these algorithms are generally costly for resource constrained position-based wireless sensor networks (WSNs). In this paper, we propose a void avoidance algorithm (VAA), a novel idea based on upgrading virtual distance. VAA allows wireless sensor nodes to remove all stuck nodes by transforming the routing graph and forwarding packets using only greedy routing. In VAA, the stuck node upgrades distance unless it finds a next hop node that is closer to the destination than it is. VAA guarantees packet delivery if there is a topologically valid path. Further, it is completely distributed, immediately responds to node failure or topology changes and does not require planarization of the network. NS-2 is used to evaluate the performance and correctness of VAA and we compare its performance to other protocols. Simulations show our proposed algorithm consumes less energy, has an efficient path and substantially less control overheads.
The Benefits of Using Dense Temperature Sensor Networks to Monitor Urban Warming
NASA Astrophysics Data System (ADS)
Twine, T. E.; Snyder, P. K.; Kucharik, C. J.; Schatz, J.
2015-12-01
Urban heat islands (UHIs) occur when urban and suburban areas experience temperatures that are elevated relative to their rural surroundings because of differences in the fraction of gray and green infrastructure. Studies have shown that communities most at risk for impacts from climate-related disasters (i.e., lower median incomes, higher poverty, lower education, and minorities) tend to live in the hottest areas of cities. Development of adequate climate adaptation tools for cities relies on knowledge of how temperature varies across space and time. Traditionally, a city's urban heat island has been quantified using near-surface air temperature measurements from a few sites. This methodology assumes (1) that the UHI can be characterized by the difference in air temperature from a small number of points, and (2) that these few points represent the urban and rural signatures of the region. This methodology ignores the rich information that could be gained from measurements across the urban to rural transect. This transect could traverse elevations, water bodies, vegetation fraction, and other land surface properties. Two temperature sensor networks were designed and implemented in the Minneapolis-Saint Paul, MN and Madison, WI metropolitan areas beginning in 2011 and 2012, respectively. Both networks use the same model sensor and record temperature every 15 minutes from ~150 sensors. Data from each network has produced new knowledge of how temperature varies diurnally and seasonally across the cities and how the UHI magnitude is influenced by weather phenomena (e.g., wind, snow cover, heat waves) and land surface characteristics such as proximity to inland lakes. However, the two metropolitan areas differ in size, population, structure, and orientation to water bodies. In addition, the sensor networks were established in very different manners. We describe these differences and present lessons learned from the design and ongoing efforts of these two dense networks located in the Midwest USA.
Broday, David M
2017-10-02
The evaluation of the effects of air pollution on public health and human-wellbeing requires reliable data. Standard air quality monitoring stations provide accurate measurements of airborne pollutant levels, but, due to their sparse distribution, they cannot capture accurately the spatial variability of air pollutant concentrations within cities. Dedicated in-depth field campaigns have dense spatial coverage of the measurements but are held for relatively short time periods. Hence, their representativeness is limited. Moreover, the oftentimes integrated measurements represent time-averaged records. Recent advances in communication and sensor technologies enable the deployment of dense grids of Wireless Distributed Environmental Sensor Networks for air quality monitoring, yet their capability to capture urban-scale spatiotemporal pollutant patterns has not been thoroughly examined to date. Here, we summarize our studies on the practicalities of using data streams from sensor nodes for air quality measurement and the required methods to tune the results to different stakeholders and applications. We summarize the results from eight cities across Europe, five sensor technologies-three stationary (with one tested also while moving) and two personal sensor platforms, and eight ambient pollutants. Overall, few sensors showed an exceptional and consistent performance, which can shed light on the fine spatiotemporal urban variability of pollutant concentrations. Stationary sensor nodes were more reliable than personal nodes. In general, the sensor measurements tend to suffer from the interference of various environmental factors and require frequent calibrations. This calls for the development of suitable field calibration procedures, and several such in situ field calibrations are presented.
2017-01-01
The evaluation of the effects of air pollution on public health and human-wellbeing requires reliable data. Standard air quality monitoring stations provide accurate measurements of airborne pollutant levels, but, due to their sparse distribution, they cannot capture accurately the spatial variability of air pollutant concentrations within cities. Dedicated in-depth field campaigns have dense spatial coverage of the measurements but are held for relatively short time periods. Hence, their representativeness is limited. Moreover, the oftentimes integrated measurements represent time-averaged records. Recent advances in communication and sensor technologies enable the deployment of dense grids of Wireless Distributed Environmental Sensor Networks for air quality monitoring, yet their capability to capture urban-scale spatiotemporal pollutant patterns has not been thoroughly examined to date. Here, we summarize our studies on the practicalities of using data streams from sensor nodes for air quality measurement and the required methods to tune the results to different stakeholders and applications. We summarize the results from eight cities across Europe, five sensor technologies-three stationary (with one tested also while moving) and two personal sensor platforms, and eight ambient pollutants. Overall, few sensors showed an exceptional and consistent performance, which can shed light on the fine spatiotemporal urban variability of pollutant concentrations. Stationary sensor nodes were more reliable than personal nodes. In general, the sensor measurements tend to suffer from the interference of various environmental factors and require frequent calibrations. This calls for the development of suitable field calibration procedures, and several such in situ field calibrations are presented. PMID:28974042
Emergent Adaptive Noise Reduction from Communal Cooperation of Sensor Grid
NASA Technical Reports Server (NTRS)
Jones, Kennie H.; Jones, Michael G.; Nark, Douglas M.; Lodding, Kenneth N.
2010-01-01
In the last decade, the realization of small, inexpensive, and powerful devices with sensors, computers, and wireless communication has promised the development of massive sized sensor networks with dense deployments over large areas capable of high fidelity situational assessments. However, most management models have been based on centralized control and research has concentrated on methods for passing data from sensor devices to the central controller. Most implementations have been small but, as it is not scalable, this methodology is insufficient for massive deployments. Here, a specific application of a large sensor network for adaptive noise reduction demonstrates a new paradigm where communities of sensor/computer devices assess local conditions and make local decisions from which emerges a global behaviour. This approach obviates many of the problems of centralized control as it is not prone to single point of failure and is more scalable, efficient, robust, and fault tolerant
Bridge damage detection using spatiotemporal patterns extracted from dense sensor network
NASA Astrophysics Data System (ADS)
Liu, Chao; Gong, Yongqiang; Laflamme, Simon; Phares, Brent; Sarkar, Soumik
2017-01-01
The alarmingly degrading state of transportation infrastructures combined with their key societal and economic importance calls for automatic condition assessment methods to facilitate smart management of maintenance and repairs. With the advent of ubiquitous sensing and communication capabilities, scalable data-driven approaches is of great interest, as it can utilize large volume of streaming data without requiring detailed physical models that can be inaccurate and computationally expensive to run. Properly designed, a data-driven methodology could enable fast and automatic evaluation of infrastructures, discovery of causal dependencies among various sub-system dynamic responses, and decision making with uncertainties and lack of labeled data. In this work, a spatiotemporal pattern network (STPN) strategy built on symbolic dynamic filtering (SDF) is proposed to explore spatiotemporal behaviors in a bridge network. Data from strain gauges installed on two bridges are generated using finite element simulation for three types of sensor networks from a density perspective (dense, nominal, sparse). Causal relationships among spatially distributed strain data streams are extracted and analyzed for vehicle identification and detection, and for localization of structural degradation in bridges. Multiple case studies show significant capabilities of the proposed approach in: (i) capturing spatiotemporal features to discover causality between bridges (geographically close), (ii) robustness to noise in data for feature extraction, (iii) detecting and localizing damage via comparison of bridge responses to similar vehicle loads, and (iv) implementing real-time health monitoring and decision making work flow for bridge networks. Also, the results demonstrate increased sensitivity in detecting damages and higher reliability in quantifying the damage level with increase in sensor network density.
Monitoring Bloom Dynamics of a Common Coastal Bioluminescent Ctenophore
2010-09-30
photodiodes. IMPACT/APPLICATIONS More frequent and more rapidly developing jellyfish blooms, especially Mnemiopsis leidyi as well as Harmful Algal...To meet the need for a bioluminescent jellyfish monitoring and forecasting system, predictive models will depend upon dense networks of sensor
Deployment of 802.15.4 Sensor Networks for C4ISR Operations
2006-06-01
43 Figure 20.MSP410CA Dense Grid Monitoring (Crossbow User’s Manual, 2005). ....................................44 Figure 21.(a)MICA2 without...Deployment of Sensor Grid (COASTS OPORD, 2006). ...56 Figure 27.Topology View of Two Nodes and Base Station .......57 Figure 28.Nodes Employing Multi...Random Access Memory TCP/IP Transmission Control Protocol/Internet Protocol TinyOS Tiny Micro Threading Operating System UARTs Universal
NASA Astrophysics Data System (ADS)
Celicourt, P.; Sam, R.; Piasecki, M.
2016-12-01
Global phenomena such as climate change and large scale environmental degradation require the collection of accurate environmental data at detailed spatial and temporal scales from which knowledge and actionable insights can be derived using data science methods. Despite significant advances in sensor network technologies, sensors and sensor network deployment remains a labor-intensive, time consuming, cumbersome and expensive task. These factors demonstrate why environmental data collection remains a challenge especially in developing countries where technical infrastructure, expertise and pecuniary resources are scarce. In addition, they also demonstrate the reason why dense and long-term environmental data collection has been historically quite difficult. Moreover, hydrometeorological data collection efforts usually overlook the (critically important) inclusion of a standards-based system for storing, managing, organizing, indexing, documenting and sharing sensor data. We are developing a cross-platform software framework using the Python programming language that will allow us to develop a low cost end-to-end (from sensor to publication) system for hydrometeorological conditions monitoring. The software framework contains provision for sensor, sensor platforms, calibration and network protocols description, sensor programming, data storage, data publication and visualization and more importantly data retrieval in a desired unit system. It is being tested on the Raspberry Pi microcomputer as end node and a laptop PC as the base station in a wireless setting.
NASA Astrophysics Data System (ADS)
Sim, Sung-Han; Spencer, Billie F., Jr.; Park, Jongwoong; Jung, Hyungjo
2012-04-01
Wireless Smart Sensor Networks (WSSNs) facilitates a new paradigm to structural identification and monitoring for civil infrastructure. Conventional monitoring systems based on wired sensors and centralized data acquisition and processing have been considered to be challenging and costly due to cabling and expensive equipment and maintenance costs. WSSNs have emerged as a technology that can overcome such difficulties, making deployment of a dense array of sensors on large civil structures both feasible and economical. However, as opposed to wired sensor networks in which centralized data acquisition and processing is common practice, WSSNs require decentralized computing algorithms to reduce data transmission due to the limitation associated with wireless communication. Thus, several system identification methods have been implemented to process sensor data and extract essential information, including Natural Excitation Technique with Eigensystem Realization Algorithm, Frequency Domain Decomposition (FDD), and Random Decrement Technique (RDT); however, Stochastic Subspace Identification (SSI) has not been fully utilized in WSSNs, while SSI has the strong potential to enhance the system identification. This study presents a decentralized system identification using SSI in WSSNs. The approach is implemented on MEMSIC's Imote2 sensor platform and experimentally verified using a 5-story shear building model.
Using Network Theory to Understand Seismic Noise in Dense Arrays
NASA Astrophysics Data System (ADS)
Riahi, N.; Gerstoft, P.
2015-12-01
Dense seismic arrays offer an opportunity to study anthropogenic seismic noise sources with unprecedented detail. Man-made sources typically have high frequency, low intensity, and propagate as surface waves. As a result attenuation restricts their measurable footprint to a small subset of sensors. Medium heterogeneities can further introduce wave front perturbations that limit processing based on travel time. We demonstrate a non-parametric technique that can reliably identify very local events within the array as a function of frequency and time without using travel-times. The approach estimates the non-zero support of the array covariance matrix and then uses network analysis tools to identify clusters of sensors that are sensing a common source. We verify the method on simulated data and then apply it to the Long Beach (CA) geophone array. The method exposes a helicopter traversing the array, oil production facilities with different characteristics, and the fact that noise sources near roads tend to be around 10-20 Hz.
Protocol to Exploit Waiting Resources for UASNs.
Hung, Li-Ling; Luo, Yung-Jeng
2016-03-08
The transmission speed of acoustic waves in water is much slower than that of radio waves in terrestrial wireless sensor networks. Thus, the propagation delay in underwater acoustic sensor networks (UASN) is much greater. Longer propagation delay leads to complicated communication and collision problems. To solve collision problems, some studies have proposed waiting mechanisms; however, long waiting mechanisms result in low bandwidth utilization. To improve throughput, this study proposes a slotted medium access control protocol to enhance bandwidth utilization in UASNs. The proposed mechanism increases communication by exploiting temporal and spatial resources that are typically idle in order to protect communication against interference. By reducing wait time, network performance and energy consumption can be improved. A performance evaluation demonstrates that when the data packets are large or sensor deployment is dense, the energy consumption of proposed protocol is less than that of existing protocols as well as the throughput is higher than that of existing protocols.
Health monitoring of offshore structures using wireless sensor network: experimental investigations
NASA Astrophysics Data System (ADS)
Chandrasekaran, Srinivasan; Chitambaram, Thailammai
2016-04-01
This paper presents a detailed methodology of deploying wireless sensor network in offshore structures for structural health monitoring (SHM). Traditional SHM is carried out by visual inspections and wired systems, which are complicated and requires larger installation space to deploy while decommissioning is a tedious process. Wireless sensor networks can enhance the art of health monitoring with deployment of scalable and dense sensor network, which consumes lesser space and lower power consumption. Proposed methodology is mainly focused to determine the status of serviceability of large floating platforms under environmental loads using wireless sensors. Data acquired by the servers will analyze the data for their exceedance with respect to the threshold values. On failure, SHM architecture will trigger an alarm or an early warning in the form of alert messages to alert the engineer-in-charge on board; emergency response plans can then be subsequently activated, which shall minimize the risk involved apart from mitigating economic losses occurring from the accidents. In the present study, wired and wireless sensors are installed in the experimental model and the structural response, acquired is compared. The wireless system comprises of Raspberry pi board, which is programmed to transmit the acquired data to the server using Wi-Fi adapter. Data is then hosted in the webpage for further post-processing, as desired.
NASA Astrophysics Data System (ADS)
Kobayashi, Y.; Watanabe, K.; Imai, M.; Watanabe, K.; Naruse, N.; Takahashi, Y.
2016-12-01
Hyper-densely monitoring for poor-visibility occurred by snowstorm is needed to make an alert system, because the snowstorm is difficult to predict from the observation only at a representative point. There are some problems in the previous approaches for the poor-visibility monitoring using video analyses or visibility meters; these require a wired network monitoring (a large amount of data: 10MB/sec at least) and the system cost is high (10,000 at each point). Thus, the risk of poor-visibility has been mainly measured at specific point such as airport and mountain pass, and estimated by simulation two dimensionally. To predict it two dimensionally and accurately, we have developed a low-cost meteorological system to observe the snowstorm hyper-densely. We have developed a low-cost visibility meter which works as the reduced intensity of semiconducting laser light when snow particles block off. Our developed system also has a capability of extending a hyper-densely observation in real-time on wireless network using Zigbee; A/D conversion and wireless data sent from temperature and illuminance sensors. We use a semiconducting laser chip (5) for the light source and a reflection mechanism by the use of three mirrors so as to send the light to a non-sensitive illuminance sensor directly. Thus, our visibility detecting system ($500) becomes much cheaper than previous one. We have checked the correlation between the reduced intensity taken by our system and the visibility recorded by conventional video camera. The value for the correlation coefficient was -0.67, which indicates a strong correlation. It means that our developed system is practical. In conclusion, we have developed low-cost meteorological detecting system to observe poor-visibility occurred by snowstorm, having a potential of hyper-densely monitoring on wireless network, and have made sure the practicability.
Delaunay Triangulation as a New Coverage Measurement Method in Wireless Sensor Network
Chizari, Hassan; Hosseini, Majid; Poston, Timothy; Razak, Shukor Abd; Abdullah, Abdul Hanan
2011-01-01
Sensing and communication coverage are among the most important trade-offs in Wireless Sensor Network (WSN) design. A minimum bound of sensing coverage is vital in scheduling, target tracking and redeployment phases, as well as providing communication coverage. Some methods measure the coverage as a percentage value, but detailed information has been missing. Two scenarios with equal coverage percentage may not have the same Quality of Coverage (QoC). In this paper, we propose a new coverage measurement method using Delaunay Triangulation (DT). This can provide the value for all coverage measurement tools. Moreover, it categorizes sensors as ‘fat’, ‘healthy’ or ‘thin’ to show the dense, optimal and scattered areas. It can also yield the largest empty area of sensors in the field. Simulation results show that the proposed DT method can achieve accurate coverage information, and provides many tools to compare QoC between different scenarios. PMID:22163792
A deployment of fine-grained sensor network and empirical analysis of urban temperature.
Thepvilojanapong, Niwat; Ono, Takahiro; Tobe, Yoshito
2010-01-01
Temperature in an urban area exhibits a complicated pattern due to complexity of infrastructure. Despite geographical proximity, structures of a group of buildings and streets affect changes in temperature. To investigate the pattern of fine-grained distribution of temperature, we installed a densely distributed sensor network called UScan. In this paper, we describe the system architecture of UScan as well as experience learned from installing 200 sensors in downtown Tokyo. The field experiment of UScan system operated for two months to collect long-term urban temperature data. To analyze the collected data in an efficient manner, we propose a lightweight clustering methodology to study the correlation between the pattern of temperature and various environmental factors including the amount of sunshine, the width of streets, and the existence of trees. The analysis reveals meaningful results and asserts the necessity of fine-grained deployment of sensors in an urban area.
Pairwise graphical models for structural health monitoring with dense sensor arrays
NASA Astrophysics Data System (ADS)
Mohammadi Ghazi, Reza; Chen, Justin G.; Büyüköztürk, Oral
2017-09-01
Through advances in sensor technology and development of camera-based measurement techniques, it has become affordable to obtain high spatial resolution data from structures. Although measured datasets become more informative by increasing the number of sensors, the spatial dependencies between sensor data are increased at the same time. Therefore, appropriate data analysis techniques are needed to handle the inference problem in presence of these dependencies. In this paper, we propose a novel approach that uses graphical models (GM) for considering the spatial dependencies between sensor measurements in dense sensor networks or arrays to improve damage localization accuracy in structural health monitoring (SHM) application. Because there are always unobserved damaged states in this application, the available information is insufficient for learning the GMs. To overcome this challenge, we propose an approximated model that uses the mutual information between sensor measurements to learn the GMs. The study is backed by experimental validation of the method on two test structures. The first is a three-story two-bay steel model structure that is instrumented by MEMS accelerometers. The second experimental setup consists of a plate structure and a video camera to measure the displacement field of the plate. Our results show that considering the spatial dependencies by the proposed algorithm can significantly improve damage localization accuracy.
Gil Jiménez, Víctor P.; Armada, Ana García
2009-01-01
Frequently, Wireless Sensor Networks (WSN) are designed focusing on applications and omitting transmission problems in these wireless networks. In this paper, we present a measurement campaign that has been carried out using one of the most commonly used WSN platforms, the micaZ from Crossbow©. Based on these measurements, some guidelines to deploy a robust and reliable WSN are provided. The results are focused on security and environmental applications but can also be extrapolated to other scenarios. A main conclusion that can be extracted is that, from the transmission point of view, a dense WSN is one of the best choices to overcome many of the transmission problems such as the existence of a transitional region, redundance, forwarding, obstructions or interference with other systems. PMID:22303175
A New Black Carbon Sensor for Dense Air Quality Monitoring Networks
Caubel, Julien J.; Cados, Troy E.; Kirchstetter, Thomas W.
2018-01-01
Low-cost air pollution sensors are emerging and increasingly being deployed in densely distributed wireless networks that provide more spatial resolution than is typical in traditional monitoring of ambient air quality. However, a low-cost option to measure black carbon (BC)—a major component of particulate matter pollution associated with adverse human health risks—is missing. This paper presents a new BC sensor designed to fill this gap, the Aerosol Black Carbon Detector (ABCD), which incorporates a compact weatherproof enclosure, solar-powered rechargeable battery, and cellular communication to enable long-term, remote operation. This paper also demonstrates a data processing methodology that reduces the ABCD’s sensitivity to ambient temperature fluctuations, and therefore improves measurement performance in unconditioned operating environments (e.g., outdoors). A fleet of over 100 ABCDs was operated outdoors in collocation with a commercial BC instrument (Magee Scientific, Model AE33) housed inside a regulatory air quality monitoring station. The measurement performance of the 105 ABCDs is comparable to the AE33. The fleet-average precision and accuracy, expressed in terms of mean absolute percentage error, are 9.2 ± 0.8% (relative to the fleet average data) and 24.6 ± 0.9% (relative to the AE33 data), respectively (fleet-average ± 90% confidence interval). PMID:29494528
A New Black Carbon Sensor for Dense Air Quality Monitoring Networks.
Caubel, Julien J; Cados, Troy E; Kirchstetter, Thomas W
2018-03-01
Low-cost air pollution sensors are emerging and increasingly being deployed in densely distributed wireless networks that provide more spatial resolution than is typical in traditional monitoring of ambient air quality. However, a low-cost option to measure black carbon (BC)-a major component of particulate matter pollution associated with adverse human health risks-is missing. This paper presents a new BC sensor designed to fill this gap, the Aerosol Black Carbon Detector (ABCD), which incorporates a compact weatherproof enclosure, solar-powered rechargeable battery, and cellular communication to enable long-term, remote operation. This paper also demonstrates a data processing methodology that reduces the ABCD's sensitivity to ambient temperature fluctuations, and therefore improves measurement performance in unconditioned operating environments (e.g., outdoors). A fleet of over 100 ABCDs was operated outdoors in collocation with a commercial BC instrument (Magee Scientific, Model AE33) housed inside a regulatory air quality monitoring station. The measurement performance of the 105 ABCDs is comparable to the AE33. The fleet-average precision and accuracy, expressed in terms of mean absolute percentage error, are 9.2 ± 0.8% (relative to the fleet average data) and 24.6 ± 0.9% (relative to the AE33 data), respectively (fleet-average ± 90% confidence interval).
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.
NASA Astrophysics Data System (ADS)
Airoldi, A.; Marelli, L.; Bettini, P.; Sala, G.; Apicella, A.
2017-04-01
Technologies based on optical fibers provide the possibility of installing relatively dense networks of sensors that can perform effective strain sensing functions during the operational life of structures. A contemporary trend is the increasing adoption of composite materials in aerospace constructions, which leads to structural architectures made of large monolithic elements. The paper is aimed at showing the feasibility of a detailed reconstruction of the strain field in a composite spar, which is based on the development of reference finite element models and the identification of load modes, consisting of a parameterized set of forces. The procedure is described and assessed in ideal conditions. Thereafter, a surrogate model is used to obtain realistic representation of the data acquired by the strain sensing system, so that the developed procedure is evaluated considering local effects due to the introduction of loads, significant modelling discrepancy in the development of the reference model and the presence of measurement noise. Results show that the method can obtain a robust and quite detailed reconstruction of strain fields, even at the level of local distributions, of the internal forces in the spars and of the displacements, by identifying an equivalent set of load parameters. Finally, the trade-off between the number of sensor and the accuracy, and the optimal position of the sensors for a given maximum number of sensors is evaluated by performing a multi-objective optimization, thus showing that even a relative dense network of externally applied sensors can be used to achieve good quality results.
Baron, Ronan; Saffell, John
2017-11-22
This review examines the use of amperometric electrochemical gas sensors for monitoring inorganic gases that affect urban air quality. First, we consider amperometric gas sensor technology including its development toward specifically designed air quality sensors. We then review recent academic and research organizations' studies where this technology has been trialed for air quality monitoring applications: early studies showed the potential of electrochemical gas sensors when colocated with reference Air Quality Monitoring (AQM) stations. Spatially dense networks with fast temporal resolution provide information not available from sparse AQMs with longer recording intervals. We review how this technology is being offered as commercial urban air quality networks and consider the remaining challenges. Sensors must be sensitive, selective, and stable; air quality monitors/nodes must be electronically and mechanically well designed. Data correction is required and models with differing levels of sophistication are being designed. Data analysis and validation is possibly the biggest remaining hurdle needed to deliver reliable concentration readings. Finally, this review also considers the roles of companies, urban infrastructure requirements, and public research in the development of this technology.
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.
NASA Astrophysics Data System (ADS)
Kim, Jinsol; Shusterman, Alexis A.; Lieschke, Kaitlyn J.; Newman, Catherine; Cohen, Ronald C.
2018-04-01
The newest generation of air quality sensors is small, low cost, and easy to deploy. These sensors are an attractive option for developing dense observation networks in support of regulatory activities and scientific research. They are also of interest for use by individuals to characterize their home environment and for citizen science. However, these sensors are difficult to interpret. Although some have an approximately linear response to the target analyte, that response may vary with time, temperature, and/or humidity, and the cross-sensitivity to non-target analytes can be large enough to be confounding. Standard approaches to calibration that are sufficient to account for these variations require a quantity of equipment and labor that negates the attractiveness of the sensors' low cost. Here we describe a novel calibration strategy for a set of sensors, including CO, NO, NO2, and O3, that makes use of (1) multiple co-located sensors, (2) a priori knowledge about the chemistry of NO, NO2, and O3, (3) an estimate of mean emission factors for CO, and (4) the global background of CO. The strategy requires one or more well calibrated anchor points within the network domain, but it does not require direct calibration of any of the individual low-cost sensors. The procedure nonetheless accounts for temperature and drift, in both the sensitivity and zero offset. We demonstrate this calibration on a subset of the sensors comprising BEACO2N, a distributed network of approximately 50 sensor nodes
, each measuring CO2, CO, NO, NO2, O3 and particulate matter at 10 s time resolution and approximately 2 km spacing within the San Francisco Bay Area.
D-DSC: Decoding Delay-based Distributed Source Coding for Internet of Sensing Things
Akan, Ozgur B.
2018-01-01
Spatial correlation between densely deployed sensor nodes in a wireless sensor network (WSN) can be exploited to reduce the power consumption through a proper source coding mechanism such as distributed source coding (DSC). In this paper, we propose the Decoding Delay-based Distributed Source Coding (D-DSC) to improve the energy efficiency of the classical DSC by employing the decoding delay concept which enables the use of the maximum correlated portion of sensor samples during the event estimation. In D-DSC, network is partitioned into clusters, where the clusterheads communicate their uncompressed samples carrying the side information, and the cluster members send their compressed samples. Sink performs joint decoding of the compressed and uncompressed samples and then reconstructs the event signal using the decoded sensor readings. Based on the observed degree of the correlation among sensor samples, the sink dynamically updates and broadcasts the varying compression rates back to the sensor nodes. Simulation results for the performance evaluation reveal that D-DSC can achieve reliable and energy-efficient event communication and estimation for practical signal detection/estimation applications having massive number of sensors towards the realization of Internet of Sensing Things (IoST). PMID:29538405
D-DSC: Decoding Delay-based Distributed Source Coding for Internet of Sensing Things.
Aktas, Metin; Kuscu, Murat; Dinc, Ergin; Akan, Ozgur B
2018-01-01
Spatial correlation between densely deployed sensor nodes in a wireless sensor network (WSN) can be exploited to reduce the power consumption through a proper source coding mechanism such as distributed source coding (DSC). In this paper, we propose the Decoding Delay-based Distributed Source Coding (D-DSC) to improve the energy efficiency of the classical DSC by employing the decoding delay concept which enables the use of the maximum correlated portion of sensor samples during the event estimation. In D-DSC, network is partitioned into clusters, where the clusterheads communicate their uncompressed samples carrying the side information, and the cluster members send their compressed samples. Sink performs joint decoding of the compressed and uncompressed samples and then reconstructs the event signal using the decoded sensor readings. Based on the observed degree of the correlation among sensor samples, the sink dynamically updates and broadcasts the varying compression rates back to the sensor nodes. Simulation results for the performance evaluation reveal that D-DSC can achieve reliable and energy-efficient event communication and estimation for practical signal detection/estimation applications having massive number of sensors towards the realization of Internet of Sensing Things (IoST).
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.
NASA Astrophysics Data System (ADS)
Simonis, Ingo
2015-04-01
Transport infrastructure monitoring and analysis is one of the focus areas in the context of smart cities. With the growing number of people moving into densely populated urban metro areas, precise tracking of moving people and goods is the basis for profound decision-making and future planning. With the goal of defining optimal extensions and modifications to existing transport infrastructures, multi-modal transport has to be monitored and analysed. This process is performed on the basis of sensor networks that combine a variety of sensor models, types, and deployments within the area of interest. Multi-generation networks, consisting of a number of sensor types and versions, are causing further challenges for the integration and processing of sensor observations. These challenges are not getting any smaller with the development of the Internet of Things, which brings promising opportunities, but is currently stuck in a type of protocol war between big industry players from both the hardware and network infrastructure domain. In this paper, we will highlight how the OGC suite of standards, with the Sensor Web standards developed by the Sensor Web Enablement Initiative together with the latest developments by the Sensor Web for Internet of Things community can be applied to the monitoring and improvement of transport infrastructures. Sensor Web standards have been applied in the past to pure technical domains, but need to be broadened now in order to meet new challenges. Only cross domain approaches will allow to develop satisfying transport infrastructure approaches that take into account requirements coming form a variety of sectors such as tourism, administration, transport industry, emergency services, or private people. The goal is the development of interoperable components that can be easily integrated within data infrastructures and follow well defined information models to allow robust processing.
NASA Astrophysics Data System (ADS)
Robertson, Jamie; Shinozuka, Masanobu; Wu, Felix
2011-04-01
When a lifeline system such as a water delivery network is damaged due to a severe earthquake, it is critical to identify its location and extent of the damage in real time in order to minimize the potentially disastrous consequence such damage could otherwise entail. This paper demonstrates how the degree of such minimization can be estimated qualitatively by using the water delivery system of Irvine Water Ranch District (IRWD) as testbed, when it is subjected to magnitude 6.6 San Joaquin Hills Earthquake. In this demonstration, we consider two cases when the IRWD system is equipped or not equipped with a next generation SCADA which consists of a network of MEMS acceleration sensors densely populated and optimally located. These sensors are capable of identifying the location and extent of the damage as well as transmitting the data to the SCADA center for monitoring and control.
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.
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.
Wireless Sensor Platform for Cultural Heritage Monitoring and Modeling System
Bermudez, Sergio A.; Schrott, Alejandro G.; Tsukada, Masahiko; Kargere, Lucretia; Marianno, Fernando; Hamann, Hendrik F.; López, Vanessa; Leona, Marco
2017-01-01
Results from three years of continuous monitoring of environmental conditions using a wireless sensor platform installed at The Cloisters, the medieval branch of the New York Metropolitan Museum of Art, are presented. The platform comprises more than 200 sensors that were distributed in five galleries to assess temperature and air flow and to quantify microclimate changes using physics-based and statistical models. The wireless sensor network data shows a very stable environment within the galleries, while the dense monitoring enables localized monitoring of subtle changes in air quality trends and impact of visitors on the microclimate conditions. The high spatial and temporal resolution data serves as a baseline study to understand the impact of visitors and building operations on the long-term preservation of art objects. PMID:28858223
Wireless Sensor Platform for Cultural Heritage Monitoring and Modeling System.
Klein, Levente J; Bermudez, Sergio A; Schrott, Alejandro G; Tsukada, Masahiko; Dionisi-Vici, Paolo; Kargere, Lucretia; Marianno, Fernando; Hamann, Hendrik F; López, Vanessa; Leona, Marco
2017-08-31
Results from three years of continuous monitoring of environmental conditions using a wireless sensor platform installed at The Cloisters, the medieval branch of the New York Metropolitan Museum of Art, are presented. The platform comprises more than 200 sensors that were distributed in five galleries to assess temperature and air flow and to quantify microclimate changes using physics-based and statistical models. The wireless sensor network data shows a very stable environment within the galleries, while the dense monitoring enables localized monitoring of subtle changes in air quality trends and impact of visitors on the microclimate conditions. The high spatial and temporal resolution data serves as a baseline study to understand the impact of visitors and building operations on the long-term preservation of art objects.
NASA Astrophysics Data System (ADS)
Stock, M.; Lapierre, J. L.; Zhu, Y.
2017-12-01
Recently, the Geostationary Lightning Mapper (GLM) began collecting optical data to locate lightning events and flashes over the North and South American continents. This new instrument promises uniformly high detection efficiency (DE) over its entire field of view, with location accuracy on the order of 10 km. In comparison, Earth Networks Total Lightning Networks (ENTLN) has a less uniform coverage, with higher DE in regions with dense sensor coverage, and lower DE with sparse sensor coverage. ENTLN also offers better location accuracy, lightning classification, and peak current estimation for their lightning locations. It is desirable to produce an integrated dataset, combining the strong points of GLM and ENTLN. The easiest way to achieve this is to simply match located lightning processes from each system using time and distance criteria. This simple method will be limited in scope by the uneven coverage of the ground based network. Instead, we will use GLM group locations to look up the electric field change data recorded by ground sensors near each GLM group, vastly increasing the coverage of the ground network. The ground waveforms can then be used for: improvements to differentiation between glint and lightning for GLM, higher precision lighting location, current estimation, and lightning process classification. Presented is an initial implementation of this type of integration using preliminary GLM data, and waveforms from ENTLN.
Shamwell, E Jared; Nothwang, William D; Perlis, Donald
2018-05-04
Aimed at improving size, weight, and power (SWaP)-constrained robotic vision-aided state estimation, we describe our unsupervised, deep convolutional-deconvolutional sensor fusion network, Multi-Hypothesis DeepEfference (MHDE). MHDE learns to intelligently combine noisy heterogeneous sensor data to predict several probable hypotheses for the dense, pixel-level correspondence between a source image and an unseen target image. We show how our multi-hypothesis formulation provides increased robustness against dynamic, heteroscedastic sensor and motion noise by computing hypothesis image mappings and predictions at 76⁻357 Hz depending on the number of hypotheses being generated. MHDE fuses noisy, heterogeneous sensory inputs using two parallel, inter-connected architectural pathways and n (1⁻20 in this work) multi-hypothesis generating sub-pathways to produce n global correspondence estimates between a source and a target image. We evaluated MHDE on the KITTI Odometry dataset and benchmarked it against the vision-only DeepMatching and Deformable Spatial Pyramids algorithms and were able to demonstrate a significant runtime decrease and a performance increase compared to the next-best performing method.
Evaluating the Reverse Time Migration Method on the dense Lapnet / Polenet seismic array in Europe
NASA Astrophysics Data System (ADS)
Dupont, Aurélien; Le Pichon, Alexis
2013-04-01
In this study, results are obtained using the reverse time migration method used as benchmark to evaluate the implemented method by Walker et al., (2010, 2011). Explosion signals recorded by the USArray and extracted from the TAIRED catalogue (TA Infrasound Reference Event Database user community / Vernon et al., 2012) are investigated. The first one is an explosion at Camp Minden, Louisiana (2012-10-16 04:25:00 UTC) and the second one is a natural gas explosion near Price, Utah (2012-11-20 15:20:00 UTC). We compare our results to automatic solutions (www.iris.edu/spud/infrasoundevent). The good agreement between both solutions validates our detection method. In a second time, we analyse data from the Lapnet / Polenet dense seismic network (Kozlovskaya et al., 2008). Detection and location in two-dimensional space and time of infrasound events presumably due to acoustic-to-seismic coupling, during the 2007-2009 period in Europe, are presented. The aim of this work is to integrate near-real time network performance predictions at regional scales to improve automatic detection of infrasonic sources. The use of dense seismic networks provides a valuable tool to monitor infrasonic phenomena, since seismic location has recently proved to be more accurate than infrasound locations due to the large number of seismic sensors.
Tsunami Simulation Method Assimilating Ocean Bottom Pressure Data Near a Tsunami Source Region
NASA Astrophysics Data System (ADS)
Tanioka, Yuichiro
2018-02-01
A new method was developed to reproduce the tsunami height distribution in and around the source area, at a certain time, from a large number of ocean bottom pressure sensors, without information on an earthquake source. A dense cabled observation network called S-NET, which consists of 150 ocean bottom pressure sensors, was installed recently along a wide portion of the seafloor off Kanto, Tohoku, and Hokkaido in Japan. However, in the source area, the ocean bottom pressure sensors cannot observe directly an initial ocean surface displacement. Therefore, we developed the new method. The method was tested and functioned well for a synthetic tsunami from a simple rectangular fault with an ocean bottom pressure sensor network using 10 arc-min, or 20 km, intervals. For a test case that is more realistic, ocean bottom pressure sensors with 15 arc-min intervals along the north-south direction and sensors with 30 arc-min intervals along the east-west direction were used. In the test case, the method also functioned well enough to reproduce the tsunami height field in general. These results indicated that the method could be used for tsunami early warning by estimating the tsunami height field just after a great earthquake without the need for earthquake source information.
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.
Smart sensing surveillance system
NASA Astrophysics Data System (ADS)
Hsu, Charles; Chu, Kai-Dee; O'Looney, James; Blake, Michael; Rutar, Colleen
2010-04-01
An effective public safety sensor system for heavily-populated applications requires sophisticated and geographically-distributed infrastructures, centralized supervision, and deployment of large-scale security and surveillance networks. Artificial intelligence in sensor systems is a critical design to raise awareness levels, improve the performance of the system and adapt to a changing scenario and environment. In this paper, a highly-distributed, fault-tolerant, and energy-efficient Smart Sensing Surveillance System (S4) is presented to efficiently provide a 24/7 and all weather security operation in crowded environments or restricted areas. Technically, the S4 consists of a number of distributed sensor nodes integrated with specific passive sensors to rapidly collect, process, and disseminate heterogeneous sensor data from near omni-directions. These distributed sensor nodes can cooperatively work to send immediate security information when new objects appear. When the new objects are detected, the S4 will smartly select the available node with a Pan- Tilt- Zoom- (PTZ) Electro-Optics EO/IR camera to track the objects and capture associated imagery. The S4 provides applicable advanced on-board digital image processing capabilities to detect and track the specific objects. The imaging detection operations include unattended object detection, human feature and behavior detection, and configurable alert triggers, etc. Other imaging processes can be updated to meet specific requirements and operations. In the S4, all the sensor nodes are connected with a robust, reconfigurable, LPI/LPD (Low Probability of Intercept/ Low Probability of Detect) wireless mesh network using Ultra-wide band (UWB) RF technology. This UWB RF technology can provide an ad-hoc, secure mesh network and capability to relay network information, communicate and pass situational awareness and messages. The Service Oriented Architecture of S4 enables remote applications to interact with the S4 network and use the specific presentation methods. In addition, the S4 is compliant with Open Geospatial Consortium - Sensor Web Enablement (OGC-SWE) standards to efficiently discover, access, use, and control heterogeneous sensors and their metadata. These S4 capabilities and technologies have great potential for both military and civilian applications, enabling highly effective security support tools for improving surveillance activities in densely crowded environments. The S4 system is directly applicable to solutions for emergency response personnel, law enforcement, and other homeland security missions, as well as in applications requiring the interoperation of sensor networks with handheld or body-worn interface devices.
Studies of infrasound propagation using the USArray seismic network (Invited)
NASA Astrophysics Data System (ADS)
Hedlin, M. A.; Degroot-Hedlin, C. D.; Walker, K. T.
2010-12-01
Although there are currently ~ 100 infrasound arrays worldwide, more than ever before, the station density is still insufficient to provide validation for detailed propagation modeling. Much structure in the atmosphere is short-lived and occurs at spatial scales much smaller than the average distance between infrasound stations. Relatively large infrasound signals can be observed on seismic channels due to coupling at the Earth's surface. Recent research, using data from the 70-km spaced 400-station USArray and other seismic network deployments, has shown the value of dense seismic network data for filling in the gaps between infrasound arrays. The dense sampling of the infrasound wavefield has allowed us to observe complete travel-time branches of infrasound signals and shed more light on the nature of infrasound propagation. We present early results from our studies of impulsive atmospheric sources, such as series of UTTR rocket motor detonations in Utah. The Utah blasts have been well recorded by USArray seismic stations and infrasound arrays in Nevada and Washington State. Recordings of seismic signals from a series of six events in 2007 are used to pinpoint the shot times to < 1 second. Variations in the acoustic branches and signal arrival times at the arrays are used to probe variations in atmospheric structure. Although we currently use coupled signals we anticipate studying dense acoustic network recordings as the USArray is currently being upgraded with infrasound microphones. These new sensors will allow us to make semi-continental scale network recordings of infrasound signals free of concerns about how the signals observed on seismic channels were modified when being coupled to seismic.
A spatiotemporal analysis of hydrological patterns based on a wireless sensor network system
NASA Astrophysics Data System (ADS)
Plaza, F.; Slater, T. A.; Zhong, X.; Li, Y.; Liang, Y.; Liang, X.
2017-12-01
Understanding complicated spatiotemporal patterns of eco-hydrological variables at a small scale plays a profound role in improving predictability of high resolution distributed hydrological models. However, accurate and continuous monitoring of these complex patterns has become one of the main challenges in the environmental sciences. Wireless sensor networks (WSNs) have emerged as one of the most widespread potential solutions to achieve this. This study presents a spatiotemporal analysis of hydrological patterns (e.g., soil moisture, soil water potential, soil temperature and transpiration) based on observational data collected from a dense multi-hop wireless sensor network (WSN) in a steep-forested testbed located in Southwestern Pennsylvania, USA. At this WSN testbed with an approximate area of 3000 m2, environmental variables are collected from over 240 sensors that are connected to more than 100 heterogeneous motes. The sensors include the soil moisture of EC-5, soil temperature and soil water potential of MPS-1 and MPS-2, and sap flow sensors constructed in house. The motes consist of MICAz, IRIS and TelosB. In addition, several data loggers have been installed along the site to provide a comparative reference to the WSN measurements for the purpose of checking the WSN data quality. The edaphic properties monitored by the WSN sensors show strong agreement with the data logger measurements. Moreover, sap flow measurements, scaled to tree stand transpiration, are found to be reasonable. This study also investigates the feasibility and roles that these sensor measurements play in improving the performance of high-resolution distributed hydrological models. In particular, we explore this using a modified version of the Distributed Hydrological Soil Vegetation Model (DHSVM).
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.
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.
The Community Seismic Network: Enabling Observations Through Citizen Science Participation
NASA Astrophysics Data System (ADS)
Kohler, M. D.; Clayton, R. W.; Heaton, T. H.; Bunn, J.; Guy, R.; Massari, A.; Chandy, K. M.
2017-12-01
The Community Seismic Network is a dense accelerometer array deployed in the greater Los Angeles area and represents the future of densely instrumented urban cities where localized vibration measurements are collected continuously throughout the free-field and built environment. The hardware takes advantage of developments in the semiconductor industry in the form of inexpensive MEMS accelerometers that are each coupled with a single board computer. The data processing and archival architecture borrows from developments in cloud computing and network connectedness. The ability to deploy densely in the free field and in upper stories of mid/high-rise buildings is enabled by community hosts for sensor locations. To this end, CSN has partnered with the Los Angeles Unified School District (LAUSD), the NASA-Jet Propulsion Laboratory (JPL), and commercial and civic building owners to host sensors. At these sites, site amplification estimates from RMS noise measurements illustrate the lateral variation in amplification over length scales of 100 m or less, that correlate with gradients in the local geology such as sedimentary basins that abut crystalline rock foothills. This is complemented by high-resolution, shallow seismic velocity models obtained using an H/V method. In addition, noise statistics are used to determine the reliability of sites for ShakeMap and earthquake early warning data. The LAUSD and JPL deployments are examples of how situational awareness and centralized warning products such as ShakeMap and ShakeCast are enabled by citizen science participation. Several buildings have been instrumented with at least one triaxial accelerometer per floor, providing measurements for real-time structural health monitoring through local, customized displays. For real-time and post-event evaluation, the free-field and built environment CSN data and products illustrate the feasibility of order-of-magnitude higher spatial resolution mapping compared to what is currently possible with traditional, regional seismic networks. The JPL experiment in particular represents a miniature prototype for city-wide earthquake monitoring that combines free-field measurements for ground shaking intensities, with mid-rise building response through advanced fragility curve computations.
Cheadle, Lucy; Deanes, Lauren; Sadighi, Kira; Gordon Casey, Joanna; Collier-Oxandale, Ashley; Hannigan, Michael
2017-09-10
Recent advances in air pollution sensors have led to a new wave of low-cost measurement systems that can be deployed in dense networks to capture small-scale spatio-temporal variations in ozone, a pollutant known to cause negative human health impacts. This study deployed a network of seven low-cost ozone metal oxide sensor systems (UPods) in both an open space and an urban location in Boulder, Colorado during June and July of 2015, to quantify ozone variations on spatial scales ranging from 12 m between UPods to 6.7 km between open space and urban measurement sites with a measurement uncertainty of ~5 ppb. The results showed spatial variability of ozone at both deployment sites, with the largest differences between UPod measurements occurring during the afternoons. The peak median hourly difference between UPods was 6 ppb at 1:00 p.m. at the open space site, and 11 ppb at 4:00 p.m. at the urban site. Overall, the urban ozone measurements were higher than in the open space measurements. This study evaluates the effectiveness of using low-cost sensors to capture microscale spatial and temporal variation of ozone; additionally, it highlights the importance of field calibrations and measurement uncertainty quantification when deploying low-cost sensors.
NASA Astrophysics Data System (ADS)
Gupta, S.; Tripathi, S.; Sinha, R.; Karumanchi, S. H.; Paul, D.; Tripathi, S. N.; Sen, I. S.; Dash, S. K.
2017-12-01
The Ganga plains represent the abode of more than 400 million people and a region of severe anthropogenic disturbance to natural processes. Changing agricultural practices, inefficient use of water, contamination of groundwater systems, and decrease in soil fertility are some of the issues that have affected the long-term resilience of hydrological processes. The quantification of these processes demands a network of hydro-meteorological instrumentation, low-cost sensors, continuous engagement of stakeholders and real time data transmission at a fine interval. We have therefore set up a Critical Zone Observatory (CZO) in a small watershed (35km2) that forms an intensively managed rural landscape consisting of 92% of agricultural land in the Pandu River Basin (a small tributary of the Ganga River). Apart from setting up a hydro-meteorological observatory, the major science questions we want to address relate to development of water balance model, understanding the soil-water interaction and estimation of nutrient fluxes in the watershed. This observatory currently has various types of sensors that are divided into three categories: (a) spatially not dense but temporally fine data, (b) spatially dense but temporally not fine data and(c) spatially dense and temporally fine data. The first category represent high-cost sensors namely automatic weather stations that are deployed at two locations and provide data at 15-minute interval. The second category includes portable soil moisture, discharge and groundwater level at weekly/ biweekly interval. The third category comprises low-cost sensors including automatic surface and groundwater level sensors installed on open wells to monitor the continuous fluctuation of water level at every 15 minutes. In addition to involving the local communities in data collection (e.g. manual rainfall measurement, water and soil sampling), this CZO also aims to provide relevant information to them for improving their sustainability. The preliminary results show significant heterogeneity in soil type, cropping system, fertilizer application, water quality, irrigation source etc. within a small catchment.
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.
NASA Astrophysics Data System (ADS)
Zeng, Zhihui; Liu, Menglong; Xu, Hao; Liu, Weijian; Liao, Yaozhong; Jin, Hao; Zhou, Limin; Zhang, Zhong; Su, Zhongqing
2016-06-01
Inspired by an innovative sensing philosophy, a light-weight nanocomposite sensor made of a hybrid of carbon black (CB)/polyvinylidene fluoride (PVDF) has been developed. The nanoscalar architecture and percolation characteristics of the hybrid were optimized in order to fulfil the in situ acquisition of dynamic elastic disturbance from low-frequency vibration to high-frequency ultrasonic waves. Dynamic particulate motion induced by elastic disturbance modulates the infrastructure of the CB conductive network in the sensor, with the introduction of the tunneling effect, leading to dynamic alteration in the piezoresistivity measured by the sensor. Electrical analysis, morphological characterization, and static/dynamic electromechanical response interrogation were implemented to advance our insight into the sensing mechanism of the sensor, and meanwhile facilitate understanding of the optimal percolation threshold. At the optimal threshold (˜6.5 wt%), the sensor exhibits high fidelity, a fast response, and high sensitivity to ultrafast elastic disturbance (in an ultrasonic regime up to 400 kHz), yet with an ultralow magnitude (on the order of micrometers). The performance of the sensor was evaluated against a conventional strain gauge and piezoelectric transducer, showing excellent coincidence, yet a much greater gauge factor and frequency-independent piezoresistive behavior. Coatable on a structure and deployable in a large quantity to form a dense sensor network, this nanocomposite sensor has blazed a trail for implementing in situ sensing for vibration- or ultrasonic-wave-based structural health monitoring, by striking a compromise between ‘sensing cost’ and ‘sensing effectiveness’.
Mahali: Space Weather Monitoring Using Multicore Mobile Devices
NASA Astrophysics Data System (ADS)
Pankratius, V.; Lind, F. D.; Coster, A. J.; Erickson, P. J.; Semeter, J. L.
2013-12-01
Analysis of Total Electron Content (TEC) measurements derived from Global Positioning System (GPS) signals has led to revolutionary new data products for space weather monitoring and ionospheric research. However, the current sensor network is sparse, especially over the oceans and in regions like Africa and Siberia, and the full potential of dense, global, real-time TEC monitoring remains to be realized. The Mahali project will prototype a revolutionary architecture that uses mobile devices, such as phones and tablets, to form a global space weather monitoring network. Mahali exploits the existing GPS infrastructure - more specifically, delays in multi-frequency GPS signals observed at the ground - to acquire a vast set of global TEC projections, with the goal of imaging multi-scale variability in the global ionosphere at unprecedented spatial and temporal resolution. With connectivity available worldwide, mobile devices are excellent candidates to establish crowd sourced global relays that feed multi-frequency GPS sensor data into a cloud processing environment. Once the data is within the cloud, it is relatively straightforward to reconstruct the structure of the space environment, and its dynamic changes. This vision is made possible owing to advances in multicore technology that have transformed mobile devices into parallel computers with several processors on a chip. For example, local data can be pre-processed, validated with other sensors nearby, and aggregated when transmission is temporarily unavailable. Intelligent devices can also autonomously decide the most practical way of transmitting data with in any given context, e.g., over cell networks or Wifi, depending on availability, bandwidth, cost, energy usage, and other constraints. In the long run, Mahali facilitates data collection from remote locations such as deserts or on oceans. For example, mobile devices on ships could collect time-tagged measurements that are transmitted at a later point in time when some connectivity is available. Our concept of the overall Mahali system will employ both auto-tuning and machine learning techniques to cope with the opportunistic nature of data collection, computational load distribution on mobile devices and in the cloud, and fault-tolerance in a dynamically changing network. "Kila Mahali" means "everywhere" in the Swahili language. This project will follow that spirit by enabling space weather data collection even in the most remote places, resulting in dramatic improvements in observational gaps that exist in space weather research today. The dense network may enable the use of the entire ionosphere as a sensor to monitor geophysical events from earthquakes to tsunamis, and other natural disasters.
Multi-criteria anomaly detection in urban noise sensor networks.
Dauwe, Samuel; Oldoni, Damiano; De Baets, Bernard; Van Renterghem, Timothy; Botteldooren, Dick; Dhoedt, Bart
2014-01-01
The growing concern of citizens about the quality of their living environment and the emergence of low-cost microphones and data acquisition systems triggered the deployment of numerous noise monitoring networks spread over large geographical areas. Due to the local character of noise pollution in an urban environment, a dense measurement network is needed in order to accurately assess the spatial and temporal variations. The use of consumer grade microphones in this context appears to be very cost-efficient compared to the use of measurement microphones. However, the lower reliability of these sensing units requires a strong quality control of the measured data. To automatically validate sensor (microphone) data, prior to their use in further processing, a multi-criteria measurement quality assessment model for detecting anomalies such as microphone breakdowns, drifts and critical outliers was developed. Each of the criteria results in a quality score between 0 and 1. An ordered weighted average (OWA) operator combines these individual scores into a global quality score. The model is validated on datasets acquired from a real-world, extensive noise monitoring network consisting of more than 50 microphones. Over a period of more than a year, the proposed approach successfully detected several microphone faults and anomalies.
NASA Astrophysics Data System (ADS)
Muller, Catherine; Chapman, Lee; Young, Duick; Grimmond, Sue; Cai, Xiaoming
2013-04-01
The Birmingham Urban Climate Laboratory (BUCL) has recently been established by the University of Birmingham. BUCL is an in-situ, real-time urban network that will incorporate 3 nested networks - a wide-array of 25 weather stations, a dense array of 131 low-cost air temperature sensors and a fine-array of temperature sensor across the city-centre (50/km^2) - with the primary aim of monitoring air temperatures across a morphologically-heterogeneous urban conurbation for a variety of applications. During its installation there have been a number of challenges to overcome, including siting equipment in suitable urban locations, ensuring that the measurements were 'representative' of the local-scale climate, managing a large, near real-time data set and implementing QA/QC procedures. From these experiences, the establishment of a standardised urban meteorological network metadata protocol has been proposed in order to improve data quality, to ensure the end-user has access to all the supplementary information they would require for conducting valid analyses and to encourage the adequate recording and documentation of any changes to in-situ urban networks over time. This paper will provide an introduction to the BUCL in-situ network, give an overview of the challenges and experiences gained from its implementation, and finally discuss the proposed applications of the network, including its use in remote sensing observations of urban temperatures, as well as health and infrastructure applications.
Smart sensing surveillance system
NASA Astrophysics Data System (ADS)
Hsu, Charles; Chu, Kai-Dee; O'Looney, James; Blake, Michael; Rutar, Colleen
2010-04-01
Unattended ground sensor (UGS) networks have been widely used in remote battlefield and other tactical applications over the last few decades due to the advances of the digital signal processing. The UGS network can be applied in a variety of areas including border surveillance, special force operations, perimeter and building protection, target acquisition, situational awareness, and force protection. In this paper, a highly-distributed, fault-tolerant, and energyefficient Smart Sensing Surveillance System (S4) is presented to efficiently provide 24/7 and all weather security operation in a situation management environment. The S4 is composed of a number of distributed nodes to collect, process, and disseminate heterogeneous sensor data. Nearly all S4 nodes have passive sensors to provide rapid omnidirectional detection. In addition, Pan- Tilt- Zoom- (PTZ) Electro-Optics EO/IR cameras are integrated to selected nodes to track the objects and capture associated imagery. These S4 camera-connected nodes will provide applicable advanced on-board digital image processing capabilities to detect and track the specific objects. The imaging detection operations include unattended object detection, human feature and behavior detection, and configurable alert triggers, etc. In the S4, all the nodes are connected with a robust, reconfigurable, LPI/LPD (Low Probability of Intercept/ Low Probability of Detect) wireless mesh network using Ultra-wide band (UWB) RF technology, which can provide an ad-hoc, secure mesh network and capability to relay network information, communicate and pass situational awareness and messages. The S4 utilizes a Service Oriented Architecture such that remote applications can interact with the S4 network and use the specific presentation methods. The S4 capabilities and technologies have great potential for both military and civilian applications, enabling highly effective security support tools for improving surveillance activities in densely crowded environments and near perimeters and borders. The S4 is compliant with Open Geospatial Consortium - Sensor Web Enablement (OGC-SWE®) standards. It would be directly applicable to solutions for emergency response personnel, law enforcement, and other homeland security missions, as well as in applications requiring the interoperation of sensor networks with handheld or body-worn interface devices.
Wireless sensor network: an aimless gadget or a necessary tool for natural hazards warning systems
NASA Astrophysics Data System (ADS)
Hloupis, George; Stavrakas, Ilias; Triantis, Dimos
2010-05-01
The purpose of the current study is to review the current technical and scientific state of wireless sensor networks (WSNs) with application on natural hazards. WSN have received great attention from the research community in the last few years, mainly due to the theoretical and practical efforts from challenges that led to mature solutions and adoption of standards, such as Bluetooth [2] and ZigBee [3]. Wireless technology solutions allows Micro-ElectroMechanical Systems sensors (MEMS) to be integrated (with all the necessary circuitry) to small wireless capable devices, the nodes. Available MEMS today include pressure, temperature, humidity, inertial and strain-gauge sensors as well as transducers for velocity, acceleration, vibration, flow position and inclination [4]. A WSN is composed by a large number of nodes which are deployed densely adjacent to the area under monitoring. Each node collects data which transmitted to a gateway. The main requirements that WSNs must fulfilled are quite different than those of ad-hoc networks. WSNs have to be self-organized (since the positions of individual nodes are not known in advance), they must present cooperative processing of tasks (where groups of nodes cooperate in order to provide the gathered data to the user), they require security mechanisms that are adaptive to monitoring conditions and all algorithms must be energy optimized. In this paper, the state of the art in hardware, software, algorithms and protocols for WSNs, focused on natural hazards, is surveyed. Architectures for WSNs are investigated along with their advantages and drawbacks. Available research prototypes as well as commercially proposed solutions that can be used for natural hazards monitoring and early warning systems are listed and classified. [1] I.F. Akyildiz, W. Su, Y. Sankarasubramaniam, E. Cayirci, Wireless sensor networks: a survey, Comput. Networks (Elsevier) 38 (4) (2002) 393-422. [2] Dursch, A.; Yen, D.C.; Shih, D.H. Bluetooth technology: an exploratory study of the analysis and implementation frameworks. Comput. Stand. Interface. 2004, 26, 263-277. [3] Baronti, P.; Pillai, P.; Chook, V.W.C.; Chessa, S.; Gotta, A.; Hu, Y.F. Wireless sensor networks: A survey on the state of the art and the 802.15.4 and ZigBee standards. Comput. Commun. 2007, 30, 1655-1695. [4] Arampatzis, T.; Lygeros, J.; Manesis, S. A survey of applications of wireless sensors and Wireless Sensor Networks. In 2005 IEEE International Symposium on Intelligent Control & 13th Mediterranean Conference on Control and Automation. Limassol, Cyprus, 2005, 1-2, 719-724.
NASA Astrophysics Data System (ADS)
Chowdhry, Bhawani Shankar; White, Neil M.; Jeswani, Jai Kumar; Dayo, Khalil; Rathi, Manorma
2009-07-01
Disasters affecting infrastructure, such as the 2001 earthquakes in India, 2005 in Pakistan, 2008 in China and the 2004 tsunami in Asia, provide a common need for intelligent buildings and smart civil structures. Now, imagine massive reductions in time to get the infrastructure working again, realtime information on damage to buildings, massive reductions in cost and time to certify that structures are undamaged and can still be operated, reductions in the number of structures to be rebuilt (if they are known not to be damaged). Achieving these ideas would lead to huge, quantifiable, long-term savings to government and industry. Wireless sensor networks (WSNs) can be deployed in buildings to make any civil structure both smart and intelligent. WSNs have recently gained much attention in both public and research communities because they are expected to bring a new paradigm to the interaction between humans, environment, and machines. This paper presents the deployment of WSN nodes in the Top Quality Centralized Instrumentation Centre (TQCIC). We created an ad hoc networking application to collect real-time data sensed from the nodes that were randomly distributed throughout the building. If the sensors are relocated, then the application automatically reconfigures itself in the light of the new routing topology. WSNs are event-based systems that rely on the collective effort of several micro-sensor nodes, which are continuously observing a physical phenomenon. WSN applications require spatially dense sensor deployment in order to achieve satisfactory coverage. The degree of spatial correlation increases with the decreasing inter-node separation. Energy consumption is reduced dramatically by having only those sensor nodes with unique readings transmit their data. We report on an algorithm based on a spatial correlation technique that assures high QoS (in terms of SNR) of the network as well as proper utilization of energy, by suppressing redundant data transmission. The visualization and analysis of WSN data are presented in a Windows-based user interface.
Moraes, Celso; Myung, Sunghee; Lee, Sangkeum; Har, Dongsoo
2017-01-10
Provision of energy to wireless sensor networks is crucial for their sustainable operation. Sensor nodes are typically equipped with batteries as their operating energy sources. However, when the sensor nodes are sited in almost inaccessible locations, replacing their batteries incurs high maintenance cost. Under such conditions, wireless charging of sensor nodes by a mobile charger with an antenna can be an efficient solution. When charging distributed sensor nodes, a directional antenna, rather than an omnidirectional antenna, is more energy-efficient because of smaller proportion of off-target radiation. In addition, for densely distributed sensor nodes, it can be more effective for some undercharged sensor nodes to harvest energy from neighboring overcharged sensor nodes than from the remote mobile charger, because this reduces the pathloss of charging signal due to smaller distances. In this paper, we propose a hybrid charging scheme that combines charging by a mobile charger with a directional antenna, and energy trading, e.g., transferring and harvesting, between neighboring sensor nodes. The proposed scheme is compared with other charging scheme. Simulations demonstrate that the hybrid charging scheme with a directional antenna achieves a significant reduction in the total charging time required for all sensor nodes to reach a target energy level.
Moraes, Celso; Myung, Sunghee; Lee, Sangkeum; Har, Dongsoo
2017-01-01
Provision of energy to wireless sensor networks is crucial for their sustainable operation. Sensor nodes are typically equipped with batteries as their operating energy sources. However, when the sensor nodes are sited in almost inaccessible locations, replacing their batteries incurs high maintenance cost. Under such conditions, wireless charging of sensor nodes by a mobile charger with an antenna can be an efficient solution. When charging distributed sensor nodes, a directional antenna, rather than an omnidirectional antenna, is more energy-efficient because of smaller proportion of off-target radiation. In addition, for densely distributed sensor nodes, it can be more effective for some undercharged sensor nodes to harvest energy from neighboring overcharged sensor nodes than from the remote mobile charger, because this reduces the pathloss of charging signal due to smaller distances. In this paper, we propose a hybrid charging scheme that combines charging by a mobile charger with a directional antenna, and energy trading, e.g., transferring and harvesting, between neighboring sensor nodes. The proposed scheme is compared with other charging scheme. Simulations demonstrate that the hybrid charging scheme with a directional antenna achieves a significant reduction in the total charging time required for all sensor nodes to reach a target energy level. PMID:28075372
Distributed Coding/Decoding Complexity in Video Sensor Networks
Cordeiro, Paulo J.; Assunção, Pedro
2012-01-01
Video Sensor Networks (VSNs) are recent communication infrastructures used to capture and transmit dense visual information from an application context. In such large scale environments which include video coding, transmission and display/storage, there are several open problems to overcome in practical implementations. This paper addresses the most relevant challenges posed by VSNs, namely stringent bandwidth usage and processing time/power constraints. In particular, the paper proposes a novel VSN architecture where large sets of visual sensors with embedded processors are used for compression and transmission of coded streams to gateways, which in turn transrate the incoming streams and adapt them to the variable complexity requirements of both the sensor encoders and end-user decoder terminals. Such gateways provide real-time transcoding functionalities for bandwidth adaptation and coding/decoding complexity distribution by transferring the most complex video encoding/decoding tasks to the transcoding gateway at the expense of a limited increase in bit rate. Then, a method to reduce the decoding complexity, suitable for system-on-chip implementation, is proposed to operate at the transcoding gateway whenever decoders with constrained resources are targeted. The results show that the proposed method achieves good performance and its inclusion into the VSN infrastructure provides an additional level of complexity control functionality. PMID:22736972
Distributed coding/decoding complexity in video sensor networks.
Cordeiro, Paulo J; Assunção, Pedro
2012-01-01
Video Sensor Networks (VSNs) are recent communication infrastructures used to capture and transmit dense visual information from an application context. In such large scale environments which include video coding, transmission and display/storage, there are several open problems to overcome in practical implementations. This paper addresses the most relevant challenges posed by VSNs, namely stringent bandwidth usage and processing time/power constraints. In particular, the paper proposes a novel VSN architecture where large sets of visual sensors with embedded processors are used for compression and transmission of coded streams to gateways, which in turn transrate the incoming streams and adapt them to the variable complexity requirements of both the sensor encoders and end-user decoder terminals. Such gateways provide real-time transcoding functionalities for bandwidth adaptation and coding/decoding complexity distribution by transferring the most complex video encoding/decoding tasks to the transcoding gateway at the expense of a limited increase in bit rate. Then, a method to reduce the decoding complexity, suitable for system-on-chip implementation, is proposed to operate at the transcoding gateway whenever decoders with constrained resources are targeted. The results show that the proposed method achieves good performance and its inclusion into the VSN infrastructure provides an additional level of complexity control functionality.
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.
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.
Persistent regional carbon dioxide anomalies driven by land use
NASA Astrophysics Data System (ADS)
Schultz, Colin
2012-04-01
Researchers have traditionally used measurements from remote locations, such as Hawaii's Mauna Loa Observatory and other isolated stations, to determine atmospheric carbon dioxide (CO2) concentrations and estimate the strengths of various carbon sources and sinks. The prevailing wisdom was that attempts to measure regional differences in CO2 over land would end up with signals that were either so small that they were undetectable or that were dominated by high-frequency variability due to atmospheric turbulence or weather. Measurements drawn from a moderately dense network of atmospheric gas composition sensors distributed across the upper midwestern United States, however, showed that large regional variations in tropospheric CO2 are readily observable. Drawing on measurements made at nine sensors spread over 400,000 square kilometers between 2007 and 2009, Miles et al. found that seasonal variations in atmospheric CO2 depend strongly on the type of ecosystem lying at the foot of each sensor tower.
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.
NASA Astrophysics Data System (ADS)
Nick, C.; Yadav, S.; Joshi, R.; Schneider, J. J.; Thielemann, C.
2015-07-01
Electrodes based on carbon nanotubes are a promising approach to manufacture highly sensitive sensors with a low limit of signal detection and a high signal-to-noise ratio. This is achieved by dramatically increasing the electrochemical active surface area without increasing the overall geometrical dimensions. Typically, carbon nanotube electrodes are nearly planar and composed of randomly distributed carbon nanotube networks having a limited surface gain for a specific geometrical surface area. To overcome this limitation, we have introduced vertically aligned carbon nanotube (VACNT) networks as electrodes, which are arranged in a microelectrode pattern of 60 single electrodes. Each microelectrode features a very high aspect ratio of more than 300 and thus a dramatically increased surface area. These microelectrodes composed of VACNT networks display dramatically decreased impedance over the entire frequency range compared to planar microelectrodes caused by the enormous capacity increase. This is experimentally verified by electrochemical impedance spectroscopy and cyclic voltammetry.
Real-Time Station Grouping under Dynamic Traffic for IEEE 802.11ah
Tian, Le; Latré, Steven
2017-01-01
IEEE 802.11ah, marketed as Wi-Fi HaLow, extends Wi-Fi to the sub-1 GHz spectrum. Through a number of physical layer (PHY) and media access control (MAC) optimizations, it aims to bring greatly increased range, energy-efficiency, and scalability. This makes 802.11ah the perfect candidate for providing connectivity to Internet of Things (IoT) devices. One of these new features, referred to as the Restricted Access Window (RAW), focuses on improving scalability in highly dense deployments. RAW divides stations into groups and reduces contention and collisions by only allowing channel access to one group at a time. However, the standard does not dictate how to determine the optimal RAW grouping parameters. The optimal parameters depend on the current network conditions, and it has been shown that incorrect configuration severely impacts throughput, latency and energy efficiency. In this paper, we propose a traffic-adaptive RAW optimization algorithm (TAROA) to adapt the RAW parameters in real time based on the current traffic conditions, optimized for sensor networks in which each sensor transmits packets with a certain (predictable) frequency and may change the transmission frequency over time. The TAROA algorithm is executed at each target beacon transmission time (TBTT), and it first estimates the packet transmission interval of each station only based on packet transmission information obtained by access point (AP) during the last beacon interval. Then, TAROA determines the RAW parameters and assigns stations to RAW slots based on this estimated transmission frequency. The simulation results show that, compared to enhanced distributed channel access/distributed coordination function (EDCA/DCF), the TAROA algorithm can highly improve the performance of IEEE 802.11ah dense networks in terms of throughput, especially when hidden nodes exist, although it does not always achieve better latency performance. This paper contributes with a practical approach to optimizing RAW grouping under dynamic traffic in real time, which is a major leap towards applying RAW mechanism in real-life IoT networks. PMID:28677617
Real-Time Station Grouping under Dynamic Traffic for IEEE 802.11ah.
Tian, Le; Khorov, Evgeny; Latré, Steven; Famaey, Jeroen
2017-07-04
IEEE 802.11ah, marketed as Wi-Fi HaLow, extends Wi-Fi to the sub-1 GHz spectrum. Through a number of physical layer (PHY) and media access control (MAC) optimizations, it aims to bring greatly increased range, energy-efficiency, and scalability. This makes 802.11ah the perfect candidate for providing connectivity to Internet of Things (IoT) devices. One of these new features, referred to as the Restricted Access Window (RAW), focuses on improving scalability in highly dense deployments. RAW divides stations into groups and reduces contention and collisions by only allowing channel access to one group at a time. However, the standard does not dictate how to determine the optimal RAW grouping parameters. The optimal parameters depend on the current network conditions, and it has been shown that incorrect configuration severely impacts throughput, latency and energy efficiency. In this paper, we propose a traffic-adaptive RAW optimization algorithm (TAROA) to adapt the RAW parameters in real time based on the current traffic conditions, optimized for sensor networks in which each sensor transmits packets with a certain (predictable) frequency and may change the transmission frequency over time. The TAROA algorithm is executed at each target beacon transmission time (TBTT), and it first estimates the packet transmission interval of each station only based on packet transmission information obtained by access point (AP) during the last beacon interval. Then, TAROA determines the RAW parameters and assigns stations to RAW slots based on this estimated transmission frequency. The simulation results show that, compared to enhanced distributed channel access/distributed coordination function (EDCA/DCF), the TAROA algorithm can highly improve the performance of IEEE 802.11ah dense networks in terms of throughput, especially when hidden nodes exist, although it does not always achieve better latency performance. This paper contributes with a practical approach to optimizing RAW grouping under dynamic traffic in real time, which is a major leap towards applying RAW mechanism in real-life IoT networks.
Distributed Fiber Optic Sensors for Earthquake Detection and Early Warning
NASA Astrophysics Data System (ADS)
Karrenbach, M. H.; Cole, S.
2016-12-01
Fiber optic cables placed along pipelines, roads or other infrastructure provide dense sampling of passing seismic wavefields. Laser interrogation units illuminate the fiber over its entire length, and strain at desired points along the fiber can be determined from the reflected signal. Single-mode optical fibers up to 50 km in length can provide a distributed acoustic sensing system (DAS) where the acoustic bandwidth of each channel is limited only by the round-trip time over the length of the cable (0.0005 s for a 50 km cable). Using a 10 m spatial resolution results in 4000 channels sampled at 2.5 kHz spanning a 40 km-long fiber deployed along a pipeline. The inline strain field is averaged along the fiber over a 10 m section of the cable at each desired spatial sample, creating a virtual sensor location. Typically, a dynamic strain sensitivity of sub-nanometers within each gauge along the entire length of the fiber can be achieved. This sensitivity corresponds to a particle displacement figure of approximately -90 dB ms-2Hz-½. Such a fiber optic sensor is not as sensitive as long-period seismometers used in earthquake networks, but given the large number of channels, small to medium-sized earthquakes can be detected, depending on distance from the array, and can be located with precision through arrival time inversions. We show several examples of earthquake recordings using distributed fiber optic arrays that were deployed originally for other purposes. A 480 km long section of a pipeline in Turkey was actively monitored with a DAS fiber optic system for activities in the immediate vicinity of the pipeline. The densely spaced sensor array along the pipeline detected earthquakes of 3.6 - 7.2 magnitude range, centered near Van, Turkey. Secondly, a fiber optic system located along a rail line near the Salton Sea in California was used to create a smaller scale fiber optic sensor array, on which earthquakes with magnitudes 2.2 - 2.7 were recorded from epicenters up to 65 km away. Our analysis shows that existing fiber optic installations along infrastructure could be combined to form a large aperture array with tens of thousands of channels for epicenter estimation and for early warning purposes, augmenting existing earthquake sensor networks.
High Resolution Sensing and Control of Urban Water Networks
NASA Astrophysics Data System (ADS)
Bartos, M. D.; Wong, B. P.; Kerkez, B.
2016-12-01
We present a framework to enable high-resolution sensing, modeling, and control of urban watersheds using (i) a distributed sensor network based on low-cost cellular-enabled motes, (ii) hydraulic models powered by a cloud computing infrastructure, and (iii) automated actuation valves that allow infrastructure to be controlled in real time. This platform initiates two major advances. First, we achieve a high density of measurements in urban environments, with an anticipated 40+ sensors over each urban area of interest. In addition to new measurements, we also illustrate the design and evaluation of a "smart" control system for real-world hydraulic networks. This control system improves water quality and mitigates flooding by using real-time hydraulic models to adaptively control releases from retention basins. We evaluate the potential of this platform through two ongoing deployments: (i) a flood monitoring network in the Dallas-Fort Worth metropolitan area that detects and anticipates floods at the level of individual roadways, and (ii) a real-time hydraulic control system in the city of Ann Arbor, MI—soon to be one of the most densely instrumented urban watersheds in the United States. Through these applications, we demonstrate that distributed sensing and control of water infrastructure can improve flash flood predictions, emergency response, and stormwater contaminant mitigation.
NASA Astrophysics Data System (ADS)
Tanioka, Yuichiro
2017-04-01
After tsunami disaster due to the 2011 Tohoku-oki great earthquake, improvement of the tsunami forecast has been an urgent issue in Japan. National Institute of Disaster Prevention is installing a cable network system of earthquake and tsunami observation (S-NET) at the ocean bottom along the Japan and Kurile trench. This cable system includes 125 pressure sensors (tsunami meters) which are separated by 30 km. Along the Nankai trough, JAMSTEC already installed and operated the cable network system of seismometers and pressure sensors (DONET and DONET2). Those systems are the most dense observation network systems on top of source areas of great underthrust earthquakes in the world. Real-time tsunami forecast has depended on estimation of earthquake parameters, such as epicenter, depth, and magnitude of earthquakes. Recently, tsunami forecast method has been developed using the estimation of tsunami source from tsunami waveforms observed at the ocean bottom pressure sensors. However, when we have many pressure sensors separated by 30km on top of the source area, we do not need to estimate the tsunami source or earthquake source to compute tsunami. Instead, we can initiate a tsunami simulation from those dense tsunami observed data. Observed tsunami height differences with a time interval at the ocean bottom pressure sensors separated by 30 km were used to estimate tsunami height distribution at a particular time. In our new method, tsunami numerical simulation was initiated from those estimated tsunami height distribution. In this paper, the above method is improved and applied for the tsunami generated by the 2011 Tohoku-oki great earthquake. Tsunami source model of the 2011 Tohoku-oki great earthquake estimated using observed tsunami waveforms, coseimic deformation observed by GPS and ocean bottom sensors by Gusman et al. (2012) is used in this study. The ocean surface deformation is computed from the source model and used as an initial condition of tsunami simulation. By assuming that this computed tsunami is a real tsunami and observed at ocean bottom sensors, new tsunami simulation is carried out using the above method. The station distribution (each station is separated by 15 min., about 30 km) observed tsunami waveforms which were actually computed from the source model. Tsunami height distributions are estimated from the above method at 40, 80, and 120 seconds after the origin time of the earthquake. The Near-field Tsunami Inundation forecast method (Gusman et al. 2014) was used to estimate the tsunami inundation along the Sanriku coast. The result shows that the observed tsunami inundation was well explained by those estimated inundation. This also shows that it takes about 10 minutes to estimate the tsunami inundation from the origin time of the earthquake. This new method developed in this paper is very effective for a real-time tsunami forecast.
Kim, Min Young; Lee, Hyunkee; Cho, Hyungsuck
2008-04-10
One major research issue associated with 3D perception by robotic systems is the creation of efficient sensor systems that can generate dense range maps reliably. A visual sensor system for robotic applications is developed that is inherently equipped with two types of sensor, an active trinocular vision and a passive stereo vision. Unlike in conventional active vision systems that use a large number of images with variations of projected patterns for dense range map acquisition or from conventional passive vision systems that work well on specific environments with sufficient feature information, a cooperative bidirectional sensor fusion method for this visual sensor system enables us to acquire a reliable dense range map using active and passive information simultaneously. The fusion algorithms are composed of two parts, one in which the passive stereo vision helps active vision and the other in which the active trinocular vision helps the passive one. The first part matches the laser patterns in stereo laser images with the help of intensity images; the second part utilizes an information fusion technique using the dynamic programming method in which image regions between laser patterns are matched pixel-by-pixel with help of the fusion results obtained in the first part. To determine how the proposed sensor system and fusion algorithms can work in real applications, the sensor system is implemented on a robotic system, and the proposed algorithms are applied. A series of experimental tests is performed for a variety of configurations of robot and environments. The performance of the sensor system is discussed in detail.
Citizen seismology in Taiwan: what went wrong and what is the future?
NASA Astrophysics Data System (ADS)
Chen, K. H.; Liang, W. T.; Wu, Y. F.
2017-12-01
Citizen seismology encourages the public involvement to data collection, analysis, and reporting, and has the potential to greatly improve the emergency response to seismic hazard. This of course, is important for scientific achievement due to the dense network. We believed the value of citizen seismology and started with distributing Quake-Catcher-Network (QCN) sensor at schools in Taiwan. While working with teachers, we hoped to motivate the learning of how to read seismograms, what to see in the data, and what to teach in the class. Through lots of workshops and activities, even with near-real time earthquake game competition and board game (quake-nopoly) developed along the way, we came to realize the huge gap between what people need and what we do. And to bridge the gap, a new generation of citizen seismic network is needed. Imagine at work, you receive the alarm from sensors at home that tells you the location, size, and type of anomalous shaking events in the neighborhood. Can this future "warning" system happen, allowing citizen to do emergence response? This is a story about facing the challenge, transforming the doubt of "why do I care" to a future IoT world.
SPECTRE (www.noveltis.fr/spectre): a web Service for Ionospheric Products
NASA Astrophysics Data System (ADS)
Jeansou, E.; Crespon, F.; Garcia, R.; Helbert, J.; Moreaux, G.; Lognonne, P.
2005-12-01
The dense GPS networks developed for geodesic applications appear to be very efficient ionospheric sensors because of interaction between plasma and electromagnetic waves. Indeed, the dual frequency receivers provide data from which the Slant Total Electron Content (STEC) can be easily extracted to compute Vertical Total Electron Content (VTEC) maps. The SPECTRE project, Service and Products for ionospheric Electron Content and Tropospheric Refractivity over Europe, is currently a pre-operational service providing VTEC maps with high time and space resolution after 3 days time delay (http://www.noveltis.fr/spectre and http://ganymede.ipgp.jussieu.fr/spectre). This project is a part of SWENET, SpaceWeather European Network, initiated by the European Space Agency. The SPECTRE data products are useful for many applications. We will present these applications in term of interest for the scientific community with a special focus on spaceweather and transient ionospheric perturbations related to Earthquakes. Moreover, the pre-operational extensions of SPECTRE to the californian (SCIGN/BARD) and japanese (GEONET) dense GPS networks will be presented. Then the method of 3D tomography of the electron density from GPS data will be presented and its resolution discussed. The expected improvements of the 3D tomographic images by new tomographic reconstruction algorithms and by the advent of the Galileo system will conclude the presentation.
Meoni, Andrea; D'Alessandro, Antonella; Downey, Austin; García-Macías, Enrique; Rallini, Marco; Materazzi, A Luigi; Torre, Luigi; Laflamme, Simon; Castro-Triguero, Rafael; Ubertini, Filippo
2018-03-09
The availability of new self-sensing cement-based strain sensors allows the development of dense sensor networks for Structural Health Monitoring (SHM) of reinforced concrete structures. These sensors are fabricated by doping cement-matrix mterials with conductive fillers, such as Multi Walled Carbon Nanotubes (MWCNTs), and can be embedded into structural elements made of reinforced concrete prior to casting. The strain sensing principle is based on the multifunctional composites outputting a measurable change in their electrical properties when subjected to a deformation. Previous work by the authors was devoted to material fabrication, modeling and applications in SHM. In this paper, we investigate the behavior of several sensors fabricated with and without aggregates and with different MWCNT contents. The strain sensitivity of the sensors, in terms of fractional change in electrical resistivity for unit strain, as well as their linearity are investigated through experimental testing under both quasi-static and sine-sweep dynamic uni-axial compressive loadings. Moreover, the responses of the sensors when subjected to destructive compressive tests are evaluated. Overall, the presented results contribute to improving the scientific knowledge on the behavior of smart concrete sensors and to furthering their understanding for SHM applications.
Meoni, Andrea; D’Alessandro, Antonella; García-Macías, Enrique; Rallini, Marco; Materazzi, A. Luigi; Torre, Luigi; Laflamme, Simon; Castro-Triguero, Rafael
2018-01-01
The availability of new self-sensing cement-based strain sensors allows the development of dense sensor networks for Structural Health Monitoring (SHM) of reinforced concrete structures. These sensors are fabricated by doping cement-matrix mterials with conductive fillers, such as Multi Walled Carbon Nanotubes (MWCNTs), and can be embedded into structural elements made of reinforced concrete prior to casting. The strain sensing principle is based on the multifunctional composites outputting a measurable change in their electrical properties when subjected to a deformation. Previous work by the authors was devoted to material fabrication, modeling and applications in SHM. In this paper, we investigate the behavior of several sensors fabricated with and without aggregates and with different MWCNT contents. The strain sensitivity of the sensors, in terms of fractional change in electrical resistivity for unit strain, as well as their linearity are investigated through experimental testing under both quasi-static and sine-sweep dynamic uni-axial compressive loadings. Moreover, the responses of the sensors when subjected to destructive compressive tests are evaluated. Overall, the presented results contribute to improving the scientific knowledge on the behavior of smart concrete sensors and to furthering their understanding for SHM applications. PMID:29522498
Dense module enumeration in biological networks
NASA Astrophysics Data System (ADS)
Tsuda, Koji; Georgii, Elisabeth
2009-12-01
Analysis of large networks is a central topic in various research fields including biology, sociology, and web mining. Detection of dense modules (a.k.a. clusters) is an important step to analyze the networks. Though numerous methods have been proposed to this aim, they often lack mathematical rigorousness. Namely, there is no guarantee that all dense modules are detected. Here, we present a novel reverse-search-based method for enumerating all dense modules. Furthermore, constraints from additional data sources such as gene expression profiles or customer profiles can be integrated, so that we can systematically detect dense modules with interesting profiles. We report successful applications in human protein interaction network analyses.
NASA Astrophysics Data System (ADS)
Maurer, T.; Avanzi, F.; Oroza, C.; Malek, S. A.; Glaser, S. D.; Bales, R. C.; Conklin, M. H.
2017-12-01
We use data gathered from Wireless Sensor Networks (WSNs) between 2008 and 2017 to investigate the temporal/spatial patterns of rain-on-snow events in three river basins of California's Sierra Nevada. Rain-on-snow transitions occur across a broad elevation range (several hundred meters), both between storms and within a given storm, creating an opportunity to use spatially and temporally dense data to forecast and study them. WSNs collect snow depth; meteorological data; and soil moisture and temperature data across relatively dense sensor clusters. Ten to twelve measurement nodes per cluster are placed across 1-km2 areas in locations representative of snow patterns at larger scales. Combining precipitation and snow data from snow-pillow and climate stations with an estimation of dew-point temperature from WSNs, we determine the frequency, timing, and geographic extent of rain-on-snow events. We compare these results to WSN data to evaluate the impact of rain-on-snow events on snowpack energy balance, density, and depth as well as on soil moisture. Rain-on-snow events are compared to dry warm-weather days to identify the relative importance of rain and radiation as the primary energy input to the snowpack for snowmelt generation. An intercomparison of rain-on-snow events for the WSNs in the Feather, American, and Kings River basins captures the behavior across a 2° latitudinal range of the Sierra Nevada. Rain-on-snow events are potentially a more important streamflow generation mechanism in the lower-elevation Feather River basin. Snowmelt response to rain-on-snow events changes throughout the wet season, with later events resulting in more melt due to snow isothermal conditions, coarser grain size, and more-homogeneous snow stratigraphy. Regardless of snowmelt response, rain-on-snow events tend to result in decreasing snow depth and a corresponding increase in snow density. Our results demonstrate that strategically placed WSNs can provide the necessary data at high temporal resolution to investigate how hydrologic responses evolve in both space and time, data not available from operational networks.
NASA Astrophysics Data System (ADS)
Turkelli, N.; Teoman, U.; Altuncu Poyraz, S.; Cambaz, D.; Mutlu, A. K.; Kahraman, M.; Houseman, G. A.; Rost, S.; Thompson, D. A.; Cornwell, D. G.; Utkucu, M.; Gülen, L.
2013-12-01
The North Anatolian Fault (NAF) is one of the major strike slip fault systems on Earth comparable to San Andreas Fault in some ways. Devastating earthquakes have occurred along this system causing major damage and casualties. In order to comprehensively investigate the shallow and deep crustal structure beneath the western segment of NAF, a temporary dense seismic network for North Anatolia (DANA) consisting of 73 broadband sensors was deployed in early May 2012 surrounding a rectangular grid of by 70 km and a nominal station spacing of 7 km with the aim of further enhancing the detection capability of this dense seismic array. This joint project involves researchers from University of Leeds, UK, Bogazici University Kandilli Observatory and Earthquake Research Institute (KOERI), and University of Sakarya and primarily focuses on upper crustal studies such as earthquake locations (especially micro-seismic activity), receiver functions, moment tensor inversions, shear wave splitting, and ambient noise correlations. To begin with, we obtained the hypocenter locations of local earthquakes that occured within the DANA network. The dense 2-D grid geometry considerably enhanced the earthquake detection capability which allowed us to precisely locate events with local magnitudes (Ml) less than 1.0. Accurate earthquake locations will eventually lead to high resolution images of the upper crustal structure beneath the northern and southern branches of NAF in Sakarya region. In order to put additional constraints on the active tectonics of the western part of NAF, we also determined fault plane solutions using Regional Moment Tensor Inversion (RMT) and P wave first motion methods. For the analysis of high quality fault plane solutions, data from KOERI and the DANA project were merged. Furthermore, with the aim of providing insights on crustal anisotropy, shear wave splitting parameters such as lag time and fast polarization direction were obtained for local events recorded within the seismic network with magnitudes larger than 2.5.
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.
Nanotwinned metal MEMS films with unprecedented strength and stability
Sim, Gi-Dong; Krogstad, Jessica A.; Reddy, K. Madhav; Xie, Kelvin Y.; Valentino, Gianna M.; Weihs, Timothy P.; Hemker, Kevin J.
2017-01-01
Silicon-based microelectromechanical systems (MEMS) sensors have become ubiquitous in consumer-based products, but realization of an interconnected network of MEMS devices that allows components to be remotely monitored and controlled, a concept often described as the “Internet of Things,” will require a suite of MEMS materials and properties that are not currently available. We report on the synthesis of metallic nickel-molybdenum-tungsten films with direct current sputter deposition, which results in fully dense crystallographically textured films that are filled with nanotwins. These films exhibit linear elastic mechanical behavior and tensile strengths exceeding 3 GPa, which is unprecedented for materials that are compatible with wafer-level device fabrication processes. The ultrahigh strength is attributed to a combination of solid solution strengthening and the presence of dense nanotwins. These films also have excellent thermal and mechanical stability, high density, and electrical properties that are attractive for next-generation metal MEMS applications. PMID:28782015
Dense power-law networks and simplicial complexes
NASA Astrophysics Data System (ADS)
Courtney, Owen T.; Bianconi, Ginestra
2018-05-01
There is increasing evidence that dense networks occur in on-line social networks, recommendation networks and in the brain. In addition to being dense, these networks are often also scale-free, i.e., their degree distributions follow P (k ) ∝k-γ with γ ∈(1 ,2 ] . Models of growing networks have been successfully employed to produce scale-free networks using preferential attachment, however these models can only produce sparse networks as the numbers of links and nodes being added at each time step is constant. Here we present a modeling framework which produces networks that are both dense and scale-free. The mechanism by which the networks grow in this model is based on the Pitman-Yor process. Variations on the model are able to produce undirected scale-free networks with exponent γ =2 or directed networks with power-law out-degree distribution with tunable exponent γ ∈(1 ,2 ) . We also extend the model to that of directed two-dimensional simplicial complexes. Simplicial complexes are generalization of networks that can encode the many body interactions between the parts of a complex system and as such are becoming increasingly popular to characterize different data sets ranging from social interacting systems to the brain. Our model produces dense directed simplicial complexes with power-law distribution of the generalized out-degrees of the nodes.
Measuring Large-Scale Social Networks with High Resolution
Stopczynski, Arkadiusz; Sekara, Vedran; Sapiezynski, Piotr; Cuttone, Andrea; Madsen, Mette My; Larsen, Jakob Eg; Lehmann, Sune
2014-01-01
This paper describes the deployment of a large-scale study designed to measure human interactions across a variety of communication channels, with high temporal resolution and spanning multiple years—the Copenhagen Networks Study. Specifically, we collect data on face-to-face interactions, telecommunication, social networks, location, and background information (personality, demographics, health, politics) for a densely connected population of 1 000 individuals, using state-of-the-art smartphones as social sensors. Here we provide an overview of the related work and describe the motivation and research agenda driving the study. Additionally, the paper details the data-types measured, and the technical infrastructure in terms of both backend and phone software, as well as an outline of the deployment procedures. We document the participant privacy procedures and their underlying principles. The paper is concluded with early results from data analysis, illustrating the importance of multi-channel high-resolution approach to data collection. PMID:24770359
NASA Astrophysics Data System (ADS)
Ramanathan, N.; Estrin, D.; Harmon, T.; Harvey, C.; Jay, J.; Kohler, E.; Rothenberg, S.
2006-12-01
The presence of arsenic in the groundwater has led to the largest environmental poisoning in history; tens of millions of people in the Ganges Delta continue to drink groundwater that is dangerously contaminated with arsenic. A current working hypothesis is that arsenic is mobilized in the near surface environment where sediments are weathered by seasonal changes in the redox state that drive a cycle of pyrite oxidation and iron oxide reduction. In order to test the supporting hypothesis that subsurface geochemical changes may be induced by agricultural activity, we deployed 42 wirelessly networked ion-selective electrodes, including calcium, ammonium, nitrate, ORP, chloride, carbonate, and pH in a rice paddy in the Munshiganj district of Bangladesh in January of 2006. Each sensor was connected to an MDA300 sensor board and Mica2 wireless transceiver and computational device. Over a period of 11 days, we observed clear diel, and diurnal trends in 4 of the electrodes (calcium, ammonium, chloride and carbonate). The trends may be due to hydrological changes, or geochemical changes induced either by photosynthesis in the overlying water (which then infiltrated to the depth of the sensors) or in the root zone of rice plants. While the spatiotemporally dense measurements from wireless sensor networks enable scientists to ask new questions and elucidate complex relationships in heterogeneous physical environments such as soil, there are many practical issues to address in order to collect data usable for scientific purposes. For example, in response to a stream of faults in one of our sensor network deployments, we designed Sympathy to enable users to find and fix problems impacting the quantity of data collected in the field. Sympathy detects packet loss experienced at the base station and systematically assigns blame to faulty components in the network for remediation, replacing the prior policy of ad-hoc node rebooting and battery replacements. Sympathy has been deployed in many habitat monitoring sensor networks. While using Sympathy at our Bangladesh field site we received 80% of the sensor data expected at the base station, upon returning, post-deployment analysis revealed that 42% of these sensor data were potentially faulty. Due to the remote location of the deployment, we were unable to go back and validate the questionable segments of the data set, forcing us to discard potentially interesting information. In addition to being undesirable, this response is often avoidable as well. Even simple actions such as checking sensor connections and quickly validating sensors in the field could have increased our confidence in the quality of the data, minimizing doubts that data observations were simply caused by badly behaving hardware. To improve data quality, we have designed a system called Confidence, which continuously monitors data collected at a base-station to identify faulty data and notify the user in the field of actions they can take to validate the data or remediate the sensor fault. Augmenting a sensor network deployment with Confidence and Sympathy enables users in the identification and remediation of faults impacting the quality and quantity of data respectively.
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.
NASA Astrophysics Data System (ADS)
Van De Giesen, N.; Hut, R.; Andreini, M.; Selker, J. S.
2013-12-01
The Trans-African Hydro-Meteorological Observatory (TAHMO) has a goal to design, build, install and operate a dense network of hydro-meteorological monitoring stations in sub-Saharan Africa; one every 35 km. This corresponds to a total of 20,000 stations. By applying ICT and innovative sensors, each station should cost not more than $500. The stations would be placed at schools and integrated in the environmental curriculum. Data will be combined with models and satellite observations to obtain a very complete insight into the distribution of water and energy stocks and fluxes. Within this project, we have built a prototype of an acoustic disdrometer (rain gauge) that can be produced for much less than the cost of a commercial equivalent with the same specifications. The disdrometer was developed in The Netherlands and tested in Tanzania for a total project cost of Euro 5000. First tests have been run at junior high schools in Ghana to incorporate hydro-meteorological measurements in the science curriculum. The latest activity concerns the organization of a crowdsourcing competitions across Africa to address business development and the design and building of new robust sensors. This has resulted in a wide network throughout the continent to bring this program forward.
NASA Astrophysics Data System (ADS)
Su, Jun; Yang, Ning; Fan, Zhiqiang; Qiu, Qi
2017-10-01
We report on a fiber-optic delay-based quasidistributed temperature sensor with high precision. The device works by detecting the delay induced by the temperature instead of the spectrum. To analyze the working principle of this sensor, the thermal dependence of the fiber-optic delay was theoretically investigated and the delay-temperature coefficient was measured to be 42.2 ps/km°C. In this sensor, quasidistributed measurement of temperature could be easily realized by dense wavelength-division multiplexing and wavelength addressing. We built and tested a prototype quasidistributed temperature sensor with eight testing points equally distributed along a 32.61-km-long fiber. The experimental results demonstrate an average error of <0.1°C. These results prove that this quasidistributed temperature sensor is feasible and that it is a viable option for simple and economic temperature measurements.
Comparison of Calibration Techniques for Low-Cost Air Quality Monitoring
NASA Astrophysics Data System (ADS)
Malings, C.; Ramachandran, S.; Tanzer, R.; Kumar, S. P. N.; Hauryliuk, A.; Zimmerman, N.; Presto, A. A.
2017-12-01
Assessing the intra-city spatial distribution and temporal variability of air quality can be facilitated by a dense network of monitoring stations. However, the cost of implementing such a network can be prohibitive if high-quality but high-cost monitoring systems are used. To this end, the Real-time Affordable Multi-Pollutant (RAMP) sensor package has been developed at the Center for Atmospheric Particle Studies of Carnegie Mellon University, in collaboration with SenSevere LLC. This self-contained unit can measure up to five gases out of CO, SO2, NO, NO2, O3, VOCs, and CO2, along with temperature and relative humidity. Responses of individual gas sensors can vary greatly even when exposed to the same ambient conditions. Those of VOC sensors in particular were observed to vary by a factor-of-8, which suggests that each sensor requires its own calibration model. To this end, we apply and compare two different calibration methods to data collected by RAMP sensors collocated with a reference monitor station. The first method, random forest (RF) modeling, is a rule-based method which maps sensor responses to pollutant concentrations by implementing a trained sequence of decision rules. RF modeling has previously been used for other RAMP gas sensors by the group, and has produced precise calibrated measurements. However, RF models can only predict pollutant concentrations within the range observed in the training data collected during the collocation period. The second method, Gaussian process (GP) modeling, is a probabilistic Bayesian technique whereby broad prior estimates of pollutant concentrations are updated using sensor responses to generate more refined posterior predictions, as well as allowing predictions beyond the range of the training data. The accuracy and precision of these techniques are assessed and compared on VOC data collected during the summer of 2017 in Pittsburgh, PA. By combining pollutant data gathered by each RAMP sensor and applying appropriate calibration techniques, the potentially noisy or biased responses of individual sensors can be mapped to pollutant concentration values which are comparable to those of reference instruments.
A novel new tsunami detection network using GNSS on commercial ships
NASA Astrophysics Data System (ADS)
Foster, J. H.; Ericksen, T.; Avery, J.
2015-12-01
Accurate and rapid detection and assessment of tsunamis in the open ocean is critical for predicting how they will impact distant coastlines, enabling appropriate mitigation efforts. The unexpectedly huge fault slip for the 2011 Tohoku, Japan earthquake, and the unanticipated type of slip for the 2012 event at Queen Charlotte Islands, Canada highlighted weaknesses in our understanding of earthquake and tsunami hazards, and emphasized the need for more densely-spaced observing capabilities. Crucially, when each sensor is extremely expensive to build, deploy, and maintain, only a limited network of them can be installed. Gaps in the coverage of the network as well as routine outages of instruments, limit the ability of the detection system to accurately characterize events. Ship-based geodetic GNSS has been demonstrated to be able to detect and measure the properties of tsunamis in the open ocean. Based on this approach, we have used commercial ships operating in the North Pacific to construct a pilot network of low-cost, tsunami sensors to augment the existing detection systems. Partnering with NOAA, Maersk and Matson Navigation, we have equipped 10 ships with high-accuracy GNSS systems running the Trimble RTX high-accuracy real-time positioning service. Satellite communications transmit the position data streams to our shore-side server for processing and analysis. We present preliminary analyses of this novel network, assessing the robustness of the system, the quality of the time-series and the effectiveness of various processing and filtering strategies for retrieving accurate estimates of sea surface height variations for triggering detection and characterization of tsunami in the open ocean.
Efficient large-scale graph data optimization for intelligent video surveillance
NASA Astrophysics Data System (ADS)
Shang, Quanhong; Zhang, Shujun; Wang, Yanbo; Sun, Chen; Wang, Zepeng; Zhang, Luming
2017-08-01
Society is rapidly accepting the use of a wide variety of cameras Location and applications: site traffic monitoring, parking Lot surveillance, car and smart space. These ones here the camera provides data every day in an analysis Effective way. Recent advances in sensor technology Manufacturing, communications and computing are stimulating.The development of new applications that can change the traditional Vision system incorporating universal smart camera network. This Analysis of visual cues in multi camera networks makes wide Applications ranging from smart home and office automation to large area surveillance and traffic surveillance. In addition, dense Camera networks, most of which have large overlapping areas of cameras. In the view of good research, we focus on sparse camera networks. One Sparse camera network using large area surveillance. As few cameras as possible, most cameras do not overlap Each other’s field of vision. This task is challenging Lack of knowledge of topology Network, the specific changes in appearance and movement Track different opinions of the target, as well as difficulties Understanding complex events in a network. In this review in this paper, we present a comprehensive survey of recent studies Results to solve the problem of topology learning, Object appearance modeling and global activity understanding sparse camera network. In addition, some of the current open Research issues are discussed.
A novel hydrogel electrolyte extender for rapid application of EEG sensors and extended recordings.
Kleffner-Canucci, Killian; Luu, Phan; Naleway, John; Tucker, Don M
2012-04-30
Dense-array EEG recordings are now commonplace in research and gaining acceptance in clinical settings. Application of many sensors with traditional electrolytes is time consuming. Saline electrolytes can be used to minimize application time but recording duration is limited due to evaporation. In the present study, we evaluate a NIPAm (N-isopropyl acrylamide:acrylic acid) base electrolyte extender for use with saline electrolytes. Sensor-scalp impedances and EEG data quality acquired with the electrolyte extender are compared with those obtained for saline and an EEG electrolyte commonly used in clinical exams (Elefix). The results show that when used in conjunction with saline, electrode-scalp impedances and data across the EEG spectrum are comparable with those obtained using Elefix EEG paste. When used in conjunction with saline, the electrolyte extender permits rapid application of dense-sensor arrays and stable, high-quality EEG data to be obtained for at least 4.5 h. This is an enabling technology that will make benefits of dense-array EEG recordings practical for clinical applications. Copyright © 2011 Elsevier B.V. All rights reserved.
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.
Ship Noise in the SW Indian Ocean Recorded by Ocean Bottom Seismic and Hydroacoustic Sensors
NASA Astrophysics Data System (ADS)
Barruol, G.; Dreo, R.; Fontaine, F. R.; Scholz, J. R.; Sigloch, K.
2016-12-01
In the frame of the RHUM-RUM project (Réunion Hotspot and Upper Mantle - Réunions Unterer Mantel, www.rhum-rum.net), a network of 57 ocean-bottom seismometers (OBS) has been installed on the ocean floor around La Réunion Island, but also on the neighbouring Southwest and Central Indian Ridges. The OBS were equipped by wide- and broad-band three-components seismic and hydroacoustic sensors. They were deployed in Nov. 2012, and depending on the configuration, they recorded for 8 to 13 months. Interestingly, part of the network was located beneath a NE-SW trending lane of very dense ship traffic connecting SE-Asia and the South-Atlantic region. By combining the vessel position - provided by AIS GPS data - and our geophysical data recorded on the ocean floor, we analyze the seismic and hydroacoustic ship signatures. From spectral analyzes, we show clear signals over the whole high-frequency range available from our instruments (between 1 and 50 Hz). The RHUM-RUM network covering latitude between 17 and 34° South, this allows to detect numerous vessels and to compare the noise characteristics (frequency content, polarization) of each vessel. We also investigate the possibility of using the polarization of the noise emitted by ships passing above an ocean-bottom seismometer, to help retrieving the orientation of the OBS horizontal components on the ocean floor in the geographic reference frame.
Sensing fluid pressure during plucking events in a natural bedrock channel and experimental flume
NASA Astrophysics Data System (ADS)
Wilkinson, C.; Harbor, D. J.; Keel, D.; Levy, S.; Kuehner, J. P.
2016-12-01
River channel erosion by plucking is believed to be the dominant erosional process in channels with fractured or jointed bedrock. However, despite its significance as an erosional mechanism, plucking is poorly studied in both laboratory and natural channels. In previous flume studies, model bedrock was plucked by fluid forces alone in nonuniform flow near jumps and waves even where blocks do not protrude into the flow. Here we develop sensor systems to test the hypothesis that bed fluid pressure gradients lift "pluckable" bedrock blocks in a natural field setting and a hydraulic flume. The field setting closely mimics the previous flume setup; the instrumented block is downstream of a roughly 1m step and exhibits no protrusion into the flow. The presence of the step promotes nonuniform flow which changes pressure in the bedrock crack network; slabs of bedrock that have slid downstream and sediment that has been pushed upstream 3-4 m under the bed and in the cracks suggest the influence of pressure differences throughout the crack network and below the bed. In this initial deployment, we evaluate a sensor that monitors movement and simultaneous pressure above and below the block. Sensors are emplaced in a 26kg, 45-cm-long, 20-cm-wide block broken from a 4.5-m-long, 11-cm-thick sandstone bed with a dense network of cracks nearly parallel to flow direction and include a tri-axial accelerometer/gyroscope and two fluid pressure sensors. The electronics are housed in a custom-designed 3D-printed ABS waterproof capsule that is mounted in a vertical hole through the rock. A concurrent flume study develops the sensors necessary to investigate the longitudinal pressure difference below a step using multiple analog sensors (0-1 psi gauge pressure) mounted flush to a false floor under the center of a 30x14-cm test zone. The 15-mm-wide sensors are aligned along the flow centerline and are placed under 25 1-cm-thick "pluckable" bedrock blocks constructed with a proprietary plaster cement. Measured mean pressure and transmission of pressure pulses under the test bed are compared to the visual record of plucking. In addition, conducting runs with blocks removed permits simulation of the mean and varying pressure conditions above the modeled "pluckable" layer as a hydraulic jump is moved downstream through the step.
Real-time method for establishing a detection map for a network of sensors
Nguyen, Hung D; Koch, Mark W; Giron, Casey; Rondeau, Daniel M; Russell, John L
2012-09-11
A method for establishing a detection map of a dynamically configurable sensor network. This method determines an appropriate set of locations for a plurality of sensor units of a sensor network and establishes a detection map for the network of sensors while the network is being set up; the detection map includes the effects of the local terrain and individual sensor performance. Sensor performance is characterized during the placement of the sensor units, which enables dynamic adjustment or reconfiguration of the placement of individual elements of the sensor network during network set-up to accommodate variations in local terrain and individual sensor performance. The reconfiguration of the network during initial set-up to accommodate deviations from idealized individual sensor detection zones improves the effectiveness of the sensor network in detecting activities at a detection perimeter and can provide the desired sensor coverage of an area while minimizing unintentional gaps in coverage.
Sensor Network Architectures for Monitoring Underwater Pipelines
Mohamed, Nader; Jawhar, Imad; Al-Jaroodi, Jameela; Zhang, Liren
2011-01-01
This paper develops and compares different sensor network architecture designs that can be used for monitoring underwater pipeline infrastructures. These architectures are underwater wired sensor networks, underwater acoustic wireless sensor networks, RF (Radio Frequency) wireless sensor networks, integrated wired/acoustic wireless sensor networks, and integrated wired/RF wireless sensor networks. The paper also discusses the reliability challenges and enhancement approaches for these network architectures. The reliability evaluation, characteristics, advantages, and disadvantages among these architectures are discussed and compared. Three reliability factors are used for the discussion and comparison: the network connectivity, the continuity of power supply for the network, and the physical network security. In addition, the paper also develops and evaluates a hierarchical sensor network framework for underwater pipeline monitoring. PMID:22346669
Sensor network architectures for monitoring underwater pipelines.
Mohamed, Nader; Jawhar, Imad; Al-Jaroodi, Jameela; Zhang, Liren
2011-01-01
This paper develops and compares different sensor network architecture designs that can be used for monitoring underwater pipeline infrastructures. These architectures are underwater wired sensor networks, underwater acoustic wireless sensor networks, RF (radio frequency) wireless sensor networks, integrated wired/acoustic wireless sensor networks, and integrated wired/RF wireless sensor networks. The paper also discusses the reliability challenges and enhancement approaches for these network architectures. The reliability evaluation, characteristics, advantages, and disadvantages among these architectures are discussed and compared. Three reliability factors are used for the discussion and comparison: the network connectivity, the continuity of power supply for the network, and the physical network security. In addition, the paper also develops and evaluates a hierarchical sensor network framework for underwater pipeline monitoring.
Localization Strategies in WSNs as applied to Landslide Monitoring (Invited)
NASA Astrophysics Data System (ADS)
Massa, A.; Robol, F.; Polo, A.; Giarola, E.; Viani, F.
2013-12-01
In the last years, heterogeneous integrated smart systems based on wireless sensor network (WSN) technology have been developed at the ELEDIA Research Center of the University of Trento [1]. One of the key features of WSNs as applied to distributed monitoring is that, while the capabilities of each single sensor node is limited, the implementation of cooperative schemes throughout the whole network enables the solution of even complex tasks, as the landslide monitoring. The capability of localizing targets respect to the position of the sensor nodes turns out to be fundamental in those application fields where relative movements arise. The main properties like the target typology, the movement characteristics, and the required localization resolution are different changing the reference scenario. However, the common key issue is still the localization of moving targets within the area covered by the sensor network. Many experiences were preparatory for the challenging activities in the field of landslide monitoring where the basic idea is mostly that of detecting slight soil movements. Among them, some examples of WSN-based systems experimentally applied to the localization of people [2] and wildlife [3] have been proposed. More recently, the WSN backbone as well as the investigated sensing technologies have been customized for monitoring superficial movements of the soil. The relative positions of wireless sensor nodes deployed where high probability of landslide exists is carefully monitored to forecast dangerous events. Multiple sensors like ultrasound, laser, high precision GPS, for the precise measurement of relative distances between the nodes of the network and the absolute positions respect to reference targets have been integrated in a prototype system. The millimeter accuracy in the position estimation enables the detection of small soil modifications and to infer the superficial evolution profile of the landslide. This information locally acquired also represent a fine tuning of large scale satellite acquisitions, usually adopted for remote sensing of landslides. The integration of dense and frequent WSN data within satellite image analysis will enhance the sensing capabilities leading to a multi-resolution and an highly space-time calibrated system. The WSN-based system has been preliminary tested in controlled environments in the ELEDIA laboratories and is now installed in a real test site where an active landslide is evolving. Preliminary data are here presented to assess the feasibility of the investigated solution in landslide monitoring and event forecasting. REFERENCES [1] M. Benedetti, L. Ioriatti, M. Martinelli, and F. Viani, 'Wireless sensor network: a pervasive technology for earth observation,' in IEEE Journal of Selected Topics in App. Earth Obs. And Remote Sens., vol. 3, no. 4, pp. 488-497, 2010. [2] F. Viani, M. Donelli, P. Rocca, G. Oliveri, D. Trinchero, and A. Massa, 'Localization, tracking and imaging of targets in wireless sensor networks,' Radio Science, vol. 46, no. 5, 2011. [3] F. Viani, F. Robol, M. Salucci, E. Giarola, S. De Vigili, M. Rocca, F. Boldrini, G. Benedetti, and A. Massa, 'WSN-based early alert system for preventing wildlife-vehicle collisions in Alps regions - From the laboratory test to the real-world implementation,' 7th European Conference on Antennas and Propagation 2013 (EUCAP2013), Gothenburg, Sweden, April 8-12, 2013.
NASA Astrophysics Data System (ADS)
Neighbors, C.; Liao, E. J.; Cochran, E. S.; Chung, A. I.; Lawrence, J.; Kaiser, A. E.; Fry, B.; Christensen, C. M.
2011-12-01
The 3 September 2010 Mw 7.1 Darfield earthquake was felt over 900 km from the source. The maximum felt-intensity was estimated to be at Modified Mercalli Intensity (MMI) 9 and measured near-field accelerations were found to exceed 1 g. The mainshock damaged or destroyed over 100,000 buildings and spatially variable effects (such as liquefaction, slumping, and amplification) were observed throughout the city of Christchurch. Following the mainshock, a vigorous aftershock sequence has continued for months in the region. To record the aftershocks for early warning and other hazard mitigation efforts, a network of over 192 low-cost, 14-bit accelerometers were deployed in local buildings as part of the Quake-Catcher Network Rapid Aftershock Mobilization Project (RAMP). With a large number of sensors covering a city area of ~300 km2, the RAMP collected vastly more data and at a finer scale relative to the deployment of costly traditional broadband sensors. Recent comparison of the signal-to-noise quality of the 14-bit QCN sensors to the strong motion 24-bit New Zealand GeoNet sensors show similar responses. Initial analyses of the data show that aftershocks of magnitude >M4.5 within 30 km of the hypocentral distance were well recorded by QCN sensors. Utilizing the dense coverage, we investigate local site amplification by analyzing the spectra decay parameter, kappa (κ). Following the routine outlined in Douglas et al. (2010, Pure Appl. Geophys.), whereby a 5-sec S-wave window is used to calculate the Fourier spectra and κ for each station, investigations of κ values between stations are used to estimate site conditions on seismic wave behavior at each location. Results from this study will be compared to work performed by New Zealand researchers using other methods to calculate site response, such as the spectral ratio method. Together, these studies will highlight areas of the Christchurch region that may be more susceptible to ground shaking, which can be used to mitigate loss prior to future large earthquakes.
Performance Evaluation of a Prototyped Wireless Ground Sensor Network
2005-03-01
the network was capable of dynamic adaptation to failure and degradation. 14. SUBJECT TERMS: Wireless Sensor Network , Unmanned Sensor, Unattended...2 H. WIRELESS SENSOR NETWORKS .................................................................... 3...zation, and network traffic. The evaluated scenarios included outdoor, urban and indoor environments. The characteristics of wireless sensor networks , types
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
Matrix Factorisation-based Calibration For Air Quality Crowd-sensing
NASA Astrophysics Data System (ADS)
Dorffer, Clement; Puigt, Matthieu; Delmaire, Gilles; Roussel, Gilles; Rouvoy, Romain; Sagnier, Isabelle
2017-04-01
Internet of Things (IoT) is extending internet to physical objects and places. The internet-enabled objects are thus able to communicate with each other and with their users. One main interest of IoT is the ease of production of huge masses of data (Big Data) using distributed networks of connected objects, thus making possible a fine-grained yet accurate analysis of physical phenomena. Mobile crowdsensing is a way to collect data using IoT. It basically consists of acquiring geolocalized data from the sensors (from or connected to the mobile devices, e.g., smartphones) of a crowd of volunteers. The sensed data are then collectively shared using wireless connection—such as GSM or WiFi—and stored on a dedicated server to be processed. One major application of mobile crowdsensing is environment monitoring. Indeed, with the proliferation of miniaturized yet sensitive sensors on one hand and, on the other hand, of low-cost microcontrollers/single-card PCs, it is easy to extend the sensing abilities of smartphones. Alongside the conventional, regulated, bulky and expensive instruments used in authoritative air quality stations, it is then possible to create a large-scale mobile sensor network providing insightful information about air quality. In particular, the finer spatial sampling rate due to such a dense network should allow air quality models to take into account local effects such as street canyons. However, one key issue with low-cost air quality sensors is the lack of trust in the sensed data. In most crowdsensing scenarios, the sensors (i) cannot be calibrated in a laboratory before or during their deployment and (ii) might be sparsely or continuously faulty (thus providing outliers in the data). Such issues should be automatically handled from the sensor readings. Indeed, due to the masses of generated data, solving the above issues cannot be performed by experts but requires specific data processing techniques. In this work, we assume that some mobile sensors share some information using the APISENSE® crowdsensing platform and we aim to calibrate the sensor responses from the data directly. For that purpose, we express the sensor readings as a low-rank matrix with missing entries and we revisit self-calibration as a Matrix Factorization (MF) problem. In our proposed framework, one factor matrix contains the calibration parameters while the other is structured by the calibration model and contains some values of the sensed phenomenon. The MF calibration approach also uses the precise measurements from ATMO—the French public institution—to drive the calibration of the mobile sensors. MF calibration can be improved using, e.g., the mean calibration parameters provided by the sensor manufacturers, or using sparse priors or a model of the physical phenomenon. All our approaches are shown to provide a better calibration accuracy than matrix-completion-based and robust-regression-based methods, even in difficult scenarios involving a lot of missing data and/or very few accurate references. When combined with a dictionary of air quality patterns, our experiments suggest that MF is not only able to perform sensor network calibration but also to provide detailed maps of air quality.
An efficient management system for wireless sensor networks.
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.
Spatio-thermal depth correction of RGB-D sensors based on Gaussian processes in real-time
NASA Astrophysics Data System (ADS)
Heindl, Christoph; Pönitz, Thomas; Stübl, Gernot; Pichler, Andreas; Scharinger, Josef
2018-04-01
Commodity RGB-D sensors capture color images along with dense pixel-wise depth information in real-time. Typical RGB-D sensors are provided with a factory calibration and exhibit erratic depth readings due to coarse calibration values, ageing and thermal influence effects. This limits their applicability in computer vision and robotics. We propose a novel method to accurately calibrate depth considering spatial and thermal influences jointly. Our work is based on Gaussian Process Regression in a four dimensional Cartesian and thermal domain. We propose to leverage modern GPUs for dense depth map correction in real-time. For reproducibility we make our dataset and source code publicly available.
Hybrid architecture for building secure sensor networks
NASA Astrophysics Data System (ADS)
Owens, Ken R., Jr.; Watkins, Steve E.
2012-04-01
Sensor networks have various communication and security architectural concerns. Three approaches are defined to address these concerns for sensor networks. The first area is the utilization of new computing architectures that leverage embedded virtualization software on the sensor. Deploying a small, embedded virtualization operating system on the sensor nodes that is designed to communicate to low-cost cloud computing infrastructure in the network is the foundation to delivering low-cost, secure sensor networks. The second area focuses on securing the sensor. Sensor security components include developing an identification scheme, and leveraging authentication algorithms and protocols that address security assurance within the physical, communication network, and application layers. This function will primarily be accomplished through encrypting the communication channel and integrating sensor network firewall and intrusion detection/prevention components to the sensor network architecture. Hence, sensor networks will be able to maintain high levels of security. The third area addresses the real-time and high priority nature of the data that sensor networks collect. This function requires that a quality-of-service (QoS) definition and algorithm be developed for delivering the right data at the right time. A hybrid architecture is proposed that combines software and hardware features to handle network traffic with diverse QoS requirements.
A method for detecting and locating geophysical events using groups of arrays
NASA Astrophysics Data System (ADS)
de Groot-Hedlin, Catherine D.; Hedlin, Michael A. H.
2015-11-01
We have developed a novel method to detect and locate geophysical events that makes use of any sufficiently dense sensor network. This method is demonstrated using acoustic sensor data collected in 2013 at the USArray Transportable Array (TA). The algorithm applies Delaunay triangulation to divide the sensor network into a mesh of three-element arrays, called triads. Because infrasound waveforms are incoherent between the sensors within each triad, the data are transformed into envelopes, which are cross-correlated to find signals that satisfy a consistency criterion. The propagation azimuth, phase velocity and signal arrival time are computed for each signal. Triads with signals that are consistent with a single source are bundled as an event group. The ensemble of arrival times and azimuths of detected signals within each group are used to locate a common source in space and time. A total of 513 infrasonic stations that were active for part or all of 2013 were divided into over 2000 triads. Low (0.5-2 Hz) and high (2-8 Hz) catalogues of infrasonic events were created for the eastern USA. The low-frequency catalogue includes over 900 events and reveals several highly active source areas on land that correspond with coal mining regions. The high-frequency catalogue includes over 2000 events, with most occurring offshore. Although their cause is not certain, most events are clearly anthropogenic as almost all occur during regular working hours each week. The regions to which the TA is most sensitive vary seasonally, with the direction of reception dependent on the direction of zonal winds. The catalogue has also revealed large acoustic events that may provide useful insight into the nature of long-range infrasound propagation in the atmosphere.
Scaling an in situ network for high resolution modeling during SMAPVEX15
NASA Astrophysics Data System (ADS)
Coopersmith, E. J.; Cosh, M. H.; Jacobs, J. M.; Jackson, T. J.; Crow, W. T.; Holifield Collins, C.; Goodrich, D. C.; Colliander, A.
2015-12-01
Among the greatest challenges within the field of soil moisture estimation is that of scaling sparse point measurements within a network to produce higher resolution map products. Large-scale field experiments present an ideal opportunity to develop methodologies for this scaling, by coupling in situ networks, temporary networks, and aerial mapping of soil moisture. During the Soil Moisture Active Passive Validation Experiments in 2015 (SMAPVEX15) in and around the USDA-ARS Walnut Gulch Experimental Watershed and LTAR site in southeastern Arizona, USA, a high density network of soil moisture stations was deployed across a sparse, permanent in situ network in coordination with intensive soil moisture sampling and an aircraft campaign. This watershed is also densely instrumented with precipitation gages (one gauge/0.57 km2) to monitor the North American Monsoon System, which dominates the hydrologic cycle during the summer months in this region. Using the precipitation and soil moisture time series values provided, a physically-based model is calibrated that will provide estimates at the 3km, 9km, and 36km scales. The results from this model will be compared with the point-scale gravimetric samples, aircraft-based sensor, and the satellite-based products retrieved from NASA's Soil Moisture Active Passive mission.
2014-03-31
Network Connectivity Assessment via Local Data Exchange for Underwater Acoustic Sensor Networks M.M. Asadi H. Mahboubi A...2014 Global Network Connectivity Assessment via Local Data Exchange for Underwater Acoustic Sensor Networks Contract Report # AMBUSH.1.1 Contract...pi j /= 0. The sensor network considered in this work is composed of underwater sensors , which use acoustic waves for
Decentralized modal identification using sparse blind source separation
NASA Astrophysics Data System (ADS)
Sadhu, A.; Hazra, B.; Narasimhan, S.; Pandey, M. D.
2011-12-01
Popular ambient vibration-based system identification methods process information collected from a dense array of sensors centrally to yield the modal properties. In such methods, the need for a centralized processing unit capable of satisfying large memory and processing demands is unavoidable. With the advent of wireless smart sensor networks, it is now possible to process information locally at the sensor level, instead. The information at the individual sensor level can then be concatenated to obtain the global structure characteristics. A novel decentralized algorithm based on wavelet transforms to infer global structure mode information using measurements obtained using a small group of sensors at a time is proposed in this paper. The focus of the paper is on algorithmic development, while the actual hardware and software implementation is not pursued here. The problem of identification is cast within the framework of under-determined blind source separation invoking transformations of measurements to the time-frequency domain resulting in a sparse representation. The partial mode shape coefficients so identified are then combined to yield complete modal information. The transformations are undertaken using stationary wavelet packet transform (SWPT), yielding a sparse representation in the wavelet domain. Principal component analysis (PCA) is then performed on the resulting wavelet coefficients, yielding the partial mixing matrix coefficients from a few measurement channels at a time. This process is repeated using measurements obtained from multiple sensor groups, and the results so obtained from each group are concatenated to obtain the global modal characteristics of the structure.
Detection of Steel Fatigue Cracks with Strain Sensing Sheets Based on Large Area Electronics
Yao, Yao; Glisic, Branko
2015-01-01
Reliable early-stage damage detection requires continuous monitoring over large areas of structure, and with sensors of high spatial resolution. Technologies based on Large Area Electronics (LAE) can enable direct sensing and can be scaled to the level required for Structural Health Monitoring (SHM) of civil structures and infrastructure. Sensing sheets based on LAE contain dense arrangements of thin-film strain sensors, associated electronics and various control circuits deposited and integrated on a flexible polyimide substrate that can cover large areas of structures. This paper presents the development stage of a prototype strain sensing sheet based on LAE for crack detection and localization. Two types of sensing-sheet arrangements with size 6 × 6 inch (152 × 152 mm) were designed and manufactured, one with a very dense arrangement of sensors and the other with a less dense arrangement of sensors. The sensing sheets were bonded to steel plates, which had a notch on the boundary, so the fatigue cracks could be generated under cyclic loading. The sensors within the sensing sheet that were close to the notch tip successfully detected the initialization of fatigue crack and localized the damage on the plate. The sensors that were away from the crack successfully detected the propagation of fatigue cracks based on the time history of the measured strain. The results of the tests have validated the general principles of the proposed sensing sheets for crack detection and identified advantages and challenges of the two tested designs. PMID:25853407
Cooperative UAV-Based Communications Backbone for Sensor Networks
DOE Office of Scientific and Technical Information (OSTI.GOV)
Roberts, R S
2001-10-07
The objective of this project is to investigate the use of unmanned air vehicles (UAVs) as mobile, adaptive communications backbones for ground-based sensor networks. In this type of network, the UAVs provide communication connectivity to sensors that cannot communicate with each other because of terrain, distance, or other geographical constraints. In these situations, UAVs provide a vertical communication path for the sensors, thereby mitigating geographic obstacles often imposed on networks. With the proper use of UAVs, connectivity to a widely disbursed sensor network in rugged terrain is readily achieved. Our investigation has focused on networks where multiple cooperating UAVs aremore » used to form a network backbone. The advantage of using multiple UAVs to form the network backbone is parallelization of sensor connectivity. Many widely spaced or isolated sensors can be connected to the network at once using this approach. In these networks, the UAVs logically partition the sensor network into sub-networks (subnets), with one UAV assigned per subnet. Partitioning the network into subnets allows the UAVs to service sensors in parallel thereby decreasing the sensor-to-network connectivity. A UAV services sensors in its subnet by flying a route (path) through the subnet, uplinking data collected by the sensors, and forwarding the data to a ground station. An additional advantage of using multiple UAVs in the network is that they provide redundancy in the communications backbone, so that the failure of a single UAV does not necessarily imply the loss of the network.« less
NASA Astrophysics Data System (ADS)
Provost, Floriane; Malet, Jean-Philippe; Hibert, Clément; Vergne, Jérôme
2017-04-01
Clayey landslides present various seismic sources generated by the slope deformation (rockfall, slidequakes, tremors, fluid transfers). However, the characterization of the micro-seismicity and the construction of advanced catalogs (classification of the seismic source, time, and location) are complex for such objects because of the variety of recorded signals, the low signal to noise ratios, the highly attenuating medium, and the small size of the object that limits the picking of the P and S-waves. A full understanding of the seismic sources is hence often difficult because of the few number of seismometers, the large distance source-to-sensor (> 50m) and because of the lack of a continous spatially distributed record of the slope deformation. Recent progress in the geophysical instrumentation allowed the deployment of a dense network of 150 ZLand nodes (Tesla Corp.) combined with a Ground-Based InSAR sensor (IDS, IBIS-FM) for a period of ca. 2 months at the Super-Sauze clayey landslide (South French Alps). The Zland nodes are vertical wireless seismometers with 12 days autonomy. Three nodes were co-located at 50 locations in the most active part of the landslide and above the main scarp with a sensor-to-sensor distance of ca. 50m and a sample frequency of 400Hz. The Ground-Based InSAR sensor was installed in front of the landslide at a distance of ca. 800m and acquired an image every 15 minutes. The seismic events are detected automatically based on their spectrogram content with Signal-to-Noise Ratio (SNR) larger than 1.5 and automatically classified using the Random Forest algorithm. The landslide endogenous sources are then located by optimization of the inter-trace correlation of the first arrivals. This experiment aims to document the deformation of the landslide by combining surface and in depth information and provides a new insight into the seismic sources interpretation. The spatial distribution of the deformation is compared to the location of the endogenous seismic events in order to analyze seismic vs. aseismic deformation.
Low cost sensors for PM and related air pollutants in the US and India
Emerging air quality sensors have a variety of possible applications. If accurate and reliable, they have a number of benefits over conventional monitors. They are low-cost, lightweight, and have low power consumption. Because of their low cost, a dense array of sensors instal...
Comparison of Fiber Optic Strain Demodulation Implementations
NASA Technical Reports Server (NTRS)
Quach, Cuong C.; Vazquez, Sixto L.
2005-01-01
NASA Langley Research Center is developing instrumentation based upon principles of Optical Frequency-Domain Reflectometry (OFDR) for the provision of large-scale, dense distribution of strain sensors using fiber optics embedded with Bragg gratings. Fiber Optic Bragg Grating technology enables the distribution of thousands of sensors immune to moisture and electromagnetic interference with negligible weight penalty. At Langley, this technology provides a key component for research and development relevant to comprehensive aerospace vehicle structural health monitoring. A prototype system is under development that includes hardware and software necessary for the acquisition of data from an optical network and conversion of the data into strain measurements. This report documents the steps taken to verify the software that implements the algorithm for calculating the fiber strain. Brief descriptions of the strain measurement system and the test article are given. The scope of this report is the verification of software implementations as compared to a reference model. The algorithm will be detailed along with comparison results.
Cognitive radio wireless sensor networks: applications, challenges and research trends.
Joshi, Gyanendra Prasad; Nam, Seung Yeob; Kim, Sung Won
2013-08-22
A cognitive radio wireless sensor network is one of the candidate areas where cognitive techniques can be used for opportunistic spectrum access. Research in this area is still in its infancy, but it is progressing rapidly. The aim of this study is to classify the existing literature of this fast emerging application area of cognitive radio wireless sensor networks, highlight the key research that has already been undertaken, and indicate open problems. This paper describes the advantages of cognitive radio wireless sensor networks, the difference between ad hoc cognitive radio networks, wireless sensor networks, and cognitive radio wireless sensor networks, potential application areas of cognitive radio wireless sensor networks, challenges and research trend in cognitive radio wireless sensor networks. The sensing schemes suited for cognitive radio wireless sensor networks scenarios are discussed with an emphasis on cooperation and spectrum access methods that ensure the availability of the required QoS. Finally, this paper lists several open research challenges aimed at drawing the attention of the readers toward the important issues that need to be addressed before the vision of completely autonomous cognitive radio wireless sensor networks can be realized.
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.
Utilization of a Terrestrial Laser Scanner for the Calibration of Mobile Mapping Systems
Hong, Seunghwan; Park, Ilsuk; Lee, Jisang; Lim, Kwangyong; Choi, Yoonjo; Sohn, Hong-Gyoo
2017-01-01
This paper proposes a practical calibration solution for estimating the boresight and lever-arm parameters of the sensors mounted on a Mobile Mapping System (MMS). On our MMS devised for conducting the calibration experiment, three network video cameras, one mobile laser scanner, and one Global Navigation Satellite System (GNSS)/Inertial Navigation System (INS) were mounted. The geometric relationships between three sensors were solved by the proposed calibration, considering the GNSS/INS as one unit sensor. Our solution basically uses the point cloud generated by a 3-dimensional (3D) terrestrial laser scanner rather than using conventionally obtained 3D ground control features. With the terrestrial laser scanner, accurate and precise reference data could be produced and the plane features corresponding with the sparse mobile laser scanning data could be determined with high precision. Furthermore, corresponding point features could be extracted from the dense terrestrial laser scanning data and the images captured by the video cameras. The parameters of the boresight and the lever-arm were calculated based on the least squares approach and the precision of the boresight and lever-arm could be achieved by 0.1 degrees and 10 mm, respectively. PMID:28264457
Time Synchronization in Wireless Sensor Networks
2003-01-01
University of California Los Angeles Time Synchronization in Wireless Sensor Networks A dissertation submitted in partial satisfaction of the...4. TITLE AND SUBTITLE Time Synchronization in Wireless Sensor Networks 5a. CONTRACT NUMBER 5b. GRANT NUMBER 5c. PROGRAM ELEMENT NUMBER 6...1 1.1 Wireless Sensor Networks . . . . . . . . . . . . . . . . . . . . . . 1 1.2 Time Synchronization in Sensor Networks
NASA Astrophysics Data System (ADS)
Takaesu, M.; Horikawa, H.; Sueki, K.; Kamiya, S.; Nakamura, T.; Nakano, M.; Takahashi, N.; Sonoda, A.; Tsuboi, S.
2014-12-01
Mega-thrust earthquakes are anticipated to occur in the Nankai Trough in southwest Japan. In the source areas, we installed seafloor seismic network, DONET (Dense Ocean-floor Network System for Earthquake and Tsunamis), in 2010 in order to monitor seismicity, crustal deformations, and tsunamis. DONET system consists of totally 20 stations, which is composed of six kinds of sensors; strong-motion and broadband seismometers, quartz and differential pressure gauges, hydrophone, and thermometer. The stations are densely distributed with an average spatial interval of 15-20 km and cover near coastal areas to the trench axis. Observed data are transferred to a land station through a fiber-optical cable and then to JAMSTEC (Japan Agency for Marine-Earth Science and Technology) data management center through a private network in real time. The data are based on WIN32 format in the private network and finally archived in SEED format in the management center to combine waveform data with related metadata. We are developing a web-based application system to easily download seismic waveform data of DONET. In this system, users can select 20 Hz broadband (BH type) and 200 Hz strong-motion (EH type) data and download them in SEED. Users can also search events from the options of time periods, magnitude, source area and depth in a GUI platform. Event data are produced referring to event catalogues from USGS and JMA (Japan Meteorological Agency). The thresholds of magnitudes for the production are M6 for far-field and M4 for local events using the USGS and JMA lists, respectively. Available data lengths depend on magnitudes and epicentral distances. In this presentation, we briefly introduce DONET stations and then show our developed application system. We open DONET data through the system and want them to be widely recognized so that many users analyze. We also discuss next plans for further developments of the system.
Sigma Routing Metric for RPL Protocol.
Sanmartin, Paul; Rojas, Aldo; Fernandez, Luis; Avila, Karen; Jabba, Daladier; Valle, Sebastian
2018-04-21
This paper presents the adaptation of a specific metric for the RPL protocol in the objective function MRHOF. Among the functions standardized by IETF, we find OF0, which is based on the minimum hop count, as well as MRHOF, which is based on the Expected Transmission Count (ETX). However, when the network becomes denser or the number of nodes increases, both OF0 and MRHOF introduce long hops, which can generate a bottleneck that restricts the network. The adaptation is proposed to optimize both OFs through a new routing metric. To solve the above problem, the metrics of the minimum number of hops and the ETX are combined by designing a new routing metric called SIGMA-ETX, in which the best route is calculated using the standard deviation of ETX values between each node, as opposed to working with the ETX average along the route. This method ensures a better routing performance in dense sensor networks. The simulations are done through the Cooja simulator, based on the Contiki operating system. The simulations showed that the proposed optimization outperforms at a high margin in both OF0 and MRHOF, in terms of network latency, packet delivery ratio, lifetime, and power consumption.
Sigma Routing Metric for RPL Protocol
Rojas, Aldo; Fernandez, Luis
2018-01-01
This paper presents the adaptation of a specific metric for the RPL protocol in the objective function MRHOF. Among the functions standardized by IETF, we find OF0, which is based on the minimum hop count, as well as MRHOF, which is based on the Expected Transmission Count (ETX). However, when the network becomes denser or the number of nodes increases, both OF0 and MRHOF introduce long hops, which can generate a bottleneck that restricts the network. The adaptation is proposed to optimize both OFs through a new routing metric. To solve the above problem, the metrics of the minimum number of hops and the ETX are combined by designing a new routing metric called SIGMA-ETX, in which the best route is calculated using the standard deviation of ETX values between each node, as opposed to working with the ETX average along the route. This method ensures a better routing performance in dense sensor networks. The simulations are done through the Cooja simulator, based on the Contiki operating system. The simulations showed that the proposed optimization outperforms at a high margin in both OF0 and MRHOF, in terms of network latency, packet delivery ratio, lifetime, and power consumption. PMID:29690524
Deployment operation of NanTroSEIZE C0002 riserless LTBMS
NASA Astrophysics Data System (ADS)
Kyo, N.; Saruhashi, T.; Sawada, I.; Namba, Y.; Kitada, K.; Kimura, T.; Toczko, S.; Araki, E.; Kopf, A.; IODP EXP 332 Scientists
2011-12-01
The installation of LTBMS (Long Term Borehole Monitoring System) for NanTroSEIZE (Nankai Trough Seismogenic Zone Experiment) C0002 riserless hole was successfully carried out as part of IODP Expedition 332 operations by DV Chikyu in November - December 2010. The water depth of the site and penetration depth of the hole are 1937.5 m and 980 mbsf respectively. Casing (9-5/8") was set to the depth of 888 mbsf and below the CORK head, 3-1/2" tubing was deployed inside the casing as the support structure for the downhole instruments. Within the rat hole section, two pressure ports, a strain meter, a tilt meter, a broadband seismometer, geophone, and accelerometer were deployed. These seismic and geodetic sensors were set within the borehole, and coupled to the formation via cement whose physical properties (Young's modulus, Poisson's ratio, density) were adjusted to fit the formation's properties. Screen sections were set to access the pore fluids, while isolating them from the sea floor and the lower lithological units by a swellable packer, and cement, respectively. At the top of wellhead, and at the apex of the 3-1/2" tubing assembly, a CORK head was landed. The CORK head holds the pressure sensor unit (4 pressure sensors), underwater mateable data connectors (connected to the cemented sensors), and hydraulic valves to access and sample formation fluids by ROV. The major scientific features of the Hole C0002G (riserless) LTBMS are sensors monitoring multiple parameters related to seismic, geodetic and pore fluid behavior simultaneously at distinct, multiple, layers within the same borehole. The main technical difficulties in the LTBMS development are as follows: (1) Reduction method for current-induced VIV (Vortex Induced Vibration) (2) Borehole coupling for seismic and geodetic sensors (3) Anti-vibration/shock and protection method for borehole sensors/instruments (4) Attachment and protection for sensor cables and pressure lines (5) Zone isolation for multi-layer pressure measurements (6) Wellhead system (CORK) for data connection to submarine cable network (7) Downsizing borehole instruments (installation with 3-1/2-in tubing) (8) System reliability (redundant sensor system) We carried out sea trials using a dummy sensor assembly to study the effects of deploying the assembly in strong currents, and also carried out additional pool experiments and numerical simulations to evaluate VIV countermeasures. Through shock and vibration mechanical tests, we improved the robustness of sensors and the sensor carrier. As part of these investigations, we conducted risk analysis based on the operation, science, and engineering points of view from, which helped clarify operational procedures for actual deployment. Future plans include returning to Hole C0002G site to deploy a data logger and battery for temporary observations. After examining the data quality, we'll finally connect the LTBMS to the DONET (Dense Oceanfloor Network System for Earthquakes and Tsunamis) submarine cabled network. Plans are also underway for deploying more LTBMS's into Site C0010 (riserless) and Site C0002 (riser).
Real-Time Performance of a Self-Powered Environmental IoT Sensor Network System.
Wu, Fan; Rüdiger, Christoph; Yuce, Mehmet Rasit
2017-02-01
Wireless sensor networks (WSNs) play an increasingly important role in monitoring applications in many areas. With the emergence of the Internet-of-Things (IoT), many more lowpower sensors will need to be deployed in various environments to collect and monitor data about environmental factors in real time. Providing power supply to these sensor nodes becomes a critical challenge for realizations of IoT applications as sensor nodes are normally battery-powered and have a limited lifetime. This paper proposes a wireless sensor network that is powered by solar energy harvesting. The sensor network monitors the environmental data with low-power sensor electronics and forms a network using multiple XBee wireless modules. A detailed performance analysis of the network system under solar energy harvesting has been presented. The sensor network system and the proposed energy-harvesting techniques are configured to achieve a continuous energy source for the sensor network. The proposed energy-harvesting system has been successfully designed to enable an energy solution in order to keep sensor nodes active and reliable for a whole day. The paper also outlines some of our experiences in real-time implementation of a sensor network system with energy harvesting.
Real-Time Performance of a Self-Powered Environmental IoT Sensor Network System
Wu, Fan; Rüdiger, Christoph; Yuce, Mehmet Rasit
2017-01-01
Wireless sensor networks (WSNs) play an increasingly important role in monitoring applications in many areas. With the emergence of the Internet-of-Things (IoT), many more low-power sensors will need to be deployed in various environments to collect and monitor data about environmental factors in real time. Providing power supply to these sensor nodes becomes a critical challenge for realizations of IoT applications as sensor nodes are normally battery-powered and have a limited lifetime. This paper proposes a wireless sensor network that is powered by solar energy harvesting. The sensor network monitors the environmental data with low-power sensor electronics and forms a network using multiple XBee wireless modules. A detailed performance analysis of the network system under solar energy harvesting has been presented. The sensor network system and the proposed energy-harvesting techniques are configured to achieve a continuous energy source for the sensor network. The proposed energy-harvesting system has been successfully designed to enable an energy solution in order to keep sensor nodes active and reliable for a whole day. The paper also outlines some of our experiences in real-time implementation of a sensor network system with energy harvesting. PMID:28157148
Cognitive Radio Wireless Sensor Networks: Applications, Challenges and Research Trends
Joshi, Gyanendra Prasad; Nam, Seung Yeob; Kim, Sung Won
2013-01-01
A cognitive radio wireless sensor network is one of the candidate areas where cognitive techniques can be used for opportunistic spectrum access. Research in this area is still in its infancy, but it is progressing rapidly. The aim of this study is to classify the existing literature of this fast emerging application area of cognitive radio wireless sensor networks, highlight the key research that has already been undertaken, and indicate open problems. This paper describes the advantages of cognitive radio wireless sensor networks, the difference between ad hoc cognitive radio networks, wireless sensor networks, and cognitive radio wireless sensor networks, potential application areas of cognitive radio wireless sensor networks, challenges and research trend in cognitive radio wireless sensor networks. The sensing schemes suited for cognitive radio wireless sensor networks scenarios are discussed with an emphasis on cooperation and spectrum access methods that ensure the availability of the required QoS. Finally, this paper lists several open research challenges aimed at drawing the attention of the readers toward the important issues that need to be addressed before the vision of completely autonomous cognitive radio wireless sensor networks can be realized. PMID:23974152
An iterative network partition algorithm for accurate identification of dense network modules
Sun, Siqi; Dong, Xinran; Fu, Yao; Tian, Weidong
2012-01-01
A key step in network analysis is to partition a complex network into dense modules. Currently, modularity is one of the most popular benefit functions used to partition network modules. However, recent studies suggested that it has an inherent limitation in detecting dense network modules. In this study, we observed that despite the limitation, modularity has the advantage of preserving the primary network structure of the undetected modules. Thus, we have developed a simple iterative Network Partition (iNP) algorithm to partition a network. The iNP algorithm provides a general framework in which any modularity-based algorithm can be implemented in the network partition step. Here, we tested iNP with three modularity-based algorithms: multi-step greedy (MSG), spectral clustering and Qcut. Compared with the original three methods, iNP achieved a significant improvement in the quality of network partition in a benchmark study with simulated networks, identified more modules with significantly better enrichment of functionally related genes in both yeast protein complex network and breast cancer gene co-expression network, and discovered more cancer-specific modules in the cancer gene co-expression network. As such, iNP should have a broad application as a general method to assist in the analysis of biological networks. PMID:22121225
NASA Astrophysics Data System (ADS)
Nordal Petersen, Martin; Nuijts, Roeland; Lange Bjørn, Lars
2014-05-01
This article presents an advanced optical model for simulation of alien wavelengths in multi-domain and multi-vendor dense wavelength-division multiplexing networks. The model aids optical network planners with a better understanding of the non-linear effects present in dense wavelength-division multiplexing systems and better utilization of alien wavelengths in future applications. The limiting physical effects for alien wavelengths are investigated in relation to power levels, channel spacing, and other factors. The simulation results are verified through experimental setup in live multi-domain dense wavelength-division multiplexing systems between two national research networks: SURFnet in Holland and NORDUnet in Denmark.
Dependable Wireless Sensor Networks for Prognostics and Health Management: A Survey
2014-10-02
sensor network has many advantages. First of all, the absence of wires gives sensor networks the ability to cover a large scale surveillance area...system/component health state. Usually, this information is gathered through independent sensors or a wired network of sensors. The use of a wireless
Multipath Routing in Wireless Sensor Networks: Survey and Research Challenges
Radi, Marjan; Dezfouli, Behnam; Bakar, Kamalrulnizam Abu; Lee, Malrey
2012-01-01
A wireless sensor network is a large collection of sensor nodes with limited power supply and constrained computational capability. Due to the restricted communication range and high density of sensor nodes, packet forwarding in sensor networks is usually performed through multi-hop data transmission. Therefore, routing in wireless sensor networks has been considered an important field of research over the past decade. Nowadays, multipath routing approach is widely used in wireless sensor networks to improve network performance through efficient utilization of available network resources. Accordingly, the main aim of this survey is to present the concept of the multipath routing approach and its fundamental challenges, as well as the basic motivations for utilizing this technique in wireless sensor networks. In addition, we present a comprehensive taxonomy on the existing multipath routing protocols, which are especially designed for wireless sensor networks. We highlight the primary motivation behind the development of each protocol category and explain the operation of different protocols in detail, with emphasis on their advantages and disadvantages. Furthermore, this paper compares and summarizes the state-of-the-art multipath routing techniques from the network application point of view. Finally, we identify open issues for further research in the development of multipath routing protocols for wireless sensor networks. PMID:22368490
Multipath routing in wireless sensor networks: survey and research challenges.
Radi, Marjan; Dezfouli, Behnam; Abu Bakar, Kamalrulnizam; Lee, Malrey
2012-01-01
A wireless sensor network is a large collection of sensor nodes with limited power supply and constrained computational capability. Due to the restricted communication range and high density of sensor nodes, packet forwarding in sensor networks is usually performed through multi-hop data transmission. Therefore, routing in wireless sensor networks has been considered an important field of research over the past decade. Nowadays, multipath routing approach is widely used in wireless sensor networks to improve network performance through efficient utilization of available network resources. Accordingly, the main aim of this survey is to present the concept of the multipath routing approach and its fundamental challenges, as well as the basic motivations for utilizing this technique in wireless sensor networks. In addition, we present a comprehensive taxonomy on the existing multipath routing protocols, which are especially designed for wireless sensor networks. We highlight the primary motivation behind the development of each protocol category and explain the operation of different protocols in detail, with emphasis on their advantages and disadvantages. Furthermore, this paper compares and summarizes the state-of-the-art multipath routing techniques from the network application point of view. Finally, we identify open issues for further research in the development of multipath routing protocols for wireless sensor networks.
Wireless Sensor Networks for Detection of IED Emplacement
2009-06-01
unclassified Standard Form 298 (Rev. 8-98) Prescribed by ANSI Std Z39-18 Abstract We are investigating the use of wireless nonimaging -sensor...networks for the difficult problem of detection of suspicious behavior related to IED emplacement. Hardware for surveillance by nonimaging -sensor networks...with people crossing a live sensor network. We conclude that nonimaging -sensor networks can detect a variety of suspicious behavior, but
Naranjo, Ramon C.
2017-01-01
Groundwater-flow models are often calibrated using a limited number of observations relative to the unknown inputs required for the model. This is especially true for models that simulate groundwater surface-water interactions. In this case, subsurface temperature sensors can be an efficient means for collecting long-term data that capture the transient nature of physical processes such as seepage losses. Continuous and spatially dense network of diverse observation data can be used to improve knowledge of important physical drivers, conceptualize and calibrate variably saturated groundwater flow models. An example is presented for which the results of such analysis were used to help guide irrigation districts and water management decisions on costly upgrades to conveyance systems to improve water usage, farm productivity and restoration efforts to improve downstream water quality and ecosystems.
A Two-Phase Coverage-Enhancing Algorithm for Hybrid Wireless Sensor Networks.
Zhang, Qingguo; Fok, Mable P
2017-01-09
Providing field coverage is a key task in many sensor network applications. In certain scenarios, the sensor field may have coverage holes due to random initial deployment of sensors; thus, the desired level of coverage cannot be achieved. A hybrid wireless sensor network is a cost-effective solution to this problem, which is achieved by repositioning a portion of the mobile sensors in the network to meet the network coverage requirement. This paper investigates how to redeploy mobile sensor nodes to improve network coverage in hybrid wireless sensor networks. We propose a two-phase coverage-enhancing algorithm for hybrid wireless sensor networks. In phase one, we use a differential evolution algorithm to compute the candidate's target positions in the mobile sensor nodes that could potentially improve coverage. In the second phase, we use an optimization scheme on the candidate's target positions calculated from phase one to reduce the accumulated potential moving distance of mobile sensors, such that the exact mobile sensor nodes that need to be moved as well as their final target positions can be determined. Experimental results show that the proposed algorithm provided significant improvement in terms of area coverage rate, average moving distance, area coverage-distance rate and the number of moved mobile sensors, when compare with other approaches.
A Two-Phase Coverage-Enhancing Algorithm for Hybrid Wireless Sensor Networks
Zhang, Qingguo; Fok, Mable P.
2017-01-01
Providing field coverage is a key task in many sensor network applications. In certain scenarios, the sensor field may have coverage holes due to random initial deployment of sensors; thus, the desired level of coverage cannot be achieved. A hybrid wireless sensor network is a cost-effective solution to this problem, which is achieved by repositioning a portion of the mobile sensors in the network to meet the network coverage requirement. This paper investigates how to redeploy mobile sensor nodes to improve network coverage in hybrid wireless sensor networks. We propose a two-phase coverage-enhancing algorithm for hybrid wireless sensor networks. In phase one, we use a differential evolution algorithm to compute the candidate’s target positions in the mobile sensor nodes that could potentially improve coverage. In the second phase, we use an optimization scheme on the candidate’s target positions calculated from phase one to reduce the accumulated potential moving distance of mobile sensors, such that the exact mobile sensor nodes that need to be moved as well as their final target positions can be determined. Experimental results show that the proposed algorithm provided significant improvement in terms of area coverage rate, average moving distance, area coverage–distance rate and the number of moved mobile sensors, when compare with other approaches. PMID:28075365
NASA Astrophysics Data System (ADS)
Gonzalez, Elias; Kish, Laszlo B.
2016-03-01
As the utilization of sensor networks continue to increase, the importance of security becomes more profound. Many industries depend on sensor networks for critical tasks, and a malicious entity can potentially cause catastrophic damage. We propose a new key exchange trust evaluation for peer-to-peer sensor networks, where part of the network has unconditionally secure key exchange. For a given sensor, the higher the portion of channels with unconditionally secure key exchange the higher the trust value. We give a brief introduction to unconditionally secured key exchange concepts and mention current trust measures in sensor networks. We demonstrate the new key exchange trust measure on a hypothetical sensor network using both wired and wireless communication channels.
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.
Availability Issues in Wireless Visual Sensor Networks
Costa, Daniel G.; Silva, Ivanovitch; Guedes, Luiz Affonso; Vasques, Francisco; Portugal, Paulo
2014-01-01
Wireless visual sensor networks have been considered for a large set of monitoring applications related with surveillance, tracking and multipurpose visual monitoring. When sensors are deployed over a monitored field, permanent faults may happen during the network lifetime, reducing the monitoring quality or rendering parts or the entire network unavailable. In a different way from scalar sensor networks, camera-enabled sensors collect information following a directional sensing model, which changes the notions of vicinity and redundancy. Moreover, visual source nodes may have different relevancies for the applications, according to the monitoring requirements and cameras' poses. In this paper we discuss the most relevant availability issues related to wireless visual sensor networks, addressing availability evaluation and enhancement. Such discussions are valuable when designing, deploying and managing wireless visual sensor networks, bringing significant contributions to these networks. PMID:24526301
A comparative study of wireless sensor networks and their routing protocols.
Bhattacharyya, Debnath; Kim, Tai-hoon; Pal, Subhajit
2010-01-01
Recent developments in the area of micro-sensor devices have accelerated advances in the sensor networks field leading to many new protocols specifically designed for wireless sensor networks (WSNs). Wireless sensor networks with hundreds to thousands of sensor nodes can gather information from an unattended location and transmit the gathered data to a particular user, depending on the application. These sensor nodes have some constraints due to their limited energy, storage capacity and computing power. Data are routed from one node to other using different routing protocols. There are a number of routing protocols for wireless sensor networks. In this review article, we discuss the architecture of wireless sensor networks. Further, we categorize the routing protocols according to some key factors and summarize their mode of operation. Finally, we provide a comparative study on these various protocols.
Underwater Sensor Nodes and Networks
Lloret, Jaime
2013-01-01
Sensor technology has matured enough to be used in any type of environment. The appearance of new physical sensors has increased the range of environmental parameters for gathering data. Because of the huge amount of unexploited resources in the ocean environment, there is a need of new research in the field of sensors and sensor networks. This special issue is focused on collecting recent advances on underwater sensors and underwater sensor networks in order to measure, monitor, surveillance of and control of underwater environments. On the one hand, from the sensor node perspective, we will see works related with the deployment of physical sensors, development of sensor nodes and transceivers for sensor nodes, sensor measurement analysis and several issues such as layer 1 and 2 protocols for underwater communication and sensor localization and positioning systems. On the other hand, from the sensor network perspective, we will see several architectures and protocols for underwater environments and analysis concerning sensor network measurements. Both sides will provide us a complete view of last scientific advances in this research field. PMID:24013489
Development and Implementation of Low-Cost Mobile Sensor Platforms Within a Wireless Sensor Network
2010-09-01
WIRELESS SENSOR NETWORK by Michael Jay Tozzi September 2010 Thesis Advisor: Rachel Goshorn Second Reader: Duane Davis Approved for...Platforms Within a Wireless Sensor Network 6. AUTHOR(S) Tozzi, Michael Jay 5. FUNDING NUMBERS 7. PERFORMING ORGANIZATION NAME(S) AND ADDRESS(ES) Naval...IMPLEMENTATION OF LOW-COST MOBILE SENSOR PLATFORMS WITHIN A WIRELESS SENSOR NETWORK Michael Jay Tozzi Lieutenant, United States Navy B.S., United
Engineering of Sensor Network Structure for Dependable Fusion
2014-08-15
Lossy Wireless Sensor Networks , IEEE/ACM Transactions on Networking , (04 2013): 0. doi: 10.1109/TNET.2013.2256795 Soumik Sarkar, Kushal Mukherjee...Phoha, Bharat B. Madan, Asok Ray. Distributed Network Control for Mobile Multi-Modal Wireless Sensor Networks , Journal of Parallel and Distributed...Deadline Constraints, IEEE Transactions on Automatic Control special issue on Wireless Sensor and Actuator Networks , (01 2011): 1. doi: Eric Keller
Distributed sensor coordination for advanced energy systems
DOE Office of Scientific and Technical Information (OSTI.GOV)
Tumer, Kagan
Motivation: The ability to collect key system level information is critical to the safe, efficient and reliable operation of advanced power systems. Recent advances in sensor technology have enabled some level of decision making directly at the sensor level. However, coordinating large numbers of sensors, particularly heterogeneous sensors, to achieve system level objectives such as predicting plant efficiency, reducing downtime or predicting outages requires sophisticated coordination algorithms. Indeed, a critical issue in such systems is how to ensure the interaction of a large number of heterogenous system components do not interfere with one another and lead to undesirable behavior. Objectivesmore » and Contributions: The long-term objective of this work is to provide sensor deployment, coordination and networking algorithms for large numbers of sensors to ensure the safe, reliable, and robust operation of advanced energy systems. Our two specific objectives are to: 1. Derive sensor performance metrics for heterogeneous sensor networks. 2. Demonstrate effectiveness, scalability and reconfigurability of heterogeneous sensor network in advanced power systems. The key technical contribution of this work is to push the coordination step to the design of the objective functions of the sensors, allowing networks of heterogeneous sensors to be controlled. By ensuring that the control and coordination is not specific to particular sensor hardware, this approach enables the design and operation of large heterogeneous sensor networks. In addition to the coordination coordination mechanism, this approach allows the system to be reconfigured in response to changing needs (e.g., sudden external events requiring new responses) or changing sensor network characteristics (e.g., sudden changes to plant condition). Impact: The impact of this work extends to a large class of problems relevant to the National Energy Technology Laboratory including sensor placement, heterogeneous sensor coordination, and sensor network control in advanced power systems. Each application has specific needs, but they all share the one crucial underlying problem: how to ensure that the interactions of a large number of heterogenous agents lead to coordinated system behavior. This proposal describes a new paradigm that addresses that very issue in a systematic way. Key Results and Findings: All milestones have been completed. Our results demonstrate that by properly shaping agent objective functions, we can develop large (up to 10,000 devices) heterogeneous sensor networks with key desirable properties. The first milestone shows that properly choosing agent-specific objective functions increases system performance by up to 99.9% compared to global evaluations. The second milestone shows evolutionary algorithms learn excellent sensor network coordination policies prior to network deployment, and these policies can be refined online once the network is deployed. The third milestone shows the resulting sensor networks networks are extremely robust to sensor noise, where networks with up to 25% sensor noise are capable of providing measurements with errors on the order of 10⁻³. The fourth milestone shows the resulting sensor networks are extremely robust to sensor failure, with 25% of the sensors in the system failing resulting in no significant performance losses after system reconfiguration.« less
A feedback-based secure path approach for wireless sensor network data collection.
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.
Using algebra for massively parallel processor design and utilization
NASA Technical Reports Server (NTRS)
Campbell, Lowell; Fellows, Michael R.
1990-01-01
This paper summarizes the author's advances in the design of dense processor networks. Within is reported a collection of recent constructions of dense symmetric networks that provide the largest know values for the number of nodes that can be placed in a network of a given degree and diameter. The constructions are in the range of current potential engineering significance and are based on groups of automorphisms of finite-dimensional vector spaces.
NASA Astrophysics Data System (ADS)
Volcke, P.; Pequegnat, C.; Grunberg, M.; Lecointre, A.; Bzeznik, B.; Wolyniec, D.; Engels, F.; Maron, C.; Cheze, J.; Pardo, C.; Saurel, J. M.; André, F.
2015-12-01
RESIF is a nationwide french project aimed at building a high quality observation system to observe and understand the inner earth. RESIF deals with permanent seismic networks data as well as mobile networks data, including dense/semi-dense arrays. RESIF project is distributed among different nodes providing qualified data to the main datacentre in Université Grenoble Alpes, France. Data control and qualification is performed by each individual nodes : the poster will provide some insights on RESIF broadband seismic component data quality control. We will then present data that has been recently made publicly available. Data is distributed through worldwide FDSN and european EIDA standards protocols. A new web portal is now opened to explore and download seismic data and metadata. The RESIF datacentre is also now connected to Grenoble University High Performance Computing (HPC) facility : a typical use-case will be presented using iRODS technologies. The use of dense observation networks is increasing, bringing challenges in data growth and handling : we will present an example where HDF5 data format was used as an alternative to usual seismology data formats.
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.
On Applicability of Network Coding Technique for 6LoWPAN-based Sensor Networks.
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.
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.
Colak, Recep; Moser, Flavia; Chu, Jeffrey Shih-Chieh; Schönhuth, Alexander; Chen, Nansheng; Ester, Martin
2010-10-25
Computational prediction of functionally related groups of genes (functional modules) from large-scale data is an important issue in computational biology. Gene expression experiments and interaction networks are well studied large-scale data sources, available for many not yet exhaustively annotated organisms. It has been well established, when analyzing these two data sources jointly, modules are often reflected by highly interconnected (dense) regions in the interaction networks whose participating genes are co-expressed. However, the tractability of the problem had remained unclear and methods by which to exhaustively search for such constellations had not been presented. We provide an algorithmic framework, referred to as Densely Connected Biclustering (DECOB), by which the aforementioned search problem becomes tractable. To benchmark the predictive power inherent to the approach, we computed all co-expressed, dense regions in physical protein and genetic interaction networks from human and yeast. An automatized filtering procedure reduces our output which results in smaller collections of modules, comparable to state-of-the-art approaches. Our results performed favorably in a fair benchmarking competition which adheres to standard criteria. We demonstrate the usefulness of an exhaustive module search, by using the unreduced output to more quickly perform GO term related function prediction tasks. We point out the advantages of our exhaustive output by predicting functional relationships using two examples. We demonstrate that the computation of all densely connected and co-expressed regions in interaction networks is an approach to module discovery of considerable value. Beyond confirming the well settled hypothesis that such co-expressed, densely connected interaction network regions reflect functional modules, we open up novel computational ways to comprehensively analyze the modular organization of an organism based on prevalent and largely available large-scale datasets. Software and data sets are available at http://www.sfu.ca/~ester/software/DECOB.zip.
Network Computing for Distributed Underwater Acoustic Sensors
2014-03-31
underwater sensor network with mobility. In preparation. [3] EvoLogics (2013), Underwater Acoustic Modems, (Product Information Guide... Wireless Communications, 9(9), 2934–2944. [21] Pompili, D. and Akyildiz, I. (2010), A multimedia cross-layer protocol for underwater acoustic sensor networks ... Network Computing for Distributed Underwater Acoustic Sensors M. Barbeau E. Kranakis
Capacity Building for Research and Education in GIS/GPS Technology and Systems
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
NASA Astrophysics Data System (ADS)
Horikawa, H.; Takaesu, M.; Sueki, K.; Takahashi, N.; Sonoda, A.; Miura, S.; Tsuboi, S.
2014-12-01
Mega-thrust earthquakes are anticipated to occur in the Nankai Trough in southwest Japan. In the source areas, we have deployed seafloor seismic network, DONET (Dense Ocean-floor Network System for Earthquake and Tsunamis), in 2010 in order to monitor seismicity, crustal deformations, and tsunamis. DONET system consists of totally 20 stations, which is composed of six kinds of sensors, including strong-motion seismometers and quartz pressure gauges. Those stations are densely distributed with an average spatial interval of 15-20 km and cover near the trench axis to coastal areas. Observed data are transferred to a land station through a fiber-optical cable and then to JAMSTEC (Japan Agency for Marine-Earth Science and Technology) data management center through a private network in real time. After 2011 off the Pacific coast of Tohoku Earthquake, each local government close to Nankai Trough try to plan disaster prevention scheme. JAMSTEC will disseminate DONET data combined with research accomplishment so that they will be widely recognized as important earthquake information. In order to open DONET data observed for research to local government, we have developed a web application system, REIS (Real-time Earthquake Information System). REIS is providing seismic waveform data to some local governments close to Nankai Trough as a pilot study. As soon as operation of DONET is ready, REIS will start full-scale operation. REIS can display seismic waveform data of DONET in real-time, users can select strong motion and pressure data, and configure the options of trace view arrangement, time scale, and amplitude. In addition to real-time monitoring, REIS can display past seismic waveform data and show earthquake epicenters on the map. In this presentation, we briefly introduce DONET system and then show our web application system. We also discuss our future plans for further developments of REIS.
Towards Integrated Marmara Strong Motion Network
NASA Astrophysics Data System (ADS)
Durukal, E.; Erdik, M.; Safak, E.; Ansal, A.; Ozel, O.; Alcik, H.; Mert, A.; Kafadar, N.; Korkmaz, A.; Kurtulus, A.
2009-04-01
Istanbul has a 65% chance of having a magnitude 7 or above earthquake within the next 30 years. As part of the preparations for the future earthquake, strong motion networks have been installed in and around Istanbul. The Marmara Strong Motion Network, operated by the Department of Earthquake Engineering of Kandilli Observatory and Earthquake Research Institute, encompasses permanent systems outlined below. It is envisaged that the networks will be run by a single entity responsible for technical management and maintanence, as well as for data management, archiving and dissemination through dedicated web-based interfaces. • Istanbul Earthquake Rapid Response and Early Warning System - IERREWS (one hundred 18-bit accelerometers for rapid response; ten 24-bit accelerometers for early warning) • IGDAŞ Gas Shutoff Network (100 accelerometers to be installed in 2010 and integrated with IERREWS) • Structural Monitoring Arrays - Fatih Sultan Mehmet Suspension Bridge (1200m-long suspension bridge across the Bosphorus, five 3-component accelerometers + GPS sensors) - Hagia Sophia Array (1500-year-old historical edifice, 9 accelerometers) - Süleymaniye Mosque Array (450-year-old historical edifice,9 accelerometers) - Fatih Mosque Array (237-year-old historical edifice, 9 accelerometers) - Kanyon Building Array (high-rise office building, 5 accelerometers) - Isbank Tower Array (high-rise office building, 5 accelerometers) - ENRON Array (power generation facility, 4 acelerometers) - Mihrimah Sultan Mosque Array (450-year-old historical edifice,9 accelerometers + tiltmeters, to be installed in 2009) - Sultanahmet Mosque Array, (390-year-old historical edifice, 9 accelerometers + tiltmeters, to be installed in 2009) • Special Arrays - Atakoy Vertical Array (four 3-component accelerometers at 25, 50, 75, and 150 m depths) - Marmara Tube Tunnel (1400 m long submerged tunnel, 128 ch. accelerometric data, 24 ch. strain data, to be installed in 2010) - Air-Force Academy Array (72 ch. dense accelerometric array to be installed in 2010) - Gemlik Array (a dense basin array of 8 stations, to be installed in 2010) The objectives of these systems and networks are: (1) to produce rapid earthquake intensity, damage and loss assessment information after an earthquake (in the case of IERREWS), (2) to monitor conditions of structural systems, (3) to develop real-time data processing, analysis, and damage detection and location tools (in the case of structural networks) after an extreme event, (4) to assess spatial properties of strong ground motion and ground strain, and to characterise basin response (in the case of special arrays), (5) to investigate site response and wave propagation (in the case of vertical array). Ground motion data obtained from these strong motion networks have and are being used for investigations of attenuation, spatial variation (coherence), simulation benchmarking, source modeling, site response, seismic microzonation, system identification and structural model verification and structural health control. In addition to the systems and networks outlined above there are two temporary networks: KIMNET - a dense urban noise and microtremor network consisting of 50 broadband stations expected to be operational in mid 2009, and SOSEWIN - a 20-station, self-organizing structural integrated array at Ataköy in Istanbul.
NASA Astrophysics Data System (ADS)
Mascarenas, David D. L.; Flynn, Eric; Lin, Kaisen; Farinholt, Kevin; Park, Gyuhae; Gupta, Rajesh; Todd, Michael; Farrar, Charles
2008-03-01
A major challenge impeding the deployment of wireless sensor networks for structural health monitoring (SHM) is developing means to supply power to the sensor nodes in a cost-effective manner. In this work an initial test of a roving-host wireless sensor network was performed on a bridge near Truth or Consequences, NM in August of 2007. The roving-host wireless sensor network features a radio controlled helicopter responsible for wirelessly delivering energy to sensor nodes on an "as-needed" basis. In addition, the helicopter also serves as a central data repository and processing center for the information collected by the sensor network. The sensor nodes used on the bridge were developed for measuring the peak displacement of the bridge, as well as measuring the preload of some of the bolted joints in the bridge. These sensors and sensor nodes were specifically designed to be able to operate from energy supplied wirelessly from the helicopter. The ultimate goal of this research is to ease the requirement for battery power supplies in wireless sensor networks.
An Embedded Multi-Agent Systems Based Industrial Wireless Sensor Network
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.
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.
Cooperative Game-Based Energy Efficiency Management over Ultra-Dense Wireless Cellular Networks
Li, Ming; Chen, Pengpeng; Gao, Shouwan
2016-01-01
Ultra-dense wireless cellular networks have been envisioned as a promising technique for handling the explosive increase of wireless traffic volume. With the extensive deployment of small cells in wireless cellular networks, the network spectral efficiency (SE) is improved with the use of limited frequency. However, the mutual inter-tier and intra-tier interference between or among small cells and macro cells becomes serious. On the other hand, more chances for potential cooperation among different cells are introduced. Energy efficiency (EE) has become one of the most important problems for future wireless networks. This paper proposes a cooperative bargaining game-based method for comprehensive EE management in an ultra-dense wireless cellular network, which highlights the complicated interference influence on energy-saving challenges and the power-coordination process among small cells and macro cells. Especially, a unified EE utility with the consideration of the interference mitigation is proposed to jointly address the SE, the deployment efficiency (DE), and the EE. In particular, closed-form power-coordination solutions for the optimal EE are derived to show the convergence property of the algorithm. Moreover, a simplified algorithm is presented to reduce the complexity of the signaling overhead, which is significant for ultra-dense small cells. Finally, numerical simulations are provided to illustrate the efficiency of the proposed cooperative bargaining game-based and simplified schemes. PMID:27649170
An automated method for finding molecular complexes in large protein interaction networks
Bader, Gary D; Hogue, Christopher WV
2003-01-01
Background Recent advances in proteomics technologies such as two-hybrid, phage display and mass spectrometry have enabled us to create a detailed map of biomolecular interaction networks. Initial mapping efforts have already produced a wealth of data. As the size of the interaction set increases, databases and computational methods will be required to store, visualize and analyze the information in order to effectively aid in knowledge discovery. Results This paper describes a novel graph theoretic clustering algorithm, "Molecular Complex Detection" (MCODE), that detects densely connected regions in large protein-protein interaction networks that may represent molecular complexes. The method is based on vertex weighting by local neighborhood density and outward traversal from a locally dense seed protein to isolate the dense regions according to given parameters. The algorithm has the advantage over other graph clustering methods of having a directed mode that allows fine-tuning of clusters of interest without considering the rest of the network and allows examination of cluster interconnectivity, which is relevant for protein networks. Protein interaction and complex information from the yeast Saccharomyces cerevisiae was used for evaluation. Conclusion Dense regions of protein interaction networks can be found, based solely on connectivity data, many of which correspond to known protein complexes. The algorithm is not affected by a known high rate of false positives in data from high-throughput interaction techniques. The program is available from . PMID:12525261
Cooperative Game-Based Energy Efficiency Management over Ultra-Dense Wireless Cellular Networks.
Li, Ming; Chen, Pengpeng; Gao, Shouwan
2016-09-13
Ultra-dense wireless cellular networks have been envisioned as a promising technique for handling the explosive increase of wireless traffic volume. With the extensive deployment of small cells in wireless cellular networks, the network spectral efficiency (SE) is improved with the use of limited frequency. However, the mutual inter-tier and intra-tier interference between or among small cells and macro cells becomes serious. On the other hand, more chances for potential cooperation among different cells are introduced. Energy efficiency (EE) has become one of the most important problems for future wireless networks. This paper proposes a cooperative bargaining game-based method for comprehensive EE management in an ultra-dense wireless cellular network, which highlights the complicated interference influence on energy-saving challenges and the power-coordination process among small cells and macro cells. Especially, a unified EE utility with the consideration of the interference mitigation is proposed to jointly address the SE, the deployment efficiency (DE), and the EE. In particular, closed-form power-coordination solutions for the optimal EE are derived to show the convergence property of the algorithm. Moreover, a simplified algorithm is presented to reduce the complexity of the signaling overhead, which is significant for ultra-dense small cells. Finally, numerical simulations are provided to illustrate the efficiency of the proposed cooperative bargaining game-based and simplified schemes.
Bio-Inspired Stretchable Absolute Pressure Sensor Network
Guo, Yue; Li, Yu-Hung; Guo, Zhiqiang; Kim, Kyunglok; Chang, Fu-Kuo; Wang, Shan X.
2016-01-01
A bio-inspired absolute pressure sensor network has been developed. Absolute pressure sensors, distributed on multiple silicon islands, are connected as a network by stretchable polyimide wires. This sensor network, made on a 4’’ wafer, has 77 nodes and can be mounted on various curved surfaces to cover an area up to 0.64 m × 0.64 m, which is 100 times larger than its original size. Due to Micro Electro-Mechanical system (MEMS) surface micromachining technology, ultrathin sensing nodes can be realized with thicknesses of less than 100 µm. Additionally, good linearity and high sensitivity (~14 mV/V/bar) have been achieved. Since the MEMS sensor process has also been well integrated with a flexible polymer substrate process, the entire sensor network can be fabricated in a time-efficient and cost-effective manner. Moreover, an accurate pressure contour can be obtained from the sensor network. Therefore, this absolute pressure sensor network holds significant promise for smart vehicle applications, especially for unmanned aerial vehicles. PMID:26729134
The Coverage Problem in Video-Based Wireless Sensor Networks: A Survey
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
Distributed Estimation, Coding, and Scheduling in Wireless Visual Sensor Networks
ERIC Educational Resources Information Center
Yu, Chao
2013-01-01
In this thesis, we consider estimation, coding, and sensor scheduling for energy efficient operation of wireless visual sensor networks (VSN), which consist of battery-powered wireless sensors with sensing (imaging), computation, and communication capabilities. The competing requirements for applications of these wireless sensor networks (WSN)…
Optimizing Cluster Heads for Energy Efficiency in Large-Scale Heterogeneous Wireless Sensor Networks
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
Wireless Sensor Network Applications for the Combat Air Forces
2006-06-13
WIRELESS SENSOR NETWORK APPLICATIONS FOR THE COMBAT AIR FORCES GRADUATE RESEARCH PROJECT...Government. AFIT/IC4/ENG/06-05 WIRELESS SENSOR NETWORK APPLICATIONS FOR THE COMBAT AIR FORCES GRADUATE RESEARCH PROJECT Presented to the...Major, USAF June 2006 APPROVED FOR PUBLIC RELEASE; DISTRIBUTION UNLIMITED AFIT/IC4/ENG/06-05 WIRELESS SENSOR NETWORK APPLICATIONS
A Feedback-Based Secure Path Approach for Wireless Sensor Network Data Collection
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
Smart border: ad-hoc wireless sensor networks for border surveillance
NASA Astrophysics Data System (ADS)
He, Jun; Fallahi, Mahmoud; Norwood, Robert A.; Peyghambarian, Nasser
2011-06-01
Wireless sensor networks have been proposed as promising candidates to provide automated monitoring, target tracking, and intrusion detection for border surveillance. In this paper, we demonstrate an ad-hoc wireless sensor network system for border surveillance. The network consists of heterogeneously autonomous sensor nodes that distributively cooperate with each other to enable a smart border in remote areas. This paper also presents energy-aware and sleeping algorithms designed to maximize the operating lifetime of the deployed sensor network. Lessons learned in building the network and important findings from field experiments are shared in the paper.
Automated Construction of Node Software Using Attributes in a Ubiquitous Sensor Network Environment
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.
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.
Zhao, Xue Jiao; Kuang, Shuang Yang; Wang, Zhong Lin; Zhu, Guang
2018-05-22
Harvesting water wave energy presents a significantly practical route to energy supply for self-powered wireless sensing networks. Here we report a networked integrated triboelectric nanogenerator (NI-TENG) as a highly adaptive means of harvesting energy from interfacing interactions with various types of water waves. Having an arrayed networking structure, the NI-TENG can accommodate diverse water wave motions and generate stable electric output regardless of how random the water wave is. Nanoscaled surface morphology consisting of dense nanowire arrays is the key for obtaining high electric output. A NI-TENG having an area of 100 × 70 mm 2 can produce a stable short-circuit current of 13.5 μA and corresponding electric power of 1.03 mW at a water wave height of 12 cm. This merit promises practical applications of the NI-TENG in real circumstances, where water waves are highly variable and unpredictable. After energy storage, the generated electric energy can drive wireless sensing by autonomously transmitting data at a period less than 1 min. This work proposes a viable solution for powering individual standalone nodes in a wireless sensor network. Potential applications include but are not limited to long-term environment monitoring, marine surveillance, and off-shore navigation.
The Potential for Harvesting Energy from the Movement of Trees
McGarry, Scott; Knight, Chris
2011-01-01
Over the last decade, wireless devices have decreased in size and power requirements. These devices generally use batteries as a power source but can employ additional means of power, such as solar, thermal or wind energy. However, sensor networks are often deployed in conditions of minimal lighting and thermal gradient such as densely wooded environments, where even normal wind energy harvesting is limited. In these cases a possible source of energy is from the motion of the trees themselves. We investigated the amount of energy and power available from the motion of a tree in a sheltered position, during Beaufort 4 winds. We measured the work performed by the tree to lift a mass, we measured horizontal acceleration of free movement, and we determined the angular deflection of the movement of the tree trunk, to determine the energy and power available to various types of harvesting devices. We found that the amount of power available from the tree, as demonstrated by lifting a mass, compares favourably with the power required to run a wireless sensor node. PMID:22163695
The potential for harvesting energy from the movement of trees.
McGarry, Scott; Knight, Chris
2011-01-01
Over the last decade, wireless devices have decreased in size and power requirements. These devices generally use batteries as a power source but can employ additional means of power, such as solar, thermal or wind energy. However, sensor networks are often deployed in conditions of minimal lighting and thermal gradient such as densely wooded environments, where even normal wind energy harvesting is limited. In these cases a possible source of energy is from the motion of the trees themselves. We investigated the amount of energy and power available from the motion of a tree in a sheltered position, during Beaufort 4 winds. We measured the work performed by the tree to lift a mass, we measured horizontal acceleration of free movement, and we determined the angular deflection of the movement of the tree trunk, to determine the energy and power available to various types of harvesting devices. We found that the amount of power available from the tree, as demonstrated by lifting a mass, compares favourably with the power required to run a wireless sensor node.
IJA: an efficient algorithm for query processing in sensor networks.
Lee, Hyun Chang; Lee, Young Jae; Lim, Ji Hyang; Kim, Dong Hwa
2011-01-01
One of main features in sensor networks is the function that processes real time state information after gathering needed data from many domains. The component technologies consisting of each node called a sensor node that are including physical sensors, processors, actuators and power have advanced significantly over the last decade. Thanks to the advanced technology, over time sensor networks have been adopted in an all-round industry sensing physical phenomenon. However, sensor nodes in sensor networks are considerably constrained because with their energy and memory resources they have a very limited ability to process any information compared to conventional computer systems. Thus query processing over the nodes should be constrained because of their limitations. Due to the problems, the join operations in sensor networks are typically processed in a distributed manner over a set of nodes and have been studied. By way of example while simple queries, such as select and aggregate queries, in sensor networks have been addressed in the literature, the processing of join queries in sensor networks remains to be investigated. Therefore, in this paper, we propose and describe an Incremental Join Algorithm (IJA) in Sensor Networks to reduce the overhead caused by moving a join pair to the final join node or to minimize the communication cost that is the main consumer of the battery when processing the distributed queries in sensor networks environments. At the same time, the simulation result shows that the proposed IJA algorithm significantly reduces the number of bytes to be moved to join nodes compared to the popular synopsis join algorithm.
IJA: An Efficient Algorithm for Query Processing in Sensor Networks
Lee, Hyun Chang; Lee, Young Jae; Lim, Ji Hyang; Kim, Dong Hwa
2011-01-01
One of main features in sensor networks is the function that processes real time state information after gathering needed data from many domains. The component technologies consisting of each node called a sensor node that are including physical sensors, processors, actuators and power have advanced significantly over the last decade. Thanks to the advanced technology, over time sensor networks have been adopted in an all-round industry sensing physical phenomenon. However, sensor nodes in sensor networks are considerably constrained because with their energy and memory resources they have a very limited ability to process any information compared to conventional computer systems. Thus query processing over the nodes should be constrained because of their limitations. Due to the problems, the join operations in sensor networks are typically processed in a distributed manner over a set of nodes and have been studied. By way of example while simple queries, such as select and aggregate queries, in sensor networks have been addressed in the literature, the processing of join queries in sensor networks remains to be investigated. Therefore, in this paper, we propose and describe an Incremental Join Algorithm (IJA) in Sensor Networks to reduce the overhead caused by moving a join pair to the final join node or to minimize the communication cost that is the main consumer of the battery when processing the distributed queries in sensor networks environments. At the same time, the simulation result shows that the proposed IJA algorithm significantly reduces the number of bytes to be moved to join nodes compared to the popular synopsis join algorithm. PMID:22319375
Zone-Based Routing Protocol for Wireless Sensor Networks
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.
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.
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.
Decentralized sensor fusion for Ubiquitous Networking Robotics in Urban Areas.
Sanfeliu, Alberto; Andrade-Cetto, Juan; Barbosa, Marco; Bowden, Richard; Capitán, Jesús; Corominas, Andreu; Gilbert, Andrew; Illingworth, John; Merino, Luis; Mirats, Josep M; Moreno, Plínio; Ollero, Aníbal; Sequeira, João; Spaan, Matthijs T J
2010-01-01
In this article we explain the architecture for the environment and sensors that has been built for the European project URUS (Ubiquitous Networking Robotics in Urban Sites), a project whose objective is to develop an adaptable network robot architecture for cooperation between network robots and human beings and/or the environment in urban areas. The project goal is to deploy a team of robots in an urban area to give a set of services to a user community. This paper addresses the sensor architecture devised for URUS and the type of robots and sensors used, including environment sensors and sensors onboard the robots. Furthermore, we also explain how sensor fusion takes place to achieve urban outdoor execution of robotic services. Finally some results of the project related to the sensor network are highlighted.
NASA Astrophysics Data System (ADS)
Wei, Shiyin; Zhang, Zhaohui; Li, Shunlong; Li, Hui
2017-10-01
Strain is a direct indicator of structural safety. Therefore, strain sensors have been used in most structural health monitoring systems for bridges. However, until now, the investigation of strain response has been insufficient. This paper conducts a comprehensive study of the strain features of the U ribs and transverse diaphragm on an orthotropic steel deck and proposes a statistical paradigm for crack detection based on the features of vehicle-induced strain response by using the densely distributed optic fibre Bragg grating (FBG) strain sensors. The local feature of strain under vehicle load is highlighted, which enables the use of measurement data to determine the vehicle loading event and to make a decision regarding the health status of a girder near the strain sensors via technical elimination of the load information. Time-frequency analysis shows that the strain contains three features: the long-term trend item, the short-term trend item, and the instantaneous vehicle-induced item (IVII). The IVII is the wheel-induced strain with a remarkable local feature, and the measured wheel-induced strain is only influenced by the vehicle near the FBG sensor, while other vehicles slightly farther away have no effect on the wheel-induced strain. This causes the local strain series, among the FBG strain sensors in the same transverse locations of different cross-sections, to present similarities in shape to some extent and presents a time delay in successive order along the driving direction. Therefore, the strain series induced by an identical vehicle can be easily tracked and compared by extracting the amplitude and calculating the mutual ratio to eliminate vehicle loading information, leaving the girder information alone. The statistical paradigm for crack detection is finally proposed, and the detection accuracy is then validated by using dense FBG strain sensors on a long-span suspension bridge in China.
Complex networks in confined comminution
NASA Astrophysics Data System (ADS)
Walker, David M.; Tordesillas, Antoinette; Einav, Itai; Small, Michael
2011-08-01
The physical process of confined comminution is investigated within the framework of complex networks. We first characterize the topology of the unweighted contact networks as generated by the confined comminution process. We find this process gives rise to an ultimate contact network which exhibits a scale-free degree distribution and small world properties. In particular, if viewed in the context of networks through which information travels along shortest paths, we find that the global average of the node vulnerability decreases as the comminution process continues, with individual node vulnerability correlating with grain size. A possible application to the design of synthetic networks (e.g., sensor networks) is highlighted. Next we turn our attention to the physics of the granular comminution process and examine force transmission with respect to the weighted contact networks, where each link is weighted by the inverse magnitude of the normal force acting at the associated contact. We find that the strong forces (i.e., force chains) are transmitted along pathways in the network which are mainly following shortest-path routing protocols, as typically found, for example, in communication systems. Motivated by our earlier studies of the building blocks for self-organization in dense granular systems, we also explore the properties of the minimal contact cycles. The distribution of the contact strain energy intensity of 4-cycle motifs in the ultimate state of the confined comminution process is shown to be consistent with a scale-free distribution with infinite variance, thereby suggesting that 4-cycle arrangements of grains are capable of storing vast amounts of energy in their contacts without breaking.
Dimitriadis, Stavros I.; Zouridakis, George; Rezaie, Roozbeh; Babajani-Feremi, Abbas; Papanicolaou, Andrew C.
2015-01-01
Mild traumatic brain injury (mTBI) may affect normal cognition and behavior by disrupting the functional connectivity networks that mediate efficient communication among brain regions. In this study, we analyzed brain connectivity profiles from resting state Magnetoencephalographic (MEG) recordings obtained from 31 mTBI patients and 55 normal controls. We used phase-locking value estimates to compute functional connectivity graphs to quantify frequency-specific couplings between sensors at various frequency bands. Overall, normal controls showed a dense network of strong local connections and a limited number of long-range connections that accounted for approximately 20% of all connections, whereas mTBI patients showed networks characterized by weak local connections and strong long-range connections that accounted for more than 60% of all connections. Comparison of the two distinct general patterns at different frequencies using a tensor representation for the connectivity graphs and tensor subspace analysis for optimal feature extraction showed that mTBI patients could be separated from normal controls with 100% classification accuracy in the alpha band. These encouraging findings support the hypothesis that MEG-based functional connectivity patterns may be used as biomarkers that can provide more accurate diagnoses, help guide treatment, and monitor effectiveness of intervention in mTBI. PMID:26640764
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.
A Mobile Sensor Network System for Monitoring of Unfriendly Environments.
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.
LinkMind: link optimization in swarming mobile sensor networks.
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
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
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.
Open-WiSe: a solar powered wireless sensor network platform.
González, Apolinar; Aquino, Raúl; Mata, Walter; Ochoa, Alberto; Saldaña, Pedro; Edwards, Arthur
2012-01-01
Because battery-powered nodes are required in wireless sensor networks and energy consumption represents an important design consideration, alternate energy sources are needed to provide more effective and optimal function. The main goal of this work is to present an energy harvesting wireless sensor network platform, the Open Wireless Sensor node (WiSe). The design and implementation of the solar powered wireless platform is described including the hardware architecture, firmware, and a POSIX Real-Time Kernel. A sleep and wake up strategy was implemented to prolong the lifetime of the wireless sensor network. This platform was developed as a tool for researchers investigating Wireless sensor network or system integrators.
Empirical Bayes conditional independence graphs for regulatory network recovery.
Mahdi, Rami; Madduri, Abishek S; Wang, Guoqing; Strulovici-Barel, Yael; Salit, Jacqueline; Hackett, Neil R; Crystal, Ronald G; Mezey, Jason G
2012-08-01
Computational inference methods that make use of graphical models to extract regulatory networks from gene expression data can have difficulty reconstructing dense regions of a network, a consequence of both computational complexity and unreliable parameter estimation when sample size is small. As a result, identification of hub genes is of special difficulty for these methods. We present a new algorithm, Empirical Light Mutual Min (ELMM), for large network reconstruction that has properties well suited for recovery of graphs with high-degree nodes. ELMM reconstructs the undirected graph of a regulatory network using empirical Bayes conditional independence testing with a heuristic relaxation of independence constraints in dense areas of the graph. This relaxation allows only one gene of a pair with a putative relation to be aware of the network connection, an approach that is aimed at easing multiple testing problems associated with recovering densely connected structures. Using in silico data, we show that ELMM has better performance than commonly used network inference algorithms including GeneNet, ARACNE, FOCI, GENIE3 and GLASSO. We also apply ELMM to reconstruct a network among 5492 genes expressed in human lung airway epithelium of healthy non-smokers, healthy smokers and individuals with chronic obstructive pulmonary disease assayed using microarrays. The analysis identifies dense sub-networks that are consistent with known regulatory relationships in the lung airway and also suggests novel hub regulatory relationships among a number of genes that play roles in oxidative stress and secretion. Software for running ELMM is made available at http://mezeylab.cb.bscb.cornell.edu/Software.aspx. ramimahdi@yahoo.com or jgm45@cornell.edu Supplementary data are available at Bioinformatics online.
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.
Dynamic Hierarchical Sleep Scheduling for Wireless Ad-Hoc Sensor Networks
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.
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.
Tactical Network Load Balancing in Multi-Gateway Wireless Sensor Networks
2013-12-01
writeup scrsz = get( 0 ,’ScreenSize’); %Creation of the random Sensor Network fig = figure(1); set(fig, ’Position’,[1 scrsz( 4 )*.25 scrsz(3)*.7...thesis writeup scrsz = get( 0 ,’ScreenSize’); %Creation of the random Sensor Network fig = figure(1); set(fig, ’Position’,[1 scrsz( 4 )*.25 scrsz(3)*.7...TYPE AND DATES COVERED Master’s Thesis 4 . TITLE AND SUBTITLE TACTICAL NETWORK LOAD BALANCING IN MULTI-GATEWAY WIRELESS SENSOR NETWORKS 5
A measure of the denseness of a phylogenetic network. [by sequenced proteins from extant species
NASA Technical Reports Server (NTRS)
Holmquist, R.
1978-01-01
An objective measure of phylogenetic denseness is developed to examine various phylogenetic criteria: alpha- and beta-hemoglobin, myoglobin, cytochrome c, and the parvalbumin family. Attention is given to the number of nucleotide replacements separating homologous sequences, and to the topology of the network (in other words, to the qualitative nature of the network as defined by how closely the studied species are related). Applications include quantitative comparisons of species origin, relation, and rates of evolution.
Crowd-Sourced Global Earthquake Early Warning
NASA Astrophysics Data System (ADS)
Minson, S. E.; Brooks, B. A.; Glennie, C. L.; Murray, J. R.; Langbein, J. O.; Owen, S. E.; Iannucci, B. A.; Hauser, D. L.
2014-12-01
Although earthquake early warning (EEW) has shown great promise for reducing loss of life and property, it has only been implemented in a few regions due, in part, to the prohibitive cost of building the required dense seismic and geodetic networks. However, many cars and consumer smartphones, tablets, laptops, and similar devices contain low-cost versions of the same sensors used for earthquake monitoring. If a workable EEW system could be implemented based on either crowd-sourced observations from consumer devices or very inexpensive networks of instruments built from consumer-quality sensors, EEW coverage could potentially be expanded worldwide. Controlled tests of several accelerometers and global navigation satellite system (GNSS) receivers typically found in consumer devices show that, while they are significantly noisier than scientific-grade instruments, they are still accurate enough to capture displacements from moderate and large magnitude earthquakes. The accuracy of these sensors varies greatly depending on the type of data collected. Raw coarse acquisition (C/A) code GPS data are relatively noisy. These observations have a surface displacement detection threshold approaching ~1 m and would thus only be useful in large Mw 8+ earthquakes. However, incorporating either satellite-based differential corrections or using a Kalman filter to combine the raw GNSS data with low-cost acceleration data (such as from a smartphone) decreases the noise dramatically. These approaches allow detection thresholds as low as 5 cm, potentially enabling accurate warnings for earthquakes as small as Mw 6.5. Simulated performance tests show that, with data contributed from only a very small fraction of the population, a crowd-sourced EEW system would be capable of warning San Francisco and San Jose of a Mw 7 rupture on California's Hayward fault and could have accurately issued both earthquake and tsunami warnings for the 2011 Mw 9 Tohoku-oki, Japan earthquake.
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
Global Seismic Monitoring: Past, Present, and Future
NASA Astrophysics Data System (ADS)
Zoback, M.; Benz, H.; Oppenheimer, D.
2007-12-01
Global seismological observations began in April 1889 when an earthquake in Tokyo, Japan was accurately recorded in Germany on two different horizontal pendulum instruments. However, modern global observational seismology really began 46 years ago when the 120-station World Wide Standard Seismograph Network was installed by the US to monitor underground nuclear tests and earthquakes using well-calibrated short- and long- period stations. At the same time rapid advances in computing technology enabled researchers to begin sophisticated analysis of the increasing amount of seismic data, which led to better understanding of earthquake source properties and their use in establishing plate tectonics. Today, global seismic networks are operated by German (Geophon), France (Geoscope), the United States (Global Seismograph Network) and the International Monitoring System. Presently, the Federation of Digital Seismograph Networks registers more than 1,000 broadband stations world-wide, a small percentage of the total number of digital seismic stations around the world. Following the devastating Kobe, Japan and Northridge, California earthquakes, Japan and the US have led the world in the integration of existing seismic sensor systems (weak and strong motion) into development of near-real-time, post-earthquake response products like ShakeMap, detailing the spatial distribution of strong shaking. Future challenges include expanding real-time integration of both seismic and geodetic sensor systems to produce early warning of strong shaking, rapid source determination, as well as near-realtime post- earthquake damage assessment. Seismic network data, hydro-acoustic arrays, deep water tide gauges, and satellite imagery of wave propagation should be integrated in real-time to provide input for hydrodynamic modeling yielding the distribution, timing and size of tsunamis runup--which would then be available instantly on the web, e.g. in a Google Earth format. Dense arrays of strong motion sensors together with deployment of MEMS-type accelerometers in buildings and equipment routinely connected to the Web could potentially provide thousands of measurements of damaging strong ground motion. This technology could ultimately become part of smart building design enabling critical facilities to change their structural response to imminent strong shaking. Looking further forward, it is likely that a continuously observing spaceborne system could image the occurrence of "silent" or "slow" earthquakes as well as the propagation of ground displacement by surface waves at scales of continents.
Kotamäki, Niina; Thessler, Sirpa; Koskiaho, Jari; Hannukkala, Asko O.; Huitu, Hanna; Huttula, Timo; Havento, Jukka; Järvenpää, Markku
2009-01-01
Sensor networks are increasingly being implemented for environmental monitoring and agriculture to provide spatially accurate and continuous environmental information and (near) real-time applications. These networks provide a large amount of data which poses challenges for ensuring data quality and extracting relevant information. In the present paper we describe a river basin scale wireless sensor network for agriculture and water monitoring. The network, called SoilWeather, is unique and the first of this type in Finland. The performance of the network is assessed from the user and maintainer perspectives, concentrating on data quality, network maintenance and applications. The results showed that the SoilWeather network has been functioning in a relatively reliable way, but also that the maintenance and data quality assurance by automatic algorithms and calibration samples requires a lot of effort, especially in continuous water monitoring over large areas. We see great benefits on sensor networks enabling continuous, real-time monitoring, while data quality control and maintenance efforts highlight the need for tight collaboration between sensor and sensor network owners to decrease costs and increase the quality of the sensor data in large scale applications. PMID:22574050
GEOScan: A GEOScience Facility From Space
NASA Astrophysics Data System (ADS)
Dyrud, L. P.; Fentzke, J. T.; Anderson, B. J.; Bishop, R. L.; Bust, G. S.; Cahoy, K.; Erlandson, R. E.; Fish, C. S.; Gunter, B. C.; Hall, F. G.; Hilker, T.; Lorentz, S. R.; Mazur, J. E.; Murphy, S. D.; Mustard, J. F.; O'Brien, P. P.; Slagowski, S.; Trenberth, K. E.; Wiscombe, W. J.
2012-12-01
GEOScan is a proposed globally networked orbiting facility that will provide revolutionary, massively dense global geosciences observations. Major scientific research projects are typically conducted using two approaches: community facilities, or investigator led focused missions. GEOScan is a new concept in space science, blending the PI mission and community facility models: it is PI-led, but it carries sensors that are the result of a grass-roots competition, and, uniquely, it preserves open slots for sensors which are purposely not yet decided. The goal is threefold: first, to select sensors that maximize science value for the greatest number of scientific disciplines, second, to target science questions that cannot be answered without simultaneous global space-based measurements, and third to reap the cost advantages of scale manufacturing for space instrumentation. The relatively small size, mass, and power requirements of the GEOScan sensor suite would make it an ideal hosted payload aboard a global constellation of communication satellites, such as Iridium NEXT's 66-satellite constellation or as hosted small-sat payload. Each GEOScan sensor suite consists of 6 instruments: a Radiometer to measure Earth's total outgoing radiation; a GPS Compact Total Electron Content Sensor to image Earth's plasma environment and gravity field; a MicroCam Multispectral Imager to provide the first uniform, instantaneous image of Earth and measure global cloud cover, vegetation, land use, and bright aurora; a Radiation Belt Mapping System (dosimeter) to measure energetic electron and proton distributions; a Compact Earth Observing Spectrometer to measure aerosol-atmospheric composition and vegetation; and MEMS Accelerometers to deduce non-conservative forces aiding gravity and neutral drag studies. These instruments, employed in a constellation, can provide major breakthroughs in Earth and Geospace science, as well as offering a low-cost technology demonstration for operational weather, climate, and land-imaging.
Fiber optic sensors; Proceedings of the Meeting, Cannes, France, November 26, 27, 1985
NASA Technical Reports Server (NTRS)
Arditty, Herve J. (Editor); Jeunhomme, Luc B. (Editor)
1986-01-01
The conference presents papers on distributed sensors and sensor networks, signal processing and detection techniques, temperature measurements, chemical sensors, and the measurement of pressure, strain, and displacements. Particular attention is given to optical fiber distributed sensors and sensor networks, tactile sensing in robotics using an optical network and Z-plane techniques, and a spontaneous Raman temperature sensor. Other topics include coherence in optical fiber gyroscopes, a high bandwidth two-phase flow void fraction fiber optic sensor, and a fiber-optic dark-field microbend sensor.
Sensor Data Qualification Technique Applied to Gas Turbine Engines
NASA Technical Reports Server (NTRS)
Csank, Jeffrey T.; Simon, Donald L.
2013-01-01
This paper applies a previously developed sensor data qualification technique to a commercial aircraft engine simulation known as the Commercial Modular Aero-Propulsion System Simulation 40,000 (C-MAPSS40k). The sensor data qualification technique is designed to detect, isolate, and accommodate faulty sensor measurements. It features sensor networks, which group various sensors together and relies on an empirically derived analytical model to relate the sensor measurements. Relationships between all member sensors of the network are analyzed to detect and isolate any faulty sensor within the network.
Multistage Security Mechanism For Hybrid, Large-Scale Wireless Sensor Networks
2007-06-01
sensor network . Building on research in the areas of the wireless sensor networks (WSN) and the mobile ad hoc networks (MANET), this thesis proposes an...A wide area network consisting of ballistic missile defense satellites and terrestrial nodes can be viewed as a hybrid, large-scale mobile wireless
Sinkhole Avoidance Routing in Wireless Sensor Networks
2011-05-09
sensor network consists of individual sensor nodes that work cooperatively to collect and communicate environmental data. In a surveillance role, a WSN...Wireless sensor networks, or WSNs, are an emerging commercial technology that may have practical applications on the modern battlefield. A wireless
NASA Astrophysics Data System (ADS)
Palla, Gergely; Derenyi, Imre; Farkas, Illes J.; Vicsek, Tamas
2006-03-01
Most tasks in a cell are performed not by individual proteins, but by functional groups of proteins (either physically interacting with each other or associated in other ways). In gene (protein) association networks these groups show up as sets of densely connected nodes. In the yeast, Saccharomyces cerevisiae, known physically interacting groups of proteins (called protein complexes) strongly overlap: the total number of proteins contained by these complexes by far underestimates the sum of their sizes (2750 vs. 8932). Thus, most functional groups of proteins, both physically interacting and other, are likely to share many of their members with other groups. However, current algorithms searching for dense groups of nodes in networks usually exclude overlaps. With the aim to discover both novel functions of individual proteins and novel protein functional groups we combine in protein association networks (i) a search for overlapping dense subgraphs based on the Clique Percolation Method (CPM) (Palla, G., et.al. Nature 435, 814-818 (2005), http://angel.elte.hu/clustering), which explicitly allows for overlaps among the groups, and (ii) a verification and characterization of the identified groups of nodes (proteins) with the help of standard annotation databases listing known functions.
Extracting Communities from Complex Networks by the k-Dense Method
NASA Astrophysics Data System (ADS)
Saito, Kazumi; Yamada, Takeshi; Kazama, Kazuhiro
To understand the structural and functional properties of large-scale complex networks, it is crucial to efficiently extract a set of cohesive subnetworks as communities. There have been proposed several such community extraction methods in the literature, including the classical k-core decomposition method and, more recently, the k-clique based community extraction method. The k-core method, although computationally efficient, is often not powerful enough for uncovering a detailed community structure and it produces only coarse-grained and loosely connected communities. The k-clique method, on the other hand, can extract fine-grained and tightly connected communities but requires a substantial amount of computational load for large-scale complex networks. In this paper, we present a new notion of a subnetwork called k-dense, and propose an efficient algorithm for extracting k-dense communities. We applied our method to the three different types of networks assembled from real data, namely, from blog trackbacks, word associations and Wikipedia references, and demonstrated that the k-dense method could extract communities almost as efficiently as the k-core method, while the qualities of the extracted communities are comparable to those obtained by the k-clique method.
Decentralized Sensor Fusion for Ubiquitous Networking Robotics in Urban Areas
Sanfeliu, Alberto; Andrade-Cetto, Juan; Barbosa, Marco; Bowden, Richard; Capitán, Jesús; Corominas, Andreu; Gilbert, Andrew; Illingworth, John; Merino, Luis; Mirats, Josep M.; Moreno, Plínio; Ollero, Aníbal; Sequeira, João; Spaan, Matthijs T.J.
2010-01-01
In this article we explain the architecture for the environment and sensors that has been built for the European project URUS (Ubiquitous Networking Robotics in Urban Sites), a project whose objective is to develop an adaptable network robot architecture for cooperation between network robots and human beings and/or the environment in urban areas. The project goal is to deploy a team of robots in an urban area to give a set of services to a user community. This paper addresses the sensor architecture devised for URUS and the type of robots and sensors used, including environment sensors and sensors onboard the robots. Furthermore, we also explain how sensor fusion takes place to achieve urban outdoor execution of robotic services. Finally some results of the project related to the sensor network are highlighted. PMID:22294927
NASA Astrophysics Data System (ADS)
Bogena, H. R.; Huisman, S.; Rosenbaum, U.; Wuethen, A.; Vereecken, H.
2009-04-01
Wireless sensor network technology allows near real-time monitoring of soil properties with a high spatial and temporal resolution for observing hydrological processes in small watersheds. The novel wireless sensor network SoilNet uses the low-cost ZigBee radio network for communication and a hybrid topology with a mixture of underground end devices each wired to several soil sensors and aboveground router devices. The SoilNet sensor network consists of soil water content, salinity and temperature sensors attached to end devices by cables, router devices and a coordinator device. The end devices are buried in the soil and linked wirelessly with nearby aboveground router devices. This ZigBee network design considers channel errors, delays, packet losses, and power and topology constraints. In order to conserve battery power, a reactive routing protocol is used that determines a new route only when it is required. The sensor network is also able to react to external influences, e.g. the occurrence of precipitation. The SoilNet communicator, routing and end devices have been developed by the Forschungszentrum Juelich and will be marketed through external companies. Simultaneously, we have also developed a data management and visualisation system. Recently, a small forest catchment Wüstebach (27 ha) was instrumented with 50 end devices and more than 400 soil sensors in the frame of the TERENO-RUR hydrological observatory. We will present first results of this large sensor network both in terms of spatial-temporal variations in soil water content and the performance of the sensor network (e.g. network stability and power use).
Quantized Synchronization of Chaotic Neural Networks With Scheduled Output Feedback Control.
Wan, Ying; Cao, Jinde; Wen, Guanghui
In this paper, the synchronization problem of master-slave chaotic neural networks with remote sensors, quantization process, and communication time delays is investigated. The information communication channel between the master chaotic neural network and slave chaotic neural network consists of several remote sensors, with each sensor able to access only partial knowledge of output information of the master neural network. At each sampling instants, each sensor updates its own measurement and only one sensor is scheduled to transmit its latest information to the controller's side in order to update the control inputs for the slave neural network. Thus, such communication process and control strategy are much more energy-saving comparing with the traditional point-to-point scheme. Sufficient conditions for output feedback control gain matrix, allowable length of sampling intervals, and upper bound of network-induced delays are derived to ensure the quantized synchronization of master-slave chaotic neural networks. Lastly, Chua's circuit system and 4-D Hopfield neural network are simulated to validate the effectiveness of the main results.In this paper, the synchronization problem of master-slave chaotic neural networks with remote sensors, quantization process, and communication time delays is investigated. The information communication channel between the master chaotic neural network and slave chaotic neural network consists of several remote sensors, with each sensor able to access only partial knowledge of output information of the master neural network. At each sampling instants, each sensor updates its own measurement and only one sensor is scheduled to transmit its latest information to the controller's side in order to update the control inputs for the slave neural network. Thus, such communication process and control strategy are much more energy-saving comparing with the traditional point-to-point scheme. Sufficient conditions for output feedback control gain matrix, allowable length of sampling intervals, and upper bound of network-induced delays are derived to ensure the quantized synchronization of master-slave chaotic neural networks. Lastly, Chua's circuit system and 4-D Hopfield neural network are simulated to validate the effectiveness of the main results.
Wireless Sensor Network Radio Power Management and Simulation Models
2010-01-01
The Open Electrical & Electronic Engineering Journal, 2010, 4, 21-31 21 1874-1290/10 2010 Bentham Open Open Access Wireless Sensor Network Radio...Air Force Institute of Technology, Wright-Patterson AFB, OH, USA Abstract: Wireless sensor networks (WSNs) create a new frontier in collecting and...consumption. Keywords: Wireless sensor network , power management, energy-efficiency, medium access control (MAC), simulation pa- rameters. 1
Building SDN-Based Agricultural Vehicular Sensor Networks Based on Extended Open vSwitch.
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
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
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.
Research Trends in Wireless Visual Sensor Networks When Exploiting Prioritization
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
DE-Sync: A Doppler-Enhanced Time Synchronization for Mobile Underwater Sensor Networks.
Zhou, Feng; Wang, Qi; Nie, DongHu; Qiao, Gang
2018-05-25
Time synchronization is the foundation of cooperative work among nodes of underwater sensor networks; it takes a critical role in the research and application of underwater sensor networks. Although numerous time synchronization protocols have been proposed for terrestrial wireless sensor networks, they cannot be directly applied to underwater sensor networks. This is because most of them typically assume that the propagation delay among sensor nodes is negligible, which is not the case in underwater sensor networks. Time synchronization is mainly affected by a long propagation delay among sensor nodes due to the low propagation speed of acoustic signals. Furthermore, sensor nodes in underwater tend to experience some degree of mobility due to wind or ocean current, or some other nodes are on self-propelled vehicles, such as autonomous underwater vehicles (AUVs). In this paper, we propose a Doppler-enhanced time synchronization scheme for mobile underwater sensor networks, called DE-Sync. Our new scheme considers the effect of the clock skew during the process of estimating the Doppler scale factor and directly substitutes the Doppler scale factor into linear regression to achieve the estimation of the clock skew and offset. Simulation results show that DE-Sync outperforms existing time synchronization protocols in both accuracy and energy efficiency.
United States Air Force Summer Faculty Research Program. Management Report. Volume 1
1988-12-01
sensors , measure reaction characteristics of fuel and oxidizer at various inlet velocities and initial conditions. Application of spectroscopy, high... applications in armament systems. False signals caused by cloud, fog, and snow interfere with proper response of the sensors , and efforts to... sensor for this application have not been fully successful (1-18). Presence of dense clouds, fog, or snow will create false signals and will obscure
Bluetooth Roaming for Sensor Network System in Clinical Environment.
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.
Integrating legacy medical data sensors in a wireless network infrastucture.
Dembeyiotis, S; Konnis, G; Koutsouris, D
2005-01-01
In the process of developing a wireless networking solution to provide effective field-deployable communications and telemetry support for rescuers during major natural disasters, we are faced with the task of interfacing the multitude of medical and other legacy data collection sensors to the network grid. In this paper, we detail a number of solutions, with particular attention given to the issue of data security. The chosen implementation allows for sensor control and management from remote network locations, while the sensors can wirelessly transmit their data to nearby network nodes securely, utilizing the latest commercially available cryptography solutions. Initial testing validates the design choices, while the network-enabled sensors are being integrated in the overall wireless network security framework.
NASA Astrophysics Data System (ADS)
Xia, Y.; Tian, J.; d'Angelo, P.; Reinartz, P.
2018-05-01
3D reconstruction of plants is hard to implement, as the complex leaf distribution highly increases the difficulty level in dense matching. Semi-Global Matching has been successfully applied to recover the depth information of a scene, but may perform variably when different matching cost algorithms are used. In this paper two matching cost computation algorithms, Census transform and an algorithm using a convolutional neural network, are tested for plant reconstruction based on Semi-Global Matching. High resolution close-range photogrammetric images from a handheld camera are used for the experiment. The disparity maps generated based on the two selected matching cost methods are comparable with acceptable quality, which shows the good performance of Census and the potential of neural networks to improve the dense matching.
Open-WiSe: A Solar Powered Wireless Sensor Network Platform
González, Apolinar; Aquino, Raúl; Mata, Walter; Ochoa, Alberto; Saldaña, Pedro; Edwards, Arthur
2012-01-01
Because battery-powered nodes are required in wireless sensor networks and energy consumption represents an important design consideration, alternate energy sources are needed to provide more effective and optimal function. The main goal of this work is to present an energy harvesting wireless sensor network platform, the Open Wireless Sensor node (WiSe). The design and implementation of the solar powered wireless platform is described including the hardware architecture, firmware, and a POSIX Real-Time Kernel. A sleep and wake up strategy was implemented to prolong the lifetime of the wireless sensor network. This platform was developed as a tool for researchers investigating Wireless sensor network or system integrators. PMID:22969396
NASA Astrophysics Data System (ADS)
Tosi, Daniele; Schena, Emiliano; Molardi, Carlo; Korganbayev, Sanzhar
2018-07-01
One of the current frontier of optical fiber sensors, and a unique asset of this sensing technology is the possibility to use a whole optical fiber, or optical fiber device, as a sensor. This solution allows shifting the whole sensing paradigm, from the measurement of a single physical parameter (such as temperature, strain, vibrations, pressure) to the measurement of a spatial distribution, or profiling, of a physical parameter along the fiber length. In the recent years, several technologies are achieving this task with unprecedentedly narrow spatial resolution, ranging from the sub-millimeter to the centimeter-level. In this work, we review the main fiber optic sensing technologies that achieve a narrow spatial resolution: Fiber Bragg Grating (FBG) dense arrays, chirped FBG (CFBG) sensors, optical frequency domain reflectometry (OFDR) based on either Rayleigh scattering or reflective elements, and microwave photonics (MWP). In the second part of the work, we present the impact of spatially dense fiber optic sensors in biomedical applications, where they find the main impact, presenting the key results obtained in thermo-therapies monitoring, high-resolution diagnostic, catheters monitoring, smart textiles, and other emerging applicative fields.
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
Source Localization Using Wireless Sensor Networks
2006-06-01
performance of the hybrid SI/ML estimation method. A wireless sensor network is simulated in NS-2 to study the network throughput, delay and jitter...indicate that the wireless sensor network has low delay and can support fast information exchange needed in counter-sniper applications.
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.
NASA Astrophysics Data System (ADS)
Rainieri, Carlo; Song, Yi; Fabbrocino, Giovanni; Schulz, Mark J.; Shanov, Vesselin
2013-08-01
Degradation phenomena can affect civil structures over their lifespan. The recent advances in nanotechnology and sensing allow to monitor the behaviour of a structure, assess its performance and identify damage at an early stage. Thus, maintenance actions can be carried out in a timely manner, improving structural reliability and safety. Structural Health Monitoring (SHM) is traditionally performed at a global level, with a limited number of sensors distributed over a relatively large area of a structure. Thus, only major damage conditions are detectable. Dense sensor networks and innovative structural neural systems, reproducing the structure and the function of the human nervous system, may overcome this drawback of current SHM systems. Miniaturization and embedment are key requirements for successful implementation of structural neural systems. Carbon nanotubes (CNTs) can play an attractive role in the development of embedded sensors and smart structural materials, since they can provide to traditional cement based materials both structural capability and measurable response to applied stresses, strains, cracks and other flaws. In this paper investigations about CNT/cement composites and their self-sensing capabilities are summarized and critically revised. The analysis of available experimental results and theoretical developments provides useful design criteria for the fabrication of CNT/cement composites optimized for SHM applications in civil engineering. Specific attention is paid to the opportunities provided by new RF plasma technologies for the functionalization of CNTs in view of sensor development and SHM applications.
Ranging through Gabor logons-a consistent, hierarchical approach.
Chang, C; Chatterjee, S
1993-01-01
In this work, the correspondence problem in stereo vision is handled by matching two sets of dense feature vectors. Inspired by biological evidence, these feature vectors are generated by a correlation between a bank of Gabor sensors and the intensity image. The sensors consist of two-dimensional Gabor filters at various scales (spatial frequencies) and orientations, which bear close resemblance to the receptive field profiles of simple V1 cells in visual cortex. A hierarchical, stochastic relaxation method is then used to obtain the dense stereo disparities. Unlike traditional hierarchical methods for stereo, feature based hierarchical processing yields consistent disparities. To avoid false matchings due to static occlusion, a dual matching, based on the imaging geometry, is used.
Geographically distributed environmental sensor system
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.
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.
Probabilistic QoS Analysis In Wireless Sensor Networks
2012-04-01
and A.O. Fapojuwo. TDMA scheduling with optimized energy efficiency and minimum delay in clustered wireless sensor networks . IEEE Trans. on Mobile...Research Computer Science and Engineering, Department of 5-1-2012 Probabilistic QoS Analysis in Wireless Sensor Networks Yunbo Wang University of...Wang, Yunbo, "Probabilistic QoS Analysis in Wireless Sensor Networks " (2012). Computer Science and Engineering: Theses, Dissertations, and Student
RF Characteristics of Mica-Z Wireless Sensor Network Motes
2006-03-01
MICA-Z WIRELESS SENSOR NETWORK MOTES by Swee Jin Koh March 2006 Thesis Advisor: Gurminder Singh Thesis Co-Advisor: John C...Mica-Z Wireless Sensor Network Motes 6. AUTHOR(S) : Swee Jin Koh 5. FUNDING NUMBERS 7. PERFORMING ORGANIZATION NAME(S) AND ADDRESS(ES) Naval...ad-hoc deployment. 15. NUMBER OF PAGES 83 14. SUBJECT TERMS: Wireless Sensor Network 16. PRICE CODE 17. SECURITY CLASSIFICATION OF
Path Calculation and Packet Translation for UAV Surveillance in Support of Wireless Sensor Networks
2006-09-01
AND PACKET TRANSLATION FOR UAV SURVEILLANCE IN SUPPORT OF WIRELESS SENSOR NETWORKS by Stephen Schall September 2006 Thesis Advisor...Calculation and Packet Translation for UAV Surveillance in Support of Wireless Sensor Networks 6. AUTHOR(S) Stephen Schall 5. FUNDING NUMBERS 7...200 words) Wireless Sensor Networks (WSNs) are a relatively new technology with many potential applications, including military and
Wireless Sensor Network With Geolocation
2006-11-01
WIRELESS SENSOR NETWORK WITH GEOLOCATION James Silverstrim and Roderick Passmore Innovative Wireless Technologies Forest, VA 24551 Dr...TYPE N/A 3. DATES COVERED - 4. TITLE AND SUBTITLE Wireless Sensor Network With Geolocation 5a. CONTRACT NUMBER 5b. GRANT NUMBER 5c. PROGRAM...Locationing in distributed ad-hoc wireless sensor networks ”, IEEE ICASSP, May 2001. D. W. Hanson, Fundamentals of Two-Way Time Transfer by Satellite
Performance Evaluation of a Routing Protocol in Wireless Sensor Network
2005-12-01
OF A ROUTING PROTOCOL IN WIRELESS SENSOR NETWORKS by Cheng Kiat Amos, Teo December 2005 Thesis Advisors: Gurminder Singh John C...Evaluation of a Routing Protocol in Wireless Sensor Network 6. AUTHOR(S) Cheng Kiat Amos, Teo 5. FUNDING NUMBERS 7. PERFORMING ORGANIZATION NAME(S...need to be strategically positioned and have topologies engineered. As such, recent research into wireless sensor networks has attracted great
2009-03-01
IN WIRELESS SENSOR NETWORKS WITH RANDOMLY DISTRIBUTED ELEMENTS UNDER MULTIPATH PROPAGATION CONDITIONS by Georgios Tsivgoulis March 2009...COVERED Engineer’s Thesis 4. TITLE Source Localization in Wireless Sensor Networks with Randomly Distributed Elements under Multipath Propagation...the non-line-of-sight information. 15. NUMBER OF PAGES 111 14. SUBJECT TERMS Wireless Sensor Network , Direction of Arrival, DOA, Random
Networked sensors for the combat forces
NASA Astrophysics Data System (ADS)
Klager, Gene
2004-11-01
Real-time and detailed information is critical to the success of ground combat forces. Current manned reconnaissance, surveillance, and target acquisition (RSTA) capabilities are not sufficient to cover battlefield intelligence gaps, provide Beyond-Line-of-Sight (BLOS) targeting, and the ambush avoidance information necessary for combat forces operating in hostile situations, complex terrain, and conducting military operations in urban terrain. This paper describes a current US Army program developing advanced networked unmanned/unattended sensor systems to survey these gaps and provide the Commander with real-time, pertinent information. Networked Sensors for the Combat Forces plans to develop and demonstrate a new generation of low cost distributed unmanned sensor systems organic to the RSTA Element. Networked unmanned sensors will provide remote monitoring of gaps, will increase a unit"s area of coverage, and will provide the commander organic assets to complete his Battlefield Situational Awareness (BSA) picture for direct and indirect fire weapons, early warning, and threat avoidance. Current efforts include developing sensor packages for unmanned ground vehicles, small unmanned aerial vehicles, and unattended ground sensors using advanced sensor technologies. These sensors will be integrated with robust networked communications and Battle Command tools for mission planning, intelligence "reachback", and sensor data management. The network architecture design is based on a model that identifies a three-part modular design: 1) standardized sensor message protocols, 2) Sensor Data Management, and 3) Service Oriented Architecture. This simple model provides maximum flexibility for data exchange, information management and distribution. Products include: Sensor suites optimized for unmanned platforms, stationary and mobile versions of the Sensor Data Management Center, Battle Command planning tools, networked communications, and sensor management software. Details of these products and recent test results will be presented.
Underwater Sensor Network Redeployment Algorithm Based on Wolf Search
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
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.
Active Self-Testing Noise Measurement Sensors for Large-Scale Environmental Sensor Networks
Domínguez, Federico; Cuong, Nguyen The; Reinoso, Felipe; Touhafi, Abdellah; Steenhaut, Kris
2013-01-01
Large-scale noise pollution sensor networks consist of hundreds of spatially distributed microphones that measure environmental noise. These networks provide historical and real-time environmental data to citizens and decision makers and are therefore a key technology to steer environmental policy. However, the high cost of certified environmental microphone sensors render large-scale environmental networks prohibitively expensive. Several environmental network projects have started using off-the-shelf low-cost microphone sensors to reduce their costs, but these sensors have higher failure rates and produce lower quality data. To offset this disadvantage, we developed a low-cost noise sensor that actively checks its condition and indirectly the integrity of the data it produces. The main design concept is to embed a 13 mm speaker in the noise sensor casing and, by regularly scheduling a frequency sweep, estimate the evolution of the microphone's frequency response over time. This paper presents our noise sensor's hardware and software design together with the results of a test deployment in a large-scale environmental network in Belgium. Our middle-range-value sensor (around €50) effectively detected all experienced malfunctions, in laboratory tests and outdoor deployments, with a few false positives. Future improvements could further lower the cost of our sensor below €10. PMID:24351634
ERIC Educational Resources Information Center
McNeal, McKenzie, III.
2012-01-01
Current networking architectures and communication protocols used for Wireless Sensor Networks (WSNs) have been designed to be energy efficient, low latency, and long network lifetime. One major issue that must be addressed is the security in data communication. Due to the limited capabilities of low cost and small sized sensor nodes, designing…
Wireless Cooperative Networks: Self-Configuration and Optimization
2011-09-09
TERMS wireless sensor networks , wireless cooperative networks, resource optimization, ultra-wideband, localization, ranging 16. SECURITY...Communications We consider two prevalent relay protocols for wireless sensor networks : decode-and-forward (DF) and amplify-and-forward (AF). To... sensor networks where each node may have its own sensing data to transmit, since they can maximally conserve energy while helping others as relays
A Survey on Security and Privacy in Emerging Sensor Networks: From Viewpoint of Close-Loop.
Zhang, Lifu; Zhang, Heng
2016-03-26
Nowadays, as the next generation sensor networks, Cyber-Physical Systems (CPSs) refer to the complex networked systems that have both physical subsystems and cyber components, and the information flow between different subsystems and components is across a communication network, which forms a closed-loop. New generation sensor networks are found in a growing number of applications and have received increasing attention from many inter-disciplines. Opportunities and challenges in the design, analysis, verification and validation of sensor networks co-exists, among which security and privacy are two important ingredients. This paper presents a survey on some recent results in the security and privacy aspects of emerging sensor networks from the viewpoint of the closed-loop. This paper also discusses several future research directions under these two umbrellas.
Autonomous distributed self-organization for mobile wireless sensor networks.
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.
NASA Astrophysics Data System (ADS)
Forcier, Bob
2003-09-01
This paper describes a digital-ultrasonic ground network, which forms an unique "unattended mote sensor system" for monitoring the environment, personnel, facilities, vehicles, power generation systems or aircraft in Counter-Terrorism, Force Protection, Prognostic Health Monitoring (PHM) and other ground applications. Unattended wireless smart sensor/tags continuously monitor the environment and provide alerts upon changes or disruptions to the environment. These wireless smart sensor/tags are networked utilizing ultrasonic wireless motes, hybrid RF/Ultrasonic Network Nodes and Base Stations. The network is monitored continuously with a 24/7 remote and secure monitoring system. This system utilizes physical objects such as a vehicle"s structure or a building to provide the media for two way secure communication of key metrics and sensor data and eliminates the "blind spots" that are common in RF solutions because of structural elements of buildings, etc. The digital-ultrasonic sensors have networking capability and a 32-bit identifier, which provide a platform for a robust data acquisition (DAQ) for a large amount of sensors. In addition, the network applies a unique "signature" of the environment by comparing sensor-to-sensor data to pick up on minute changes, which would signal an invasion of unknown elements or signal a potential tampering in equipment or facilities. The system accommodates satellite and other secure network uplinks in either RF or UWB protocols. The wireless sensors can be dispersed by ground or air maneuvers. In addition, the sensors can be incorporated into the structure or surfaces of vehicles, buildings, or clothing of field personnel.
NASA Astrophysics Data System (ADS)
Yang, Xue; Sun, Hao; Fu, Kun; Yang, Jirui; Sun, Xian; Yan, Menglong; Guo, Zhi
2018-01-01
Ship detection has been playing a significant role in the field of remote sensing for a long time but it is still full of challenges. The main limitations of traditional ship detection methods usually lie in the complexity of application scenarios, the difficulty of intensive object detection and the redundancy of detection region. In order to solve such problems above, we propose a framework called Rotation Dense Feature Pyramid Networks (R-DFPN) which can effectively detect ship in different scenes including ocean and port. Specifically, we put forward the Dense Feature Pyramid Network (DFPN), which is aimed at solving the problem resulted from the narrow width of the ship. Compared with previous multi-scale detectors such as Feature Pyramid Network (FPN), DFPN builds the high-level semantic feature-maps for all scales by means of dense connections, through which enhances the feature propagation and encourages the feature reuse. Additionally, in the case of ship rotation and dense arrangement, we design a rotation anchor strategy to predict the minimum circumscribed rectangle of the object so as to reduce the redundant detection region and improve the recall. Furthermore, we also propose multi-scale ROI Align for the purpose of maintaining the completeness of semantic and spatial information. Experiments based on remote sensing images from Google Earth for ship detection show that our detection method based on R-DFPN representation has a state-of-the-art performance.
NASA Astrophysics Data System (ADS)
Wang, Yubao; Zhu, Zhaohui; Wang, Lu; Bai, Jian
2016-05-01
A novel GPON-oriented sensing data digitalization system is proposed to achieve remote monitoring of fiber grating sensing networks utilizing existing optical communication networks in some harsh environments. In which, Quick digitalization of sensing information obtained from the reflected lightwaves by fiber Bragg grating (FBG) sensor is realized, and a novel frame format of sensor signal is designed to suit for public transport so as to facilitate sensor monitoring center to receive and analyze the sensor data. The delay effect, identification method of the sensor data, and various interference factors which influence the sensor data to be correctly received are analyzed. The system simulation is carried out with OptiSystem/Matlab co-simulation approach. The theoretical analysis and simulation results verify the feasibility of the integration of the sensor network and communication network.
Bhanot, Gyan [Princeton, NJ; Blumrich, Matthias A [Ridgefield, CT; Chen, Dong [Croton On Hudson, NY; Coteus, Paul W [Yorktown Heights, NY; Gara, Alan G [Mount Kisco, NY; Giampapa, Mark E [Irvington, NY; Heidelberger, Philip [Cortlandt Manor, NY; Steinmacher-Burow, Burkhard D [Mount Kisco, NY; Takken, Todd E [Mount Kisco, NY; Vranas, Pavlos M [Bedford Hills, NY
2009-09-08
Class network routing is implemented in a network such as a computer network comprising a plurality of parallel compute processors at nodes thereof. Class network routing allows a compute processor to broadcast a message to a range (one or more) of other compute processors in the computer network, such as processors in a column or a row. Normally this type of operation requires a separate message to be sent to each processor. With class network routing pursuant to the invention, a single message is sufficient, which generally reduces the total number of messages in the network as well as the latency to do a broadcast. Class network routing is also applied to dense matrix inversion algorithms on distributed memory parallel supercomputers with hardware class function (multicast) capability. This is achieved by exploiting the fact that the communication patterns of dense matrix inversion can be served by hardware class functions, which results in faster execution times.
Distributed Detection with Collisions in a Random, Single-Hop Wireless Sensor Network
2013-05-26
public release; distribution is unlimited. Distributed detection with collisions in a random, single-hop wireless sensor network The views, opinions...1274 2 ABSTRACT Distributed detection with collisions in a random, single-hop wireless sensor network Report Title We consider the problem of... WIRELESS SENSOR NETWORK Gene T. Whipps?† Emre Ertin† Randolph L. Moses† ?U.S. Army Research Laboratory, Adelphi, MD 20783 †The Ohio State University
A Study on Wireless Charging for Prolonging the Lifetime of Wireless Sensor Networks.
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.
A Novel Characterization of Amalgamated Networks in Natural Systems
Barranca, Victor J.; Zhou, Douglas; Cai, David
2015-01-01
Densely-connected networks are prominent among natural systems, exhibiting structural characteristics often optimized for biological function. To reveal such features in highly-connected networks, we introduce a new network characterization determined by a decomposition of network-connectivity into low-rank and sparse components. Based on these components, we discover a new class of networks we define as amalgamated networks, which exhibit large functional groups and dense connectivity. Analyzing recent experimental findings on cerebral cortex, food-web, and gene regulatory networks, we establish the unique importance of amalgamated networks in fostering biologically advantageous properties, including rapid communication among nodes, structural stability under attacks, and separation of network activity into distinct functional modules. We further observe that our network characterization is scalable with network size and connectivity, thereby identifying robust features significant to diverse physical systems, which are typically undetectable by conventional characterizations of connectivity. We expect that studying the amalgamation properties of biological networks may offer new insights into understanding their structure-function relationships. PMID:26035066
Design and evaluation of a wireless sensor network based aircraft strength testing system.
Wu, Jian; Yuan, Shenfang; Zhou, Genyuan; Ji, Sai; Wang, Zilong; Wang, Yang
2009-01-01
The verification of aerospace structures, including full-scale fatigue and static test programs, is essential for structure strength design and evaluation. However, the current overall ground strength testing systems employ a large number of wires for communication among sensors and data acquisition facilities. The centralized data processing makes test programs lack efficiency and intelligence. Wireless sensor network (WSN) technology might be expected to address the limitations of cable-based aeronautical ground testing systems. This paper presents a wireless sensor network based aircraft strength testing (AST) system design and its evaluation on a real aircraft specimen. In this paper, a miniature, high-precision, and shock-proof wireless sensor node is designed for multi-channel strain gauge signal conditioning and monitoring. A cluster-star network topology protocol and application layer interface are designed in detail. To verify the functionality of the designed wireless sensor network for strength testing capability, a multi-point WSN based AST system is developed for static testing of a real aircraft undercarriage. Based on the designed wireless sensor nodes, the wireless sensor network is deployed to gather, process, and transmit strain gauge signals and monitor results under different static test loads. This paper shows the efficiency of the wireless sensor network based AST system, compared to a conventional AST system.
Design and Evaluation of a Wireless Sensor Network Based Aircraft Strength Testing System
Wu, Jian; Yuan, Shenfang; Zhou, Genyuan; Ji, Sai; Wang, Zilong; Wang, Yang
2009-01-01
The verification of aerospace structures, including full-scale fatigue and static test programs, is essential for structure strength design and evaluation. However, the current overall ground strength testing systems employ a large number of wires for communication among sensors and data acquisition facilities. The centralized data processing makes test programs lack efficiency and intelligence. Wireless sensor network (WSN) technology might be expected to address the limitations of cable-based aeronautical ground testing systems. This paper presents a wireless sensor network based aircraft strength testing (AST) system design and its evaluation on a real aircraft specimen. In this paper, a miniature, high-precision, and shock-proof wireless sensor node is designed for multi-channel strain gauge signal conditioning and monitoring. A cluster-star network topology protocol and application layer interface are designed in detail. To verify the functionality of the designed wireless sensor network for strength testing capability, a multi-point WSN based AST system is developed for static testing of a real aircraft undercarriage. Based on the designed wireless sensor nodes, the wireless sensor network is deployed to gather, process, and transmit strain gauge signals and monitor results under different static test loads. This paper shows the efficiency of the wireless sensor network based AST system, compared to a conventional AST system. PMID:22408521
An Outline of Data Aggregation Security in Heterogeneous Wireless Sensor Networks.
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.
Chimera-like states in structured heterogeneous networks
NASA Astrophysics Data System (ADS)
Li, Bo; Saad, David
2017-04-01
Chimera-like states are manifested through the coexistence of synchronous and asynchronous dynamics and have been observed in various systems. To analyze the role of network topology in giving rise to chimera-like states, we study a heterogeneous network model comprising two groups of nodes, of high and low degrees of connectivity. The architecture facilitates the analysis of the system, which separates into a densely connected coherent group of nodes, perturbed by their sparsely connected drifting neighbors. It describes a synchronous behavior of the densely connected group and scaling properties of the induced perturbations.
A Survey on Virtualization of Wireless Sensor Networks
Islam, Md. Motaharul; Hassan, Mohammad Mehedi; Lee, Ga-Won; Huh, Eui-Nam
2012-01-01
Wireless Sensor Networks (WSNs) are gaining tremendous importance thanks to their broad range of commercial applications such as in smart home automation, health-care and industrial automation. In these applications multi-vendor and heterogeneous sensor nodes are deployed. Due to strict administrative control over the specific WSN domains, communication barriers, conflicting goals and the economic interests of different WSN sensor node vendors, it is difficult to introduce a large scale federated WSN. By allowing heterogeneous sensor nodes in WSNs to coexist on a shared physical sensor substrate, virtualization in sensor network may provide flexibility, cost effective solutions, promote diversity, ensure security and increase manageability. This paper surveys the novel approach of using the large scale federated WSN resources in a sensor virtualization environment. Our focus in this paper is to introduce a few design goals, the challenges and opportunities of research in the field of sensor network virtualization as well as to illustrate a current status of research in this field. This paper also presents a wide array of state-of-the art projects related to sensor network virtualization. PMID:22438759
A survey on virtualization of Wireless Sensor Networks.
Islam, Md Motaharul; Hassan, Mohammad Mehedi; Lee, Ga-Won; Huh, Eui-Nam
2012-01-01
Wireless Sensor Networks (WSNs) are gaining tremendous importance thanks to their broad range of commercial applications such as in smart home automation, health-care and industrial automation. In these applications multi-vendor and heterogeneous sensor nodes are deployed. Due to strict administrative control over the specific WSN domains, communication barriers, conflicting goals and the economic interests of different WSN sensor node vendors, it is difficult to introduce a large scale federated WSN. By allowing heterogeneous sensor nodes in WSNs to coexist on a shared physical sensor substrate, virtualization in sensor network may provide flexibility, cost effective solutions, promote diversity, ensure security and increase manageability. This paper surveys the novel approach of using the large scale federated WSN resources in a sensor virtualization environment. Our focus in this paper is to introduce a few design goals, the challenges and opportunities of research in the field of sensor network virtualization as well as to illustrate a current status of research in this field. This paper also presents a wide array of state-of-the art projects related to sensor network virtualization.
NASA Astrophysics Data System (ADS)
Assendelft, Rick; van Meerveld, Ilja; Seibert, Jan
2017-04-01
Streams are dynamic features in the landscape. The flowing stream network expands and contracts, connects and disconnects in response to rainfall events and seasonal changes in catchment wetness. Sections of the river system that experience these wet and dry cycles are often referred to as temporary streams. Temporary streams are abundant and widely distributed freshwater ecosystems. They account for more than half of the total length of the global stream network, are unique habitats and form important hydrological and ecological links between the uplands and perennial streams. However, temporary streams have been largely unstudied, especially in mountainous headwater catchments. The dynamic character of these systems makes it difficult to monitor them. We describe a low-cost, do-it-yourself strategy to monitor the occurrence of water and flow in temporary streams. We evaluate this strategy in two headwater catchments in Switzerland. The low cost sensor network consists of electrical resistivity sensors, water level switches, temperature sensors and flow sensors. These sensors are connected to Arduino microcontrollers and data loggers, which log the data every 5 minutes. The data from the measurement network are compared with observations (mapping of the temporary stream network) as well as time lapse camera data to evaluate the performance of the sensors. We look at how frequently the output of the sensors (presence and absence of water from the ER and water level data, and flow or no-flow from the flow sensors) corresponds to the observed channel state. This is done for each sensor, per sub-catchment, per precipitation event and per sensor location to determine the best sensor combination to monitor temporary streams in mountainous catchments and in which situation which sensor combination works best. The preliminary results show that the sensors and monitoring network work well. The data from the sensors corresponds with the observations and provides information on the expansion of the stream network pattern.
Energy Efficient Cluster Based Scheduling Scheme for Wireless Sensor Networks
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
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
TinyOS-based quality of service management in wireless sensor networks
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.
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
SOUNET: Self-Organized Underwater Wireless Sensor Network.
Kim, Hee-Won; Cho, Ho-Shin
2017-02-02
In this paper, we propose an underwater wireless sensor network (UWSN) named SOUNET where sensor nodes form and maintain a tree-topological network for data gathering in a self-organized manner. After network topology discovery via packet flooding, the sensor nodes consistently update their parent node to ensure the best connectivity by referring to the timevarying neighbor tables. Such a persistent and self-adaptive method leads to high network connectivity without any centralized control, even when sensor nodes are added or unexpectedly lost. Furthermore, malfunctions that frequently happen in self-organized networks such as node isolation and closed loop are resolved in a simple way. Simulation results show that SOUNET outperforms other conventional schemes in terms of network connectivity, packet delivery ratio (PDR), and energy consumption throughout the network. In addition, we performed an experiment at the Gyeongcheon Lake in Korea using commercial underwater modems to verify that SOUNET works well in a real environment.
SOUNET: Self-Organized Underwater Wireless Sensor Network
Kim, Hee-won; Cho, Ho-Shin
2017-01-01
In this paper, we propose an underwater wireless sensor network (UWSN) named SOUNET where sensor nodes form and maintain a tree-topological network for data gathering in a self-organized manner. After network topology discovery via packet flooding, the sensor nodes consistently update their parent node to ensure the best connectivity by referring to the time-varying neighbor tables. Such a persistent and self-adaptive method leads to high network connectivity without any centralized control, even when sensor nodes are added or unexpectedly lost. Furthermore, malfunctions that frequently happen in self-organized networks such as node isolation and closed loop are resolved in a simple way. Simulation results show that SOUNET outperforms other conventional schemes in terms of network connectivity, packet delivery ratio (PDR), and energy consumption throughout the network. In addition, we performed an experiment at the Gyeongcheon Lake in Korea using commercial underwater modems to verify that SOUNET works well in a real environment. PMID:28157164
Autonomous vision networking: miniature wireless sensor networks with imaging technology
NASA Astrophysics Data System (ADS)
Messinger, Gioia; Goldberg, Giora
2006-09-01
The recent emergence of integrated PicoRadio technology, the rise of low power, low cost, System-On-Chip (SOC) CMOS imagers, coupled with the fast evolution of networking protocols and digital signal processing (DSP), created a unique opportunity to achieve the goal of deploying large-scale, low cost, intelligent, ultra-low power distributed wireless sensor networks for the visualization of the environment. Of all sensors, vision is the most desired, but its applications in distributed sensor networks have been elusive so far. Not any more. The practicality and viability of ultra-low power vision networking has been proven and its applications are countless, from security, and chemical analysis to industrial monitoring, asset tracking and visual recognition, vision networking represents a truly disruptive technology applicable to many industries. The presentation discusses some of the critical components and technologies necessary to make these networks and products affordable and ubiquitous - specifically PicoRadios, CMOS imagers, imaging DSP, networking and overall wireless sensor network (WSN) system concepts. The paradigm shift, from large, centralized and expensive sensor platforms, to small, low cost, distributed, sensor networks, is possible due to the emergence and convergence of a few innovative technologies. Avaak has developed a vision network that is aided by other sensors such as motion, acoustic and magnetic, and plans to deploy it for use in military and commercial applications. In comparison to other sensors, imagers produce large data files that require pre-processing and a certain level of compression before these are transmitted to a network server, in order to minimize the load on the network. Some of the most innovative chemical detectors currently in development are based on sensors that change color or pattern in the presence of the desired analytes. These changes are easily recorded and analyzed by a CMOS imager and an on-board DSP processor. Image processing at the sensor node level may also be required for applications in security, asset management and process control. Due to the data bandwidth requirements posed on the network by video sensors, new networking protocols or video extensions to existing standards (e.g. Zigbee) are required. To this end, Avaak has designed and implemented an ultra-low power networking protocol designed to carry large volumes of data through the network. The low power wireless sensor nodes that will be discussed include a chemical sensor integrated with a CMOS digital camera, a controller, a DSP processor and a radio communication transceiver, which enables relaying of an alarm or image message, to a central station. In addition to the communications, identification is very desirable; hence location awareness will be later incorporated to the system in the form of Time-Of-Arrival triangulation, via wide band signaling. While the wireless imaging kernel already exists specific applications for surveillance and chemical detection are under development by Avaak, as part of a co-founded program from ONR and DARPA. Avaak is also designing vision networks for commercial applications - some of which are undergoing initial field tests.
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
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.
Self-localization of wireless sensor networks using self-organizing maps
NASA Astrophysics Data System (ADS)
Ertin, Emre; Priddy, Kevin L.
2005-03-01
Recently there has been a renewed interest in the notion of deploying large numbers of networked sensors for applications ranging from environmental monitoring to surveillance. In a typical scenario a number of sensors are distributed in a region of interest. Each sensor is equipped with sensing, processing and communication capabilities. The information gathered from the sensors can be used to detect, track and classify objects of interest. For a number of locations the sensors location is crucial in interpreting the data collected from those sensors. Scalability requirements dictate sensor nodes that are inexpensive devices without a dedicated localization hardware such as GPS. Therefore the network has to rely on information collected within the network to self-localize. In the literature a number of algorithms has been proposed for network localization which uses measurements informative of range, angle, proximity between nodes. Recent work by Patwari and Hero relies on sensor data without explicit range estimates. The assumption is that the correlation structure in the data is a monotone function of the intersensor distances. In this paper we propose a new method based on unsupervised learning techniques to extract location information from the sensor data itself. We consider a grid consisting of virtual nodes and try to fit grid in the actual sensor network data using the method of self organizing maps. Then known sensor network geometry can be used to rotate and scale the grid to a global coordinate system. Finally, we illustrate how the virtual nodes location information can be used to track a target.
Wireless Sensor Networks: Monitoring and Control
DOE Office of Scientific and Technical Information (OSTI.GOV)
Hastbacka, Mildred; Ponoum, Ratcharit; Bouza, Antonio
2013-05-31
The article discusses wireless sensor technologies for building energy monitoring and control. This article, also, addresses wireless sensor networks as well as benefits and challenges of using wireless sensors. The energy savings and market potential of wireless sensors are reviewed.
Dhamodharan, Udaya Suriya Raj Kumar; Vayanaperumal, Rajamani
2015-01-01
Wireless sensor networks are highly indispensable for securing network protection. Highly critical attacks of various kinds have been documented in wireless sensor network till now by many researchers. The Sybil attack is a massive destructive attack against the sensor network where numerous genuine identities with forged identities are used for getting an illegal entry into a network. Discerning the Sybil attack, sinkhole, and wormhole attack while multicasting is a tremendous job in wireless sensor network. Basically a Sybil attack means a node which pretends its identity to other nodes. Communication to an illegal node results in data loss and becomes dangerous in the network. The existing method Random Password Comparison has only a scheme which just verifies the node identities by analyzing the neighbors. A survey was done on a Sybil attack with the objective of resolving this problem. The survey has proposed a combined CAM-PVM (compare and match-position verification method) with MAP (message authentication and passing) for detecting, eliminating, and eventually preventing the entry of Sybil nodes in the network. We propose a scheme of assuring security for wireless sensor network, to deal with attacks of these kinds in unicasting and multicasting.
Dhamodharan, Udaya Suriya Raj Kumar; Vayanaperumal, Rajamani
2015-01-01
Wireless sensor networks are highly indispensable for securing network protection. Highly critical attacks of various kinds have been documented in wireless sensor network till now by many researchers. The Sybil attack is a massive destructive attack against the sensor network where numerous genuine identities with forged identities are used for getting an illegal entry into a network. Discerning the Sybil attack, sinkhole, and wormhole attack while multicasting is a tremendous job in wireless sensor network. Basically a Sybil attack means a node which pretends its identity to other nodes. Communication to an illegal node results in data loss and becomes dangerous in the network. The existing method Random Password Comparison has only a scheme which just verifies the node identities by analyzing the neighbors. A survey was done on a Sybil attack with the objective of resolving this problem. The survey has proposed a combined CAM-PVM (compare and match-position verification method) with MAP (message authentication and passing) for detecting, eliminating, and eventually preventing the entry of Sybil nodes in the network. We propose a scheme of assuring security for wireless sensor network, to deal with attacks of these kinds in unicasting and multicasting. PMID:26236773
Picozzi, Matteo; Milkereit, Claus; Parolai, Stefano; Jaeckel, Karl-Heinz; Veit, Ingo; Fischer, Joachim; Zschau, Jochen
2010-01-01
Over the last few years, the analysis of seismic noise recorded by two dimensional arrays has been confirmed to be capable of deriving the subsoil shear-wave velocity structure down to several hundred meters depth. In fact, using just a few minutes of seismic noise recordings and combining this with the well known horizontal-to-vertical method, it has also been shown that it is possible to investigate the average one dimensional velocity structure below an array of stations in urban areas with a sufficient resolution to depths that would be prohibitive with active source array surveys, while in addition reducing the number of boreholes required to be drilled for site-effect analysis. However, the high cost of standard seismological instrumentation limits the number of sensors generally available for two-dimensional array measurements (i.e., of the order of 10), limiting the resolution in the estimated shear-wave velocity profiles. Therefore, new themes in site-effect estimation research by two-dimensional arrays involve the development and application of low-cost instrumentation, which potentially allows the performance of dense-array measurements, and the development of dedicated signal-analysis procedures for rapid and robust estimation of shear-wave velocity profiles. In this work, we present novel low-cost wireless instrumentation for dense two-dimensional ambient seismic noise array measurements that allows the real–time analysis of the surface-wavefield and the rapid estimation of the local shear-wave velocity structure for site response studies. We first introduce the general philosophy of the new system, as well as the hardware and software that forms the novel instrument, which we have tested in laboratory and field studies. PMID:22319298
Topology Optimization for Energy Management in Underwater Sensor Networks
2015-02-01
1 To appear in International Journal of Control as a regular paper Topology Optimization for Energy Management in Underwater Sensor Networks ⋆ Devesh...K. Jha1 Thomas A. Wettergren2 Asok Ray1 Kushal Mukherjee3 Keywords: Underwater Sensor Network , Energy Management, Pareto Optimization, Adaptation...Optimization for Energy Management in Underwater Sensor Networks 5a. CONTRACT NUMBER 5b. GRANT NUMBER 5c. PROGRAM ELEMENT NUMBER 6. AUTHOR(S) 5d
Standardized Low-Power Wireless Communication Technologies for Distributed Sensing Applications
Vilajosana, Xavier; Tuset-Peiro, Pere; Vazquez-Gallego, Francisco; Alonso-Zarate, Jesus; Alonso, Luis
2014-01-01
Recent standardization efforts on low-power wireless communication technologies, including time-slotted channel hopping (TSCH) and DASH7 Alliance Mode (D7AM), are starting to change industrial sensing applications, enabling networks to scale up to thousands of nodes whilst achieving high reliability. Past technologies, such as ZigBee, rooted in IEEE 802.15.4, and ISO 18000-7, rooted in frame-slotted ALOHA (FSA), are based on contention medium access control (MAC) layers and have very poor performance in dense networks, thus preventing the Internet of Things (IoT) paradigm from really taking off. Industrial sensing applications, such as those being deployed in oil refineries, have stringent requirements on data reliability and are being built using new standards. Despite the benefits of these new technologies, industrial shifts are not happening due to the enormous technology development and adoption costs and the fact that new standards are not well-known and completely understood. In this article, we provide a deep analysis of TSCH and D7AM, outlining operational and implementation details with the aim of facilitating the adoption of these technologies to sensor application developers. PMID:24518893
Standardized low-power wireless communication technologies for distributed sensing applications.
Vilajosana, Xavier; Tuset-Peiro, Pere; Vazquez-Gallego, Francisco; Alonso-Zarate, Jesus; Alonso, Luis
2014-02-10
Recent standardization efforts on low-power wireless communication technologies, including time-slotted channel hopping (TSCH) and DASH7 Alliance Mode (D7AM), are starting to change industrial sensing applications, enabling networks to scale up to thousands of nodes whilst achieving high reliability. Past technologies, such as ZigBee, rooted in IEEE 802.15.4, and ISO 18000-7, rooted in frame-slotted ALOHA (FSA), are based on contention medium access control (MAC) layers and have very poor performance in dense networks, thus preventing the Internet of Things (IoT) paradigm from really taking off. Industrial sensing applications, such as those being deployed in oil refineries, have stringent requirements on data reliability and are being built using new standards. Despite the benefits of these new technologies, industrial shifts are not happening due to the enormous technology development and adoption costs and the fact that new standards are not well-known and completely understood. In this article, we provide a deep analysis of TSCH and D7AM, outlining operational and implementation details with the aim of facilitating the adoption of these technologies to sensor application developers.
Connectivity, Coverage and Placement in Wireless Sensor Networks
Li, Ji; Andrew, Lachlan L.H.; Foh, Chuan Heng; Zukerman, Moshe; Chen, Hsiao-Hwa
2009-01-01
Wireless communication between sensors allows the formation of flexible sensor networks, which can be deployed rapidly over wide or inaccessible areas. However, the need to gather data from all sensors in the network imposes constraints on the distances between sensors. This survey describes the state of the art in techniques for determining the minimum density and optimal locations of relay nodes and ordinary sensors to ensure connectivity, subject to various degrees of uncertainty in the locations of the nodes. PMID:22408474
IBE-Lite: a lightweight identity-based cryptography for body sensor networks.
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.
A Survey on Security and Privacy in Emerging Sensor Networks: From Viewpoint of Close-Loop
Zhang, Lifu; Zhang, Heng
2016-01-01
Nowadays, as the next generation sensor networks, Cyber-Physical Systems (CPSs) refer to the complex networked systems that have both physical subsystems and cyber components, and the information flow between different subsystems and components is across a communication network, which forms a closed-loop. New generation sensor networks are found in a growing number of applications and have received increasing attention from many inter-disciplines. Opportunities and challenges in the design, analysis, verification and validation of sensor networks co-exists, among which security and privacy are two important ingredients. This paper presents a survey on some recent results in the security and privacy aspects of emerging sensor networks from the viewpoint of the closed-loop. This paper also discusses several future research directions under these two umbrellas. PMID:27023559
Smart fabrics: integrating fiber optic sensors and information networks.
El-Sherif, Mahmoud
2004-01-01
"Smart Fabrics" are defined as fabrics capable of monitoring their own "health", and sensing environmental conditions. They consist of special type of sensors, signal processing, and communication network embedded into textile substrate. Available conventional sensors and networking systems are not fully technologically mature for such applications. New classes of miniature sensors, signal processing and networking systems are urgently needed for such application. Also, the methodology for integration into textile structures has to be developed. In this paper, the development of smart fabrics with embedded fiber optic systems is presented for applications in health monitoring and diagnostics. Successful development of such smart fabrics with embedded sensors and networks is mainly dependent on the development of the proper miniature sensors technology, and on the integration of these sensors into textile structures. The developed smart fabrics will be discussed and samples of the results will be presented.
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.
Silva Pereira, Silvana; Hindriks, Rikkert; Mühlberg, Stefanie; Maris, Eric; van Ede, Freek; Griffa, Alessandra; Hagmann, Patric; Deco, Gustavo
2017-11-01
A popular way to analyze resting-state electroencephalography (EEG) and magneto encephalography (MEG) data is to treat them as a functional network in which sensors are identified with nodes and the interaction between channel time series and the network connections. Although conceptually appealing, the network-theoretical approach to sensor-level EEG and MEG data is challenged by the fact that EEG and MEG time series are mixtures of source activity. It is, therefore, of interest to assess the relationship between functional networks of source activity and the ensuing sensor-level networks. Since these topological features are of high interest in experimental studies, we address the question of to what extent the network topology can be reconstructed from sensor-level functional connectivity (FC) measures in case of MEG data. Simple simulations that consider only a small number of regions do not allow to assess network properties; therefore, we use a diffusion magnetic resonance imaging-constrained whole-brain computational model of resting-state activity. Our motivation lies behind the fact that still many contributions found in the literature perform network analysis at sensor level, and we aim at showing the discrepancies between source- and sensor-level network topologies by using realistic simulations of resting-state cortical activity. Our main findings are that the effect of field spread on network topology depends on the type of interaction (instantaneous or lagged) and leads to an underestimation of lagged FC at sensor level due to instantaneous mixing of cortical signals, instantaneous interaction is more sensitive to field spread than lagged interaction, and discrepancies are reduced when using planar gradiometers rather than axial gradiometers. We, therefore, recommend using lagged interaction measures on planar gradiometer data when investigating network properties of resting-state sensor-level MEG data.
CMOS: Efficient Clustered Data Monitoring in Sensor Networks
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.
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.
Hummer, Blake H.; de Leeuw, Noah F.; Burns, Christian; Chen, Lan; Joens, Matthew S.; Hosford, Bethany; Fitzpatrick, James A. J.; Asensio, Cedric S.
2017-01-01
Large dense core vesicles (LDCVs) mediate the regulated release of neuropeptides and peptide hormones. They form at the trans-Golgi network (TGN), where their soluble content aggregates to form a dense core, but the mechanisms controlling biogenesis are still not completely understood. Recent studies have implicated the peripheral membrane protein HID-1 in neuropeptide sorting and insulin secretion. Using CRISPR/Cas9, we generated HID-1 KO rat neuroendocrine cells, and we show that the absence of HID-1 results in specific defects in peptide hormone and monoamine storage and regulated secretion. Loss of HID-1 causes a reduction in the number of LDCVs and affects their morphology and biochemical properties, due to impaired cargo sorting and dense core formation. HID-1 KO cells also exhibit defects in TGN acidification together with mislocalization of the Golgi-enriched vacuolar H+-ATPase subunit isoform a2. We propose that HID-1 influences early steps in LDCV formation by controlling dense core formation at the TGN. PMID:29074564
NASA Astrophysics Data System (ADS)
Ebrahimi, A.; Pahlavani, P.; Masoumi, Z.
2017-09-01
Traffic monitoring and managing in urban intelligent transportation systems (ITS) can be carried out based on vehicular sensor networks. In a vehicular sensor network, vehicles equipped with sensors such as GPS, can act as mobile sensors for sensing the urban traffic and sending the reports to a traffic monitoring center (TMC) for traffic estimation. The energy consumption by the sensor nodes is a main problem in the wireless sensor networks (WSNs); moreover, it is the most important feature in designing these networks. Clustering the sensor nodes is considered as an effective solution to reduce the energy consumption of WSNs. Each cluster should have a Cluster Head (CH), and a number of nodes located within its supervision area. The cluster heads are responsible for gathering and aggregating the information of clusters. Then, it transmits the information to the data collection center. Hence, the use of clustering decreases the volume of transmitting information, and, consequently, reduces the energy consumption of network. In this paper, Fuzzy C-Means (FCM) and Fuzzy Subtractive algorithms are employed to cluster sensors and investigate their performance on the energy consumption of sensors. It can be seen that the FCM algorithm and Fuzzy Subtractive have been reduced energy consumption of vehicle sensors up to 90.68% and 92.18%, respectively. Comparing the performance of the algorithms implies the 1.5 percent improvement in Fuzzy Subtractive algorithm in comparison.
From sparse to dense and from assortative to disassortative in online social networks
Li, Menghui; Guan, Shuguang; Wu, Chensheng; Gong, Xiaofeng; Li, Kun; Wu, Jinshan; Di, Zengru; Lai, Choy-Heng
2014-01-01
Inspired by the analysis of several empirical online social networks, we propose a simple reaction-diffusion-like coevolving model, in which individuals are activated to create links based on their states, influenced by local dynamics and their own intention. It is shown that the model can reproduce the remarkable properties observed in empirical online social networks; in particular, the assortative coefficients are neutral or negative, and the power law exponents γ are smaller than 2. Moreover, we demonstrate that, under appropriate conditions, the model network naturally makes transition(s) from assortative to disassortative, and from sparse to dense in their characteristics. The model is useful in understanding the formation and evolution of online social networks. PMID:24798703
From sparse to dense and from assortative to disassortative in online social networks.
Li, Menghui; Guan, Shuguang; Wu, Chensheng; Gong, Xiaofeng; Li, Kun; Wu, Jinshan; Di, Zengru; Lai, Choy-Heng
2014-05-06
Inspired by the analysis of several empirical online social networks, we propose a simple reaction-diffusion-like coevolving model, in which individuals are activated to create links based on their states, influenced by local dynamics and their own intention. It is shown that the model can reproduce the remarkable properties observed in empirical online social networks; in particular, the assortative coefficients are neutral or negative, and the power law exponents γ are smaller than 2. Moreover, we demonstrate that, under appropriate conditions, the model network naturally makes transition(s) from assortative to disassortative, and from sparse to dense in their characteristics. The model is useful in understanding the formation and evolution of online social networks.
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…
Detecting the Influence of Spreading in Social Networks with Excitable Sensor Networks
Pei, Sen; Tang, Shaoting; Zheng, Zhiming
2015-01-01
Detecting spreading outbreaks in social networks with sensors is of great significance in applications. Inspired by the formation mechanism of humans’ physical sensations to external stimuli, we propose a new method to detect the influence of spreading by constructing excitable sensor networks. Exploiting the amplifying effect of excitable sensor networks, our method can better detect small-scale spreading processes. At the same time, it can also distinguish large-scale diffusion instances due to the self-inhibition effect of excitable elements. Through simulations of diverse spreading dynamics on typical real-world social networks (Facebook, coauthor, and email social networks), we find that the excitable sensor networks are capable of detecting and ranking spreading processes in a much wider range of influence than other commonly used sensor placement methods, such as random, targeted, acquaintance and distance strategies. In addition, we validate the efficacy of our method with diffusion data from a real-world online social system, Twitter. We find that our method can detect more spreading topics in practice. Our approach provides a new direction in spreading detection and should be useful for designing effective detection methods. PMID:25950181
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
Information Fusion in Ad hoc Wireless Sensor Networks for Aircraft Health Monitoring
NASA Astrophysics Data System (ADS)
Fragoulis, Nikos; Tsagaris, Vassilis; Anastassopoulos, Vassilis
In this paper the use of an ad hoc wireless sensor network for implementing a structural health monitoring system is discussed. The network is consisted of sensors deployed throughout the aircraft. These sensors being in the form of a microelectronic chip and consisted of sensing, data processing and communicating components could be easily embedded in any mechanical aircraft component. The established sensor network, due to its ad hoc nature is easily scalable, allowing adding or removing any number of sensors. The position of the sensor nodes need not necessarily to be engineered or predetermined, giving this way the ability to be deployed in inaccessible points. Information collected from various sensors of different modalities throughout the aircraft is then fused in order to provide a more comprehensive image of the aircraft structural health. Sensor level fusion along with decision quality information is used, in order to enhance detection performance.
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.
Data aggregation in wireless sensor networks using the SOAP protocol
NASA Astrophysics Data System (ADS)
Al-Yasiri, A.; Sunley, A.
2007-07-01
Wireless sensor networks (WSN) offer an increasingly attractive method of data gathering in distributed system architectures and dynamic access via wireless connectivity. Wireless sensor networks have physical and resource limitations, this leads to increased complexity for application developers and often results in applications that are closely coupled with network protocols. In this paper, a data aggregation framework using SOAP (Simple Object Access Protocol) on wireless sensor networks is presented. The framework works as a middleware for aggregating data measured by a number of nodes within a network. The aim of the study is to assess the suitability of the protocol in such environments where resources are limited compared to traditional networks.
Wireless Networks under a Backoff Attack: A Game Theoretical Perspective.
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.
Integrated Sensor Architecture (ISA) for Live Virtual Constructive (LVC) Environments
2014-03-01
connect, publish their needs and capabilities, and interact with other systems even on disadvantaged networks. Within the ISA project, three levels of...constructive, disadvantaged network, sensor 1. INTRODUCTION In 2003 the Networked Sensors for the Future Force (NSFF) Advanced Technology Demonstration...While this combination is less optimal over disadvantaged networks, and we do not recommend it there, TCP and TLS perform adequately over networks with
An ontology for sensor networks
NASA Astrophysics Data System (ADS)
Compton, Michael; Neuhaus, Holger; Bermudez, Luis; Cox, Simon
2010-05-01
Sensors and networks of sensors are important ways of monitoring and digitizing reality. As the number and size of sensor networks grows, so too does the amount of data collected. Users of such networks typically need to discover the sensors and data that fit their needs without necessarily understanding the complexities of the network itself. The burden on users is eased if the network and its data are expressed in terms of concepts familiar to the users and their job functions, rather than in terms of the network or how it was designed. Furthermore, the task of collecting and combining data from multiple sensor networks is made easier if metadata about the data and the networks is stored in a format and conceptual models that is amenable to machine reasoning and inference. While the OGC's (Open Geospatial Consortium) SWE (Sensor Web Enablement) standards provide for the description and access to data and metadata for sensors, they do not provide facilities for abstraction, categorization, and reasoning consistent with standard technologies. Once sensors and networks are described using rich semantics (that is, by using logic to describe the sensors, the domain of interest, and the measurements) then reasoning and classification can be used to analyse and categorise data, relate measurements with similar information content, and manage, query and task sensors. This will enable types of automated processing and logical assurance built on OGC standards. The W3C SSN-XG (Semantic Sensor Networks Incubator Group) is producing a generic ontology to describe sensors, their environment and the measurements they make. The ontology provides definitions for the structure of sensors and observations, leaving the details of the observed domain unspecified. This allows abstract representations of real world entities, which are not observed directly but through their observable qualities. Domain semantics, units of measurement, time and time series, and location and mobility ontologies can be easily attached when instantiating the ontology for any particular sensors in a domain. After a review of previous work on the specification of sensors, the group is developing the ontology in conjunction with use case development. Part of the difficulty of such work is that relevant concepts from for example OGC standards and other ontologies must be identified and aligned and also placed in a consistent and logically correct way into the ontology. In terms of alignment with OGC's SWE, the ontology is intended to be able to model concepts from SensorML and O&M. Similar to SensorML and O&M, the ontology is based around concepts of systems, processes, and observations. It supports the description of the physical and processing structure of sensors. Sensors are not constrained to physical sensing devices: rather a sensor is anything that can estimate or calculate the value of a phenomenon, so a device or computational process or combination could play the role of a sensor. The representation of a sensor in the ontology links together what is measured (the domain phenomena), the sensor's physical and other properties and its functions and processing. Parts of the ontology are well aligned with SensorML and O&M, but parts are not, and the group is working to understand how differences from (and alignment with) the OGC standards affect the application of the ontology.
Energy-aware scheduling of surveillance in wireless multimedia sensor networks.
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.
Using Reputation Systems and Non-Deterministic Routing to Secure Wireless Sensor Networks
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
Modelling the Energy Efficient Sensor Nodes for Wireless Sensor Networks
NASA Astrophysics Data System (ADS)
Dahiya, R.; Arora, A. K.; Singh, V. R.
2015-09-01
Energy is an important requirement of wireless sensor networks for better performance. A widely employed energy-saving technique is to place nodes in sleep mode, corresponding to low-power consumption as well as to reduce operational capabilities. In this paper, Markov model of a sensor network is developed. The node is considered to enter a sleep mode. This model is used to investigate the system performance in terms of energy consumption, network capacity and data delivery delay.
Distributed Localization of Active Transmitters in a Wireless Sensor Network
2012-03-01
Distributed Localization of Active Transmitters in a Wireless Sensor Network THESIS Oba L. Vincent, 2nd Lieutenant, USAF AFIT/GE/ENG/12-41 DEPARTMENT...protection in the United States. AFIT/GE/ENG/12-41 Distributed Localization of Active Transmitters in a Wireless Sensor Network THESIS Presented to the...Transmitters in a Wireless Sensor Network Oba L. Vincent, B.S.E.E. 2nd Lieutenant, USAF Approved: /signed/ 29 Feb 2012 Maj. Mark D. Silvius, Ph.D. (Chairman
A Study on Wireless Charging for Prolonging the Lifetime of Wireless Sensor Networks
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
Multi-Domain SDN Survivability for Agricultural Wireless Sensor Networks.
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
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
An Outline of Data Aggregation Security in Heterogeneous Wireless Sensor Networks
Boubiche, Sabrina; Boubiche, Djallel Eddine; Bilami, Azzedine; Toral-Cruz, Homero
2016-01-01
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. PMID:27077866
2010-01-01
target kinematics for multiple sensor detections is referred to as the track - before - detect strategy, and is commonly adopted in multi-sensor surveillance...of moving targets. Wettergren [4] presented an application of track - before - detect strategies to undersea distributed sensor networks. In de- signing...the deployment of a distributed passive sensor network that employs this track - before - detect procedure, it is impera- tive that the placement of
2015-03-01
Wireless Sensor Network Using Unreliable GPS Signals Daniel R. Fuhrmann*, Joshua Stomberg§, Saeid Nooshabadi*§ Dustin McIntire†, William Merill... wireless sensor network , when the timing jitter is subject to a empirically determined bimodal non-Gaussian distribution. Specifically, we 1) estimate the...over a nominal 19.2 MHz frequency with an adjustment made every four hours. Index Terms— clock synchronization, GPS, wireless sensor networks , Kalman
A Survey of Wireless Sensor Network Based Air Pollution Monitoring Systems
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.
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.
2D PWV monitoring of a wide and orographically complex area with a low dense GNSS network
NASA Astrophysics Data System (ADS)
Ferrando, Ilaria; Federici, Bianca; Sguerso, Domenico
2018-04-01
This study presents an innovative procedure to monitor the precipitable water vapor (PWV) content of a wide and orographically complex area with low-density networks. The procedure, termed G4M (global navigation satellite system, GNSS, for Meteorology), has been developed in a geographic information system (GIS) environment using the free and open source GRASS GIS software (https://grass.osgeo.org). The G4M input data are zenith total delay estimates obtained from GNSS permanent stations network adjustment and pressure ( P) and temperature ( T) observations using existing infrastructure networks with different geographic distributions in the study area. In spite of the wide sensor distribution, the procedure produces 2D maps with high spatiotemporal resolution (up to 250 m and 6 min) based on a simplified mathematical model including data interpolation, which was conceived by the authors to describe the atmosphere's physics. In addition to PWV maps, the procedure provides ΔPWV and heterogeneity index maps: the former represents PWV variations with respect to a "calm" moment, which are useful for monitoring the PWV evolution; and the latter are promising indicators to localize severe meteorological events in time and space. This innovative procedure is compared with meteorological simulations in this paper; in addition, an application to a severe event that occurred in Genoa (Italy) is presented.[Figure not available: see fulltext.
The resilient hybrid fiber sensor network with self-healing function
DOE Office of Scientific and Technical Information (OSTI.GOV)
Xu, Shibo, E-mail: Shibo-Xu@tju.edu.cn; Liu, Tiegen; Ge, Chunfeng
This paper presents a novel resilient fiber sensor network (FSN) with multi-ring architecture, which could interconnect various kinds of fiber sensors responsible for more than one measurands. We explain how the intelligent control system provides sensors with self-healing function meanwhile sensors are working properly, besides each fiber in FSN is under real-time monitoring. We explain the software process and emergency mechanism to respond failures or other circumstances. To improve the efficiency in the use of limited spectrum resources in some situations, we have two different structures to distribute the light sources rationally. Then, we propose a hybrid sensor working inmore » FSN which is a combination of a distributed sensor and a FBG (Fiber Bragg Grating) array fused in a common fiber sensing temperature and vibrations simultaneously with neglectable crosstalk to each other. By making a failure to a working fiber in experiment, the feasibility and effectiveness of the network with a hybrid sensor has been demonstrated, hybrid sensors could not only work as designed but also survive from destructive failures with the help of resilient network and smart and quick self-healing actions. The network has improved the viability of the fiber sensors and diversity of measurands.« less
NASA Astrophysics Data System (ADS)
Turner, D.; Lucieer, A.; McCabe, M.; Parkes, S.; Clarke, I.
2017-08-01
In this study, we assess two push broom hyperspectral sensors as carried by small (10-15 kg) multi-rotor Unmanned Aircraft Systems (UAS). We used a Headwall Photonics micro-Hyperspec push broom sensor with 324 spectral bands (4-5 nm FWHM) and a Headwall Photonics nano-Hyperspec sensor with 270 spectral bands (6 nm FWHM) both in the VNIR spectral range (400-1000 nm). A gimbal was used to stabilise the sensors in relation to the aircraft flight dynamics, and for the micro-Hyperspec a tightly coupled dual frequency Global Navigation Satellite System (GNSS) receiver, an Inertial Measurement Unit (IMU), and Machine Vision Camera (MVC) were used for attitude and position determination. For the nano-Hyperspec, a navigation grade GNSS system and IMU provided position and attitude data. This study presents the geometric results of one flight over a grass oval on which a dense Ground Control Point (GCP) network was deployed. The aim being to ascertain the geometric accuracy achievable with the system. Using the PARGE software package (ReSe - Remote Sensing Applications) we ortho-rectify the push broom hyperspectral image strips and then quantify the accuracy of the ortho-rectification by using the GCPs as check points. The orientation (roll, pitch, and yaw) of the sensor is measured by the IMU. Alternatively imagery from a MVC running at 15 Hz, with accurate camera position data can be processed with Structure from Motion (SfM) software to obtain an estimated camera orientation. In this study, we look at which of these data sources will yield a flight strip with the highest geometric accuracy.
Optimization of Self-Directed Target Coverage in Wireless Multimedia Sensor Network
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
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
A comprehensive survey of energy-aware routing protocols in wireless body area sensor networks.
Effatparvar, Mehdi; Dehghan, Mehdi; Rahmani, Amir Masoud
2016-09-01
Wireless body area sensor network is a special purpose wireless sensor network that, employing wireless sensor nodes in, on, or around the human body, makes it possible to measure biological parameters of a person for specific applications. One of the most fundamental concerns in wireless body sensor networks is accurate routing in order to send data promptly and properly, and therefore overcome some of the challenges. Routing protocols for such networks are affected by a large number of factors including energy, topology, temperature, posture, the radio range of sensors, and appropriate quality of service in sensor nodes. Since energy is highly important in wireless body area sensor networks, and increasing the network lifetime results in benefiting greatly from sensor capabilities, improving routing performance with reduced energy consumption presents a major challenge. This paper aims to study wireless body area sensor networks and the related routing methods. It also presents a thorough, comprehensive review of routing methods in wireless body area sensor networks from the perspective of energy. Furthermore, different routing methods affecting the parameter of energy will be classified and compared according to their advantages and disadvantages. In this paper, fundamental concepts of wireless body area sensor networks are provided, and then the advantages and disadvantages of these networks are investigated. Since one of the most fundamental issues in wireless body sensor networks is to perform routing so as to transmit data precisely and promptly, we discuss the same issue. As a result, we propose a classification of the available relevant literature with respect to the key challenge of energy in the routing process. With this end in view, all important papers published between 2000 and 2015 are classified under eight categories including 'Mobility-Aware', 'Thermal-Aware', 'Restriction of Location and Number of Relays', 'Link-aware', 'Cluster- and Tree-Based', 'Cross-Layer', 'Opportunistic', and 'Medium Access Control'. We, then, provide a full description of the statistical analysis of each category in relation to all papers, current hybrid protocols, and the type of simulators used in each paper. Next, we analyze the distribution of papers in each category during various years. Moreover, for each category, the advantages and disadvantages as well as the number of issued papers in different years are given. We also analyze the type of layer and deployment of mathematical models or algorithmic techniques in each category. Finally, after introducing certain important protocols for each category, the goals, advantages, and disadvantages of the protocols are discussed and compared with each other.
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.
NASA Astrophysics Data System (ADS)
Guo, Guodong; Hackney, Drew; Pankow, Mark; Peters, Kara
2017-04-01
A spectral profile division multiplexed fiber Bragg grating (FBG) sensor network is described in this paper. The unique spectral profile of each sensor in the network is identified as a distinct feature to be interrogated. Spectrum overlap is allowed under working conditions. Thus, a specific wavelength window does not need to be allocated to each sensor as in a wavelength division multiplexed (WDM) network. When the sensors are serially connected in the network, the spectrum output is expressed through a truncated series. To track the wavelength shift of each sensor, the identification problem is transformed to a nonlinear optimization problem, which is then solved by a modified dynamic multi-swarm particle swarm optimizer (DMS-PSO). To demonstrate the application of the developed network, a network consisting of four FBGs was integrated into a Kevlar woven fabric, which was under a quasi-static load imposed by an impactor head. Due to the substantial radial strain in the fabric, the spectrums of different FBGs were found to overlap during the loading process. With the developed interrogating method, the overlapped spectrum would be distinguished thus the wavelength shift of each sensor can be monitored.
Sensor networks in the low lands.
Meratnia, Nirvana; van der Zwaag, Berend Jan; van Dijk, Hylke W; Bijwaard, Dennis J A; Havinga, Paul J M
2010-01-01
This paper provides an overview of scientific and industrial developments of the last decade in the area of sensor networks in The Netherlands (Low Lands). The goal is to highlight areas in which the Netherlands has made most contributions and is currently a dominant player in the field of sensor networks. On the one hand, motivations, addressed topics, and initiatives taken in this period are presented, while on the other hand, special emphasis is given to identifying current and future trends and formulating a vision for the coming five to ten years. The presented overview and trend analysis clearly show that Dutch research and industrial efforts, in line with recent worldwide developments in the field of sensor technology, present a clear shift from sensor node platforms, operating systems, communication, networking, and data management aspects of the sensor networks to reasoning/cognition, control, and actuation.
Social Networks, Social Circles, and Job Satisfaction.
ERIC Educational Resources Information Center
Hurlbert, Jeanne S.
1991-01-01
Tests the hypothesis that social networks serve as a social resource that effects job satisfaction through the provision of social support. Argues that three types of networks are likely to affect job satisfaction: dense networks, social circles composed of co-workers, and kin-centered networks. (JOW)
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
2009-09-01
with the flexibility provided by a wireless sensor network , could provide such enhancements. The objective of this research was to explore the...feasibility of remote management and control of a low-power/low-cost wireless sensor network by implementing a point-to-point wireless network utilizing IEEE
Wireless Sensor Network Based Subsurface Contaminant Plume Monitoring
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
Traffic Profiling in Wireless Sensor Networks
2006-12-01
components, that can be used for traffic profiling and monitoring of a wireless sensor network . The work demostrates how the IDS should capture and...observed and analyzed. Finally, initial indications from basic analysis of wireless sensor network traffic demonstrated a high degree of self-similarity.
He, Xinzi; Yu, Zhen; Wang, Tianfu; Lei, Baiying; Shi, Yiyan
2018-01-01
Dermoscopy imaging has been a routine examination approach for skin lesion diagnosis. Accurate segmentation is the first step for automatic dermoscopy image assessment. The main challenges for skin lesion segmentation are numerous variations in viewpoint and scale of skin lesion region. To handle these challenges, we propose a novel skin lesion segmentation network via a very deep dense deconvolution network based on dermoscopic images. Specifically, the deep dense layer and generic multi-path Deep RefineNet are combined to improve the segmentation performance. The deep representation of all available layers is aggregated to form the global feature maps using skip connection. Also, the dense deconvolution layer is leveraged to capture diverse appearance features via the contextual information. Finally, we apply the dense deconvolution layer to smooth segmentation maps and obtain final high-resolution output. Our proposed method shows the superiority over the state-of-the-art approaches based on the public available 2016 and 2017 skin lesion challenge dataset and achieves the accuracy of 96.0% and 93.9%, which obtained a 6.0% and 1.2% increase over the traditional method, respectively. By utilizing Dense Deconvolution Net, the average time for processing one testing images with our proposed framework was 0.253 s.
Large Scale Environmental Monitoring through Integration of Sensor and Mesh Networks.
Jurdak, Raja; Nafaa, Abdelhamid; Barbirato, Alessio
2008-11-24
Monitoring outdoor environments through networks of wireless sensors has received interest for collecting physical and chemical samples at high spatial and temporal scales. A central challenge to environmental monitoring applications of sensor networks is the short communication range of the sensor nodes, which increases the complexity and cost of monitoring commodities that are located in geographically spread areas. To address this issue, we propose a new communication architecture that integrates sensor networks with medium range wireless mesh networks, and provides users with an advanced web portal for managing sensed information in an integrated manner. Our architecture adopts a holistic approach targeted at improving the user experience by optimizing the system performance for handling data that originates at the sensors, traverses the mesh network, and resides at the server for user consumption. This holistic approach enables users to set high level policies that can adapt the resolution of information collected at the sensors, set the preferred performance targets for their application, and run a wide range of queries and analysis on both real-time and historical data. All system components and processes will be described in this paper.
NASA Astrophysics Data System (ADS)
Yuldashev, M. N.; Vlasov, A. I.; Novikov, A. N.
2018-05-01
This paper focuses on the development of an energy-efficient algorithm for classification of states of a wireless sensor network using machine learning methods. The proposed algorithm reduces energy consumption by: 1) elimination of monitoring of parameters that do not affect the state of the sensor network, 2) reduction of communication sessions over the network (the data are transmitted only if their values can affect the state of the sensor network). The studies of the proposed algorithm have shown that at classification accuracy close to 100%, the number of communication sessions can be reduced by 80%.
NASA Astrophysics Data System (ADS)
Robinson, P. W.; Neal, D.; Frome, D.; Kavanagh, K.; Davis, A.; Gessler, P. E.; Hess, H.; Holden, Z. A.; Link, T. E.; Newingham, B. A.; Smith, A. M.
2013-12-01
Developing sensor networks robust enough to perform unattended in the world's remote regions is critical since these regions serve as important benchmarks that lack anthropogenic influence. Paradoxically, the factors that make these remote, natural sites challenging for sensor networking are often what make them indispensable for climate change research. The MESA (Mountainous Ecosystem Sensor Array) project has faced these challenges and developed a wireless mesh sensor network across a 660 m topoclimatic gradient in a wilderness area in central Idaho. This sensor array uses advances in sensing, networking, and power supply technologies to provide near real-time synchronized data covering a suite of biophysical parameters used in ecosystem process models. The 76 sensors in the network monitor atmospheric carbon dioxide concentration, humidity, air and soil temperature, soil water content, precipitation, incoming and outgoing shortwave and longwave radiation, snow depth, wind speed and direction, and leaf wetness at synchronized time intervals ranging from two minutes to two hours and spatial scales from a few meters to two kilometers. We present our novel methods of placing sensors and network nodes above, below, and throughout the forest canopy without using meteorological towers. In addition, we explain our decision to use different forms of power (wind and solar) and the equipment we use to control and integrate power harvesting. Further, we describe our use of the network to sense and quantify its own power use. Using examples of environmental data from the project, we discuss how these data may be used to increase our understanding of the effects of climate change on ecosystem processes in mountainous environments. MESA sensor locations across a 700 m topoclimatic gradient at the University of Idaho Taylor Wilderness Research Station.
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.
The Robustness Analysis of Wireless Sensor Networks under Uncertain Interference
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
Wireless Networks under a Backoff Attack: A Game Theoretical Perspective
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
Lopez-Coto, Israel; Ghosh, Subhomoy; Prasad, Kuldeep; Whetstone, James
2017-09-01
The North-East Corridor (NEC) Testbed project is the 3rd of three NIST (National Institute of Standards and Technology) greenhouse gas emissions testbeds designed to advance greenhouse gas measurements capabilities. A design approach for a dense observing network combined with atmospheric inversion methodologies is described. The Advanced Research Weather Research and Forecasting Model with the Stochastic Time-Inverted Lagrangian Transport model were used to derive the sensitivity of hypothetical observations to surface greenhouse gas emissions (footprints). Unlike other network design algorithms, an iterative selection algorithm, based on a k -means clustering method, was applied to minimize the similarities between the temporal response of each site and maximize sensitivity to the urban emissions contribution. Once a network was selected, a synthetic inversion Bayesian Kalman filter was used to evaluate observing system performance. We present the performances of various measurement network configurations consisting of differing numbers of towers and tower locations. Results show that an overly spatially compact network has decreased spatial coverage, as the spatial information added per site is then suboptimal as to cover the largest possible area, whilst networks dispersed too broadly lose capabilities of constraining flux uncertainties. In addition, we explore the possibility of using a very high density network of lower cost and performance sensors characterized by larger uncertainties and temporal drift. Analysis convergence is faster with a large number of observing locations, reducing the response time of the filter. Larger uncertainties in the observations implies lower values of uncertainty reduction. On the other hand, the drift is a bias in nature, which is added to the observations and, therefore, biasing the retrieved fluxes.
NASA Astrophysics Data System (ADS)
Lopez-Coto, Israel; Ghosh, Subhomoy; Prasad, Kuldeep; Whetstone, James
2017-09-01
The North-East Corridor (NEC) Testbed project is the 3rd of three NIST (National Institute of Standards and Technology) greenhouse gas emissions testbeds designed to advance greenhouse gas measurements capabilities. A design approach for a dense observing network combined with atmospheric inversion methodologies is described. The Advanced Research Weather Research and Forecasting Model with the Stochastic Time-Inverted Lagrangian Transport model were used to derive the sensitivity of hypothetical observations to surface greenhouse gas emissions (footprints). Unlike other network design algorithms, an iterative selection algorithm, based on a k-means clustering method, was applied to minimize the similarities between the temporal response of each site and maximize sensitivity to the urban emissions contribution. Once a network was selected, a synthetic inversion Bayesian Kalman filter was used to evaluate observing system performance. We present the performances of various measurement network configurations consisting of differing numbers of towers and tower locations. Results show that an overly spatially compact network has decreased spatial coverage, as the spatial information added per site is then suboptimal as to cover the largest possible area, whilst networks dispersed too broadly lose capabilities of constraining flux uncertainties. In addition, we explore the possibility of using a very high density network of lower cost and performance sensors characterized by larger uncertainties and temporal drift. Analysis convergence is faster with a large number of observing locations, reducing the response time of the filter. Larger uncertainties in the observations implies lower values of uncertainty reduction. On the other hand, the drift is a bias in nature, which is added to the observations and, therefore, biasing the retrieved fluxes.
NASA Astrophysics Data System (ADS)
Leon, Barbara D.; Heller, Paul R.
1987-05-01
A surveillance network is a group of multiplatform sensors cooperating to improve network performance. Network control is distributed as a measure to decrease vulnerability to enemy threat. The network may contain diverse sensor types such as radar, ESM (Electronic Support Measures), IRST (Infrared search and track) and E-0 (Electro-Optical). Each platform may contain a single sensor or suite of sensors. In a surveillance network it is desirable to control sensors to make the overall system more effective. This problem has come to be known as sensor management and control (SM&C). Two major facets of network performance are surveillance and survivability. In a netted environment, surveillance can be enhanced if information from all sensors is combined and sensor operating conditions are controlled to provide a synergistic effect. In contrast, when survivability is the main concern for the network, the best operating status for all sensors would be passive or off. Of course, improving survivability tends to degrade surveillance. Hence, the objective of SM&C is to optimize surveillance and survivability of the network. Too voluminous data of various formats and the quick response time are two characteristics of this problem which make it an ideal application for Artificial Intelligence. A solution to the SM&C problem, presented as a computer simulation, will be presented in this paper. The simulation is a hybrid production written in LISP and FORTRAN. It combines the latest conventional computer programming methods with Artificial Intelligence techniques to produce a flexible state-of-the-art tool to evaluate network performance. The event-driven simulation contains environment models coupled with an expert system. These environment models include sensor (track-while-scan and agile beam) and target models, local tracking, and system tracking. These models are used to generate the environment for the sensor management and control expert system. The expert system, driven by a forward chaining inference engine, makes decisions based on the global database. The global database contains current track and sensor information supplied by the simulation. At present, the rule base emphasizes the surveillance features with rules grouped into three main categories: maintenance and enhancing track on prioritized targets; filling coverage holes and countering jamming; and evaluating sensor status. The paper will describe the architecture used for the expert system and the reasons for selecting the chosen methods. The SM&C simulation produces a graphical representation of sensors and their associated tracks such that the benefits of the sensor management and control expert system are evident. Jammer locations are also part of the display. The paper will describe results from several scenarios that best illustrate the sensor management and control concepts.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Senesac, Larry R; Datskos, Panos G; Sepaniak, Michael J
2006-01-01
In the present work, we have performed analyte species and concentration identification using an array of ten differentially functionalized microcantilevers coupled with a back-propagation artificial neural network pattern recognition algorithm. The array consists of ten nanostructured silicon microcantilevers functionalized by polymeric and gas chromatography phases and macrocyclic receptors as spatially dense, differentially responding sensing layers for identification and quantitation of individual analyte(s) and their binary mixtures. The array response (i.e. cantilever bending) to analyte vapor was measured by an optical readout scheme and the responses were recorded for a selection of individual analytes as well as several binary mixtures. Anmore » artificial neural network (ANN) was designed and trained to recognize not only the individual analytes and binary mixtures, but also to determine the concentration of individual components in a mixture. To the best of our knowledge, ANNs have not been applied to microcantilever array responses previously to determine concentrations of individual analytes. The trained ANN correctly identified the eleven test analyte(s) as individual components, most with probabilities greater than 97%, whereas it did not misidentify an unknown (untrained) analyte. Demonstrated unique aspects of this work include an ability to measure binary mixtures and provide both qualitative (identification) and quantitative (concentration) information with array-ANN-based sensor methodologies.« less
Wireless structural monitoring for homeland security applications
NASA Astrophysics Data System (ADS)
Kiremidjian, Garo K.; Kiremidjian, Anne S.; Lynch, Jerome P.
2004-07-01
This paper addresses the development of a robust, low-cost, low power, and high performance autonomous wireless monitoring system for civil assets such as large facilities, new construction, bridges, dams, commercial buildings, etc. The role of the system is to identify the onset, development, location and severity of structural vulnerability and damage. The proposed system represents an enabling infrastructure for addressing structural vulnerabilities specifically associated with homeland security. The system concept is based on dense networks of "intelligent" wireless sensing units. The fundamental properties of a wireless sensing unit include: (a) interfaces to multiple sensors for measuring structural and environmental data (such as acceleration, displacements, pressure, strain, material degradation, temperature, gas agents, biological agents, humidity, corrosion, etc.); (b) processing of sensor data with embedded algorithms for assessing damage and environmental conditions; (c) peer-to-peer wireless communications for information exchange among units(thus enabling joint "intelligent" processing coordination) and storage of data and processed information in servers for information fusion; (d) ultra low power operation; (e) cost-effectiveness and compact size through the use of low-cost small-size off-the-shelf components. An integral component of the overall system concept is a decision support environment for interpretation and dissemination of information to various decision makers.
A Computational Architecture Based on RFID Sensors for Traceability in Smart Cities.
Mora-Mora, Higinio; Gilart-Iglesias, Virgilio; Gil, David; Sirvent-Llamas, Alejandro
2015-06-10
Information Technology and Communications (ICT) is presented as the main element in order to achieve more efficient and sustainable city resource management, while making sure that the needs of the citizens to improve their quality of life are satisfied. A key element will be the creation of new systems that allow the acquisition of context information, automatically and transparently, in order to provide it to decision support systems. In this paper, we present a novel distributed system for obtaining, representing and providing the flow and movement of people in densely populated geographical areas. In order to accomplish these tasks, we propose the design of a smart sensor network based on RFID communication technologies, reliability patterns and integration techniques. Contrary to other proposals, this system represents a comprehensive solution that permits the acquisition of user information in a transparent and reliable way in a non-controlled and heterogeneous environment. This knowledge will be useful in moving towards the design of smart cities in which decision support on transport strategies, business evaluation or initiatives in the tourism sector will be supported by real relevant information. As a final result, a case study will be presented which will allow the validation of the proposal.
A Computational Architecture Based on RFID Sensors for Traceability in Smart Cities
Mora-Mora, Higinio; Gilart-Iglesias, Virgilio; Gil, David; Sirvent-Llamas, Alejandro
2015-01-01
Information Technology and Communications (ICT) is presented as the main element in order to achieve more efficient and sustainable city resource management, while making sure that the needs of the citizens to improve their quality of life are satisfied. A key element will be the creation of new systems that allow the acquisition of context information, automatically and transparently, in order to provide it to decision support systems. In this paper, we present a novel distributed system for obtaining, representing and providing the flow and movement of people in densely populated geographical areas. In order to accomplish these tasks, we propose the design of a smart sensor network based on RFID communication technologies, reliability patterns and integration techniques. Contrary to other proposals, this system represents a comprehensive solution that permits the acquisition of user information in a transparent and reliable way in a non-controlled and heterogeneous environment. This knowledge will be useful in moving towards the design of smart cities in which decision support on transport strategies, business evaluation or initiatives in the tourism sector will be supported by real relevant information. As a final result, a case study will be presented which will allow the validation of the proposal. PMID:26067195
Consistent Steering System using SCTP for Bluetooth Scatternet Sensor Network
NASA Astrophysics Data System (ADS)
Dhaya, R.; Sadasivam, V.; Kanthavel, R.
2012-12-01
Wireless communication is the best way to convey information from source to destination with flexibility and mobility and Bluetooth is the wireless technology suitable for short distance. On the other hand a wireless sensor network (WSN) consists of spatially distributed autonomous sensors to cooperatively monitor physical or environmental conditions, such as temperature, sound, vibration, pressure, motion or pollutants. Using Bluetooth piconet wireless technique in sensor nodes creates limitation in network depth and placement. The introduction of Scatternet solves the network restrictions with lack of reliability in data transmission. When the depth of the network increases, it results in more difficulties in routing. No authors so far focused on the reliability factors of Scatternet sensor network's routing. This paper illustrates the proposed system architecture and routing mechanism to increase the reliability. The another objective is to use reliable transport protocol that uses the multi-homing concept and supports multiple streams to prevent head-of-line blocking. The results show that the Scatternet sensor network has lower packet loss even in the congestive environment than the existing system suitable for all surveillance applications.
Wireless Sensors Network (Sensornet)
NASA Technical Reports Server (NTRS)
Perotti, J.
2003-01-01
The Wireless Sensor Network System presented in this paper provides a flexible reconfigurable architecture that could be used in a broad range of applications. It also provides a sensor network with increased reliability; decreased maintainability costs, and assured data availability by autonomously and automatically reconfiguring to overcome communication interferences.
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.
On computer vision in wireless sensor networks.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Berry, Nina M.; Ko, Teresa H.
Wireless sensor networks allow detailed sensing of otherwise unknown and inaccessible environments. While it would be beneficial to include cameras in a wireless sensor network because images are so rich in information, the power cost of transmitting an image across the wireless network can dramatically shorten the lifespan of the sensor nodes. This paper describe a new paradigm for the incorporation of imaging into wireless networks. Rather than focusing on transmitting images across the network, we show how an image can be processed locally for key features using simple detectors. Contrasted with traditional event detection systems that trigger an imagemore » capture, this enables a new class of sensors which uses a low power imaging sensor to detect a variety of visual cues. Sharing these features among relevant nodes cues specific actions to better provide information about the environment. We report on various existing techniques developed for traditional computer vision research which can aid in this work.« less
Joint Resource Optimization for Cognitive Sensor Networks with SWIPT-Enabled Relay.
Lu, Weidang; Lin, Yuanrong; Peng, Hong; Nan, Tian; Liu, Xin
2017-09-13
Energy-constrained wireless networks, such as wireless sensor networks (WSNs), are usually powered by fixed energy supplies (e.g., batteries), which limits the operation time of networks. Simultaneous wireless information and power transfer (SWIPT) is a promising technique to prolong the lifetime of energy-constrained wireless networks. This paper investigates the performance of an underlay cognitive sensor network (CSN) with SWIPT-enabled relay node. In the CSN, the amplify-and-forward (AF) relay sensor node harvests energy from the ambient radio-frequency (RF) signals using power splitting-based relaying (PSR) protocol. Then, it helps forward the signal of source sensor node (SSN) to the destination sensor node (DSN) by using the harvested energy. We study the joint resource optimization including the transmit power and power splitting ratio to maximize CSN's achievable rate with the constraint that the interference caused by the CSN to the primary users (PUs) is within the permissible threshold. Simulation results show that the performance of our proposed joint resource optimization can be significantly improved.
Maritime In Situ Sensing Inter-Operable Networks (MISSION)
2013-09-30
creating acoustic communications (acomms) technologies enabling underwater sensor networks and distributed systems. Figure 1. Project MISSION...Marn, S. Ramp, F. Bahr, “Implementation of an Underwater Wireless Sensor Network in San Francisco Bay,” Proc. 10th International Mine Warfare...NILUS – An Underwater Acoustic Sensor Network Demonstrator System,” Proc. 10th International Mine Warfare Technology Symposium, Monterey, CA, May 7
Wireless sensor network for monitoring soil moisture and weather conditions
USDA-ARS?s Scientific Manuscript database
A wireless sensor network (WSN) was developed and deployed in three fields to monitor soil water status and collect weather data for irrigation scheduling. The WSN consists of soil-water sensors, weather sensors, wireless data loggers, and a wireless modem. Soil-water sensors were installed at three...
Biomimetic Models for An Ecological Approach to 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 massively-deployed wireless sensor networks open avenues for new applications that will redefine the way we live and work. Due to small size and low cost of sensor devices, visionaries promise systems enabled by deployment of massive numbers of sensors ubiquitous throughout our environment working in concert. Recent research has concentrated on developing techniques for performing relatively simple tasks with minimal energy expense, assuming some form of centralized control. Unfortunately, centralized control is not conducive to parallel activities and does not scale to massive size networks. Execution of simple tasks in sparse networks will not lead to the sophisticated applications predicted. We propose a new way of looking at massively-deployed sensor networks, motivated by lessons learned from the way biological ecosystems are organized. We demonstrate that in such a model, fully distributed data aggregation can be performed in a scalable fashion in massively deployed sensor networks, where motes operate on local information, making local decisions that are aggregated across the network to achieve globally-meaningful effects. We show that such architectures may be used to facilitate communication and synchronization in a fault-tolerant manner, while balancing workload and required energy expenditure throughout the network.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Ramirez Aviles, Camila A.; Rao, Nageswara S.
We consider the problem of inferring the operational state of a reactor facility by using measurements from a radiation sensor network, which is deployed around the facility’s ventilation stack. The radiation emissions from the stack decay with distance, and the corresponding measurements are inherently random with parameters determined by radiation intensity levels at the sensor locations. We fuse measurements from network sensors to estimate the intensity at the stack, and use this estimate in a one-sided Sequential Probability Ratio Test (SPRT) to infer the on/off state of the reactor facility. We demonstrate the superior performance of this method over conventionalmore » majority vote fusers and individual sensors using (i) test measurements from a network of NaI sensors, and (ii) emulated measurements using radioactive effluents collected at a reactor facility stack. We analytically quantify the performance improvements of individual sensors and their networks with adaptive thresholds over those with fixed ones, by using the packing number of the radiation intensity space.« less
In-network processing of joins in wireless sensor networks.
Kang, Hyunchul
2013-03-11
The join or correlated filtering of sensor readings is one of the fundamental query operations in wireless sensor networks (WSNs). Although the join in centralized or distributed databases is a well-researched problem, join processing in WSNs has quite different characteristics and is much more difficult to perform due to the lack of statistics on sensor readings and the resource constraints of sensor nodes. Since data transmission is orders of magnitude more costly than processing at a sensor node, in-network processing of joins is essential. In this paper, the state-of-the-art techniques for join implementation in WSNs are surveyed. The requirements and challenges, join types, and components of join implementation are described. The open issues for further research are identified.
In-Network Processing of Joins in Wireless Sensor Networks
Kang, Hyunchul
2013-01-01
The join or correlated filtering of sensor readings is one of the fundamental query operations in wireless sensor networks (WSNs). Although the join in centralized or distributed databases is a well-researched problem, join processing in WSNs has quite different characteristics and is much more difficult to perform due to the lack of statistics on sensor readings and the resource constraints of sensor nodes. Since data transmission is orders of magnitude more costly than processing at a sensor node, in-network processing of joins is essential. In this paper, the state-of-the-art techniques for join implementation in WSNs are surveyed. The requirements and challenges, join types, and components of join implementation are described. The open issues for further research are identified. PMID:23478603
Secure Sensor Semantic Web and Information Fusion
2014-06-25
data acquired and transmitted by wireless sensor networks (WSNs). In a WSN, due to a need for robustness of monitoring and low cost of the nodes...3 S. Ozdemir and Y. Xiao, “Secure data aggregation in wireless sensor networks : A comprehensive overview...Elisa Bertino, and Somesh Jha: Secure data aggregation technique for wireless sensor networks in the presence of collusion attacks. To appear in
Deterministic quantum dense coding networks
NASA Astrophysics Data System (ADS)
Roy, Saptarshi; Chanda, Titas; Das, Tamoghna; Sen(De), Aditi; Sen, Ujjwal
2018-07-01
We consider the scenario of deterministic classical information transmission between multiple senders and a single receiver, when they a priori share a multipartite quantum state - an attempt towards building a deterministic dense coding network. Specifically, we prove that in the case of two or three senders and a single receiver, generalized Greenberger-Horne-Zeilinger (gGHZ) states are not beneficial for sending classical information deterministically beyond the classical limit, except when the shared state is the GHZ state itself. On the other hand, three- and four-qubit generalized W (gW) states with specific parameters as well as the four-qubit Dicke states can provide a quantum advantage of sending the information in deterministic dense coding. Interestingly however, numerical simulations in the three-qubit scenario reveal that the percentage of states from the GHZ-class that are deterministic dense codeable is higher than that of states from the W-class.
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.
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
Energy-efficient sensing in wireless sensor networks using compressed sensing.
Razzaque, Mohammad Abdur; Dobson, Simon
2014-02-12
Sensing of the application environment is the main purpose of a wireless sensor network. Most existing energy management strategies and compression techniques assume that the sensing operation consumes significantly less energy than radio transmission and reception. This assumption does not hold in a number of practical applications. Sensing energy consumption in these applications may be comparable to, or even greater than, that of the radio. In this work, we support this claim by a quantitative analysis of the main operational energy costs of popular sensors, radios and sensor motes. In light of the importance of sensing level energy costs, especially for power hungry sensors, we consider compressed sensing and distributed compressed sensing as potential approaches to provide energy efficient sensing in wireless sensor networks. Numerical experiments investigating the effectiveness of compressed sensing and distributed compressed sensing using real datasets show their potential for efficient utilization of sensing and overall energy costs in wireless sensor networks. It is shown that, for some applications, compressed sensing and distributed compressed sensing can provide greater energy efficiency than transform coding and model-based adaptive sensing in wireless sensor networks.
NASA Astrophysics Data System (ADS)
Stack, J. R.; Guthrie, R. S.; Cramer, M. A.
2009-05-01
The purpose of this paper is to outline the requisite technologies and enabling capabilities for network-centric sensor data analysis within the mine warfare community. The focus includes both automated processing and the traditional humancentric post-mission analysis (PMA) of tactical and environmental sensor data. This is motivated by first examining the high-level network-centric guidance and noting the breakdown in the process of distilling actionable requirements from this guidance. Examples are provided that illustrate the intuitive and substantial capability improvement resulting from processing sensor data jointly in a network-centric fashion. Several candidate technologies are introduced including the ability to fully process multi-sensor data given only partial overlap in sensor coverage and the ability to incorporate target identification information in stride. Finally the critical enabling capabilities are outlined including open architecture, open business, and a concept of operations. This ability to process multi-sensor data in a network-centric fashion is a core enabler of the Navy's vision and will become a necessity with the increasing number of manned and unmanned sensor systems and the requirement for their simultaneous use.
A controllable sensor management algorithm capable of learning
NASA Astrophysics Data System (ADS)
Osadciw, Lisa A.; Veeramacheneni, Kalyan K.
2005-03-01
Sensor management technology progress is challenged by the geographic space it spans, the heterogeneity of the sensors, and the real-time timeframes within which plans controlling the assets are executed. This paper presents a new sensor management paradigm and demonstrates its application in a sensor management algorithm designed for a biometric access control system. This approach consists of an artificial intelligence (AI) algorithm focused on uncertainty measures, which makes the high level decisions to reduce uncertainties and interfaces with the user, integrated cohesively with a bottom up evolutionary algorithm, which optimizes the sensor network"s operation as determined by the AI algorithm. The sensor management algorithm presented is composed of a Bayesian network, the AI algorithm component, and a swarm optimization algorithm, the evolutionary algorithm. Thus, the algorithm can change its own performance goals in real-time and will modify its own decisions based on observed measures within the sensor network. The definition of the measures as well as the Bayesian network determine the robustness of the algorithm and its utility in reacting dynamically to changes in the global system.
Optimisation in the Design of Environmental Sensor Networks with Robustness Consideration
Budi, Setia; de Souza, Paulo; Timms, Greg; Malhotra, Vishv; Turner, Paul
2015-01-01
This work proposes the design of Environmental Sensor Networks (ESN) through balancing robustness and redundancy. An Evolutionary Algorithm (EA) is employed to find the optimal placement of sensor nodes in the Region of Interest (RoI). Data quality issues are introduced to simulate their impact on the performance of the ESN. Spatial Regression Test (SRT) is also utilised to promote robustness in data quality of the designed ESN. The proposed method provides high network representativeness (fit for purpose) with minimum sensor redundancy (cost), and ensures robustness by enabling the network to continue to achieve its objectives when some sensors fail. PMID:26633392
Authentication and Key Establishment in Dynamic Wireless Sensor Networks
Qiu, Ying; Zhou, Jianying; Baek, Joonsang; Lopez, Javier
2010-01-01
When a sensor node roams within a very large and distributed wireless sensor network, which consists of numerous sensor nodes, its routing path and neighborhood keep changing. In order to provide a high level of security in this environment, the moving sensor node needs to be authenticated to new neighboring nodes and a key established for secure communication. The paper proposes an efficient and scalable protocol to establish and update the authentication key in a dynamic wireless sensor network environment. The protocol guarantees that two sensor nodes share at least one key with probability 1 (100%) with less memory and energy cost, while not causing considerable communication overhead. PMID:22319321
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
Sensor Networks in the Low Lands
Meratnia, Nirvana; van der Zwaag, Berend Jan; van Dijk, Hylke W.; Bijwaard, Dennis J. A.; Havinga, Paul J. M.
2010-01-01
This paper provides an overview of scientific and industrial developments of the last decade in the area of sensor networks in The Netherlands (Low Lands). The goal is to highlight areas in which the Netherlands has made most contributions and is currently a dominant player in the field of sensor networks. On the one hand, motivations, addressed topics, and initiatives taken in this period are presented, while on the other hand, special emphasis is given to identifying current and future trends and formulating a vision for the coming five to ten years. The presented overview and trend analysis clearly show that Dutch research and industrial efforts, in line with recent worldwide developments in the field of sensor technology, present a clear shift from sensor node platforms, operating systems, communication, networking, and data management aspects of the sensor networks to reasoning/cognition, control, and actuation. PMID:22163669
An Enhanced PSO-Based Clustering Energy Optimization Algorithm for Wireless Sensor Network.
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.
Shipboard Wireless Sensor Networks Utilizing Zigbee Technology
2006-09-01
This thesis studies the feasibility of utilizing Zigbee standard devices to create a shipboard wireless sensor network . Two primary methods were used...the research effort would be a completely wireless sensor network which would result in a net savings in man hours required to maintain and monitor
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...
Wireless sensor network effectively controls center pivot irrigation of sorghum
USDA-ARS?s Scientific Manuscript database
Robust automatic irrigation scheduling has been demonstrated using wired sensors and sensor network systems with subsurface drip and moving irrigation systems. However, there are limited studies that report on crop yield and water use efficiency resulting from the use of wireless networks to automat...
Real-time sensor data validation
NASA Technical Reports Server (NTRS)
Bickmore, Timothy W.
1994-01-01
This report describes the status of an on-going effort to develop software capable of detecting sensor failures on rocket engines in real time. This software could be used in a rocket engine controller to prevent the erroneous shutdown of an engine due to sensor failures which would otherwise be interpreted as engine failures by the control software. The approach taken combines analytical redundancy with Bayesian belief networks to provide a solution which has well defined real-time characteristics and well-defined error rates. Analytical redundancy is a technique in which a sensor's value is predicted by using values from other sensors and known or empirically derived mathematical relations. A set of sensors and a set of relations among them form a network of cross-checks which can be used to periodically validate all of the sensors in the network. Bayesian belief networks provide a method of determining if each of the sensors in the network is valid, given the results of the cross-checks. This approach has been successfully demonstrated on the Technology Test Bed Engine at the NASA Marshall Space Flight Center. Current efforts are focused on extending the system to provide a validation capability for 100 sensors on the Space Shuttle Main Engine.
ESAM: Endocrine inspired Sensor Activation Mechanism for multi-target tracking in WSNs
NASA Astrophysics Data System (ADS)
Adil Mahdi, Omar; Wahab, Ainuddin Wahid Abdul; Idris, Mohd Yamani Idna; Znaid, Ammar Abu; Khan, Suleman; Al-Mayouf, Yusor Rafid Bahar
2016-10-01
Target tracking is a significant application of wireless sensor networks (WSNs) in which deployment of self-organizing and energy efficient algorithms is required. The tracking accuracy increases as more sensor nodes are activated around the target but more energy is consumed. Thus, in this study, we focus on limiting the number of sensors by forming an ad-hoc network that operates autonomously. This will reduce the energy consumption and prolong the sensor network lifetime. In this paper, we propose a fully distributed algorithm, an Endocrine inspired Sensor Activation Mechanism for multi target-tracking (ESAM) which reflecting the properties of real life sensor activation system based on the information circulating principle in the endocrine system of the human body. Sensor nodes in our network are secreting different hormones according to certain rules. The hormone level enables the nodes to regulate an efficient sleep and wake up cycle of nodes to reduce the energy consumption. It is evident from the simulation results that the proposed ESAM in autonomous sensor network exhibits a stable performance without the need of commands from a central controller. Moreover, the proposed ESAM generates more efficient and persistent results as compared to other algorithms for tracking an invading object.
Hao, Kun; Jin, Zhigang; Shen, Haifeng; Wang, Ying
2015-05-28
Efficient routing protocols for data packet delivery are crucial to underwater sensor networks (UWSNs). However, communication in UWSNs is a challenging task because of the characteristics of the acoustic channel. Network coding is a promising technique for efficient data packet delivery thanks to the broadcast nature of acoustic channels and the relatively high computation capabilities of the sensor nodes. In this work, we present GPNC, a novel geographic routing protocol for UWSNs that incorporates partial network coding to encode data packets and uses sensor nodes' location information to greedily forward data packets to sink nodes. GPNC can effectively reduce network delays and retransmissions of redundant packets causing additional network energy consumption. Simulation results show that GPNC can significantly improve network throughput and packet delivery ratio, while reducing energy consumption and network latency when compared with other routing protocols.
Semantic Likelihood Models for Bayesian Inference in Human-Robot Interaction
NASA Astrophysics Data System (ADS)
Sweet, Nicholas
Autonomous systems, particularly unmanned aerial systems (UAS), remain limited in au- tonomous capabilities largely due to a poor understanding of their environment. Current sensors simply do not match human perceptive capabilities, impeding progress towards full autonomy. Recent work has shown the value of humans as sources of information within a human-robot team; in target applications, communicating human-generated 'soft data' to autonomous systems enables higher levels of autonomy through large, efficient information gains. This requires development of a 'human sensor model' that allows soft data fusion through Bayesian inference to update the probabilistic belief representations maintained by autonomous systems. Current human sensor models that capture linguistic inputs as semantic information are limited in their ability to generalize likelihood functions for semantic statements: they may be learned from dense data; they do not exploit the contextual information embedded within groundings; and they often limit human input to restrictive and simplistic interfaces. This work provides mechanisms to synthesize human sensor models from constraints based on easily attainable a priori knowledge, develops compression techniques to capture information-dense semantics, and investigates the problem of capturing and fusing semantic information contained within unstructured natural language. A robotic experimental testbed is also developed to validate the above contributions.
Autonomous chemical and biological miniature wireless-sensor
NASA Astrophysics Data System (ADS)
Goldberg, Bar-Giora
2005-05-01
The presentation discusses a new concept and a paradigm shift in biological, chemical and explosive sensor system design and deployment. From large, heavy, centralized and expensive systems to distributed wireless sensor networks utilizing miniature platforms (nodes) that are lightweight, low cost and wirelessly connected. These new systems are possible due to the emergence and convergence of new innovative radio, imaging, networking and sensor technologies. Miniature integrated radio-sensor networks, is a technology whose time has come. These network systems are based on large numbers of distributed low cost and short-range wireless platforms that sense and process their environment and communicate data thru a network to a command center. The recent emergence of chemical and explosive sensor technology based on silicon nanostructures, coupled with the fast evolution of low-cost CMOS imagers, low power DSP engines and integrated radio chips, has created an opportunity to realize the vision of autonomous wireless networks. These threat detection networks will perform sophisticated analysis at the sensor node and convey alarm information up the command chain. Sensor networks of this type are expected to revolutionize the ability to detect and locate biological, chemical, or explosive threats. The ability to distribute large numbers of low-cost sensors over large areas enables these devices to be close to the targeted threats and therefore improve detection efficiencies and enable rapid counter responses. These sensor networks will be used for homeland security, shipping container monitoring, and other applications such as laboratory medical analysis, drug discovery, automotive, environmental and/or in-vivo monitoring. Avaak"s system concept is to image a chromatic biological, chemical and/or explosive sensor utilizing a digital imager, analyze the images and distribute alarm or image data wirelessly through the network. All the imaging, processing and communications would take place within the miniature, low cost distributed sensor platforms. This concept however presents a significant challenge due to a combination and convergence of required new technologies, as mentioned above. Passive biological and chemical sensors with very high sensitivity and which require no assaying are in development using a technique to optically and chemically encode silicon wafers with tailored nanostructures. The silicon wafer is patterned with nano-structures designed to change colors ad patterns when exposed to the target analytes (TICs, TIMs, VOC). A small video camera detects the color and pattern changes on the sensor. To determine if an alarm condition is present, an on board DSP processor, using specialized image processing algorithms and statistical analysis, determines if color gradient changes occurred on the sensor array. These sensors can detect several agents simultaneously. This system is currently under development by Avaak, with funding from DARPA through an SBIR grant.
SensorKit: An End-to-End Solution for Environmental Sensor Networking
NASA Astrophysics Data System (ADS)
Silva, F.; Graham, E.; Deschon, A.; Lam, Y.; Goldman, J.; Wroclawski, J.; Kaiser, W.; Benzel, T.
2008-12-01
Modern day sensor network technology has shown great promise to transform environmental data collection. However, despite the promise, these systems have remained the purview of the engineers and computer scientists who design them rather than a useful tool for the environmental scientists who need them. SensorKit is conceived of as a way to make wireless sensor networks accessible to The People: it is an advanced, powerful tool for sensor data collection that does not require advanced technological know-how. We are aiming to make wireless sensor networks for environmental science as simple as setting up a standard home computer network by providing simple, tested configurations of commercially-available hardware, free and easy-to-use software, and step-by-step tutorials. We designed and built SensorKit using a simplicity-through-sophistication approach, supplying users a powerful sensor to database end-to-end system with a simple and intuitive user interface. Our objective in building SensorKit was to make the prospect of using environmental sensor networks as simple as possible. We built SensorKit from off the shelf hardware components, using the Compact RIO platform from National Instruments for data acquisition due to its modular architecture and flexibility to support a large number of sensor types. In SensorKit, we support various types of analog, digital and networked sensors. Our modular software architecture allows us to abstract sensor details and provide users a common way to acquire data and to command different types of sensors. SensorKit is built on top of the Sensor Processing and Acquisition Network (SPAN), a modular framework for acquiring data in the field, moving it reliably to the scientist institution, and storing it in an easily-accessible database. SPAN allows real-time access to the data in the field by providing various options for long haul communication, such as cellular and satellite links. Our system also features reliable data storage and transmission, using a custody transfer mechanism that ensures data is retained until successful delivery to the scientist can be confirmed. The ability for the scientist to communicate in real-time with the sensor network in the field enables remote sensor reconfiguration and system health and status monitoring. We use a spiral approach of design, test, deploy and revise, and, by going to the field frequently and getting feedback from field scientists, we have been able to include additional functionality that is useful to the scientist while ensuring SensorKit remains intuitive to operate. Users can configure, control, and monitor SensorKit using a number of tools we have developed. An intuitive user interface running on a desktop or laptop allows scientists to setup the system, add and configure sensors, and specify when and how the data will be collected. We also have a mobile version of our interface that runs on a PDA and lets scientists calibrate sensors and "tune" the system while in the field, allowing for data validation before leaving the field and returning to the research lab. SensorKit also features SensorBase, an intuitive user interface built on top of a standard SQL database, which allows scientists to store and share their data with other researchers. SensorKit has been used for diverse scientific applications and deployed throughout the world: from studying mercury cycling in rice paddies in China, to ecological research in the neotropical rainforests of Costa Rica, to monitoring the contamination of salt lakes in Argentina.
A Hardware-Supported Algorithm for Self-Managed and Choreographed Task Execution in Sensor Networks.
Bordel, Borja; Miguel, Carlos; Alcarria, Ramón; Robles, Tomás
2018-03-07
Nowadays, sensor networks are composed of a great number of tiny resource-constraint nodes, whose management is increasingly more complex. In fact, although collaborative or choreographic task execution schemes are which fit in the most perfect way with the nature of sensor networks, they are rarely implemented because of the high resource consumption of these algorithms (especially if networks include many resource-constrained devices). On the contrary, hierarchical networks are usually designed, in whose cusp it is included a heavy orchestrator with a remarkable processing power, being able to implement any necessary management solution. However, although this orchestration approach solves most practical management problems of sensor networks, a great amount of the operation time is wasted while nodes request the orchestrator to address a conflict and they obtain the required instructions to operate. Therefore, in this paper it is proposed a new mechanism for self-managed and choreographed task execution in sensor networks. The proposed solution considers only a lightweight gateway instead of traditional heavy orchestrators and a hardware-supported algorithm, which consume a negligible amount of resources in sensor nodes. The gateway avoids the congestion of the entire sensor network and the hardware-supported algorithm enables a choreographed task execution scheme, so no particular node is overloaded. The performance of the proposed solution is evaluated through numerical and electronic ModelSim-based simulations.
A Hardware-Supported Algorithm for Self-Managed and Choreographed Task Execution in Sensor Networks
2018-01-01
Nowadays, sensor networks are composed of a great number of tiny resource-constraint nodes, whose management is increasingly more complex. In fact, although collaborative or choreographic task execution schemes are which fit in the most perfect way with the nature of sensor networks, they are rarely implemented because of the high resource consumption of these algorithms (especially if networks include many resource-constrained devices). On the contrary, hierarchical networks are usually designed, in whose cusp it is included a heavy orchestrator with a remarkable processing power, being able to implement any necessary management solution. However, although this orchestration approach solves most practical management problems of sensor networks, a great amount of the operation time is wasted while nodes request the orchestrator to address a conflict and they obtain the required instructions to operate. Therefore, in this paper it is proposed a new mechanism for self-managed and choreographed task execution in sensor networks. The proposed solution considers only a lightweight gateway instead of traditional heavy orchestrators and a hardware-supported algorithm, which consume a negligible amount of resources in sensor nodes. The gateway avoids the congestion of the entire sensor network and the hardware-supported algorithm enables a choreographed task execution scheme, so no particular node is overloaded. The performance of the proposed solution is evaluated through numerical and electronic ModelSim-based simulations. PMID:29518986
Traffic Adaptive Energy Efficient and Low Latency Medium Access Control for Wireless Sensor Networks
NASA Astrophysics Data System (ADS)
Yadav, Rajesh; Varma, Shirshu; Malaviya, N.
2008-05-01
Medium access control for wireless sensor networks has been a very active research area in the recent years. The traditional wireless medium access control protocol such as IEEE 802.11 is not suitable for the sensor network application because these are battery powered. The recharging of these sensor nodes is expensive and also not possible. The most of the literature in the medium access for the sensor network focuses on the energy efficiency. The proposed MAC protocol solves the energy inefficiency caused by idle listening, control packet overhead and overhearing taking nodes latency into consideration based on the network traffic. Simulation experiments have been performed to demonstrate the effectiveness of the proposed approach. The validation of the simulation results of the proposed MAC has been done by comparing it with the analytical model. This protocol has been simulated in Network Simulator ns-2.
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.
A Novel Re-keying Function Protocol (NRFP) For Wireless Sensor Network Security.
Abdullah, Maan Younis; Hua, Gui Wei; Alsharabi, Naif
2008-12-04
This paper describes a novel re-keying function protocol (NRFP) for wireless sensor network security. A re-keying process management system for sensor networks is designed to support in-network processing. The design of the protocol is motivated by decentralization key management for wireless sensor networks (WSNs), covering key deployment, key refreshment, and key establishment. NRFP supports the establishment of novel administrative functions for sensor nodes that derive/re-derive a session key for each communication session. The protocol proposes direct connection, in-direct connection and hybrid connection. NRFP also includes an efficient protocol for local broadcast authentication based on the use of one-way key chains. A salient feature of the authentication protocol is that it supports source authentication without precluding in-network processing. Security and performance analysis shows that it is very efficient in computation, communication and storage and, that NRFP is also effective in defending against many sophisticated attacks.
Networking Sensors for Information Dominance - Joint Signal Processing and Communication Design
2012-01-01
2012 4. TITLE AND SUBTITLE NETWORKING SENSORS FOR INFORMATION DOMINANCE - JOINT SIGNAL PROCESSING AND COMMUNICATION DESIGN, Final Report for FA9550...Rev. 2-89) Prescribed by ANSI Std. Z39-18 298-102 Public A AFRL-OSR-VA-TR-2012-0729 NETWORKING SENSORS FOR INFORMATION DOMINANCE - JOINT
Applying Sensor Networks to Evaluate Air Pollutant Emissions from Fugitive and Area Sources
This is a presentation to be given at Duke University's Wireless Intelligent Sensor Network workshop on June 5, 2013. The presentation discusses the evaluation of a low cost carbon monoxide sensor network applied at a recent forest fire study and also evaluated against a referen...
Unmanned Ground Vehicle Navigation and Coverage Hole Patching in Wireless Sensor Networks
ERIC Educational Resources Information Center
Zhang, Guyu
2013-01-01
This dissertation presents a study of an Unmanned Ground Vehicle (UGV) navigation and coverage hole patching in coordinate-free and localization-free Wireless Sensor Networks (WSNs). Navigation and coverage maintenance are related problems since coverage hole patching requires effective navigation in the sensor network environment. A…
Performance of a wireless sensor network for crop monitoring and irrigation control
USDA-ARS?s Scientific Manuscript database
Robust automatic irrigation scheduling has been demonstrated using wired sensors and sensor network systems with subsurface drip and moving irrigation systems. However, there are limited studies that report on crop yield and water use efficiency resulting from the use of wireless networks to automat...
Social Network Analysis and Its Applications in Wireless Sensor and Vehicular Networks
NASA Astrophysics Data System (ADS)
Papadimitriou, Alexis; Katsaros, Dimitrios; Manolopoulos, Yannis
Ever since the introduction of wireless sensor networks in the research and development agenda, the corresponding community has been eager to harness the endless possibilities that this new technology has to offer. These micro sensor nodes, whose capabilities have skyrocketed over the last couple of years, have allowed for a wide range of applications to be created; applications that not so long ago would seem impossible, impractical and time-consuming. It would only be logical to expect that researchers from other fields would take an interest in sensor networks, hence expanding the already wide variety of algorithms, theoretical proofs and applications that existed beforehand. Social Network Analysis is one such field, which has instigated a paradigm shift in the way we view sensor nodes.
Simple Random Sampling-Based Probe Station Selection for Fault Detection in Wireless Sensor Networks
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
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.
Implementation Of Secure 6LoWPAN Communications For Tactical Wireless Sensor Networks
2016-09-01
wireless sensor networks (WSN) consist of power -constrained devices spread throughout a region-of-interest to provide data extraction in real time...1 A. LOW POWER WIRELESS SENSOR NETWORKS ............................1 B. INTRODUCTION TO...communication protocol for low power wireless personal area networks Since the IEEE 802.15.4 standard only defines the first two layers of the Open
Unattended Ground Sensors for Expeditionary Force 21 Intelligence Collections
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
Low-power secure body area network for vital sensors toward IEEE802.15.6.
Kuroda, Masahiro; Qiu, Shuye; Tochikubo, Osamu
2009-01-01
Many healthcare/medical services have started using personal area networks, such as Bluetooth and ZigBee; these networks consist of various types of vital sensors. These works focus on generalized functions for sensor networks that expect enough battery capacity and low-power CPU/RF (Radio Frequency) modules, but less attention to easy-to-use privacy protection. In this paper, we propose a commercially-deployable secure body area network (S-BAN) with reduced computational burden on a real sensor that has limited RAM/ROM sizes and CPU/RF power consumption under a light-weight battery. Our proposed S-BAN provides vital data ordering among sensors that are involved in an S-BAN and also provides low-power networking with zero-administration security by automatic private key generation. We design and implement the power-efficient media access control (MAC) with resource-constraint security in sensors. Then, we evaluate the power efficiency of the S-BAN consisting of small sensors, such as an accessory type ECG and ring-type SpO2. The evaluation of power efficiency of the S-BAN using real sensors convinces us in deploying S-BAN and will also help us in providing feedbacks to the IEEE802.15.6 MAC, which will be the standard for BANs.
A Wireless Sensor Network for Vineyard Monitoring That Uses Image Processing
Lloret, Jaime; Bosch, Ignacio; Sendra, Sandra; Serrano, Arturo
2011-01-01
The first step to detect when a vineyard has any type of deficiency, pest or disease is to observe its stems, its grapes and/or its leaves. To place a sensor in each leaf of every vineyard is obviously not feasible in terms of cost and deployment. We should thus look for new methods to detect these symptoms precisely and economically. In this paper, we present a wireless sensor network where each sensor node takes images from the field and internally uses image processing techniques to detect any unusual status in the leaves. This symptom could be caused by a deficiency, pest, disease or other harmful agent. When it is detected, the sensor node sends a message to a sink node through the wireless sensor network in order to notify the problem to the farmer. The wireless sensor uses the IEEE 802.11 a/b/g/n standard, which allows connections from large distances in open air. This paper describes the wireless sensor network design, the wireless sensor deployment, how the node processes the images in order to monitor the vineyard, and the sensor network traffic obtained from a test bed performed in a flat vineyard in Spain. Although the system is not able to distinguish between deficiency, pest, disease or other harmful agents, a symptoms image database and a neuronal network could be added in order learn from the experience and provide an accurate problem diagnosis. PMID:22163948
A wireless sensor network for vineyard monitoring that uses image processing.
Lloret, Jaime; Bosch, Ignacio; Sendra, Sandra; Serrano, Arturo
2011-01-01
The first step to detect when a vineyard has any type of deficiency, pest or disease is to observe its stems, its grapes and/or its leaves. To place a sensor in each leaf of every vineyard is obviously not feasible in terms of cost and deployment. We should thus look for new methods to detect these symptoms precisely and economically. In this paper, we present a wireless sensor network where each sensor node takes images from the field and internally uses image processing techniques to detect any unusual status in the leaves. This symptom could be caused by a deficiency, pest, disease or other harmful agent. When it is detected, the sensor node sends a message to a sink node through the wireless sensor network in order to notify the problem to the farmer. The wireless sensor uses the IEEE 802.11 a/b/g/n standard, which allows connections from large distances in open air. This paper describes the wireless sensor network design, the wireless sensor deployment, how the node processes the images in order to monitor the vineyard, and the sensor network traffic obtained from a test bed performed in a flat vineyard in Spain. Although the system is not able to distinguish between deficiency, pest, disease or other harmful agents, a symptoms image database and a neuronal network could be added in order learn from the experience and provide an accurate problem diagnosis.
Leveraging EarthScope USArray with the Central and Eastern United States Seismic Network
NASA Astrophysics Data System (ADS)
Busby, R.; Sumy, D. F.; Woodward, R.; Frassetto, A.; Brudzinski, M.
2015-12-01
Recent earthquakes, such as the 2011 M5.8 Mineral, Virginia earthquake, raised awareness of the comparative lack of knowledge about seismicity, site response to ground shaking, and the basic geologic underpinnings in this densely populated region. With this in mind, the National Science Foundation, United States Geological Survey, United States Nuclear Regulatory Commission, and Department of Energy supported the creation of the Central and Eastern United States Seismic Network (CEUSN). These agencies, along with the IRIS Consortium who operates the network, recognized the unique opportunity to retain EarthScope Transportable Array (TA) seismic stations in this region beyond the standard deployment duration of two years per site. The CEUSN project supports 159 broadband TA stations, more than 30 with strong motion sensors added, that are scheduled to operate through 2017. Stations were prioritized in regions of elevated seismic hazard that have not been traditionally heavily monitored, such as the Charlevoix and Central Virginia Seismic Zones, and in regions proximal to nuclear power plants and other critical facilities. The stations (network code N4) transmit data in real time, with broadband and strong motion sensors sampling at 100 samples per second. More broadly the CEUSN concept also recognizes the existing backbone coverage of permanently operating seismometers in the CEUS, and forms a network of over 300 broadband stations. This multi-agency collaboration is motivated by the opportunity to use one facility to address multiple missions and needs in a way that is rarely possible, and to produce data that enables both researchers and federal agencies to better understand seismic hazard potential and associated seismic risks. In June 2015, the CEUSN Working Group (www.usarray.org/ceusn_working_group) was formed to review and provide advice to IRIS Management on the performance of the CEUSN as it relates to the target scientific goals and objectives. Map shows the 159 CEUSN stations (yellow) that will be operated and maintained by the IRIS Consortium through 2017. The CEUSN stations were selected for proximity to nuclear power plants (black squares) and other critical infrastructure as well as to more evenly distribute seismic stations across the central and eastern United States.
Earthquake Monitoring with the MyShake Global Smartphone Seismic Network
NASA Astrophysics Data System (ADS)
Inbal, A.; Kong, Q.; Allen, R. M.; Savran, W. H.
2017-12-01
Smartphone arrays have the potential for significantly improving seismic monitoring in sparsely instrumented urban areas. This approach benefits from the dense spatial coverage of users, as well as from communication and computational capabilities built into smartphones, which facilitate big seismic data transfer and analysis. Advantages in data acquisition with smartphones trade-off with factors such as the low-quality sensors installed in phones, high noise levels, and strong network heterogeneity, all of which limit effective seismic monitoring. Here we utilize network and array-processing schemes to asses event detectability with the MyShake global smartphone network. We examine the benefits of using this network in either triggered or continuous modes of operation. A global database of ground motions measured on stationary phones triggered by M2-6 events is used to establish detection probabilities. We find that the probability of detecting an M=3 event with a single phone located <10 km from the epicenter exceeds 70%. Due to the sensor's self-noise, smaller magnitude events at short epicentral distances are very difficult to detect. To increase the signal-to-noise ratio, we employ array back-projection techniques on continuous data recorded by thousands of phones. In this class of methods, the array is used as a spatial filter that suppresses signals emitted from shallow noise sources. Filtered traces are stacked to further enhance seismic signals from deep sources. We benchmark our technique against traditional location algorithms using recordings from California, a region with large MyShake user database. We find that locations derived from back-projection images of M 3 events recorded by >20 nearby phones closely match the regional catalog locations. We use simulated broadband seismic data to examine how location uncertainties vary with user distribution and noise levels. To this end, we have developed an empirical noise model for the metropolitan Los-Angeles (LA) area. We find that densities larger than 100 stationary phones/km2 are required to accurately locate M 2 events in the LA basin. Given the projected MyShake user distribution, that condition may be met within the next few years.
Code of Federal Regulations, 2014 CFR
2014-10-01
... the images of buried objects or determining the physical properties within the ground. The energy from... dense enough to absorb the transmitted signal. (j) Surveillance system. A field disturbance sensor used...
Code of Federal Regulations, 2013 CFR
2013-10-01
... the images of buried objects or determining the physical properties within the ground. The energy from... dense enough to absorb the transmitted signal. (j) Surveillance system. A field disturbance sensor used...
Code of Federal Regulations, 2010 CFR
2010-10-01
... the images of buried objects or determining the physical properties within the ground. The energy from... dense enough to absorb the transmitted signal. (j) Surveillance system. A field disturbance sensor used...
Code of Federal Regulations, 2011 CFR
2011-10-01
... the images of buried objects or determining the physical properties within the ground. The energy from... dense enough to absorb the transmitted signal. (j) Surveillance system. A field disturbance sensor used...
Code of Federal Regulations, 2012 CFR
2012-10-01
... the images of buried objects or determining the physical properties within the ground. The energy from... dense enough to absorb the transmitted signal. (j) Surveillance system. A field disturbance sensor used...
Spider-web inspired multi-resolution graphene tactile sensor.
Liu, Lu; Huang, Yu; Li, Fengyu; Ma, Ying; Li, Wenbo; Su, Meng; Qian, Xin; Ren, Wanjie; Tang, Kanglai; Song, Yanlin
2018-05-08
Multi-dimensional accurate response and smooth signal transmission are critical challenges in the advancement of multi-resolution recognition and complex environment analysis. Inspired by the structure-activity relationship between discrepant microstructures of the spiral and radial threads in a spider web, we designed and printed graphene with porous and densely-packed microstructures to integrate into a multi-resolution graphene tactile sensor. The three-dimensional (3D) porous graphene structure performs multi-dimensional deformation responses. The laminar densely-packed graphene structure contributes excellent conductivity with flexible stability. The spider-web inspired printed pattern inherits orientational and locational kinesis tracking. The multi-structure construction with homo-graphene material can integrate discrepant electronic properties with remarkable flexibility, which will attract enormous attention for electronic skin, wearable devices and human-machine interactions.
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
ShakeNet: a portable wireless sensor network for instrumenting large civil structures
Kohler, Monica D.; Hao, Shuai; Mishra, Nilesh; Govindan, Ramesh; Nigbor, Robert
2015-08-03
We report our findings from a U.S. Geological Survey (USGS) National Earthquake Hazards Reduction Program-funded project to develop and test a wireless, portable, strong-motion network of up to 40 triaxial accelerometers for structural health monitoring. The overall goal of the project was to record ambient vibrations for several days from USGS-instrumented structures. Structural health monitoring has important applications in fields like civil engineering and the study of earthquakes. The emergence of wireless sensor networks provides a promising means to such applications. However, while most wireless sensor networks are still in the experimentation stage, very few take into consideration the realistic earthquake engineering application requirements. To collect comprehensive data for structural health monitoring for civil engineers, high-resolution vibration sensors and sufficient sampling rates should be adopted, which makes it challenging for current wireless sensor network technology in the following ways: processing capabilities, storage limit, and communication bandwidth. The wireless sensor network has to meet expectations set by wired sensor devices prevalent in the structural health monitoring community. For this project, we built and tested an application-realistic, commercially based, portable, wireless sensor network called ShakeNet for instrumentation of large civil structures, especially for buildings, bridges, or dams after earthquakes. Two to three people can deploy ShakeNet sensors within hours after an earthquake to measure the structural response of the building or bridge during aftershocks. ShakeNet involved the development of a new sensing platform (ShakeBox) running a software suite for networking, data collection, and monitoring. Deployments reported here on a tall building and a large dam were real-world tests of ShakeNet operation, and helped to refine both hardware and software.
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.
Low Latency MAC Protocol in Wireless Sensor Networks Using Timing Offset
NASA Astrophysics Data System (ADS)
Choi, Seung Sik
This paper proposes a low latency MAC protocol that can be used in sensor networks. To extend the lifetime of sensor nodes, the conventional solution is to synchronize active/sleep periods of all sensor nodes. However, due to these synchronized sensor nodes, packets in the intermediate nodes must wait until the next node wakes up before it can forward a packet. This induces a large delay in sensor nodes. To solve this latency problem, a clustered sensor network which uses two types of sensor nodes and layered architecture is considered. Clustered heads in each cluster are synchronized with different timing offsets to reduce the sleep delay. Using this concept, the latency problem can be solved and more efficient power usage can be obtained.
Wireless sensor networks for heritage object deformation detection and tracking algorithm.
Xie, Zhijun; Huang, Guangyan; Zarei, Roozbeh; He, Jing; Zhang, Yanchun; Ye, Hongwu
2014-10-31
Deformation is the direct cause of heritage object collapse. It is significant to monitor and signal the early warnings of the deformation of heritage objects. However, traditional heritage object monitoring methods only roughly monitor a simple-shaped heritage object as a whole, but cannot monitor complicated heritage objects, which may have a large number of surfaces inside and outside. Wireless sensor networks, comprising many small-sized, low-cost, low-power intelligent sensor nodes, are more useful to detect the deformation of every small part of the heritage objects. Wireless sensor networks need an effective mechanism to reduce both the communication costs and energy consumption in order to monitor the heritage objects in real time. In this paper, we provide an effective heritage object deformation detection and tracking method using wireless sensor networks (EffeHDDT). In EffeHDDT, we discover a connected core set of sensor nodes to reduce the communication cost for transmitting and collecting the data of the sensor networks. Particularly, we propose a heritage object boundary detecting and tracking mechanism. Both theoretical analysis and experimental results demonstrate that our EffeHDDT method outperforms the existing methods in terms of network traffic and the precision of the deformation detection.
Simulating Operation of a Complex Sensor Network
NASA Technical Reports Server (NTRS)
Jennings, Esther; Clare, Loren; Woo, Simon
2008-01-01
Simulation Tool for ASCTA Microsensor Network Architecture (STAMiNA) ["ASCTA" denotes the Advanced Sensors Collaborative Technology Alliance.] is a computer program for evaluating conceptual sensor networks deployed over terrain to provide military situational awareness. This or a similar program is needed because of the complexity of interactions among such diverse phenomena as sensing and communication portions of a network, deployment of sensor nodes, effects of terrain, data-fusion algorithms, and threat characteristics. STAMiNA is built upon a commercial network-simulator engine, with extensions to include both sensing and communication models in a discrete-event simulation environment. Users can define (1) a mission environment, including terrain features; (2) objects to be sensed; (3) placements and modalities of sensors, abilities of sensors to sense objects of various types, and sensor false alarm rates; (4) trajectories of threatening objects; (5) means of dissemination and fusion of data; and (6) various network configurations. By use of STAMiNA, one can simulate detection of targets through sensing, dissemination of information by various wireless communication subsystems under various scenarios, and fusion of information, incorporating such metrics as target-detection probabilities, false-alarm rates, and communication loads, and capturing effects of terrain and threat.
Wireless Sensor Networks for Heritage Object Deformation Detection and Tracking Algorithm
Xie, Zhijun; Huang, Guangyan; Zarei, Roozbeh; He, Jing; Zhang, Yanchun; Ye, Hongwu
2014-01-01
Deformation is the direct cause of heritage object collapse. It is significant to monitor and signal the early warnings of the deformation of heritage objects. However, traditional heritage object monitoring methods only roughly monitor a simple-shaped heritage object as a whole, but cannot monitor complicated heritage objects, which may have a large number of surfaces inside and outside. Wireless sensor networks, comprising many small-sized, low-cost, low-power intelligent sensor nodes, are more useful to detect the deformation of every small part of the heritage objects. Wireless sensor networks need an effective mechanism to reduce both the communication costs and energy consumption in order to monitor the heritage objects in real time. In this paper, we provide an effective heritage object deformation detection and tracking method using wireless sensor networks (EffeHDDT). In EffeHDDT, we discover a connected core set of sensor nodes to reduce the communication cost for transmitting and collecting the data of the sensor networks. Particularly, we propose a heritage object boundary detecting and tracking mechanism. Both theoretical analysis and experimental results demonstrate that our EffeHDDT method outperforms the existing methods in terms of network traffic and the precision of the deformation detection. PMID:25365458
Large Scale Environmental Monitoring through Integration of Sensor and Mesh Networks
Jurdak, Raja; Nafaa, Abdelhamid; Barbirato, Alessio
2008-01-01
Monitoring outdoor environments through networks of wireless sensors has received interest for collecting physical and chemical samples at high spatial and temporal scales. A central challenge to environmental monitoring applications of sensor networks is the short communication range of the sensor nodes, which increases the complexity and cost of monitoring commodities that are located in geographically spread areas. To address this issue, we propose a new communication architecture that integrates sensor networks with medium range wireless mesh networks, and provides users with an advanced web portal for managing sensed information in an integrated manner. Our architecture adopts a holistic approach targeted at improving the user experience by optimizing the system performance for handling data that originates at the sensors, traverses the mesh network, and resides at the server for user consumption. This holistic approach enables users to set high level policies that can adapt the resolution of information collected at the sensors, set the preferred performance targets for their application, and run a wide range of queries and analysis on both real-time and historical data. All system components and processes will be described in this paper. PMID:27873941
Routing Protocols in Wireless Sensor Networks
Villalba, Luis Javier García; Orozco, Ana Lucila Sandoval; Cabrera, Alicia Triviño; Abbas, Cláudia Jacy Barenco
2009-01-01
The applications of wireless sensor networks comprise a wide variety of scenarios. In most of them, the network is composed of a significant number of nodes deployed in an extensive area in which not all nodes are directly connected. Then, the data exchange is supported by multihop communications. Routing protocols are in charge of discovering and maintaining the routes in the network. However, the appropriateness of a particular routing protocol mainly depends on the capabilities of the nodes and on the application requirements. This paper presents a review of the main routing protocols proposed for wireless sensor networks. Additionally, the paper includes the efforts carried out by Spanish universities on developing optimization techniques in the area of routing protocols for wireless sensor networks. PMID:22291515
An Energy-Efficient Game-Theory-Based Spectrum Decision Scheme for Cognitive Radio Sensor Networks
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
Routing protocols in wireless sensor networks.
Villalba, Luis Javier García; Orozco, Ana Lucila Sandoval; Cabrera, Alicia Triviño; Abbas, Cláudia Jacy Barenco
2009-01-01
The applications of wireless sensor networks comprise a wide variety of scenarios. In most of them, the network is composed of a significant number of nodes deployed in an extensive area in which not all nodes are directly connected. Then, the data exchange is supported by multihop communications. Routing protocols are in charge of discovering and maintaining the routes in the network. However, the appropriateness of a particular routing protocol mainly depends on the capabilities of the nodes and on the application requirements. This paper presents a review of the main routing protocols proposed for wireless sensor networks. Additionally, the paper includes the efforts carried out by Spanish universities on developing optimization techniques in the area of routing protocols for wireless sensor networks.
An Energy-Efficient Game-Theory-Based Spectrum Decision Scheme for Cognitive Radio Sensor Networks.
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.
On securing wireless sensor network--novel authentication scheme against DOS attacks.
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.
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.
Battery-free Wireless Sensor Network For Advanced Fossil-Fuel Based Power Generation
DOE Office of Scientific and Technical Information (OSTI.GOV)
Yi Jia
2011-02-28
This report summarizes technical progress achieved during the project supported by the Department of Energy under Award Number DE-FG26-07NT4306. The aim of the project was to conduct basic research into battery-free wireless sensing mechanism in order to develop novel wireless sensors and sensor network for physical and chemical parameter monitoring in a harsh environment. Passive wireless sensing platform and five wireless sensors including temperature sensor, pressure sensor, humidity sensor, crack sensor and networked sensors developed and demonstrated in our laboratory setup have achieved the objective for the monitoring of various physical and chemical parameters in a harsh environment through remotemore » power and wireless sensor communication, which is critical to intelligent control of advanced power generation system. This report is organized by the sensors developed as detailed in each progress report.« less
Ubiquitous virtual private network: a solution for WSN seamless integration.
Villa, David; Moya, Francisco; Villanueva, Félix Jesús; Aceña, Óscar; López, Juan Carlos
2014-01-06
Sensor networks are becoming an essential part of ubiquitous systems and applications. However, there are no well-defined protocols or mechanisms to access the sensor network from the enterprise information system. We consider this issue as a heterogeneous network interconnection problem, and as a result, the same concepts may be applied. Specifically, we propose the use of object-oriented middlewares to provide a virtual private network in which all involved elements (sensor nodes or computer applications) will be able to communicate as if all of them were in a single and uniform network.
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.
Li, Yue; Jha, Devesh K; Ray, Asok; Wettergren, Thomas A; Yue Li; Jha, Devesh K; Ray, Asok; Wettergren, Thomas A; Wettergren, Thomas A; Li, Yue; Ray, Asok; Jha, Devesh K
2018-06-01
This paper presents information-theoretic performance analysis of passive sensor networks for detection of moving targets. The proposed method falls largely under the category of data-level information fusion in sensor networks. To this end, a measure of information contribution for sensors is formulated in a symbolic dynamics framework. The network information state is approximately represented as the largest principal component of the time series collected across the network. To quantify each sensor's contribution for generation of the information content, Markov machine models as well as x-Markov (pronounced as cross-Markov) machine models, conditioned on the network information state, are constructed; the difference between the conditional entropies of these machines is then treated as an approximate measure of information contribution by the respective sensors. The x-Markov models represent the conditional temporal statistics given the network information state. The proposed method has been validated on experimental data collected from a local area network of passive sensors for target detection, where the statistical characteristics of environmental disturbances are similar to those of the target signal in the sense of time scale and texture. A distinctive feature of the proposed algorithm is that the network decisions are independent of the behavior and identity of the individual sensors, which is desirable from computational perspectives. Results are presented to demonstrate the proposed method's efficacy to correctly identify the presence of a target with very low false-alarm rates. The performance of the underlying algorithm is compared with that of a recent data-driven, feature-level information fusion algorithm. It is shown that the proposed algorithm outperforms the other algorithm.
NASA Astrophysics Data System (ADS)
Kohler, M. D.; Castillo, J.; Massari, A.; Clayton, R. W.
2017-12-01
Earthquake-induced motions recorded by spatially dense seismic arrays in buildings located in the northern Los Angeles basin suggest the presence of complex, amplified surface wave effects on the seismic demand of mid-rise buildings. Several moderate earthquakes produced large-amplitude, seismic energy with slow shear-wave velocities that cannot be explained or accurately modeled by any published 3D seismic velocity models or by Vs30 values. Numerical experiments are conducted to determine if sedimentary basin features are responsible for these rarely modeled and poorly documented contributions to seismic demand computations. This is accomplished through a physics-based wave propagation examination of the effects of different sedimentary basin geometries on the nonlinear response of a mid-rise structural model based on an existing, instrumented building. Using two-dimensional finite-difference predictive modeling, we show that when an earthquake focal depth is near the vertical edge of an elongated and relatively shallow sedimentary basin, dramatically amplified and complex surface waves are generated as a result of the waveguide effect introduced by this velocity structure. In addition, for certain source-receiver distances and basin geometries, body waves convert to secondary Rayleigh waves that propagate both at the free-surface interface and along the depth interface of the basin that show up as multiple large-amplitude arrivals. This study is motivated by observations from the spatially dense, high-sample-rate acceleration data recorded by the Community Seismic Network, a community-hosted strong-motion network, currently consisting of hundreds of sensors located in the southern California area. The results provide quantitative insight into the causative relationship between a sedimentary basin shape and the generation of Rayleigh waves at depth, surface waves at the free surface, scattered seismic energy, and the sensitivity of building responses to each of these.
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.
2009-09-01
Wireless Sensor Network (WSN) Simulator Research Personnel: Dr. Ali Abu-El Humos Task No. Task Current Status 1 Literature review and problem definition...networks.com/ [2] S. Dulman, P. Havinga, "A Simulation Template for Wireless Sensor Networks ," Supplement of the Sixth International Symposium on Autonomous... Sensor Network (WSN) Simulator 76 I Breakdown of the Research Activity to Tasks 76 II Description of the Tasks 76 Task 1 Literature Review and
Minimum energy information fusion in sensor networks
DOE Office of Scientific and Technical Information (OSTI.GOV)
Chapline, G
1999-05-11
In this paper we consider how to organize the sharing of information in a distributed network of sensors and data processors so as to provide explanations for sensor readings with minimal expenditure of energy. We point out that the Minimum Description Length principle provides an approach to information fusion that is more naturally suited to energy minimization than traditional Bayesian approaches. In addition we show that for networks consisting of a large number of identical sensors Kohonen self-organization provides an exact solution to the problem of combing the sensor outputs into minimal description length explanations.
ClueNet: Clustering a temporal network based on topological similarity rather than denseness.
Crawford, Joseph; Milenković, Tijana
2018-01-01
Network clustering is a very popular topic in the network science field. Its goal is to divide (partition) the network into groups (clusters or communities) of "topologically related" nodes, where the resulting topology-based clusters are expected to "correlate" well with node label information, i.e., metadata, such as cellular functions of genes/proteins in biological networks, or age or gender of people in social networks. Even for static data, the problem of network clustering is complex. For dynamic data, the problem is even more complex, due to an additional dimension of the data-their temporal (evolving) nature. Since the problem is computationally intractable, heuristic approaches need to be sought. Existing approaches for dynamic network clustering (DNC) have drawbacks. First, they assume that nodes should be in the same cluster if they are densely interconnected within the network. We hypothesize that in some applications, it might be of interest to cluster nodes that are topologically similar to each other instead of or in addition to requiring the nodes to be densely interconnected. Second, they ignore temporal information in their early steps, and when they do consider this information later on, they do so implicitly. We hypothesize that capturing temporal information earlier in the clustering process and doing so explicitly will improve results. We test these two hypotheses via our new approach called ClueNet. We evaluate ClueNet against six existing DNC methods on both social networks capturing evolving interactions between individuals (such as interactions between students in a high school) and biological networks capturing interactions between biomolecules in the cell at different ages. We find that ClueNet is superior in over 83% of all evaluation tests. As more real-world dynamic data are becoming available, DNC and thus ClueNet will only continue to gain importance.
Dense modifiable interconnections utilizing photorefractive volume holograms
NASA Astrophysics Data System (ADS)
Psaltis, Demetri; Qiao, Yong
1990-11-01
This report describes an experimental two-layer optical neural network built at Caltech. The system uses photorefractive volume holograms to implement dense, modifiable synaptic interconnections and liquid crystal light valves (LCVS) to perform nonlinear thresholding operations. Kanerva's Sparse, Distributed Memory was implemented using this network and its ability to recognize handwritten character-alphabet (A-Z) has been demonstrated experimentally. According to Kanerva's model, the first layer has fixed, random weights of interconnections and the second layer is trained by sum-of-outer-products rule. After training, the recognition rates of the network on the training set (104 patterns) and test set (520 patterns) are 100 and 50 percent, respectively.
2009-03-01
SENSOR NETWORKS THESIS Presented to the Faculty Department of Electrical and Computer Engineering Graduate School of Engineering and...hierarchical, and Secure Lock within a wireless sensor network (WSN) under the Hubenko architecture. Using a Matlab computer simulation, the impact of the...rekeying protocol should be applied given particular network parameters, such as WSN size. 10 1.3 Experimental Approach A computer simulation in
Insights into mountain precipitation and snowpack from a basin-scale wireless-sensor network
USDA-ARS?s Scientific Manuscript database
A spatially distributed wireless-sensor network, installed across the 2154 km2 portion of the 5311 km2 American River basin above 1500 m elevation, provided spatial measurements of temperature, relative humidity and snow depth. The network consisted of 10 sensor clusters, each with 10 measurement no...
A Wireless Platform for Energy Efficient Building Control Retrofits
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
NASA Astrophysics Data System (ADS)
Johnson, Nicholas E.; Bonczak, Bartosz; Kontokosta, Constantine E.
2018-07-01
The increased availability and improved quality of new sensing technologies have catalyzed a growing body of research to evaluate and leverage these tools in order to quantify and describe urban environments. Air quality, in particular, has received greater attention because of the well-established links to serious respiratory illnesses and the unprecedented levels of air pollution in developed and developing countries and cities around the world. Though numerous laboratory and field evaluation studies have begun to explore the use and potential of low-cost air quality monitoring devices, the performance and stability of these tools has not been adequately evaluated in complex urban environments, and further research is needed. In this study, we present the design of a low-cost air quality monitoring platform based on the Shinyei PPD42 aerosol monitor and examine the suitability of the sensor for deployment in a dense heterogeneous urban environment. We assess the sensor's performance during a field calibration campaign from February 7th to March 25th 2017 with a reference instrument in New York City, and present a novel calibration approach using a machine learning method that incorporates publicly available meteorological data in order to improve overall sensor performance. We find that while the PPD42 performs well in relation to the reference instrument using linear regression (R2 = 0.36-0.51), a gradient boosting regression tree model can significantly improve device calibration (R2 = 0.68-0.76). We discuss the sensor's performance and reliability when deployed in a dense, heterogeneous urban environment during a period of significant variation in weather conditions, and important considerations when using machine learning techniques to improve the performance of low-cost air quality monitors.
Freeze cast porous barium titanate for enhanced piezoelectric energy harvesting
NASA Astrophysics Data System (ADS)
Roscow, J. I.; Zhang, Y.; Kraśny, M. J.; Lewis, R. W. C.; Taylor, J.; Bowen, C. R.
2018-06-01
Energy harvesting is an important developing technology for a new generation of self-powered sensor networks. This paper demonstrates the significant improvement in the piezoelectric energy harvesting performance of barium titanate by forming highly aligned porosity using freeze casting. Firstly, a finite element model demonstrating the effect of pore morphology and angle with respect to poling field on the poling behaviour of porous ferroelectrics was developed. A second model was then developed to understand the influence of microstructure-property relationships on the poling behaviour of porous freeze cast ferroelectric materials and their resultant piezoelectric and energy harvesting properties. To compare with model predictions, porous barium titanate was fabricated using freeze casting to form highly aligned microstructures with excellent longitudinal piezoelectric strain coefficients, d 33. The freeze cast barium titanate with 45 vol.% porosity had a d 33 = 134.5 pC N‑1 compared to d 33 = 144.5 pC N‑1 for dense barium titanate. The d 33 coefficients of the freeze cast materials were also higher than materials with uniformly distributed spherical porosity due to improved poling of the aligned microstructures, as predicted by the models. Both model and experimental data indicated that introducing porosity provides a large reduction in the permittivity () of barium titanate, which leads to a substantial increase in energy harvesting figure of merit, , with a maximum of 3.79 pm2 N‑1 for barium titanate with 45 vol.% porosity, compared to only 1.40 pm2 N‑1 for dense barium titanate. Dense and porous barium titanate materials were then used to harvest energy from a mechanical excitation by rectification and storage of the piezoelectric charge on a capacitor. The porous barium titanate charged the capacitor to a voltage of 234 mV compared to 96 mV for the dense material, indicating a 2.4-fold increase that was similar to that predicted by the energy harvesting figures of merit.
Enterprise virtual private network (VPN) with dense wavelength division multiplexing (DWDM) design
NASA Astrophysics Data System (ADS)
Carranza, Aparicio
An innovative computer simulation and modeling tool for metropolitan area optical data communication networks is presented. These models address the unique requirements of Virtual Private Networks for enterprise data centers, which may comprise a mixture of protocols including ESCON, FICON, Fibre Channel, Sysplex protocols (ETR, CLO, ISC); and other links interconnected over dark fiber using Dense Wavelength Division Multiplexing (DWDM). Our models have the capability of designing a network with minimal inputs; to compute optical link budgets; suggest alternative configurations; and also optimize the design based on user-defined performance metrics. The models make use of Time Division Multiplexing (TDM) wherever possible for lower data rate traffics. Simulation results for several configurations are presented and they have been validated by means of experiments conducted on the IBM enterprise network testbed in Poughkeepsie, N.Y.
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
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.
Intelligent self-organization methods for wireless ad hoc sensor networks based on limited resources
NASA Astrophysics Data System (ADS)
Hortos, William S.
2006-05-01
A wireless ad hoc sensor network (WSN) is a configuration for area surveillance that affords rapid, flexible deployment in arbitrary threat environments. There is no infrastructure support and sensor nodes communicate with each other only when they are in transmission range. To a greater degree than the terminals found in mobile ad hoc networks (MANETs) for communications, sensor nodes are resource-constrained, with limited computational processing, bandwidth, memory, and power, and are typically unattended once in operation. Consequently, the level of information exchange among nodes, to support any complex adaptive algorithms to establish network connectivity and optimize throughput, not only deplete those limited resources and creates high overhead in narrowband communications, but also increase network vulnerability to eavesdropping by malicious nodes. Cooperation among nodes, critical to the mission of sensor networks, can thus be disrupted by the inappropriate choice of the method for self-organization. Recent published contributions to the self-configuration of ad hoc sensor networks, e.g., self-organizing mapping and swarm intelligence techniques, have been based on the adaptive control of the cross-layer interactions found in MANET protocols to achieve one or more performance objectives: connectivity, intrusion resistance, power control, throughput, and delay. However, few studies have examined the performance of these algorithms when implemented with the limited resources of WSNs. In this paper, self-organization algorithms for the initiation, operation and maintenance of a network topology from a collection of wireless sensor nodes are proposed that improve the performance metrics significant to WSNs. The intelligent algorithm approach emphasizes low computational complexity, energy efficiency and robust adaptation to change, allowing distributed implementation with the actual limited resources of the cooperative nodes of the network. Extensions of the algorithms from flat topologies to two-tier hierarchies of sensor nodes are presented. Results from a few simulations of the proposed algorithms are compared to the published results of other approaches to sensor network self-organization in common scenarios. The estimated network lifetime and extent under static resource allocations are computed.
A wireless sensor enabled by wireless power.
Lee, Da-Sheng; Liu, Yu-Hong; Lin, Chii-Ruey
2012-11-22
Through harvesting energy by wireless charging and delivering data by wireless communication, this study proposes the concept of a wireless sensor enabled by wireless power (WPWS) and reports the fabrication of a prototype for functional tests. One WPWS node consists of wireless power module and sensor module with different chip-type sensors. Its main feature is the dual antenna structure. Following RFID system architecture, a power harvesting antenna was designed to gather power from a standard reader working in the 915 MHz band. Referring to the Modbus protocol, the other wireless communication antenna was integrated on a node to send sensor data in parallel. The dual antenna structure integrates both the advantages of an RFID system and a wireless sensor. Using a standard UHF RFID reader, WPWS can be enabled in a distributed area with a diameter up to 4 m. Working status is similar to that of a passive tag, except that a tag can only be queried statically, while the WPWS can send dynamic data from the sensors. The function is the same as a wireless sensor node. Different WPWSs equipped with temperature and humidity, optical and airflow velocity sensors are tested in this study. All sensors can send back detection data within 8 s. The accuracy is within 8% deviation compared with laboratory equipment. A wireless sensor network enabled by wireless power should be a totally wireless sensor network using WPWS. However, distributed WPWSs only can form a star topology, the simplest topology for constructing a sensor network. Because of shielding effects, it is difficult to apply other complex topologies. Despite this limitation, WPWS still can be used to extend sensor network applications in hazardous environments. Further research is needed to improve WPWS to realize a totally wireless sensor network.
A Wireless Sensor Enabled by Wireless Power
Lee, Da-Sheng; Liu, Yu-Hong; Lin, Chii-Ruey
2012-01-01
Through harvesting energy by wireless charging and delivering data by wireless communication, this study proposes the concept of a wireless sensor enabled by wireless power (WPWS) and reports the fabrication of a prototype for functional tests. One WPWS node consists of wireless power module and sensor module with different chip-type sensors. Its main feature is the dual antenna structure. Following RFID system architecture, a power harvesting antenna was designed to gather power from a standard reader working in the 915 MHz band. Referring to the Modbus protocol, the other wireless communication antenna was integrated on a node to send sensor data in parallel. The dual antenna structure integrates both the advantages of an RFID system and a wireless sensor. Using a standard UHF RFID reader, WPWS can be enabled in a distributed area with a diameter up to 4 m. Working status is similar to that of a passive tag, except that a tag can only be queried statically, while the WPWS can send dynamic data from the sensors. The function is the same as a wireless sensor node. Different WPWSs equipped with temperature and humidity, optical and airflow velocity sensors are tested in this study. All sensors can send back detection data within 8 s. The accuracy is within 8% deviation compared with laboratory equipment. A wireless sensor network enabled by wireless power should be a totally wireless sensor network using WPWS. However, distributed WPWSs only can form a star topology, the simplest topology for constructing a sensor network. Because of shielding effects, it is difficult to apply other complex topologies. Despite this limitation, WPWS still can be used to extend sensor network applications in hazardous environments. Further research is needed to improve WPWS to realize a totally wireless sensor network. PMID:23443370
Propagation Modeling and Defending of a Mobile Sensor Worm in Wireless Sensor and Actuator Networks.
Wang, Tian; Wu, Qun; Wen, Sheng; Cai, Yiqiao; Tian, Hui; Chen, Yonghong; Wang, Baowei
2017-01-13
WSANs (Wireless Sensor and Actuator Networks) are derived from traditional wireless sensor networks by introducing mobile actuator elements. Previous studies indicated that mobile actuators can improve network performance in terms of data collection, energy supplementation, etc. However, according to our experimental simulations, the actuator's mobility also causes the sensor worm to spread faster if an attacker launches worm attacks on an actuator and compromises it successfully. Traditional worm propagation models and defense strategies did not consider the diffusion with a mobile worm carrier. To address this new problem, we first propose a microscopic mathematical model to describe the propagation dynamics of the sensor worm. Then, a two-step local defending strategy (LDS) with a mobile patcher (a mobile element which can distribute patches) is designed to recover the network. In LDS, all recovering operations are only taken in a restricted region to minimize the cost. Extensive experimental results demonstrate that our model estimations are rather accurate and consistent with the actual spreading scenario of the mobile sensor worm. Moreover, on average, the LDS outperforms other algorithms by approximately 50% in terms of the cost.
An Advanced Sensor Network Design For Subglacial Sensing
NASA Astrophysics Data System (ADS)
Martinez, K.; Hart, J. K.; Elsaify, A.; Zou, G.; Padhy, P.; Riddoch, A.
2006-12-01
In the Glacsweb project a sensor network has been designed to take sensor measurements inside glaciers and send the data back to a web server autonomously. A wide range of experience was gained in the deployment of the earlier systems and this has been used to develop new hardware and software to better meet the needs of glaciologists using the data from the system. The system was reduced in size, new sensors (compass, light sensor) were added and the radio communications system completely changed. The new 173MHz radio system was designed with an antenna tuned to work in ice and a new network algorithm written to provide better data security. Probes can communicate data through each other (ad-hoc network) and store many months of data in a large buffer to cope with long term communications failures. New sensors include a light reflection measurement in order to provide data on the surrounding material. This paper will discuss the design decisions, the effectiveness of the final system and generic outcomes of use to sensor network designers deploying in difficult environments.
Content-Based Multi-Channel Network Coding Algorithm in the Millimeter-Wave Sensor Network
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
Performance Evaluation Modeling of Network Sensors
NASA Technical Reports Server (NTRS)
Clare, Loren P.; Jennings, Esther H.; Gao, Jay L.
2003-01-01
Substantial benefits are promised by operating many spatially separated sensors collectively. Such systems are envisioned to consist of sensor nodes that are connected by a communications network. A simulation tool is being developed to evaluate the performance of networked sensor systems, incorporating such metrics as target detection probabilities, false alarms rates, and classification confusion probabilities. The tool will be used to determine configuration impacts associated with such aspects as spatial laydown, and mixture of different types of sensors (acoustic, seismic, imaging, magnetic, RF, etc.), and fusion architecture. The QualNet discrete-event simulation environment serves as the underlying basis for model development and execution. This platform is recognized for its capabilities in efficiently simulating networking among mobile entities that communicate via wireless media. We are extending QualNet's communications modeling constructs to capture the sensing aspects of multi-target sensing (analogous to multiple access communications), unimodal multi-sensing (broadcast), and multi-modal sensing (multiple channels and correlated transmissions). Methods are also being developed for modeling the sensor signal sources (transmitters), signal propagation through the media, and sensors (receivers) that are consistent with the discrete event paradigm needed for performance determination of sensor network systems. This work is supported under the Microsensors Technical Area of the Army Research Laboratory (ARL) Advanced Sensors Collaborative Technology Alliance.
NASA Astrophysics Data System (ADS)
Pikelnaya, O.; Polidori, A.; Wimmer, R.; Mellqvist, J.; Samuelsson, J.; Marianne, E.; Andersson, P.; Brohede, S.; Izos, O.
2017-12-01
Industrial facilities such as refineries and oil processing facilities can be sources of chemicals adversely affecting human health, for example aromatic hydrocarbons and formaldehyde. In an urban setting, such as the South Coast Air Basin (SCAB), exposure to harmful air pollutants (HAP's) for residents of communities neighboring such facilities is of serious concern. Traditionally, exposure assessments are performed by modeling a community exposure using emission inventories and data collected at fixed air monitoring sites. However, recent field measurements found that emission inventories may underestimate HAP emissions from refineries; and HAP measurements data from fixed sites is lacking spatial resolution; as a result, the impact of HAP emissions on communities is highly uncertain. The next generation air monitoring technologies can help address these challenges. For example, dense "low-cost" sensors allow continuous monitoring of concentrations of pollutants within communities with high temporal- and spatial- resolution, and optical remote sensing (ORS) technologies offer measurements of emission fluxes and real-time ground-concentration mapping of HAPs. South Coast Air Quality Management District (SCAQMD) is currently conducting a multi-year study using ORS methods and "low-cost" Volatile Organic Compounds (VOCs) sensors to monitor HAP emissions from selected industrial facilities in the SCAB and their ambient concentrations in neighboring communities. For this purpose, quarterly mobile ORS surveys are conducted to quantify facility-wide emissions for VOCs, aromatic hydrocarbons and HCHO, and to collect ground-concentration profiles of these pollutants inside neighboring communities. Additionally, "low-cost" sensor nodes for deployment in neighborhood(s) downwind of the facilities have been developed in order to obtain long-term, granular data on neighborhood VOC concentrations, During this presentation we will discuss initial results of quarterly ORS surveys and pilot "low-cost" sensor deployments. We will also outline benefits of using a combination of mobile ORS surveys and "low-cost" sensor networks for community exposure monitoring.
Operation of remote mobile sensors for security of drinking water distribution systems.
Perelman, By Lina; Ostfeld, Avi
2013-09-01
The deployment of fixed online water quality sensors in water distribution systems has been recognized as one of the key components of contamination warning systems for securing public health. This study proposes to explore how the inclusion of mobile sensors for inline monitoring of various water quality parameters (e.g., residual chlorine, pH) can enhance water distribution system security. Mobile sensors equipped with sampling, sensing, data acquisition, wireless transmission and power generation systems are being designed, fabricated, and tested, and prototypes are expected to be released in the very near future. This study initiates the development of a theoretical framework for modeling mobile sensor movement in water distribution systems and integrating the sensory data collected from stationary and non-stationary sensor nodes to increase system security. The methodology is applied and demonstrated on two benchmark networks. Performance of different sensor network designs are compared for fixed and combined fixed and mobile sensor networks. Results indicate that complementing online sensor networks with inline monitoring can increase detection likelihood and decrease mean time to detection. Copyright © 2013 Elsevier Ltd. All rights reserved.
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.
Bio-mimic optimization strategies in wireless sensor networks: a survey.
Adnan, Md Akhtaruzzaman; Abdur Razzaque, Mohammd; Ahmed, Ishtiaque; Isnin, Ismail Fauzi
2013-12-24
For the past 20 years, many authors have focused their investigations on wireless sensor networks. Various issues related to wireless sensor networks such as energy minimization (optimization), compression schemes, self-organizing network algorithms, routing protocols, quality of service management, security, energy harvesting, etc., have been extensively explored. The three most important issues among these are energy efficiency, quality of service and security management. To get the best possible results in one or more of these issues in wireless sensor networks optimization is necessary. Furthermore, in number of applications (e.g., body area sensor networks, vehicular ad hoc networks) these issues might conflict and require a trade-off amongst them. Due to the high energy consumption and data processing requirements, the use of classical algorithms has historically been disregarded. In this context contemporary researchers started using bio-mimetic strategy-based optimization techniques in the field of wireless sensor networks. These techniques are diverse and involve many different optimization algorithms. As far as we know, most existing works tend to focus only on optimization of one specific issue of the three mentioned above. It is high time that these individual efforts are put into perspective and a more holistic view is taken. In this paper we take a step in that direction by presenting a survey of the literature in the area of wireless sensor network optimization concentrating especially on the three most widely used bio-mimetic algorithms, namely, particle swarm optimization, ant colony optimization and genetic algorithm. In addition, to stimulate new research and development interests in this field, open research issues, challenges and future research directions are highlighted.
NASA Astrophysics Data System (ADS)
Mukherjee, A. D.; Brown, S. G.; McCarthy, M. C.
2017-12-01
A new generation of low cost air quality sensors have the potential to provide valuable information on the spatial-temporal variability of air pollution - if the measurements have sufficient quality. This study examined the performance of a particulate matter sensor model, the AirBeam (HabitatMap Inc., Brooklyn, NY), over a three month period in the urban environment of Sacramento, California. Nineteen AirBeam sensors were deployed at a regulatory air monitoring site collocated with meteorology measurements and as a local network over an 80 km2 domain in Sacramento, CA. This study presents the methodology to evaluate the precision, accuracy, and reliability of the sensors over a range of meteorological and aerosol conditions. The sensors demonstrated a robust degree of precision during collocated measurement periods (R2 = 0.98 - 0.99) and a moderate degree of correlation against a Beta Attenuation Monitor PM2.5 monitor (R2 0.6). A normalization correction is applied during the study period so that each AirBeam sensor in the network reports a comparable value. The role of the meteorological environment on the accuracy of the sensor measurements is investigated, along with the possibility of improving the measurements through a meteorology weighted correction. The data quality of the network of sensors is examined, and the spatial variability of particulate matter through the study domain derived from the sensor network is presented.
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
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.
Faulty node detection in wireless sensor networks using a recurrent neural network
NASA Astrophysics Data System (ADS)
Atiga, Jamila; Mbarki, Nour Elhouda; Ejbali, Ridha; Zaied, Mourad
2018-04-01
The wireless sensor networks (WSN) consist of a set of sensors that are more and more used in surveillance applications on a large scale in different areas: military, Environment, Health ... etc. Despite the minimization and the reduction of the manufacturing costs of the sensors, they can operate in places difficult to access without the possibility of reloading of battery, they generally have limited resources in terms of power of emission, of processing capacity, data storage and energy. These sensors can be used in a hostile environment, such as, for example, on a field of battle, in the presence of fires, floods, earthquakes. In these environments the sensors can fail, even in a normal operation. It is therefore necessary to develop algorithms tolerant and detection of defects of the nodes for the network of sensor without wires, therefore, the faults of the sensor can reduce the quality of the surveillance if they are not detected. The values that are measured by the sensors are used to estimate the state of the monitored area. We used the Non-linear Auto- Regressive with eXogeneous (NARX), the recursive architecture of the neural network, to predict the state of a node of a sensor from the previous values described by the functions of time series. The experimental results have verified that the prediction of the State is enhanced by our proposed model.
Totally opportunistic routing algorithm (TORA) for underwater wireless sensor network
Hashim, Fazirulhisyam; Rasid, Mohd Fadlee A.; Othman, Mohamed
2018-01-01
Underwater Wireless Sensor Network (UWSN) has emerged as promising networking techniques to monitor and explore oceans. Research on acoustic communication has been conducted for decades, but had focused mostly on issues related to physical layer such as high latency, low bandwidth, and high bit error. However, data gathering process is still severely limited in UWSN due to channel impairment. One way to improve data collection in UWSN is the design of routing protocol. Opportunistic Routing (OR) is an emerging technique that has the ability to improve the performance of wireless network, notably acoustic network. In this paper, we propose an anycast, geographical and totally opportunistic routing algorithm for UWSN, called TORA. Our proposed scheme is designed to avoid horizontal transmission, reduce end to end delay, overcome the problem of void nodes and maximize throughput and energy efficiency. We use TOA (Time of Arrival) and range based equation to localize nodes recursively within a network. Once nodes are localized, their location coordinates and residual energy are used as a matrix to select the best available forwarder. All data packets may or may not be acknowledged based on the status of sender and receiver. Thus, the number of acknowledgments for a particular data packet may vary from zero to 2-hop. Extensive simulations were performed to evaluate the performance of the proposed scheme for high network traffic load under very sparse and very dense network scenarios. Simulation results show that TORA significantly improves the network performance when compared to some relevant existing routing protocols, such as VBF, HHVBF, VAPR, and H2DAB, for energy consumption, packet delivery ratio, average end-to-end delay, average hop-count and propagation deviation factor. TORA reduces energy consumption by an average of 35% of VBF, 40% of HH-VBF, 15% of VAPR, and 29% of H2DAB, whereas the packet delivery ratio has been improved by an average of 43% of VBF, 26% of HH-VBF, 15% of VAPR, and 25% of H2DAB. Moreover, the average end-to-end delay has been reduced by 70% of VBF, 69% of HH-VBF, 46% of VAPR, and 73% of H2DAB. Furthermore, average hope-count has been improved by 57%, 53%, 16% and 31% as compared to VBF, HHVBF, VAPR, and H2DAB, respectively. Also, propagation delay has been reduced by 34%, 30%, 15% and 23% as compared to VBF, HHVBF, VAPR, and H2DAB, respectively. PMID:29874237
Totally opportunistic routing algorithm (TORA) for underwater wireless sensor network.
Rahman, Ziaur; Hashim, Fazirulhisyam; Rasid, Mohd Fadlee A; Othman, Mohamed
2018-01-01
Underwater Wireless Sensor Network (UWSN) has emerged as promising networking techniques to monitor and explore oceans. Research on acoustic communication has been conducted for decades, but had focused mostly on issues related to physical layer such as high latency, low bandwidth, and high bit error. However, data gathering process is still severely limited in UWSN due to channel impairment. One way to improve data collection in UWSN is the design of routing protocol. Opportunistic Routing (OR) is an emerging technique that has the ability to improve the performance of wireless network, notably acoustic network. In this paper, we propose an anycast, geographical and totally opportunistic routing algorithm for UWSN, called TORA. Our proposed scheme is designed to avoid horizontal transmission, reduce end to end delay, overcome the problem of void nodes and maximize throughput and energy efficiency. We use TOA (Time of Arrival) and range based equation to localize nodes recursively within a network. Once nodes are localized, their location coordinates and residual energy are used as a matrix to select the best available forwarder. All data packets may or may not be acknowledged based on the status of sender and receiver. Thus, the number of acknowledgments for a particular data packet may vary from zero to 2-hop. Extensive simulations were performed to evaluate the performance of the proposed scheme for high network traffic load under very sparse and very dense network scenarios. Simulation results show that TORA significantly improves the network performance when compared to some relevant existing routing protocols, such as VBF, HHVBF, VAPR, and H2DAB, for energy consumption, packet delivery ratio, average end-to-end delay, average hop-count and propagation deviation factor. TORA reduces energy consumption by an average of 35% of VBF, 40% of HH-VBF, 15% of VAPR, and 29% of H2DAB, whereas the packet delivery ratio has been improved by an average of 43% of VBF, 26% of HH-VBF, 15% of VAPR, and 25% of H2DAB. Moreover, the average end-to-end delay has been reduced by 70% of VBF, 69% of HH-VBF, 46% of VAPR, and 73% of H2DAB. Furthermore, average hope-count has been improved by 57%, 53%, 16% and 31% as compared to VBF, HHVBF, VAPR, and H2DAB, respectively. Also, propagation delay has been reduced by 34%, 30%, 15% and 23% as compared to VBF, HHVBF, VAPR, and H2DAB, respectively.
Given, Douglas D.; Cochran, Elizabeth S.; Heaton, Thomas; Hauksson, Egill; Allen, Richard; Hellweg, Peggy; Vidale, John; Bodin, Paul
2014-01-01
Earthquake Early Warning (EEW) systems can provide as much as tens of seconds of warning to people and automated systems before strong shaking arrives. The United States Geological Survey (USGS) and its partners are developing such an EEW system, called ShakeAlert, for the West Coast of the United States. This document describes the technical implementation of that system, which leverages existing stations and infrastructure of the Advanced National Seismic System (ANSS) regional networks to achieve this new capability. While significant progress has been made in developing the ShakeAlert early warning system, improved robustness of each component of the system and additional testing and certification are needed for the system to be reliable enough to issue public alerts. Major components of the system include dense networks of ground motion sensors, telecommunications from those sensors to central processing systems, algorithms for event detection and alert creation, and distribution systems to alert users. Capital investment costs for a West Coast EEW system are projected to be $38.3M, with additional annual maintenance and operations totaling $16.1M—in addition to current ANSS expenditures for earthquake monitoring. An EEW system is complementary to, but does not replace, other strategies to mitigate earthquake losses. The system has limitations: false and missed alerts are possible, and the area very near to an earthquake epicenter may receive little or no warning. However, such an EEW system would save lives, reduce injuries and damage, and improve community resilience by reducing longer-term economic losses for both public and private entities.
NASA Astrophysics Data System (ADS)
Mach-Batlle, Rosa; Navau, Carles; Sanchez, Alvaro
2018-04-01
Sensing magnetic fields is essential in many applications in biomedicine, transportation, or smart cities. The distortion magnetic sensors create in response to the field they are detecting may hinder their use, for example, in applications requiring dense packaging of sensors or accurately shaped field distributions. For sensing electromagnetic waves, cloaking shells that reduce the scattering of sensors have been introduced. However, the problem of making a magnetic sensor undetectable remains unsolved. Here, we present a general strategy on how to make a sensor magnetically invisible while keeping its ability to sense. The sensor is rendered undetectable by surrounding it with a spherical shell having a tailored magnetic permeability. Our method can be applied to arbitrary shaped magnetic sensors in arbitrary magnetic fields. The invisibility can be made exact when the sensor is spherical and the probed field is uniform. A metasurface composed of superconducting pieces is presented as a practical realization of the ideal invisibility shell.
NASA Technical Reports Server (NTRS)
Mehr, Ali Farhang; Sauvageon, Julien; Agogino, Alice M.; Tumer, Irem Y.
2006-01-01
Recent advances in micro electromechanical systems technology, digital electronics, and wireless communications have enabled development of low-cost, low-power, multifunctional miniature smart sensors. These sensors can be deployed throughout a region in an aerospace vehicle to build a network for measurement, detection and surveillance applications. Event detection using such centralized sensor networks is often regarded as one of the most promising health management technologies in aerospace applications where timely detection of local anomalies has a great impact on the safety of the mission. In this paper, we propose to conduct a qualitative comparison of several local event detection algorithms for centralized redundant sensor networks. The algorithms are compared with respect to their ability to locate and evaluate an event in the presence of noise and sensor failures for various node geometries and densities.
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.
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.
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.
Automated general temperature correction method for dielectric soil moisture sensors
NASA Astrophysics Data System (ADS)
Kapilaratne, R. G. C. Jeewantinie; Lu, Minjiao
2017-08-01
An effective temperature correction method for dielectric sensors is important to ensure the accuracy of soil water content (SWC) measurements of local to regional-scale soil moisture monitoring networks. These networks are extensively using highly temperature sensitive dielectric sensors due to their low cost, ease of use and less power consumption. Yet there is no general temperature correction method for dielectric sensors, instead sensor or site dependent correction algorithms are employed. Such methods become ineffective at soil moisture monitoring networks with different sensor setups and those that cover diverse climatic conditions and soil types. This study attempted to develop a general temperature correction method for dielectric sensors which can be commonly used regardless of the differences in sensor type, climatic conditions and soil type without rainfall data. In this work an automated general temperature correction method was developed by adopting previously developed temperature correction algorithms using time domain reflectometry (TDR) measurements to ThetaProbe ML2X, Stevens Hydra probe II and Decagon Devices EC-TM sensor measurements. The rainy day effects removal procedure from SWC data was automated by incorporating a statistical inference technique with temperature correction algorithms. The temperature correction method was evaluated using 34 stations from the International Soil Moisture Monitoring Network and another nine stations from a local soil moisture monitoring network in Mongolia. Soil moisture monitoring networks used in this study cover four major climates and six major soil types. Results indicated that the automated temperature correction algorithms developed in this study can eliminate temperature effects from dielectric sensor measurements successfully even without on-site rainfall data. Furthermore, it has been found that actual daily average of SWC has been changed due to temperature effects of dielectric sensors with a significant error factor comparable to ±1% manufacturer's accuracy.
An open and reconfigurable wireless sensor network for pervasive health monitoring.
Triantafyllidis, A; Koutkias, V; Chouvarda, I; Maglaveras, N
2008-01-01
Sensor networks constitute the backbone for the construction of personalized monitoring systems. Up to now, several sensor networks have been proposed for diverse pervasive healthcare applications, which are however characterized by a significant lack of open architectures, resulting in closed, non-interoperable and difficult to extend solutions. In this context, we propose an open and reconfigurable wireless sensor network (WSN) for pervasive health monitoring, with particular emphasis in its easy extension with additional sensors and functionality by incorporating embedded intelligence mechanisms. We consider a generic WSN architecture comprised of diverse sensor nodes (with communication and processing capabilities) and a mobile base unit (MBU) operating as the gateway between the sensors and the medical personnel, formulating this way a body area network (BAN). The primary focus of this work is on the intra-BAN data communication issues, adopting SensorML as the data representation mean, including the encoding of the monitoring patterns and the functionality of the sensor network. In our prototype implementation two sensor nodes are emulated; one for heart rate monitoring and the other for blood glucose observations, while the MBU corresponds to a personal digital assistant (PDA) device. Java 2 Micro Edition (J2ME) is used to implement both the sensor nodes and the MBU components. Intra-BAN wireless communication relies on the Blue-tooth protocol. Via an adaptive user interface in the MBU, health professionals may specify the monitoring parameters of the WSN and define the monitoring patterns of interest in terms of rules. This work constitutes an essential step towards the construction of open, extensible, inter-operable and intelligent WSNs for pervasive health monitoring.
NASA Astrophysics Data System (ADS)
Stewart, G.; Popoola, O. A.; Mead, M. I.; McKeating, S. J.; Calleja, M.; Hayes, M.; Baron, R. P.; Saffell, J.; Jones, R.
2012-12-01
In this paper we describe how low-cost, lightweight devices, which incorporate GPS and GPRS facilities and contain electrochemical sensors for carbon monoxide (CO), nitrogen monoxide (NO) and nitrogen dioxide (NO2), have been used to collect data representative of personal exposure to these important urban air pollutants. E.U. legislation has set target levels for gases thought to have adverse impacts on human health, and consequently led to a need for a more informed air pollution control policy. With many sites in the U.K. and in the rest of the E.U. still failing to meet annual targets for NO2, a need to better understand pollutant sources and behaviour has arisen. Moreover, while traditional chemiluminescence techniques provide precise measurements, the instruments are sparsely populated around urban centres and are thus limited in their ability to account for true personal exposure. Through a series of laboratory and field studies, it has been shown that electrochemical sensor nodes, when configured suitably and after post-processing of data, can provide selective, reproducible measurements, and that the devices have appropriate detection limits (at the low parts-per-billion level), as well as fast enough response times, for urban air quality studies. Both mobile nodes and their static analogues have been deployed with different aims. Static nodes have been used in dense networks in both the urban environment and in the grounds of a major international airport, as described in the partner papers of Mead et al and Bright et al. Mobile units are easily deployed in scalable networks for short-term studies on personal exposure; these studies have been carried out in a wide range of locations including Lagos, Kuala-Lumpur, London and Valencia. Data collected by both mobile and static sensor nodes illustrate the insufficiency of the existing infrastructure in accounting for both the spatial and temporal variability in air pollutants due to road traffic emissions, and thus also the potential insufficiency at quantifying the risks to health in the surrounding area. Recent campaigns with mobile sensor nodes have included attempts to probe the differences in personal exposure to gas-phase air pollutants at different heights of breathing zone and between different methods of transport.
Sensor Networking Testbed with IEEE 1451 Compatibility and Network Performance Monitoring
NASA Technical Reports Server (NTRS)
Gurkan, Deniz; Yuan, X.; Benhaddou, D.; Figueroa, F.; Morris, Jonathan
2007-01-01
Design and implementation of a testbed for testing and verifying IEEE 1451-compatible sensor systems with network performance monitoring is of significant importance. The performance parameters measurement as well as decision support systems implementation will enhance the understanding of sensor systems with plug-and-play capabilities. The paper will present the design aspects for such a testbed environment under development at University of Houston in collaboration with NASA Stennis Space Center - SSST (Smart Sensor System Testbed).
In-network Coding for Resilient Sensor Data Storage and Efficient Data Mule Collection
NASA Astrophysics Data System (ADS)
Albano, Michele; Gao, Jie
In a sensor network of n nodes in which k of them have sensed interesting data, we perform in-network erasure coding such that each node stores a linear combination of all the network data with random coefficients. This scheme greatly improves data resilience to node failures: as long as there are k nodes that survive an attack, all the data produced in the sensor network can be recovered with high probability. The in-network coding storage scheme also improves data collection rate by mobile mules and allows for easy scheduling of data mules.
Network Coding on Heterogeneous Multi-Core Processors for Wireless Sensor Networks
Kim, Deokho; Park, Karam; Ro, Won W.
2011-01-01
While network coding is well known for its efficiency and usefulness in wireless sensor networks, the excessive costs associated with decoding computation and complexity still hinder its adoption into practical use. On the other hand, high-performance microprocessors with heterogeneous multi-cores would be used as processing nodes of the wireless sensor networks in the near future. To this end, this paper introduces an efficient network coding algorithm developed for the heterogenous multi-core processors. The proposed idea is fully tested on one of the currently available heterogeneous multi-core processors referred to as the Cell Broadband Engine. PMID:22164053
Ubiquitous Virtual Private Network: A Solution for WSN Seamless Integration
Villa, David; Moya, Francisco; Villanueva, Félix Jesús; Aceña, Óscar; López, Juan Carlos
2014-01-01
Sensor networks are becoming an essential part of ubiquitous systems and applications. However, there are no well-defined protocols or mechanisms to access the sensor network from the enterprise information system. We consider this issue as a heterogeneous network interconnection problem, and as a result, the same concepts may be applied. Specifically, we propose the use of object-oriented middlewares to provide a virtual private network in which all involved elements (sensor nodes or computer applications) will be able to communicate as if all of them were in a single and uniform network. PMID:24399154
Test Plan of the Anticipatory Wirelss Sensor Network for the Critical Energy Infrastructure
DOE Office of Scientific and Technical Information (OSTI.GOV)
Carlos Rentel
2006-09-01
The test plan for the performance of the Anticipatory Wireless Sensor Network (A-WSN) is presented. The results of the test campaigns will be obtained after actual measurements are taken in the field with the Wireless Sensor Network developed by The Innovation Center-Eaton Corp., and the Anticipatory algorithms developed by ORNL.
NASA Astrophysics Data System (ADS)
Kavanagh, K.; Davis, A.; Gessler, P.; Hess, H.; Holden, Z.; Link, T. E.; Newingham, B. A.; Smith, A. M.; Robinson, P.
2011-12-01
Developing sensor networks that are robust enough to perform in the world's remote regions is critical since these regions serve as important benchmarks compared to human-dominated areas. Paradoxically, the factors that make these remote, natural sites challenging for sensor networking are often what make them indispensable for climate change research. We aim to overcome these challenges by developing a three-dimensional sensor network arrayed across a topoclimatic gradient (1100-1800 meters) in a wilderness area in central Idaho. Development of this sensor array builds upon advances in sensing, networking, and power supply technologies coupled with experiences of the multidisciplinary investigators in conducting research in remote mountainous locations. The proposed gradient monitoring network will provide near real-time data from a three-dimensional (3-D) array of sensors measuring biophysical parameters used in ecosystem process models. The network will monitor atmospheric carbon dioxide concentration, humidity, air and soil temperature, soil water content, precipitation, incoming and outgoing shortwave and longwave radiation, snow depth, wind speed and direction, tree stem growth and leaf wetness at time intervals ranging from seconds to days. The long-term goal of this project is to realize a transformative integration of smart sensor networks adaptively communicating data in real-time to ultimately achieve a 3-D visualization of ecosystem processes within remote mountainous regions. Process models will be the interface between the visualization platforms and the sensor network. This will allow us to better predict how non-human dominated terrestrial and aquatic ecosystems function and respond to climate dynamics. Access to the data will be ensured as part of the Northwest Knowledge Network being developed at the University of Idaho, through ongoing Idaho NSF-funded cyber infrastructure initiatives, and existing data management systems funded by NSF, such as the CUAHSI Hydrologic Information System (HIS). These efforts will enhance cross-disciplinary understanding of natural and anthropogenic influences on ecosystem function and ultimately inform decision-making.
Decentralized Hypothesis Testing in Energy Harvesting Wireless Sensor Networks
NASA Astrophysics Data System (ADS)
Tarighati, Alla; Gross, James; Jalden, Joakim
2017-09-01
We consider the problem of decentralized hypothesis testing in a network of energy harvesting sensors, where sensors make noisy observations of a phenomenon and send quantized information about the phenomenon towards a fusion center. The fusion center makes a decision about the present hypothesis using the aggregate received data during a time interval. We explicitly consider a scenario under which the messages are sent through parallel access channels towards the fusion center. To avoid limited lifetime issues, we assume each sensor is capable of harvesting all the energy it needs for the communication from the environment. Each sensor has an energy buffer (battery) to save its harvested energy for use in other time intervals. Our key contribution is to formulate the problem of decentralized detection in a sensor network with energy harvesting devices. Our analysis is based on a queuing-theoretic model for the battery and we propose a sensor decision design method by considering long term energy management at the sensors. We show how the performance of the system changes for different battery capacities. We then numerically show how our findings can be used in the design of sensor networks with energy harvesting sensors.
Shell-corona microgels from double interpenetrating networks.
Rudyak, Vladimir Yu; Gavrilov, Alexey A; Kozhunova, Elena Yu; Chertovich, Alexander V
2018-04-18
Polymer microgels with a dense outer shell offer outstanding features as universal carriers for different guest molecules. In this paper, microgels formed by an interpenetrating network comprised of collapsed and swollen subnetworks are investigated using dissipative particle dynamics (DPD) computer simulations, and it is found that such systems can form classical core-corona structures, shell-corona structures, and core-shell-corona structures, depending on the subchain length and molecular mass of the system. The core-corona structures consisting of a dense core and soft corona are formed at small microgel sizes when the subnetworks are able to effectively separate in space. The most interesting shell-corona structures consist of a soft cavity in a dense shell surrounded with a loose corona, and are found at intermediate gel sizes; the area of their existence depends on the subchain length and the corresponding mesh size. At larger molecular masses the collapsing network forms additional cores inside the soft cavity, leading to the core-shell-corona structure.
Autonomous smart sensor network for full-scale structural health monitoring
NASA Astrophysics Data System (ADS)
Rice, Jennifer A.; Mechitov, Kirill A.; Spencer, B. F., Jr.; Agha, Gul A.
2010-04-01
The demands of aging infrastructure require effective methods for structural monitoring and maintenance. Wireless smart sensor networks offer the ability to enhance structural health monitoring (SHM) practices through the utilization of onboard computation to achieve distributed data management. Such an approach is scalable to the large number of sensor nodes required for high-fidelity modal analysis and damage detection. While smart sensor technology is not new, the number of full-scale SHM applications has been limited. This slow progress is due, in part, to the complex network management issues that arise when moving from a laboratory setting to a full-scale monitoring implementation. This paper presents flexible network management software that enables continuous and autonomous operation of wireless smart sensor networks for full-scale SHM applications. The software components combine sleep/wake cycling for enhanced power management with threshold detection for triggering network wide tasks, such as synchronized sensing or decentralized modal analysis, during periods of critical structural response.
Cross-Layer Algorithms for QoS Enhancement in Wireless Multimedia Sensor Networks
NASA Astrophysics Data System (ADS)
Saxena, Navrati; Roy, Abhishek; Shin, Jitae
A lot of emerging applications like advanced telemedicine and surveillance systems, demand sensors to deliver multimedia content with precise level of QoS enhancement. Minimizing energy in sensor networks has been a much explored research area but guaranteeing QoS over sensor networks still remains an open issue. In this letter we propose a cross-layer approach combining Network and MAC layers, for QoS enhancement in wireless multimedia sensor networks. In the network layer a statistical estimate of sensory QoS parameters is performed and a nearoptimal genetic algorithmic solution is proposed to solve the NP-complete QoS-routing problem. On the other hand the objective of the proposed MAC algorithm is to perform the QoS-based packet classification and automatic adaptation of the contention window. Simulation results demonstrate that the proposed protocol is capable of providing lower delay and better throughput, at the cost of reasonable energy consumption, in comparison with other existing sensory QoS protocols.
Peer-to-peer model for the area coverage and cooperative control of mobile sensor networks
NASA Astrophysics Data System (ADS)
Tan, Jindong; Xi, Ning
2004-09-01
This paper presents a novel model and distributed algorithms for the cooperation and redeployment of mobile sensor networks. A mobile sensor network composes of a collection of wireless connected mobile robots equipped with a variety of sensors. In such a sensor network, each mobile node has sensing, computation, communication, and locomotion capabilities. The locomotion ability enhances the autonomous deployment of the system. The system can be rapidly deployed to hostile environment, inaccessible terrains or disaster relief operations. The mobile sensor network is essentially a cooperative multiple robot system. This paper first presents a peer-to-peer model to define the relationship between neighboring communicating robots. Delaunay Triangulation and Voronoi diagrams are used to define the geometrical relationship between sensor nodes. This distributed model allows formal analysis for the fusion of spatio-temporal sensory information of the network. Based on the distributed model, this paper discusses a fault tolerant algorithm for autonomous self-deployment of the mobile robots. The algorithm considers the environment constraints, the presence of obstacles and the nonholonomic constraints of the robots. The distributed algorithm enables the system to reconfigure itself such that the area covered by the system can be enlarged. Simulation results have shown the effectiveness of the distributed model and deployment algorithms.
A Multi-Objective Partition Method for Marine Sensor Networks Based on Degree of Event Correlation.
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.
Network resiliency through memory health monitoring and proactive management
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.
Daamen, Ruby C.; Edwin A. Roehl, Jr.; Conrads, Paul
2010-01-01
A technology often used for industrial applications is “inferential sensor.” Rather than installing a redundant sensor to measure a process, such as an additional waterlevel gage, an inferential sensor, or virtual sensor, is developed that estimates the processes measured by the physical sensor. The advantage of an inferential sensor is that it provides a redundant signal to the sensor in the field but without exposure to environmental threats. In the event that a gage does malfunction, the inferential sensor provides an estimate for the period of missing data. The inferential sensor also can be used in the quality assurance and quality control of the data. Inferential sensors for gages in the EDEN network are currently (2010) under development. The inferential sensors will be automated so that the real-time EDEN data will continuously be compared to the inferential sensor signal and digital reports of the status of the real-time data will be sent periodically to the appropriate support personnel. The development and application of inferential sensors is easily transferable to other real-time hydrologic monitoring networks.
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
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.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Chapline, G.
1998-03-01
The engineering problems of constructing autonomous networks of sensors and data processors that can provide alerts for dangerous situations provide a new context for debating the question whether man-made systems can emulate the cognitive capabilities of the mammalian brain. In this paper we consider the question whether a distributed network of sensors and data processors can form ``perceptions`` based on sensory data. Because sensory data can have exponentially many explanations, the use of a central data processor to analyze the outputs from a large ensemble of sensors will in general introduce unacceptable latencies for responding to dangerous situations. A bettermore » idea is to use a distributed ``Helmholtz machine`` architecture in which the sensors are connected to a network of simple processors, and the collective state of the network as a whole provides an explanation for the sensory data. In general communication within such a network will require time division multiplexing, which opens the door to the possibility that with certain refinements to the Helmholtz machine architecture it may be possible to build sensor networks that exhibit a form of artificial consciousness.« less