Analysis and Evaluation of the LANDSAT-4 MSS and TM Sensors and Ground Data Processing Systems: Early Results

NASA Technical Reports Server (NTRS)

Bernstein, R.; Lotspiech, J. B.

1985-01-01

The MSS and TM sensor performances were evaluated by studying both the sensors and the characteristics of the data. Information content analysis, image statistics, band-to-band registration, the presence of failed or failing detectors, and sensor resolution are discussed. The TM data were explored from the point of view of adequacy of the ground processing and improvements that could be made to compensate for sensor problems and deficiencies. Radiometric correction processing, compensation for a failed detector, and geometric correction processing are also considered.

NASA End-to-End Data System /NEEDS/ information adaptive system - Performing image processing onboard the spacecraft

NASA Technical Reports Server (NTRS)

Kelly, W. L.; Howle, W. M.; Meredith, B. D.

1980-01-01

The Information Adaptive System (IAS) is an element of the NASA End-to-End Data System (NEEDS) Phase II and is focused toward onbaord image processing. Since the IAS is a data preprocessing system which is closely coupled to the sensor system, it serves as a first step in providing a 'Smart' imaging sensor. Some of the functions planned for the IAS include sensor response nonuniformity correction, geometric correction, data set selection, data formatting, packetization, and adaptive system control. The inclusion of these sensor data preprocessing functions onboard the spacecraft will significantly improve the extraction of information from the sensor data in a timely and cost effective manner and provide the opportunity to design sensor systems which can be reconfigured in near real time for optimum performance. The purpose of this paper is to present the preliminary design of the IAS and the plans for its development.

Study on intelligent processing system of man-machine interactive garment frame model

NASA Astrophysics Data System (ADS)

Chen, Shuwang; Yin, Xiaowei; Chang, Ruijiang; Pan, Peiyun; Wang, Xuedi; Shi, Shuze; Wei, Zhongqian

2018-05-01

A man-machine interactive garment frame model intelligent processing system is studied in this paper. The system consists of several sensor device, voice processing module, mechanical parts and data centralized acquisition devices. The sensor device is used to collect information on the environment changes brought by the body near the clothes frame model, the data collection device is used to collect the information of the environment change induced by the sensor device, voice processing module is used for speech recognition of nonspecific person to achieve human-machine interaction, mechanical moving parts are used to make corresponding mechanical responses to the information processed by data collection device.it is connected with data acquisition device by a means of one-way connection. There is a one-way connection between sensor device and data collection device, two-way connection between data acquisition device and voice processing module. The data collection device is one-way connection with mechanical movement parts. The intelligent processing system can judge whether it needs to interact with the customer, realize the man-machine interaction instead of the current rigid frame model.

Quantized Synchronization of Chaotic Neural Networks With Scheduled Output Feedback Control.

PubMed

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.

Dynamic Database. Efficiently Convert Massive Quantities of Sensor Data into Actionable Information for Tactical Commanders

DTIC Science & Technology

2000-06-01

As the number of sensors, platforms, exploitation sites, and command and control nodes continues to grow in response to Joint Vision 2010 information ... dominance requirements, Commanders and analysts will have an ever increasing need to collect and process vast amounts of data over wide areas using a large number of disparate sensors and information gathering sources.

On-line soft sensing in upstream bioprocessing.

PubMed

Randek, Judit; Mandenius, Carl-Fredrik

2018-02-01

This review provides an overview and a critical discussion of novel possibilities of applying soft sensors for on-line monitoring and control of industrial bioprocesses. Focus is on bio-product formation in the upstream process but also the integration with other parts of the process is addressed. The term soft sensor is used for the combination of analytical hardware data (from sensors, analytical devices, instruments and actuators) with mathematical models that create new real-time information about the process. In particular, the review assesses these possibilities from an industrial perspective, including sensor performance, information value and production economy. The capabilities of existing analytical on-line techniques are scrutinized in view of their usefulness in soft sensor setups and in relation to typical needs in bioprocessing in general. The review concludes with specific recommendations for further development of soft sensors for the monitoring and control of upstream bioprocessing.

Fusing Sensor Paradigms to Acquire Chemical Information: An Integrative Role for Smart Biopolymeric Hydrogels

PubMed Central

Kim, Eunkyoung; Liu, Yi; Ben-Yoav, Hadar; Winkler, Thomas E.; Yan, Kun; Shi, Xiaowen; Shen, Jana; Kelly, Deanna L.; Ghodssi, Reza; Bentley, William E.

2017-01-01

The Information Age transformed our lives but it has had surprisingly little impact on the way chemical information (e.g., from our biological world) is acquired, analyzed and communicated. Sensor systems are poised to change this situation by providing rapid access to chemical information. This access will be enabled by technological advances from various fields: biology enables the synthesis, design and discovery of molecular recognition elements as well as the generation of cell-based signal processors; physics and chemistry are providing nano-components that facilitate the transmission and transduction of signals rich with chemical information; microfabrication is yielding sensors capable of receiving these signals through various modalities; and signal processing analysis enhances the extraction of chemical information. The authors contend that integral to the development of functional sensor systems will be materials that (i) enable the integrative and hierarchical assembly of various sensing components (for chemical recognition and signal transduction) and (ii) facilitate meaningful communication across modalities. It is suggested that stimuli-responsive self-assembling biopolymers can perform such integrative functions, and redox provides modality-spanning communication capabilities. Recent progress toward the development of electrochemical sensors to manage schizophrenia is used to illustrate the opportunities and challenges for enlisting sensors for chemical information processing. PMID:27616350

An Interoperable Architecture for Air Pollution Early Warning System Based on Sensor Web

NASA Astrophysics Data System (ADS)

Samadzadegan, F.; Zahmatkesh, H.; Saber, M.; Ghazi khanlou, H. J.

2013-09-01

Environmental monitoring systems deal with time-sensitive issues which require quick responses in emergency situations. Handling the sensor observations in near real-time and obtaining valuable information is challenging issues in these systems from a technical and scientific point of view. The ever-increasing population growth in urban areas has caused certain problems in developing countries, which has direct or indirect impact on human life. One of applicable solution for controlling and managing air quality by considering real time and update air quality information gathered by spatially distributed sensors in mega cities, using sensor web technology for developing monitoring and early warning systems. Urban air quality monitoring systems using functionalities of geospatial information system as a platform for analysing, processing, and visualization of data in combination with Sensor Web for supporting decision support systems in disaster management and emergency situations. This system uses Sensor Web Enablement (SWE) framework of the Open Geospatial Consortium (OGC), which offers a standard framework that allows the integration of sensors and sensor data into spatial data infrastructures. SWE framework introduces standards for services to access sensor data and discover events from sensor data streams as well as definition set of standards for the description of sensors and the encoding of measurements. The presented system provides capabilities to collect, transfer, share, process air quality sensor data and disseminate air quality status in real-time. It is possible to overcome interoperability challenges by using standard framework. In a routine scenario, air quality data measured by in-situ sensors are communicated to central station where data is analysed and processed. The extracted air quality status is processed for discovering emergency situations, and if necessary air quality reports are sent to the authorities. This research proposed an architecture to represent how integrate air quality sensor data stream into geospatial data infrastructure to present an interoperable air quality monitoring system for supporting disaster management systems by real time information. Developed system tested on Tehran air pollution sensors for calculating Air Quality Index (AQI) for CO pollutant and subsequently notifying registered users in emergency cases by sending warning E-mails. Air quality monitoring portal used to retrieving and visualize sensor observation through interoperable framework. This system provides capabilities to retrieve SOS observation using WPS in a cascaded service chaining pattern for monitoring trend of timely sensor observation.

System model the processing of heterogeneous sensory information in robotized complex

NASA Astrophysics Data System (ADS)

Nikolaev, V.; Titov, V.; Syryamkin, V.

2018-05-01

Analyzed the scope and the types of robotic systems consisting of subsystems of the form "a heterogeneous sensors data processing subsystem". On the basis of the Queuing theory model is developed taking into account the unevenness of the intensity of information flow from the sensors to the subsystem of information processing. Analytical solution to assess the relationship of subsystem performance and uneven flows. The research of the obtained solution in the range of parameter values of practical interest.

Integrated optical sensor

DOEpatents

Watkins, Arthur D.; Smartt, Herschel B.; Taylor, Paul L.

1994-01-01

An integrated optical sensor for arc welding having multifunction feedback control. The sensor, comprising generally a CCD camera and diode laser, is positioned behind the arc torch for measuring weld pool position and width, standoff distance, and post-weld centerline cooling rate. Computer process information from this sensor is passed to a controlling computer for use in feedback control loops to aid in the control of the welding process. Weld pool position and width are used in a feedback loop, by the weld controller, to track the weld pool relative to the weld joint. Sensor standoff distance is used in a feedback loop to control the contact tip to base metal distance during the welding process. Cooling rate information is used to determine the final metallurgical state of the weld bead and heat affected zone, thereby controlling post-weld mechanical properties.

Integrated optical sensor

DOEpatents

Watkins, A.D.; Smartt, H.B.; Taylor, P.L.

1994-01-04

An integrated optical sensor for arc welding having multifunction feedback control is described. The sensor, comprising generally a CCD camera and diode laser, is positioned behind the arc torch for measuring weld pool position and width, standoff distance, and post-weld centerline cooling rate. Computer process information from this sensor is passed to a controlling computer for use in feedback control loops to aid in the control of the welding process. Weld pool position and width are used in a feedback loop, by the weld controller, to track the weld pool relative to the weld joint. Sensor standoff distance is used in a feedback loop to control the contact tip to base metal distance during the welding process. Cooling rate information is used to determine the final metallurgical state of the weld bead and heat affected zone, thereby controlling post-weld mechanical properties. 6 figures.

Image interpolation and denoising for division of focal plane sensors using Gaussian processes.

PubMed

Gilboa, Elad; Cunningham, John P; Nehorai, Arye; Gruev, Viktor

2014-06-16

Image interpolation and denoising are important techniques in image processing. These methods are inherent to digital image acquisition as most digital cameras are composed of a 2D grid of heterogeneous imaging sensors. Current polarization imaging employ four different pixelated polarization filters, commonly referred to as division of focal plane polarization sensors. The sensors capture only partial information of the true scene, leading to a loss of spatial resolution as well as inaccuracy of the captured polarization information. Interpolation is a standard technique to recover the missing information and increase the accuracy of the captured polarization information. Here we focus specifically on Gaussian process regression as a way to perform a statistical image interpolation, where estimates of sensor noise are used to improve the accuracy of the estimated pixel information. We further exploit the inherent grid structure of this data to create a fast exact algorithm that operates in ����(N(3/2)) (vs. the naive ���� (N³)), thus making the Gaussian process method computationally tractable for image data. This modeling advance and the enabling computational advance combine to produce significant improvements over previously published interpolation methods for polarimeters, which is most pronounced in cases of low signal-to-noise ratio (SNR). We provide the comprehensive mathematical model as well as experimental results of the GP interpolation performance for division of focal plane polarimeter.

Mixed Traffic Information Collection System based on Pressure Sensor

NASA Astrophysics Data System (ADS)

Liao, Wenzhe; Liu, Mingsheng; Meng, Qingli

The traffic information collection is the base of Intelligent Traffic.At present, there exist mixed traffic situation in urban road in China. This paper researched and implemented a system through collecting the vehicle and bicycle mixed traffic flow parameters based on pressure sensor. According to information collection requirements, we selected pressure sensor, designed the data collection, storage and other hardware circuitries and information processing software. The experiment shows that the system can meet the demand of traffic information collection in the actual.

Bluetooth Roaming for Sensor Network System in Clinical Environment.

PubMed

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

2015-01-01

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

Analysis of acoustic emission signals and monitoring of machining processes

PubMed

Govekar; Gradisek; Grabec

2000-03-01

Monitoring of a machining process on the basis of sensor signals requires a selection of informative inputs in order to reliably characterize and model the process. In this article, a system for selection of informative characteristics from signals of multiple sensors is presented. For signal analysis, methods of spectral analysis and methods of nonlinear time series analysis are used. With the aim of modeling relationships between signal characteristics and the corresponding process state, an adaptive empirical modeler is applied. The application of the system is demonstrated by characterization of different parameters defining the states of a turning machining process, such as: chip form, tool wear, and onset of chatter vibration. The results show that, in spite of the complexity of the turning process, the state of the process can be well characterized by just a few proper characteristics extracted from a representative sensor signal. The process characterization can be further improved by joining characteristics from multiple sensors and by application of chaotic characteristics.

Information processing for aerospace structural health monitoring

NASA Astrophysics Data System (ADS)

Lichtenwalner, Peter F.; White, Edward V.; Baumann, Erwin W.

1998-06-01

Structural health monitoring (SHM) technology provides a means to significantly reduce life cycle of aerospace vehicles by eliminating unnecessary inspections, minimizing inspection complexity, and providing accurate diagnostics and prognostics to support vehicle life extension. In order to accomplish this, a comprehensive SHM system will need to acquire data from a wide variety of diverse sensors including strain gages, accelerometers, acoustic emission sensors, crack growth gages, corrosion sensors, and piezoelectric transducers. Significant amounts of computer processing will then be required to convert this raw sensor data into meaningful information which indicates both the diagnostics of the current structural integrity as well as the prognostics necessary for planning and managing the future health of the structure in a cost effective manner. This paper provides a description of the key types of information processing technologies required in an effective SHM system. These include artificial intelligence techniques such as neural networks, expert systems, and fuzzy logic for nonlinear modeling, pattern recognition, and complex decision making; signal processing techniques such as Fourier and wavelet transforms for spectral analysis and feature extraction; statistical algorithms for optimal detection, estimation, prediction, and fusion; and a wide variety of other algorithms for data analysis and visualization. The intent of this paper is to provide an overview of the role of information processing for SHM, discuss various technologies which can contribute to accomplishing this role, and present some example applications of information processing for SHM implemented at the Boeing Company.

Wireless Sensor Node for Autonomous Monitoring and Alerts in Remote Environments

NASA Technical Reports Server (NTRS)

Panangadan, Anand V. (Inventor); Monacos, Steve P. (Inventor)

2015-01-01

A method, apparatus, system, and computer program products provides personal alert and tracking capabilities using one or more nodes. Each node includes radio transceiver chips operating at different frequency ranges, a power amplifier, sensors, a display, and embedded software. The chips enable the node to operate as either a mobile sensor node or a relay base station node while providing a long distance relay link between nodes. The power amplifier enables a line-of-sight communication between the one or more nodes. The sensors provide a GPS signal, temperature, and accelerometer information (used to trigger an alert condition). The embedded software captures and processes the sensor information, provides a multi-hop packet routing protocol to relay the sensor information to and receive alert information from a command center, and to display the alert information on the display.

Engineering workstation: Sensor modeling

NASA Technical Reports Server (NTRS)

Pavel, M; Sweet, B.

1993-01-01

The purpose of the engineering workstation is to provide an environment for rapid prototyping and evaluation of fusion and image processing algorithms. Ideally, the algorithms are designed to optimize the extraction of information that is useful to a pilot for all phases of flight operations. Successful design of effective fusion algorithms depends on the ability to characterize both the information available from the sensors and the information useful to a pilot. The workstation is comprised of subsystems for simulation of sensor-generated images, image processing, image enhancement, and fusion algorithms. As such, the workstation can be used to implement and evaluate both short-term solutions and long-term solutions. The short-term solutions are being developed to enhance a pilot's situational awareness by providing information in addition to his direct vision. The long term solutions are aimed at the development of complete synthetic vision systems. One of the important functions of the engineering workstation is to simulate the images that would be generated by the sensors. The simulation system is designed to use the graphics modeling and rendering capabilities of various workstations manufactured by Silicon Graphics Inc. The workstation simulates various aspects of the sensor-generated images arising from phenomenology of the sensors. In addition, the workstation can be used to simulate a variety of impairments due to mechanical limitations of the sensor placement and due to the motion of the airplane. Although the simulation is currently not performed in real-time, sequences of individual frames can be processed, stored, and recorded in a video format. In that way, it is possible to examine the appearance of different dynamic sensor-generated and fused images.

Sensor trustworthiness in uncertain time varying stochastic environments

NASA Astrophysics Data System (ADS)

Verma, Ajay; Fernandes, Ronald; Vadakkeveedu, Kalyan

2011-06-01

Persistent surveillance applications require unattended sensors deployed in remote regions to track and monitor some physical stimulant of interest that can be modeled as output of time varying stochastic process. However, the accuracy or the trustworthiness of the information received through a remote and unattended sensor and sensor network cannot be readily assumed, since sensors may get disabled, corrupted, or even compromised, resulting in unreliable information. The aim of this paper is to develop information theory based metric to determine sensor trustworthiness from the sensor data in an uncertain and time varying stochastic environment. In this paper we show an information theory based determination of sensor data trustworthiness using an adaptive stochastic reference sensor model that tracks the sensor performance for the time varying physical feature, and provides a baseline model that is used to compare and analyze the observed sensor output. We present an approach in which relative entropy is used for reference model adaptation and determination of divergence of the sensor signal from the estimated reference baseline. We show that that KL-divergence is a useful metric that can be successfully used in determination of sensor failures or sensor malice of various types.

FPGA-based real time processing of the Plenoptic Wavefront Sensor

NASA Astrophysics Data System (ADS)

Rodríguez-Ramos, L. F.; Marín, Y.; Díaz, J. J.; Piqueras, J.; García-Jiménez, J.; Rodríguez-Ramos, J. M.

The plenoptic wavefront sensor combines measurements at pupil and image planes in order to obtain simultaneously wavefront information from different points of view, being capable to sample the volume above the telescope to extract the tomographic information of the atmospheric turbulence. The advantages of this sensor are presented elsewhere at this conference (José M. Rodríguez-Ramos et al). This paper will concentrate in the processing required for pupil plane phase recovery, and its computation in real time using FPGAs (Field Programmable Gate Arrays). This technology eases the implementation of massive parallel processing and allows tailoring the system to the requirements, maintaining flexibility, speed and cost figures.

Advances in Multi-Sensor Information Fusion: Theory and Applications 2017.

PubMed

Jin, Xue-Bo; Sun, Shuli; Wei, Hong; Yang, Feng-Bao

2018-04-11

The information fusion technique can integrate a large amount of data and knowledge representing the same real-world object and obtain a consistent, accurate, and useful representation of that object. The data may be independent or redundant, and can be obtained by different sensors at the same time or at different times. A suitable combination of investigative methods can substantially increase the profit of information in comparison with that from a single sensor. Multi-sensor information fusion has been a key issue in sensor research since the 1970s, and it has been applied in many fields. For example, manufacturing and process control industries can generate a lot of data, which have real, actionable business value. The fusion of these data can greatly improve productivity through digitization. The goal of this special issue is to report innovative ideas and solutions for multi-sensor information fusion in the emerging applications era, focusing on development, adoption, and applications.

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.

All-IP-Ethernet architecture for real-time sensor-fusion processing

NASA Astrophysics Data System (ADS)

Hiraki, Kei; Inaba, Mary; Tezuka, Hiroshi; Tomari, Hisanobu; Koizumi, Kenichi; Kondo, Shuya

2016-03-01

Serendipter is a device that distinguishes and selects very rare particles and cells from huge amount of population. We are currently designing and constructing information processing system for a Serendipter. The information processing system for Serendipter is a kind of sensor-fusion system but with much more difficulties: To fulfill these requirements, we adopt All IP based architecture: All IP-Ethernet based data processing system consists of (1) sensor/detector directly output data as IP-Ethernet packet stream, (2) single Ethernet/TCP/IP streams by a L2 100Gbps Ethernet switch, (3) An FPGA board with 100Gbps Ethernet I/F connected to the switch and a Xeon based server. Circuits in the FPGA include 100Gbps Ethernet MAC, buffers and preprocessing, and real-time Deep learning circuits using multi-layer neural networks. Proposed All-IP architecture solves existing problem to construct large-scale sensor-fusion systems.

MITRE sensor layer prototype

NASA Astrophysics Data System (ADS)

Duff, Francis; McGarry, Donald; Zasada, David; Foote, Scott

2009-05-01

The MITRE Sensor Layer Prototype is an initial design effort to enable every sensor to help create new capabilities through collaborative data sharing. By making both upstream (raw) and downstream (processed) sensor data visible, users can access the specific level, type, and quantities of data needed to create new data products that were never anticipated by the original designers of the individual sensors. The major characteristic that sets sensor data services apart from typical enterprise services is the volume (on the order of multiple terabytes) of raw data that can be generated by most sensors. Traditional tightly coupled processing approaches extract pre-determined information from the incoming raw sensor data, format it, and send it to predetermined users. The community is rapidly reaching the conclusion that tightly coupled sensor processing loses too much potentially critical information.1 Hence upstream (raw and partially processed) data must be extracted, rapidly archived, and advertised to the enterprise for unanticipated uses. The authors believe layered sensing net-centric integration can be achieved through a standardize-encapsulate-syndicateaggregate- manipulate-process paradigm. The Sensor Layer Prototype's technical approach focuses on implementing this proof of concept framework to make sensor data visible, accessible and useful to the enterprise. To achieve this, a "raw" data tap between physical transducers associated with sensor arrays and the embedded sensor signal processing hardware and software has been exploited. Second, we encapsulate and expose both raw and partially processed data to the enterprise within the context of a service-oriented architecture. Third, we advertise the presence of multiple types, and multiple layers of data through geographic-enabled Really Simple Syndication (GeoRSS) services. These GeoRSS feeds are aggregated, manipulated, and filtered by a feed aggregator. After filtering these feeds to bring just the type and location of data sought by multiple processes to the attention of each processing station, just that specifically sought data is downloaded to each process application. The Sensor Layer Prototype participated in a proof-of-concept demonstration in April 2008. This event allowed multiple MITRE innovation programs to interact among themselves to demonstrate the ability to couple value-adding but previously unanticipated users to the enterprise. For this event, the Sensor Layer Prototype was used to show data entering the environment in real time. Multiple data types were encapsulated and added to the database via the Sensor Layer Prototype, specifically National Imagery Transmission Format 2.1 (NITF), NATO Standardization Format 4607 (STANAG 4607), Cursor-on-Target (CoT), Joint Photographic Experts Group (JPEG), Hierarchical Data Format (HDF5) and several additional sensor file formats describing multiple sensors addressing a common scenario.

Ontology-Based Architecture for Intelligent Transportation Systems Using a Traffic Sensor Network.

PubMed

Fernandez, Susel; Hadfi, Rafik; Ito, Takayuki; Marsa-Maestre, Ivan; Velasco, Juan R

2016-08-15

Intelligent transportation systems are a set of technological solutions used to improve the performance and safety of road transportation. A crucial element for the success of these systems is the exchange of information, not only between vehicles, but also among other components in the road infrastructure through different applications. One of the most important information sources in this kind of systems is sensors. Sensors can be within vehicles or as part of the infrastructure, such as bridges, roads or traffic signs. Sensors can provide information related to weather conditions and traffic situation, which is useful to improve the driving process. To facilitate the exchange of information between the different applications that use sensor data, a common framework of knowledge is needed to allow interoperability. In this paper an ontology-driven architecture to improve the driving environment through a traffic sensor network is proposed. The system performs different tasks automatically to increase driver safety and comfort using the information provided by the sensors.

Ontology-Based Architecture for Intelligent Transportation Systems Using a Traffic Sensor Network

PubMed Central

Fernandez, Susel; Hadfi, Rafik; Ito, Takayuki; Marsa-Maestre, Ivan; Velasco, Juan R.

2016-01-01

Intelligent transportation systems are a set of technological solutions used to improve the performance and safety of road transportation. A crucial element for the success of these systems is the exchange of information, not only between vehicles, but also among other components in the road infrastructure through different applications. One of the most important information sources in this kind of systems is sensors. Sensors can be within vehicles or as part of the infrastructure, such as bridges, roads or traffic signs. Sensors can provide information related to weather conditions and traffic situation, which is useful to improve the driving process. To facilitate the exchange of information between the different applications that use sensor data, a common framework of knowledge is needed to allow interoperability. In this paper an ontology-driven architecture to improve the driving environment through a traffic sensor network is proposed. The system performs different tasks automatically to increase driver safety and comfort using the information provided by the sensors. PMID:27537878

LANDSAT-D Investigations Workshop

NASA Technical Reports Server (NTRS)

1982-01-01

Viewgraphs are presented which highlight LANDSAT-D project status and ground segment; early access TM processing; LANDSAT-D data acquisition and availability; LANDSAT-D performance characterization; MSS pre-NOAA characterization; MSS radiometric sensor performance (spectral information, absolute calibration, and ground processing); MSS geometric sensor performance; and MSS geometric processing and calibration.

From data to information and knowledge for geospatial applications

NASA Astrophysics Data System (ADS)

Schenk, T.; Csatho, B.; Yoon, T.

2006-12-01

An ever-increasing number of airborne and spaceborne data-acquisition missions with various sensors produce a glut of data. Sensory data rarely contains information in a explicit form such that an application can directly use it. The processing and analyzing of data constitutes a real bottleneck; therefore, automating the processes of gaining useful information and knowledge from the raw data is of paramount interest. This presentation is concerned with the transition from data to information and knowledge. With data we refer to the sensor output and we notice that data provide very rarely direct answers for applications. For example, a pixel in a digital image or a laser point from a LIDAR system (data) have no direct relationship with elevation changes of topographic surfaces or the velocity of a glacier (information, knowledge). We propose to employ the computer vision paradigm to extract information and knowledge as it pertains to a wide range of geoscience applications. After introducing the paradigm we describe the major steps to be undertaken for extracting information and knowledge from sensory input data. Features play an important role in this process. Thus we focus on extracting features and their perceptual organization to higher order constructs. We demonstrate these concepts with imaging data and laser point clouds. The second part of the presentation addresses the problem of combining data obtained by different sensors. An absolute prerequisite for successful fusion is to establish a common reference frame. We elaborate on the concept of sensor invariant features that allow the registration of such disparate data sets as aerial/satellite imagery, 3D laser point clouds, and multi/hyperspectral imagery. Fusion takes place on the data level (sensor registration) and on the information level. We show how fusion increases the degree of automation for reconstructing topographic surfaces. Moreover, fused information gained from the three sensors results in a more abstract surface representation with a rich set of explicit surface information that can be readily used by an analyst for applications such as change detection.

Surveillance of industrial processes with correlated parameters

DOEpatents

White, Andrew M.; Gross, Kenny C.; Kubic, William L.; Wigeland, Roald A.

1996-01-01

A system and method for surveillance of an industrial process. The system and method includes a plurality of sensors monitoring industrial process parameters, devices to convert the sensed data to computer compatible information and a computer which executes computer software directed to analyzing the sensor data to discern statistically reliable alarm conditions. The computer software is executed to remove serial correlation information and then calculate Mahalanobis distribution data to carry out a probability ratio test to determine alarm conditions.

Adding Processing Functionality to the Sensor Web

NASA Astrophysics Data System (ADS)

Stasch, Christoph; Pross, Benjamin; Jirka, Simon; Gräler, Benedikt

2017-04-01

The Sensor Web allows discovering, accessing and tasking different kinds of environmental sensors in the Web, ranging from simple in-situ sensors to remote sensing systems. However, (geo-)processing functionality needs to be applied to integrate data from different sensor sources and to generate higher level information products. Yet, a common standardized approach for processing sensor data in the Sensor Web is still missing and the integration differs from application to application. Standardizing not only the provision of sensor data, but also the processing facilitates sharing and re-use of processing modules, enables reproducibility of processing results, and provides a common way to integrate external scalable processing facilities or legacy software. In this presentation, we provide an overview on on-going research projects that develop concepts for coupling standardized geoprocessing technologies with Sensor Web technologies. At first, different architectures for coupling sensor data services with geoprocessing services are presented. Afterwards, profiles for linear regression and spatio-temporal interpolation of the OGC Web Processing Services that allow consuming sensor data coming from and uploading predictions to Sensor Observation Services are introduced. The profiles are implemented in processing services for the hydrological domain. Finally, we illustrate how the R software can be coupled with existing OGC Sensor Web and Geoprocessing Services and present an example, how a Web app can be built that allows exploring the results of environmental models in an interactive way using the R Shiny framework. All of the software presented is available as Open Source Software.

Summary of the First Network-Centric Sensing Community Workshop, ’Netted Sensors: A Government, Industry and Academia Dialogue’

DTIC Science & Technology

2006-04-01

and Scalability, (2) Sensors and Platforms, (3) Distributed Computing and Processing , (4) Information Management, (5) Fusion and Resource Management...use of the deployed system. 3.3 Distributed Computing and Processing Session The Distributed Computing and Processing Session consisted of three

Strategy Developed for Selecting Optimal Sensors for Monitoring Engine Health

NASA Technical Reports Server (NTRS)

2004-01-01

Sensor indications during rocket engine operation are the primary means of assessing engine performance and health. Effective selection and location of sensors in the operating engine environment enables accurate real-time condition monitoring and rapid engine controller response to mitigate critical fault conditions. These capabilities are crucial to ensure crew safety and mission success. Effective sensor selection also facilitates postflight condition assessment, which contributes to efficient engine maintenance and reduced operating costs. Under the Next Generation Launch Technology program, the NASA Glenn Research Center, in partnership with Rocketdyne Propulsion and Power, has developed a model-based procedure for systematically selecting an optimal sensor suite for assessing rocket engine system health. This optimization process is termed the systematic sensor selection strategy. Engine health management (EHM) systems generally employ multiple diagnostic procedures including data validation, anomaly detection, fault-isolation, and information fusion. The effectiveness of each diagnostic component is affected by the quality, availability, and compatibility of sensor data. Therefore systematic sensor selection is an enabling technology for EHM. Information in three categories is required by the systematic sensor selection strategy. The first category consists of targeted engine fault information; including the description and estimated risk-reduction factor for each identified fault. Risk-reduction factors are used to define and rank the potential merit of timely fault diagnoses. The second category is composed of candidate sensor information; including type, location, and estimated variance in normal operation. The final category includes the definition of fault scenarios characteristic of each targeted engine fault. These scenarios are defined in terms of engine model hardware parameters. Values of these parameters define engine simulations that generate expected sensor values for targeted fault scenarios. Taken together, this information provides an efficient condensation of the engineering experience and engine flow physics needed for sensor selection. The systematic sensor selection strategy is composed of three primary algorithms. The core of the selection process is a genetic algorithm that iteratively improves a defined quality measure of selected sensor suites. A merit algorithm is employed to compute the quality measure for each test sensor suite presented by the selection process. The quality measure is based on the fidelity of fault detection and the level of fault source discrimination provided by the test sensor suite. An inverse engine model, whose function is to derive hardware performance parameters from sensor data, is an integral part of the merit algorithm. The final component is a statistical evaluation algorithm that characterizes the impact of interference effects, such as control-induced sensor variation and sensor noise, on the probability of fault detection and isolation for optimal and near-optimal sensor suites.

An integrative solution for managing, tracing and citing sensor-related information

NASA Astrophysics Data System (ADS)

Koppe, Roland; Gerchow, Peter; Macario, Ana; Schewe, Ingo; Rehmcke, Steven; Düde, Tobias

2017-04-01

In a data-driven scientific world, the need to capture information on sensors used in the data acquisition process has become increasingly important. Following the recommendations of the Open Geospatial Consortium (OGC), we started by adopting the SensorML standard for describing platforms, devices and sensors. However, it soon became obvious to us that understanding, implementing and filling such standards costs significant effort and cannot be expected from every scientist individually. So we developed a web-based sensor management solution (https://sensor.awi.de) for describing platforms, devices and sensors as hierarchy of systems which supports tracing changes to a system whereas hiding complexity. Each platform contains devices where each device can have sensors associated with specific identifiers, contacts, events, related online resources (e.g. manufacturer factsheets, calibration documentation, data processing documentation), sensor output parameters and geo-location. In order to better understand and address real world requirements, we have closely interacted with field-going scientists in the context of the key national infrastructure project "FRontiers in Arctic marine Monitoring ocean observatory" (FRAM) during the software development. We learned that not only the lineage of observations is crucial for scientists but also alert services using value ranges, flexible output formats and information on data providers (e.g. FTP sources) for example. Mostly important, persistent and citable versions of sensor descriptions are required for traceability and reproducibility allowing seamless integration with existing information systems, e.g. PANGAEA. Within the context of the EU-funded Ocean Data Interoperability Platform project (ODIP II) and in cooperation with 52north we are proving near real-time data via Sensor Observation Services (SOS) along with sensor descriptions based on our sensor management solution. ODIP II also aims to develop a harmonized SensorML profile for the marine community which we will be adopting in our solution as soon as available. In this presentation we will show our sensor management solution which is embedded in our data flow framework to offer out-of-the-box interoperability with existing information systems and standards. In addition, we will present real world examples and challenges related to the description and traceability of sensor metadata.

Haptic Edge Detection Through Shear

NASA Astrophysics Data System (ADS)

Platkiewicz, Jonathan; Lipson, Hod; Hayward, Vincent

2016-03-01

Most tactile sensors are based on the assumption that touch depends on measuring pressure. However, the pressure distribution at the surface of a tactile sensor cannot be acquired directly and must be inferred from the deformation field induced by the touched object in the sensor medium. Currently, there is no consensus as to which components of strain are most informative for tactile sensing. Here, we propose that shape-related tactile information is more suitably recovered from shear strain than normal strain. Based on a contact mechanics analysis, we demonstrate that the elastic behavior of a haptic probe provides a robust edge detection mechanism when shear strain is sensed. We used a jamming-based robot gripper as a tactile sensor to empirically validate that shear strain processing gives accurate edge information that is invariant to changes in pressure, as predicted by the contact mechanics study. This result has implications for the design of effective tactile sensors as well as for the understanding of the early somatosensory processing in mammals.

Haptic Edge Detection Through Shear

PubMed Central

Platkiewicz, Jonathan; Lipson, Hod; Hayward, Vincent

2016-01-01

Most tactile sensors are based on the assumption that touch depends on measuring pressure. However, the pressure distribution at the surface of a tactile sensor cannot be acquired directly and must be inferred from the deformation field induced by the touched object in the sensor medium. Currently, there is no consensus as to which components of strain are most informative for tactile sensing. Here, we propose that shape-related tactile information is more suitably recovered from shear strain than normal strain. Based on a contact mechanics analysis, we demonstrate that the elastic behavior of a haptic probe provides a robust edge detection mechanism when shear strain is sensed. We used a jamming-based robot gripper as a tactile sensor to empirically validate that shear strain processing gives accurate edge information that is invariant to changes in pressure, as predicted by the contact mechanics study. This result has implications for the design of effective tactile sensors as well as for the understanding of the early somatosensory processing in mammals. PMID:27009331

Haptic Edge Detection Through Shear.

PubMed

Platkiewicz, Jonathan; Lipson, Hod; Hayward, Vincent

2016-03-24

Most tactile sensors are based on the assumption that touch depends on measuring pressure. However, the pressure distribution at the surface of a tactile sensor cannot be acquired directly and must be inferred from the deformation field induced by the touched object in the sensor medium. Currently, there is no consensus as to which components of strain are most informative for tactile sensing. Here, we propose that shape-related tactile information is more suitably recovered from shear strain than normal strain. Based on a contact mechanics analysis, we demonstrate that the elastic behavior of a haptic probe provides a robust edge detection mechanism when shear strain is sensed. We used a jamming-based robot gripper as a tactile sensor to empirically validate that shear strain processing gives accurate edge information that is invariant to changes in pressure, as predicted by the contact mechanics study. This result has implications for the design of effective tactile sensors as well as for the understanding of the early somatosensory processing in mammals.

Survey of Visual and Force/Tactile Control of Robots for Physical Interaction in Spain

PubMed Central

Garcia, Gabriel J.; Corrales, Juan A.; Pomares, Jorge; Torres, Fernando

2009-01-01

Sensors provide robotic systems with the information required to perceive the changes that happen in unstructured environments and modify their actions accordingly. The robotic controllers which process and analyze this sensory information are usually based on three types of sensors (visual, force/torque and tactile) which identify the most widespread robotic control strategies: visual servoing control, force control and tactile control. This paper presents a detailed review on the sensor architectures, algorithmic techniques and applications which have been developed by Spanish researchers in order to implement these mono-sensor and multi-sensor controllers which combine several sensors. PMID:22303146

Surveillance of industrial processes with correlated parameters

DOEpatents

White, A.M.; Gross, K.C.; Kubic, W.L.; Wigeland, R.A.

1996-12-17

A system and method for surveillance of an industrial process are disclosed. The system and method includes a plurality of sensors monitoring industrial process parameters, devices to convert the sensed data to computer compatible information and a computer which executes computer software directed to analyzing the sensor data to discern statistically reliable alarm conditions. The computer software is executed to remove serial correlation information and then calculate Mahalanobis distribution data to carry out a probability ratio test to determine alarm conditions. 10 figs.

Guide to remote-sensor data systems

NASA Technical Reports Server (NTRS)

Dewitt, R. R.; Ellison, J. L.

1980-01-01

Remote sensing data-handbook presents theoretical and practical information on spaceborne sensors and associated systems for Earth-resources applications. Handbook provides discussion on historical information, principles of operations, factors affecting performances, nature of data output, and system required to process data and trends in research and development.

A wearable context aware system for ubiquitous healthcare.

PubMed

Kang, Dong-Oh; Lee, Hyung-Jik; Ko, Eun-Jung; Kang, Kyuchang; Lee, Jeunwoo

2006-01-01

Recent developments of information technologies are leading the advent of the era of ubiquitous healthcare, which means healthcare services at any time and at any places. The ubiquitous healthcare service needs a wearable system for more continual measurement of biological signals of a user, which gives information of the user from wearable sensors. In this paper, we propose a wearable context aware system for ubiquitous healthcare, and its systematic design process of a ubiquitous healthcare service. Some wearable sensor systems are introduced with Zigbee communication. We develop a context aware framework to send information from wearable sensors to healthcare service entities as a middleware to solve the interoperability problem between sensor makers and healthcare service providers. And, we propose a systematic process of design of ubiquitous healthcare services with the context aware framework. In order to show the feasibility of the proposed system, some application examples are given, which are applied to remote monitoring, and a self check service.

Haptic seat for fuel economy feedback

DOEpatents

Bobbitt, III, John Thomas

2016-08-30

A process of providing driver fuel economy feedback is disclosed in which vehicle sensors provide for haptic feedback on fuel usage. Such sensors may include one or more of a speed sensors, global position satellite units, vehicle pitch/roll angle sensors, suspension displacement sensors, longitudinal accelerometer sensors, throttle position in sensors, steering angle sensors, break pressure sensors, and lateral accelerometer sensors. Sensors used singlely or collectively can provide enhanced feedback as to various environmental conditions and operating conditions such that a more accurate assessment of fuel economy information can be provided to the driver.

Towards a Unified Approach to Information Integration - A review paper on data/information fusion

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

Whitney, Paul D.; Posse, Christian; Lei, Xingye C.

2005-10-14

Information or data fusion of data from different sources are ubiquitous in many applications, from epidemiology, medical, biological, political, and intelligence to military applications. Data fusion involves integration of spectral, imaging, text, and many other sensor data. For example, in epidemiology, information is often obtained based on many studies conducted by different researchers at different regions with different protocols. In the medical field, the diagnosis of a disease is often based on imaging (MRI, X-Ray, CT), clinical examination, and lab results. In the biological field, information is obtained based on studies conducted on many different species. In military field, informationmore » is obtained based on data from radar sensors, text messages, chemical biological sensor, acoustic sensor, optical warning and many other sources. Many methodologies are used in the data integration process, from classical, Bayesian, to evidence based expert systems. The implementation of the data integration ranges from pure software design to a mixture of software and hardware. In this review we summarize the methodologies and implementations of data fusion process, and illustrate in more detail the methodologies involved in three examples. We propose a unified multi-stage and multi-path mapping approach to the data fusion process, and point out future prospects and challenges.« less

On Certain New Methodology for Reducing Sensor and Readout Electronics Circuitry Noise in Digital Domain

NASA Technical Reports Server (NTRS)

Kizhner, Semion; Miko, Joseph; Bradley, Damon; Heinzen, Katherine

2008-01-01

NASA Hubble Space Telescope (HST) and upcoming cosmology science missions carry instruments with multiple focal planes populated with many large sensor detector arrays. These sensors are passively cooled to low temperatures for low-level light (L3) and near-infrared (NIR) signal detection, and the sensor readout electronics circuitry must perform at extremely low noise levels to enable new required science measurements. Because we are at the technological edge of enhanced performance for sensors and readout electronics circuitry, as determined by thermal noise level at given temperature in analog domain, we must find new ways of further compensating for the noise in the signal digital domain. To facilitate this new approach, state-of-the-art sensors are augmented at their array hardware boundaries by non-illuminated reference pixels, which can be used to reduce noise attributed to sensors. There are a few proposed methodologies of processing in the digital domain the information carried by reference pixels, as employed by the Hubble Space Telescope and the James Webb Space Telescope Projects. These methods involve using spatial and temporal statistical parameters derived from boundary reference pixel information to enhance the active (non-reference) pixel signals. To make a step beyond this heritage methodology, we apply the NASA-developed technology known as the Hilbert- Huang Transform Data Processing System (HHT-DPS) for reference pixel information processing and its utilization in reconfigurable hardware on-board a spaceflight instrument or post-processing on the ground. The methodology examines signal processing for a 2-D domain, in which high-variance components of the thermal noise are carried by both active and reference pixels, similar to that in processing of low-voltage differential signals and subtraction of a single analog reference pixel from all active pixels on the sensor. Heritage methods using the aforementioned statistical parameters in the digital domain (such as statistical averaging of the reference pixels themselves) zeroes out the high-variance components, and the counterpart components in the active pixels remain uncorrected. This paper describes how the new methodology was demonstrated through analysis of fast-varying noise components using the Hilbert-Huang Transform Data Processing System tool (HHT-DPS) developed at NASA and the high-level programming language MATLAB (Trademark of MathWorks Inc.), as well as alternative methods for correcting for the high-variance noise component, using an HgCdTe sensor data. The NASA Hubble Space Telescope data post-processing, as well as future deep-space cosmology projects on-board instrument data processing from all the sensor channels, would benefit from this effort.

Graphite nanoplatelet enabled embeddable fiber sensor for in situ curing monitoring and structural health monitoring of polymeric composites.

PubMed

Luo, Sida; Liu, Tao

2014-06-25

A graphite nanoplatelet (GNP) thin film enabled 1D fiber sensor (GNP-FibSen) was fabricated by a continuous roll-to-roll spray coating process, characterized by scanning electron microscopy and Raman spectroscopy and evaluated by coupled electrical-mechanical tensile testing. The neat GNP-FibSen sensor shows very high gauge sensitivity with a gauge factor of ∼17. By embedding the sensor in fiberglass prepreg laminate parts, the dual functionalities of the GNP-FibSen sensor were demonstrated. In the manufacturing process, the resistance change of the embedded sensor provides valuable local resin curing information. After the manufacturing process, the same sensor is able to map the strain/stress states and detect the failure of the host composite. The superior durability of the embedded GNP-FibSen sensor has been demonstrated through 10,000 cycles of coupled electromechanical tests.

Network-Capable Application Process and Wireless Intelligent Sensors for ISHM

NASA Technical Reports Server (NTRS)

Figueroa, Fernando; Morris, Jon; Turowski, Mark; Wang, Ray

2011-01-01

Intelligent sensor technology and systems are increasingly becoming attractive means to serve as frameworks for intelligent rocket test facilities with embedded intelligent sensor elements, distributed data acquisition elements, and onboard data acquisition elements. Networked intelligent processors enable users and systems integrators to automatically configure their measurement automation systems for analog sensors. NASA and leading sensor vendors are working together to apply the IEEE 1451 standard for adding plug-and-play capabilities for wireless analog transducers through the use of a Transducer Electronic Data Sheet (TEDS) in order to simplify sensor setup, use, and maintenance, to automatically obtain calibration data, and to eliminate manual data entry and error. A TEDS contains the critical information needed by an instrument or measurement system to identify, characterize, interface, and properly use the signal from an analog sensor. A TEDS is deployed for a sensor in one of two ways. First, the TEDS can reside in embedded, nonvolatile memory (typically flash memory) within the intelligent processor. Second, a virtual TEDS can exist as a separate file, downloadable from the Internet. This concept of virtual TEDS extends the benefits of the standardized TEDS to legacy sensors and applications where the embedded memory is not available. An HTML-based user interface provides a visual tool to interface with those distributed sensors that a TEDS is associated with, to automate the sensor management process. Implementing and deploying the IEEE 1451.1-based Network-Capable Application Process (NCAP) can achieve support for intelligent process in Integrated Systems Health Management (ISHM) for the purpose of monitoring, detection of anomalies, diagnosis of causes of anomalies, prediction of future anomalies, mitigation to maintain operability, and integrated awareness of system health by the operator. It can also support local data collection and storage. This invention enables wide-area sensing and employs numerous globally distributed sensing devices that observe the physical world through the existing sensor network. This innovation enables distributed storage, distributed processing, distributed intelligence, and the availability of DiaK (Data, Information, and Knowledge) to any element as needed. It also enables the simultaneous execution of multiple processes, and represents models that contribute to the determination of the condition and health of each element in the system. The NCAP (intelligent process) can configure data-collection and filtering processes in reaction to sensed data, allowing it to decide when and how to adapt collection and processing with regard to sophisticated analysis of data derived from multiple sensors. The user will be able to view the sensing device network as a single unit that supports a high-level query language. Each query would be able to operate over data collected from across the global sensor network just as a search query encompasses millions of Web pages. The sensor web can preserve ubiquitous information access between the querier and the queried data. Pervasive monitoring of the physical world raises significant data and privacy concerns. This innovation enables different authorities to control portions of the sensing infrastructure, and sensor service authors may wish to compose services across authority boundaries.

Signal processing methods for MFE plasma diagnostics

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

Candy, J.V.; Casper, T.; Kane, R.

1985-02-01

The application of various signal processing methods to extract energy storage information from plasma diamagnetism sensors occurring during physics experiments on the Tandom Mirror Experiment-Upgrade (TMX-U) is discussed. We show how these processing techniques can be used to decrease the uncertainty in the corresponding sensor measurements. The algorithms suggested are implemented using SIG, an interactive signal processing package developed at LLNL.

An Analog Circuit Approximation of the Discrete Wavelet Transform for Ultra Low Power Signal Processing in Wearable Sensor Nodes

PubMed Central

Casson, Alexander J.

2015-01-01

Ultra low power signal processing is an essential part of all sensor nodes, and particularly so in emerging wearable sensors for biomedical applications. Analog signal processing has an important role in these low power, low voltage, low frequency applications, and there is a key drive to decrease the power consumption of existing analog domain signal processing and to map more signal processing approaches into the analog domain. This paper presents an analog domain signal processing circuit which approximates the output of the Discrete Wavelet Transform (DWT) for use in ultra low power wearable sensors. Analog filters are used for the DWT filters and it is demonstrated how these generate analog domain DWT-like information that embeds information from Butterworth and Daubechies maximally flat mother wavelet responses. The Analog DWT is realised in hardware via gmC circuits, designed to operate from a 1.3 V coin cell battery, and provide DWT-like signal processing using under 115 nW of power when implemented in a 0.18 μm CMOS process. Practical examples demonstrate the effective use of the new Analog DWT on ECG (electrocardiogram) and EEG (electroencephalogram) signals recorded from humans. PMID:26694414

An Analog Circuit Approximation of the Discrete Wavelet Transform for Ultra Low Power Signal Processing in Wearable Sensor Nodes.

PubMed

Casson, Alexander J

2015-12-17

Ultra low power signal processing is an essential part of all sensor nodes, and particularly so in emerging wearable sensors for biomedical applications. Analog signal processing has an important role in these low power, low voltage, low frequency applications, and there is a key drive to decrease the power consumption of existing analog domain signal processing and to map more signal processing approaches into the analog domain. This paper presents an analog domain signal processing circuit which approximates the output of the Discrete Wavelet Transform (DWT) for use in ultra low power wearable sensors. Analog filters are used for the DWT filters and it is demonstrated how these generate analog domain DWT-like information that embeds information from Butterworth and Daubechies maximally flat mother wavelet responses. The Analog DWT is realised in hardware via g(m)C circuits, designed to operate from a 1.3 V coin cell battery, and provide DWT-like signal processing using under 115 nW of power when implemented in a 0.18 μm CMOS process. Practical examples demonstrate the effective use of the new Analog DWT on ECG (electrocardiogram) and EEG (electroencephalogram) signals recorded from humans.

An evolutionary sensor approach for self-organizing production chains

NASA Astrophysics Data System (ADS)

Mocan, M.; Gillich, E. V.; Mituletu, I. C.; Korka, Z. I.

2018-01-01

Industry 4.0 is the actual great step in industrial progress. Convergence of industrial equipment with the power of advanced computing and analysis, low-cost sensing, and new connecting technologies are presumed to bring unexpected advancements in automation, flexibility, and efficiency. In this context, sensors ensure information regarding three essential areas: the number of processed elements, the quality of production and the condition of tools and equipment. To obtain this valuable information, the data resulted from a sensor has to be firstly processed and afterward used by the different stakeholders. If machines are linked together, this information can be employed to organize the production chain with few or without human intervention. We describe here the implementation of a sensor in a milling machine that is part of a simple production chain, capable of providing information regarding the number of manufactured pieces. It is used by the other machines in the production chain, in order to define the type and number of pieces to be manufactured by them and/or to set optimal parameters for their working regime. Secondly, the information achieved by monitoring the machine and manufactured piece dynamic behavior is used to evaluate the product quality. This information is used to warn about the need of maintenance, being transmitted to the specialized department. It is also transmitted to the central unit, in order to reorganize the production by involving other machines or by reconsidering the manufacturing regime of the existing machines. A special attention is drawn on analyzing and classifying the signals acquired via optical sensor from simulated processes.

Transitioning mine warfare to network-centric sensor analysis: future PMA technologies & capabilities

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.

Sensor Data Fusion with Z-Numbers and Its Application in Fault Diagnosis

PubMed Central

Jiang, Wen; Xie, Chunhe; Zhuang, Miaoyan; Shou, Yehang; Tang, Yongchuan

2016-01-01

Sensor data fusion technology is widely employed in fault diagnosis. The information in a sensor data fusion system is characterized by not only fuzziness, but also partial reliability. Uncertain information of sensors, including randomness, fuzziness, etc., has been extensively studied recently. However, the reliability of a sensor is often overlooked or cannot be analyzed adequately. A Z-number, Z = (A, B), can represent the fuzziness and the reliability of information simultaneously, where the first component A represents a fuzzy restriction on the values of uncertain variables and the second component B is a measure of the reliability of A. In order to model and process the uncertainties in a sensor data fusion system reasonably, in this paper, a novel method combining the Z-number and Dempster–Shafer (D-S) evidence theory is proposed, where the Z-number is used to model the fuzziness and reliability of the sensor data and the D-S evidence theory is used to fuse the uncertain information of Z-numbers. The main advantages of the proposed method are that it provides a more robust measure of reliability to the sensor data, and the complementary information of multi-sensors reduces the uncertainty of the fault recognition, thus enhancing the reliability of fault detection. PMID:27649193

Distributed multimodal data fusion for large scale wireless sensor networks

NASA Astrophysics Data System (ADS)

Ertin, Emre

2006-05-01

Sensor network technology has enabled new surveillance systems where sensor nodes equipped with processing and communication capabilities can collaboratively detect, classify and track targets of interest over a large surveillance area. In this paper we study distributed fusion of multimodal sensor data for extracting target information from a large scale sensor network. Optimal tracking, classification, and reporting of threat events require joint consideration of multiple sensor modalities. Multiple sensor modalities improve tracking by reducing the uncertainty in the track estimates as well as resolving track-sensor data association problems. Our approach to solving the fusion problem with large number of multimodal sensors is construction of likelihood maps. The likelihood maps provide a summary data for the solution of the detection, tracking and classification problem. The likelihood map presents the sensory information in an easy format for the decision makers to interpret and is suitable with fusion of spatial prior information such as maps, imaging data from stand-off imaging sensors. We follow a statistical approach to combine sensor data at different levels of uncertainty and resolution. The likelihood map transforms each sensor data stream to a spatio-temporal likelihood map ideally suitable for fusion with imaging sensor outputs and prior geographic information about the scene. We also discuss distributed computation of the likelihood map using a gossip based algorithm and present simulation results.

On-Board Mining in the Sensor Web

NASA Astrophysics Data System (ADS)

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

2004-12-01

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

Critical review of real-time methods for solid waste characterisation: Informing material recovery and fuel production.

PubMed

Vrancken, C; Longhurst, P J; Wagland, S T

2017-03-01

Waste management processes generally represent a significant loss of material, energy and economic resources, so legislation and financial incentives are being implemented to improve the recovery of these valuable resources whilst reducing contamination levels. Material recovery and waste derived fuels are potentially valuable options being pursued by industry, using mechanical and biological processes incorporating sensor and sorting technologies developed and optimised for recycling plants. In its current state, waste management presents similarities to other industries that could improve their efficiencies using process analytical technology tools. Existing sensor technologies could be used to measure critical waste characteristics, providing data required by existing legislation, potentially aiding waste treatment processes and assisting stakeholders in decision making. Optical technologies offer the most flexible solution to gather real-time information applicable to each of the waste mechanical and biological treatment processes used by industry. In particular, combinations of optical sensors in the visible and the near-infrared range from 800nm to 2500nm of the spectrum, and different mathematical techniques, are able to provide material information and fuel properties with typical performance levels between 80% and 90%. These sensors not only could be used to aid waste processes, but to provide most waste quality indicators required by existing legislation, whilst offering better tools to the stakeholders. Copyright © 2017 Elsevier Ltd. All rights reserved.

Study on an agricultural environment monitoring server system using Wireless Sensor Networks.

PubMed

Hwang, Jeonghwan; Shin, Changsun; Yoe, Hyun

2010-01-01

This paper proposes an agricultural environment monitoring server system for monitoring information concerning an outdoors agricultural production environment utilizing Wireless Sensor Network (WSN) technology. The proposed agricultural environment monitoring server system collects environmental and soil information on the outdoors through WSN-based environmental and soil sensors, collects image information through CCTVs, and collects location information using GPS modules. This collected information is converted into a database through the agricultural environment monitoring server consisting of a sensor manager, which manages information collected from the WSN sensors, an image information manager, which manages image information collected from CCTVs, and a GPS manager, which processes location information of the agricultural environment monitoring server system, and provides it to producers. In addition, a solar cell-based power supply is implemented for the server system so that it could be used in agricultural environments with insufficient power infrastructure. This agricultural environment monitoring server system could even monitor the environmental information on the outdoors remotely, and it could be expected that the use of such a system could contribute to increasing crop yields and improving quality in the agricultural field by supporting the decision making of crop producers through analysis of the collected information.

NEEDS - Information Adaptive System

NASA Technical Reports Server (NTRS)

Kelly, W. L.; Benz, H. F.; Meredith, B. D.

1980-01-01

The Information Adaptive System (IAS) is an element of the NASA End-to-End Data System (NEEDS) Phase II and is focused toward onboard image processing. The IAS is a data preprocessing system which is closely coupled to the sensor system. Some of the functions planned for the IAS include sensor response nonuniformity correction, geometric correction, data set selection, data formatting, packetization, and adaptive system control. The inclusion of these sensor data preprocessing functions onboard the spacecraft will significantly improve the extraction of information from the sensor data in a timely and cost effective manner, and provide the opportunity to design sensor systems which can be reconfigured in near real-time for optimum performance. The purpose of this paper is to present the preliminary design of the IAS and the plans for its development.

Evaluation of an electronic nose for improved biosolids alkaline-stabilization treatment and odor management

USDA-ARS?s Scientific Manuscript database

Electronic nose sensors are designed to detect differences in complex air sample matrices. For example, they have been used in the food industry to monitor process performance and quality control. However, no information is available on the application of sensor arrays to monitor process performanc...

Research of marine sensor web based on SOA and EDA

NASA Astrophysics Data System (ADS)

Jiang, Yongguo; Dou, Jinfeng; Guo, Zhongwen; Hu, Keyong

2015-04-01

A great deal of ocean sensor observation data exists, for a wide range of marine disciplines, derived from in situ and remote observing platforms, in real-time, near-real-time and delayed mode. Ocean monitoring is routinely completed using sensors and instruments. Standardization is the key requirement for exchanging information about ocean sensors and sensor data and for comparing and combining information from different sensor networks. One or more sensors are often physically integrated into a single ocean `instrument' device, which often brings in many challenges related to diverse sensor data formats, parameters units, different spatiotemporal resolution, application domains, data quality and sensors protocols. To face these challenges requires the standardization efforts aiming at facilitating the so-called Sensor Web, which making it easy to provide public access to sensor data and metadata information. In this paper, a Marine Sensor Web, based on SOA and EDA and integrating the MBARI's PUCK protocol, IEEE 1451 and OGC SWE 2.0, is illustrated with a five-layer architecture. The Web Service layer and Event Process layer are illustrated in detail with an actual example. The demo study has demonstrated that a standard-based system can be built to access sensors and marine instruments distributed globally using common Web browsers for monitoring the environment and oceanic conditions besides marine sensor data on the Web, this framework of Marine Sensor Web can also play an important role in many other domains' information integration.

Neuromorphic sensory systems.

PubMed

Liu, Shih-Chii; Delbruck, Tobi

2010-06-01

Biology provides examples of efficient machines which greatly outperform conventional technology. Designers in neuromorphic engineering aim to construct electronic systems with the same efficient style of computation. This task requires a melding of novel engineering principles with knowledge gleaned from neuroscience. We discuss recent progress in realizing neuromorphic sensory systems which mimic the biological retina and cochlea, and subsequent sensor processing. The main trends are the increasing number of sensors and sensory systems that communicate through asynchronous digital signals analogous to neural spikes; the improved performance and usability of these sensors; and novel sensory processing methods which capitalize on the timing of spikes from these sensors. Experiments using these sensors can impact how we think the brain processes sensory information. 2010 Elsevier Ltd. All rights reserved.

Qualitative Features Extraction from Sensor Data using Short-time Fourier Transform

NASA Technical Reports Server (NTRS)

Amini, Abolfazl M.; Figueroa, Fernando

2004-01-01

The information gathered from sensors is used to determine the health of a sensor. Once a normal mode of operation is established any deviation from the normal behavior indicates a change. This change may be due to a malfunction of the sensor(s) or the system (or process). The step-up and step-down features, as well as sensor disturbances are assumed to be exponential. An RC network is used to model the main process, which is defined by a step-up (charging), drift, and step-down (discharging). The sensor disturbances and spike are added while the system is in drift. The system runs for a period of at least three time-constants of the main process every time a process feature occurs (e.g. step change). The Short-Time Fourier Transform of the Signal is taken using the Hamming window. Three window widths are used. The DC value is removed from the windowed data prior to taking the FFT. The resulting three dimensional spectral plots provide good time frequency resolution. The results indicate distinct shapes corresponding to each process.

Process and control systems for composites manufacturing

NASA Technical Reports Server (NTRS)

Tsiang, T. H.; Wanamaker, John L.

1992-01-01

A precise control of composite material processing would not only improve part quality, but it would also directly reduce the overall manufacturing cost. The development and incorporation of sensors will help to generate real-time information for material processing relationships and equipment characteristics. In the present work, the thermocouple, pressure transducer, and dielectrometer technologies were investigated. The monitoring sensors were integrated with the computerized control system in three non-autoclave fabrication techniques: hot-press, self contained tool (self heating and pressurizing), and pressure vessel). The sensors were implemented in the parts and tools.

Research and development program in fiber optic sensors and distributed sensing for high temperature harsh environment energy applications (Conference Presentation)

NASA Astrophysics Data System (ADS)

Romanosky, Robert R.

2017-05-01

he National Energy Technology Laboratory (NETL) under the Department of Energy (DOE) Fossil Energy (FE) Program is leading the effort to not only develop near zero emission power generation systems, but to increaser the efficiency and availability of current power systems. The overarching goal of the program is to provide clean affordable power using domestic resources. Highly efficient, low emission power systems can have extreme conditions of high temperatures up to 1600 oC, high pressures up to 600 psi, high particulate loadings, and corrosive atmospheres that require monitoring. Sensing in these harsh environments can provide key information that directly impacts process control and system reliability. The lack of suitable measurement technology serves as a driver for the innovations in harsh environment sensor development. Advancements in sensing using optical fibers are key efforts within NETL's sensor development program as these approaches offer the potential to survive and provide critical information about these processes. An overview of the sensor development supported by the National Energy Technology Laboratory (NETL) will be given, including research in the areas of sensor materials, designs, and measurement types. New approaches to intelligent sensing, sensor placement and process control using networked sensors will be discussed as will novel approaches to fiber device design concurrent with materials development research and development in modified and coated silica and sapphire fiber based sensors. The use of these sensors for both single point and distributed measurements of temperature, pressure, strain, and a select suite of gases will be addressed. Additional areas of research includes novel control architecture and communication frameworks, device integration for distributed sensing, and imaging and other novel approaches to monitoring and controlling advanced processes. The close coupling of the sensor program with process modeling and control will be discussed for the overarching goal of clean power production.

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

NASA Astrophysics Data System (ADS)

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

2016-05-01

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

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.

Modeling, simulation, and analysis of optical remote sensing systems

NASA Technical Reports Server (NTRS)

Kerekes, John Paul; Landgrebe, David A.

1989-01-01

Remote Sensing of the Earth's resources from space-based sensors has evolved in the past 20 years from a scientific experiment to a commonly used technological tool. The scientific applications and engineering aspects of remote sensing systems have been studied extensively. However, most of these studies have been aimed at understanding individual aspects of the remote sensing process while relatively few have studied their interrelations. A motivation for studying these interrelationships has arisen with the advent of highly sophisticated configurable sensors as part of the Earth Observing System (EOS) proposed by NASA for the 1990's. Two approaches to investigating remote sensing systems are developed. In one approach, detailed models of the scene, the sensor, and the processing aspects of the system are implemented in a discrete simulation. This approach is useful in creating simulated images with desired characteristics for use in sensor or processing algorithm development. A less complete, but computationally simpler method based on a parametric model of the system is also developed. In this analytical model the various informational classes are parameterized by their spectral mean vector and covariance matrix. These class statistics are modified by models for the atmosphere, the sensor, and processing algorithms and an estimate made of the resulting classification accuracy among the informational classes. Application of these models is made to the study of the proposed High Resolution Imaging Spectrometer (HRIS). The interrelationships among observational conditions, sensor effects, and processing choices are investigated with several interesting results.

Soft sensor for monitoring biomass subpopulations in mammalian cell culture processes.

PubMed

Kroll, Paul; Stelzer, Ines V; Herwig, Christoph

2017-11-01

Biomass subpopulations in mammalian cell culture processes cause impurities and influence productivity, which requires this critical process parameter to be monitored in real-time. For this reason, a novel soft sensor concept for estimating viable, dead and lysed cell concentration was developed, based on the robust and cheap in situ measurements of permittivity and turbidity in combination with a simple model. It could be shown that the turbidity measurements contain information about all investigated biomass subpopulations. The novelty of the developed soft sensor is the real-time estimation of lysed cell concentration, which is directly correlated to process-related impurities such as DNA and host cell protein in the supernatant. Based on data generated by two fed-batch processes the developed soft sensor is described and discussed. The presented soft sensor concept provides a tool for viable, dead and lysed cell concentration estimation in real-time with adequate accuracy and enables further applications with respect to process optimization and control.

Automated analysis of long-term bridge behavior and health using a cyber-enabled wireless monitoring system

NASA Astrophysics Data System (ADS)

O'Connor, Sean M.; Zhang, Yilan; Lynch, Jerome; Ettouney, Mohammed; van der Linden, Gwen

2014-04-01

A worthy goal for the structural health monitoring field is the creation of a scalable monitoring system architecture that abstracts many of the system details (e.g., sensors, data) from the structure owner with the aim of providing "actionable" information that aids in their decision making process. While a broad array of sensor technologies have emerged, the ability for sensing systems to generate large amounts of data have far outpaced advances in data management and processing. To reverse this trend, this study explores the creation of a cyber-enabled wireless SHM system for highway bridges. The system is designed from the top down by considering the damage mechanisms of concern to bridge owners and then tailoring the sensing and decision support system around those concerns. The enabling element of the proposed system is a powerful data repository system termed SenStore. SenStore is designed to combine sensor data with bridge meta-data (e.g., geometric configuration, material properties, maintenance history, sensor locations, sensor types, inspection history). A wireless sensor network deployed to a bridge autonomously streams its measurement data to SenStore via a 3G cellular connection for storage. SenStore securely exposes the bridge meta- and sensor data to software clients that can process the data to extract information relevant to the decision making process of the bridge owner. To validate the proposed cyber-enable SHM system, the system is implemented on the Telegraph Road Bridge (Monroe, MI). The Telegraph Road Bridge is a traditional steel girder-concrete deck composite bridge located along a heavily travelled corridor in the Detroit metropolitan area. A permanent wireless sensor network has been installed to measure bridge accelerations, strains and temperatures. System identification and damage detection algorithms are created to automatically mine bridge response data stored in SenStore over an 18-month period. Tools like Gaussian Process (GP) regression are used to predict changes in the bridge behavior as a function of environmental parameters. Based on these analyses, pertinent behavioral information relevant to bridge management is autonomously extracted.

Enhanced intelligence through optimized TCPED concepts for airborne ISR

NASA Astrophysics Data System (ADS)

Spitzer, M.; Kappes, E.; Böker, D.

2012-06-01

Current multinational operations show an increased demand for high quality actionable intelligence for different operational levels and users. In order to achieve sufficient availability, quality and reliability of information, various ISR assets are orchestrated within operational theatres. Especially airborne Intelligence, Surveillance and Reconnaissance (ISR) assets provide - due to their endurance, non-intrusiveness, robustness, wide spectrum of sensors and flexibility to mission changes - significant intelligence coverage of areas of interest. An efficient and balanced utilization of airborne ISR assets calls for advanced concepts for the entire ISR process framework including the Tasking, Collection, Processing, Exploitation and Dissemination (TCPED). Beyond this, the employment of current visualization concepts, shared information bases and information customer profiles, as well as an adequate combination of ISR sensors with different information age and dynamic (online) retasking process elements provides the optimization of interlinked TCPED processes towards higher process robustness, shorter process duration, more flexibility between ISR missions and, finally, adequate "entry points" for information requirements by operational users and commands. In addition, relevant Trade-offs of distributed and dynamic TCPED processes are examined and future trends are depicted.

Perception as Abduction: Turning Sensor Data into Meaningful Representation

ERIC Educational Resources Information Center

Shanahan, Murray

2005-01-01

This article presents a formal theory of robot perception as a form of abduction. The theory pins down the process whereby low-level sensor data is transformed into a symbolic representation of the external world, drawing together aspects such as incompleteness, top-down information flow, active perception, attention, and sensor fusion in a…

Statistical sensor fusion analysis of near-IR polarimetric and thermal imagery for the detection of minelike targets

NASA Astrophysics Data System (ADS)

Weisenseel, Robert A.; Karl, William C.; Castanon, David A.; DiMarzio, Charles A.

1999-02-01

We present an analysis of statistical model based data-level fusion for near-IR polarimetric and thermal data, particularly for the detection of mines and mine-like targets. Typical detection-level data fusion methods, approaches that fuse detections from individual sensors rather than fusing at the level of the raw data, do not account rationally for the relative reliability of different sensors, nor the redundancy often inherent in multiple sensors. Representative examples of such detection-level techniques include logical AND/OR operations on detections from individual sensors and majority vote methods. In this work, we exploit a statistical data model for the detection of mines and mine-like targets to compare and fuse multiple sensor channels. Our purpose is to quantify the amount of knowledge that each polarimetric or thermal channel supplies to the detection process. With this information, we can make reasonable decisions about the usefulness of each channel. We can use this information to improve the detection process, or we can use it to reduce the number of required channels.

Frequency Domain Analysis of Sensor Data for Event Classification in Real-Time Robot Assisted Deburring

PubMed Central

Pappachan, Bobby K; Caesarendra, Wahyu; Tjahjowidodo, Tegoeh; Wijaya, Tomi

2017-01-01

Process monitoring using indirect methods relies on the usage of sensors. Using sensors to acquire vital process related information also presents itself with the problem of big data management and analysis. Due to uncertainty in the frequency of events occurring, a higher sampling rate is often used in real-time monitoring applications to increase the chances of capturing and understanding all possible events related to the process. Advanced signal processing methods are used to further decipher meaningful information from the acquired data. In this research work, power spectrum density (PSD) of sensor data acquired at sampling rates between 40–51.2 kHz was calculated and the corelation between PSD and completed number of cycles/passes is presented. Here, the progress in number of cycles/passes is the event this research work intends to classify and the algorithm used to compute PSD is Welch’s estimate method. A comparison between Welch’s estimate method and statistical methods is also discussed. A clear co-relation was observed using Welch’s estimate to classify the number of cycles/passes. The paper also succeeds in classifying vibration signal generated by the spindle from the vibration signal acquired during finishing process. PMID:28556809

Design and Deployment of Low-Cost Sensors for Monitoring the Water Quality and Fish Behavior in Aquaculture Tanks during the Feeding Process

PubMed Central

Parra, Lorena; García, Laura

2018-01-01

The monitoring of farming processes can optimize the use of resources and improve its sustainability and profitability. In fish farms, the water quality, tank environment, and fish behavior must be monitored. Wireless sensor networks (WSNs) are a promising option to perform this monitoring. Nevertheless, its high cost is slowing the expansion of its use. In this paper, we propose a set of sensors for monitoring the water quality and fish behavior in aquaculture tanks during the feeding process. The WSN is based on physical sensors, composed of simple electronic components. The system proposed can monitor water quality parameters, tank status, the feed falling and fish swimming depth and velocity. In addition, the system includes a smart algorithm to reduce the energy waste when sending the information from the node to the database. The system is composed of three nodes in each tank that send the information though the local area network to a database on the Internet and a smart algorithm that detects abnormal values and sends alarms when they happen. All the sensors are designed, calibrated, and deployed to ensure its suitability. The greatest efforts have been accomplished with the fish presence sensor. The total cost of the sensors and nodes for the proposed system is less than 90 €. PMID:29494560

Design and Deployment of Low-Cost Sensors for Monitoring the Water Quality and Fish Behavior in Aquaculture Tanks during the Feeding Process.

PubMed

Parra, Lorena; Sendra, Sandra; García, Laura; Lloret, Jaime

2018-03-01

The monitoring of farming processes can optimize the use of resources and improve its sustainability and profitability. In fish farms, the water quality, tank environment, and fish behavior must be monitored. Wireless sensor networks (WSNs) are a promising option to perform this monitoring. Nevertheless, its high cost is slowing the expansion of its use. In this paper, we propose a set of sensors for monitoring the water quality and fish behavior in aquaculture tanks during the feeding process. The WSN is based on physical sensors, composed of simple electronic components. The system proposed can monitor water quality parameters, tank status, the feed falling and fish swimming depth and velocity. In addition, the system includes a smart algorithm to reduce the energy waste when sending the information from the node to the database. The system is composed of three nodes in each tank that send the information though the local area network to a database on the Internet and a smart algorithm that detects abnormal values and sends alarms when they happen. All the sensors are designed, calibrated, and deployed to ensure its suitability. The greatest efforts have been accomplished with the fish presence sensor. The total cost of the sensors and nodes for the proposed system is less than 90 €.

Microfabricated Hydrogen Sensor Technology for Aerospace and Commercial Applications

NASA Technical Reports Server (NTRS)

Hunter, Gary W.; Bickford, R. L.; Jansa, E. D.; Makel, D. B.; Liu, C. C.; Wu, Q. H.; Powers, W. T.

1994-01-01

Leaks on the Space Shuttle while on the Launch Pad have generated interest in hydrogen leak monitoring technology. An effective leak monitoring system requires reliable hydrogen sensors, hardware, and software to monitor the sensors. The system should process the sensor outputs and provide real-time leak monitoring information to the operator. This paper discusses the progress in developing such a complete leak monitoring system. Advanced microfabricated hydrogen sensors are being fabricated at Case Western Reserve University (CWRU) and tested at NASA Lewis Research Center (LeRC) and Gencorp Aerojet (Aerojet). Changes in the hydrogen concentrations are detected using a PdAg on silicon Schottky diode structure. Sensor temperature control is achieved with a temperature sensor and heater fabricated onto the sensor chip. Results of the characterization of these sensors are presented. These sensors can detect low concentrations of hydrogen in inert environments with high sensitivity and quick response time. Aerojet is developing the hardware and software for a multipoint leak monitoring system designed to provide leak source and magnitude information in real time. The monitoring system processes data from the hydrogen sensors and presents the operator with a visual indication of the leak location and magnitude. Work has commenced on integrating the NASA LeRC-CWRU hydrogen sensors with the Aerojet designed monitoring system. Although the leak monitoring system was designed for hydrogen propulsion systems, the possible applications of this monitoring system are wide ranged. Possible commercialization of the system will also be discussed.

An Adaptive Altitude Information Fusion Method for Autonomous Landing Processes of Small Unmanned Aerial Rotorcraft

PubMed Central

Lei, Xusheng; Li, Jingjing

2012-01-01

This paper presents an adaptive information fusion method to improve the accuracy and reliability of the altitude measurement information for small unmanned aerial rotorcraft during the landing process. Focusing on the low measurement performance of sensors mounted on small unmanned aerial rotorcraft, a wavelet filter is applied as a pre-filter to attenuate the high frequency noises in the sensor output. Furthermore, to improve altitude information, an adaptive extended Kalman filter based on a maximum a posteriori criterion is proposed to estimate measurement noise covariance matrix in real time. Finally, the effectiveness of the proposed method is proved by static tests, hovering flight and autonomous landing flight tests. PMID:23201993

Extended Logic Intelligent Processing System for a Sensor Fusion Processor Hardware

NASA Technical Reports Server (NTRS)

Stoica, Adrian; Thomas, Tyson; Li, Wei-Te; Daud, Taher; Fabunmi, James

2000-01-01

The paper presents the hardware implementation and initial tests from a low-power, highspeed reconfigurable sensor fusion processor. The Extended Logic Intelligent Processing System (ELIPS) is described, which combines rule-based systems, fuzzy logic, and neural networks to achieve parallel fusion of sensor signals in compact low power VLSI. The development of the ELIPS concept is being done to demonstrate the interceptor functionality which particularly underlines the high speed and low power requirements. The hardware programmability allows the processor to reconfigure into different machines, taking the most efficient hardware implementation during each phase of information processing. Processing speeds of microseconds have been demonstrated using our test hardware.

Development of Conductivity Sensors for Multi-Phase Flow Local Measurements at the Polytechnic University of Valencia (UPV) and University Jaume I of Castellon (UJI).

PubMed

Muñoz-Cobo, José Luis; Chiva, Sergio; Méndez, Santos; Monrós, Guillem; Escrivá, Alberto; Cuadros, José Luis

2017-05-10

This paper describes all the procedures and methods currently used at UPV (Universitat Politécnica de Valencia) and UJI (University Jaume I) for the development and use of sensors for multi-phase flow analysis in vertical pipes. This paper also describes the methods that we use to obtain the values of the two-phase flow magnitudes from the sensor signals and the validation and cross-verification methods developed to check the consistency of the results obtained for these magnitudes with the sensors. First, we provide information about the procedures used to build the multi-sensor conductivity probes and some of the tests performed with different materials to avoid sensor degradation issues. In addition, we provide information about the characteristics of the electric circuits that feed the sensors. Then the data acquisition of the conductivity probe, the signal conditioning and the data processing including the device that have been designed to automatize all the measurement process of moving the sensors inside the channels by means of stepper electric motors controlled by computer are shown in operation. Then, we explain the methods used for bubble identification and categorization. Finally, we describe the methodology used to obtain the two-phase flow information from the sensor signals. This includes the following items: void fraction, gas velocity, Sauter mean diameter and interfacial area concentration. The last part of this paper is devoted to the conductance probes developed for the annular flow analysis, which includes the analysis of the interfacial waves produced in annular flow and that requires a different type of sensor.

Development of Conductivity Sensors for Multi-Phase Flow Local Measurements at the Polytechnic University of Valencia (UPV) and University Jaume I of Castellon (UJI)

PubMed Central

Muñoz-Cobo, José Luis; Chiva, Sergio; Méndez, Santos; Monrós, Guillem; Escrivá, Alberto; Cuadros, José Luis

2017-01-01

This paper describes all the procedures and methods currently used at UPV (Universitat Politécnica de Valencia) and UJI (University Jaume I) for the development and use of sensors for multi-phase flow analysis in vertical pipes. This paper also describes the methods that we use to obtain the values of the two-phase flow magnitudes from the sensor signals and the validation and cross-verification methods developed to check the consistency of the results obtained for these magnitudes with the sensors. First, we provide information about the procedures used to build the multi-sensor conductivity probes and some of the tests performed with different materials to avoid sensor degradation issues. In addition, we provide information about the characteristics of the electric circuits that feed the sensors. Then the data acquisition of the conductivity probe, the signal conditioning and the data processing including the device that have been designed to automatize all the measurement process of moving the sensors inside the channels by means of stepper electric motors controlled by computer are shown in operation. Then, we explain the methods used for bubble identification and categorization. Finally, we describe the methodology used to obtain the two-phase flow information from the sensor signals. This includes the following items: void fraction, gas velocity, Sauter mean diameter and interfacial area concentration. The last part of this paper is devoted to the conductance probes developed for the annular flow analysis, which includes the analysis of the interfacial waves produced in annular flow and that requires a different type of sensor. PMID:28489035

Intelligent sensor-model automated control of PMR-15 autoclave processing

NASA Technical Reports Server (NTRS)

Hart, S.; Kranbuehl, D.; Loos, A.; Hinds, B.; Koury, J.

1992-01-01

An intelligent sensor model system has been built and used for automated control of the PMR-15 cure process in the autoclave. The system uses frequency-dependent FM sensing (FDEMS), the Loos processing model, and the Air Force QPAL intelligent software shell. The Loos model is used to predict and optimize the cure process including the time-temperature dependence of the extent of reaction, flow, and part consolidation. The FDEMS sensing system in turn monitors, in situ, the removal of solvent, changes in the viscosity, reaction advancement and cure completion in the mold continuously throughout the processing cycle. The sensor information is compared with the optimum processing conditions from the model. The QPAL composite cure control system allows comparison of the sensor monitoring with the model predictions to be broken down into a series of discrete steps and provides a language for making decisions on what to do next regarding time-temperature and pressure.

Probe for optically monitoring progress of in-situ vitrification of soil

DOEpatents

Timmerman, Craig L.; Oma, Kenton H.; Davis, Karl C.

1988-01-01

A detector system for sensing the progress of an ISV process along an expected path comprises multiple sensors each having an input port. The input ports are distributed along the expected path of the ISV process between a starting location and an expected ending location. Each sensor generates an electrical signal representative of the temperature in the vicinity of its input port. A signal processor is coupled to the sensors to receive an electrical signal generated by a sensor, and generate a signal which is encoded with information which identifies the sensor and whether the ISV process has reached the sensor's input port. A transmitter propagates the encoded signal. The signal processor and the transmitter are below ground at a location beyond the expected ending location of the ISV process in the direction from the starting location to the expected ending location. A signal receiver and a decoder are located above ground for receiving the encoded signal propagated by the transmitter, decoding the encoded signal and providing a human-perceptible indication of the progress of the ISV process.

Probe for optically monitoring progress of in-situ vitrification of soil

DOEpatents

Timmerman, C.L.; Oma, K.H.; Davis, K.C.

1988-08-09

A detector system for sensing the progress of an ISV process along an expected path comprises multiple sensors each having an input port. The input ports are distributed along the expected path of the ISV process between a starting location and an expected ending location. Each sensor generates an electrical signal representative of the temperature in the vicinity of its input port. A signal processor is coupled to the sensors to receive an electrical signal generated by a sensor, and generate a signal which is encoded with information which identifies the sensor and whether the ISV process has reached the sensor's input port. A transmitter propagates the encoded signal. The signal processor and the transmitter are below ground at a location beyond the expected ending location of the ISV process in the direction from the starting location to the expected ending location. A signal receiver and a decoder are located above ground for receiving the encoded signal propagated by the transmitter, decoding the encoded signal and providing a human-perceptible indication of the progress of the ISV process. 7 figs.

Sensor-based architecture for medical imaging workflow analysis.

PubMed

Silva, Luís A Bastião; Campos, Samuel; Costa, Carlos; Oliveira, José Luis

2014-08-01

The growing use of computer systems in medical institutions has been generating a tremendous quantity of data. While these data have a critical role in assisting physicians in the clinical practice, the information that can be extracted goes far beyond this utilization. This article proposes a platform capable of assembling multiple data sources within a medical imaging laboratory, through a network of intelligent sensors. The proposed integration framework follows a SOA hybrid architecture based on an information sensor network, capable of collecting information from several sources in medical imaging laboratories. Currently, the system supports three types of sensors: DICOM repository meta-data, network workflows and examination reports. Each sensor is responsible for converting unstructured information from data sources into a common format that will then be semantically indexed in the framework engine. The platform was deployed in the Cardiology department of a central hospital, allowing identification of processes' characteristics and users' behaviours that were unknown before the utilization of this solution.

Real-Time Joint Streaming Data Processing from Social and Physical Sensors

NASA Astrophysics Data System (ADS)

Kropivnitskaya, Y. Y.; Qin, J.; Tiampo, K. F.; Bauer, M.

2014-12-01

The results of the technological breakthroughs in computing that have taken place over the last few decades makes it possible to achieve emergency management objectives that focus on saving human lives and decreasing economic effects. In particular, the integration of a wide variety of information sources, including observations from spatially-referenced physical sensors and new social media sources, enables better real-time seismic hazard analysis through distributed computing networks. The main goal of this work is to utilize innovative computational algorithms for better real-time seismic risk analysis by integrating different data sources and processing tools into streaming and cloud computing applications. The Geological Survey of Canada operates the Canadian National Seismograph Network (CNSN) with over 100 high-gain instruments and 60 low-gain or strong motion seismographs. The processing of the continuous data streams from each station of the CNSN provides the opportunity to detect possible earthquakes in near real-time. The information from physical sources is combined to calculate a location and magnitude for an earthquake. The automatically calculated results are not always sufficiently precise and prompt that can significantly reduce the response time to a felt or damaging earthquake. Social sensors, here represented as Twitter users, can provide information earlier to the general public and more rapidly to the emergency planning and disaster relief agencies. We introduce joint streaming data processing from social and physical sensors in real-time based on the idea that social media observations serve as proxies for physical sensors. By using the streams of data in the form of Twitter messages, each of which has an associated time and location, we can extract information related to a target event and perform enhanced analysis by combining it with physical sensor data. Results of this work suggest that the use of data from social media, in conjunction with the development of innovative computing algorithms, when combined with sensor data can provide a new paradigm for real-time earthquake detection in order to facilitate rapid and inexpensive natural risk reduction.

Communal Cooperation in Sensor Networks for Situation Management

NASA Technical Reports Server (NTRS)

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

2006-01-01

Situation management is a rapidly evolving science where managed sources are processed as realtime streams of events and fused in a way that maximizes comprehension, thus enabling better decisions for action. Sensor networks provide a new technology that promises ubiquitous input and action throughout an environment, which can substantially improve information available to the process. Here we describe a NASA program that requires improvements in sensor networks and situation management. We present an approach for massively deployed sensor networks that does not rely on centralized control but is founded in lessons learned from the way biological ecosystems are organized. In this approach, fully distributed data aggregation and integration can be performed in a scalable fashion where individual motes operate based on local information, making local decisions that achieve globally-meaningful results. This exemplifies the robust, fault-tolerant infrastructure required for successful situation management systems.

An Investigation into Spike-Based Neuromorphic Approaches for Artificial Olfactory Systems

PubMed Central

Osseiran, Adam

2017-01-01

The implementation of neuromorphic methods has delivered promising results for vision and auditory sensors. These methods focus on mimicking the neuro-biological architecture to generate and process spike-based information with minimal power consumption. With increasing interest in developing low-power and robust chemical sensors, the application of neuromorphic engineering concepts for electronic noses has provided an impetus for research focusing on improving these instruments. While conventional e-noses apply computationally expensive and power-consuming data-processing strategies, neuromorphic olfactory sensors implement the biological olfaction principles found in humans and insects to simplify the handling of multivariate sensory data by generating and processing spike-based information. Over the last decade, research on neuromorphic olfaction has established the capability of these sensors to tackle problems that plague the current e-nose implementations such as drift, response time, portability, power consumption and size. This article brings together the key contributions in neuromorphic olfaction and identifies future research directions to develop near-real-time olfactory sensors that can be implemented for a range of applications such as biosecurity and environmental monitoring. Furthermore, we aim to expose the computational parallels between neuromorphic olfaction and gustation for future research focusing on the correlation of these senses. PMID:29125586

Processing and Fusion of Electro-Optic Information

DTIC Science & Technology

2001-04-01

UNCLASSIFIED Defense Technical Information Center Compilation Part Notice ADP010886 TITLE: Processing and Fusion of Electro - Optic Information...component part numbers comprise the compilation report: ADP010865 thru ADP010894 UNCLASSIFIED 21-1 Processing and Fusion of Electro - Optic Information I...additional electro - optic (EO) sensor model within OOPSDG. It describes TM IT TT T T T performance estimates found prior to producing the New Ne- New

Usage of Wireless Sensor Networks in a service based spatial data infrastructure for Landslide Monitoring and Early Warning

NASA Astrophysics Data System (ADS)

Arnhardt, C.; Fernandez-Steeger, T. M.; Walter, K.; Kallash, A.; Niemeyer, F.; Azzam, R.; Bill, R.

2007-12-01

The joint project Sensor based Landslide Early Warning System (SLEWS) aims at a systematic development of a prototyping alarm- and early warning system for the detection of mass movements by application of an ad hoc wireless sensor network (WSN). Next to the development of suitable sensor setups, sensor fusion and network fusion are applied to enhance data quality and reduce false alarm rates. Of special interest is the data retrieval, processing and visualization in GI-Systems. Therefore a suitable serviced based Spatial Data Infrastructure (SDI) will be developed with respect to existing and upcoming Open Geospatial Consortium (OGC) standards.The application of WSN provides a cheap and easy to set up solution for special monitoring and data gathering in large areas. Measurement data from different low-cost transducers for deformation observation (acceleration, displacement, tilting) is collected by distributed sensor nodes (motes), which interact separately and connect each other in a self-organizing manner. Data are collected and aggregated at the beacon (transmission station) and further operations like data pre-processing and compression can be performed. The WSN concept provides next to energy efficiency, miniaturization, real-time monitoring and remote operation, but also new monitoring strategies like sensor and network fusion. Since not only single sensors can be integrated at single motes either cross-validation or redundant sensor setups are possible to enhance data quality. The planned monitoring and information system will include a mobile infrastructure (information technologies and communication components) as well as methods and models to estimate surface deformation parameters (positioning systems). The measurements result in heterogeneous observation sets that have to be integrated in a common adjustment and filtering approach. Reliable real-time information will be obtained using a range of sensor input and algorithms, from which early warnings and prognosis may be derived. Implementation of sensor algorithms is an important task to form the business logic. This will be represented in self-contained web-based processing services (WPS). In the future different types of sensor networks can communicate via an infrastructure of OGC services using an interoperable way by standardized protocols as the Sensor Markup Language (SensorML) and Observations & Measurements Schema (O&M). Synchronous and asynchronous information services as the Sensor Alert Service (SAS) and the Web Notification Services (WNS) will provide defined users and user groups with time-critical readings from the observation site. Techniques using services for visualizing mapping data (WMS), meta data (CSW), vector (WFS) and raster data (WCS) will range from high detailed expert based output to fuzzy graphical warning elements.The expected results will be an advancement regarding classical alarm and early warning systems as the WSN are free scalable, extensible and easy to install.

State machine analysis of sensor data from dynamic processes

DOEpatents

Cook, William R.; Brabson, John M.; Deland, Sharon M.

2003-12-23

A state machine model analyzes sensor data from dynamic processes at a facility to identify the actual processes that were performed at the facility during a period of interest for the purpose of remote facility inspection. An inspector can further input the expected operations into the state machine model and compare the expected, or declared, processes to the actual processes to identify undeclared processes at the facility. The state machine analysis enables the generation of knowledge about the state of the facility at all levels, from location of physical objects to complex operational concepts. Therefore, the state machine method and apparatus may benefit any agency or business with sensored facilities that stores or manipulates expensive, dangerous, or controlled materials or information.

AQS-20 through-the-sensor environmental data sharing

NASA Astrophysics Data System (ADS)

Steed, Chad A.; Sample, John; Harris, Mike; Avera, Will; Bibee, L. Dale

2005-05-01

The Naval Research Laboratory (NRL) has developed an advanced architecture for connecting many maturing Through-The-Sensor (TTS) efforts for an end-to-end demonstration using the AQS-20 mine hunting sensor. The goal of TTS technologies is to exploit tactical sensors to characterize the battlespace environment for Navy Fleet Tactical Decision Aids (TDAs) with minimal impact on tactical systems. The AQS-20 Rapid Transition Process (RTP) will utilize the AQS-20 to demonstrate sensor data collection, processing, fusion, storage, distribution and use in a tactical decision aid. In recent years, NRL has shown that the AQS-20 can be used to obtain swath bathymetry and bottom sediment information in a single flight. In the AQS-20 RTP, these data will be processed and fused with historical databases to provide an improved environmental picture. The RTP will also utilize the Geophysical Data Base Variable resolution (GDBV) dynamic format for storing local datasets. The GDBV dynamic has been developed in prior years to provide an extensible, efficient data storage format for TTS systems. To provide the interconnectivity that is critical to Network Centric Warfare (NCW), the GDBV will be connected to the SPAWAR funded Tactical Environmental Data Services (TEDServices). To complete the flow of information from sensor to user, the RTP will transmit information to the MEDAL TDA through existing connections in The Naval Oceanographic Office"s (NAVOCEANO) Bottom Mapping Workstation (BMW). In addition, TEDServices will handle transmission of the AQS-20 data to NAVOCEANO who serves as the domain authority for oceanographic datasets in the U.S. Navy.

Average Throughput Performance of Myopic Policy in Energy Harvesting Wireless Sensor Networks.

PubMed

Gul, Omer Melih; Demirekler, Mubeccel

2017-09-26

This paper considers a single-hop wireless sensor network where a fusion center collects data from M energy harvesting wireless sensors. The harvested energy is stored losslessly in an infinite-capacity battery at each sensor. In each time slot, the fusion center schedules K sensors for data transmission over K orthogonal channels. The fusion center does not have direct knowledge on the battery states of sensors, or the statistics of their energy harvesting processes. The fusion center only has information of the outcomes of previous transmission attempts. It is assumed that the sensors are data backlogged, there is no battery leakage and the communication is error-free. An energy harvesting sensor can transmit data to the fusion center whenever being scheduled only if it has enough energy for data transmission. We investigate average throughput of Round-Robin type myopic policy both analytically and numerically under an average reward (throughput) criterion. We show that Round-Robin type myopic policy achieves optimality for some class of energy harvesting processes although it is suboptimal for a broad class of energy harvesting processes.

Average Throughput Performance of Myopic Policy in Energy Harvesting Wireless Sensor Networks

PubMed Central

Demirekler, Mubeccel

2017-01-01

This paper considers a single-hop wireless sensor network where a fusion center collects data from M energy harvesting wireless sensors. The harvested energy is stored losslessly in an infinite-capacity battery at each sensor. In each time slot, the fusion center schedules K sensors for data transmission over K orthogonal channels. The fusion center does not have direct knowledge on the battery states of sensors, or the statistics of their energy harvesting processes. The fusion center only has information of the outcomes of previous transmission attempts. It is assumed that the sensors are data backlogged, there is no battery leakage and the communication is error-free. An energy harvesting sensor can transmit data to the fusion center whenever being scheduled only if it has enough energy for data transmission. We investigate average throughput of Round-Robin type myopic policy both analytically and numerically under an average reward (throughput) criterion. We show that Round-Robin type myopic policy achieves optimality for some class of energy harvesting processes although it is suboptimal for a broad class of energy harvesting processes. PMID:28954420

An Approach to Automated Fusion System Design and Adaptation

PubMed Central

Fritze, Alexander; Mönks, Uwe; Holst, Christoph-Alexander; Lohweg, Volker

2017-01-01

Industrial applications are in transition towards modular and flexible architectures that are capable of self-configuration and -optimisation. This is due to the demand of mass customisation and the increasing complexity of industrial systems. The conversion to modular systems is related to challenges in all disciplines. Consequently, diverse tasks such as information processing, extensive networking, or system monitoring using sensor and information fusion systems need to be reconsidered. The focus of this contribution is on distributed sensor and information fusion systems for system monitoring, which must reflect the increasing flexibility of fusion systems. This contribution thus proposes an approach, which relies on a network of self-descriptive intelligent sensor nodes, for the automatic design and update of sensor and information fusion systems. This article encompasses the fusion system configuration and adaptation as well as communication aspects. Manual interaction with the flexibly changing system is reduced to a minimum. PMID:28300762

An Approach to Automated Fusion System Design and Adaptation.

PubMed

Fritze, Alexander; Mönks, Uwe; Holst, Christoph-Alexander; Lohweg, Volker

2017-03-16

Industrial applications are in transition towards modular and flexible architectures that are capable of self-configuration and -optimisation. This is due to the demand of mass customisation and the increasing complexity of industrial systems. The conversion to modular systems is related to challenges in all disciplines. Consequently, diverse tasks such as information processing, extensive networking, or system monitoring using sensor and information fusion systems need to be reconsidered. The focus of this contribution is on distributed sensor and information fusion systems for system monitoring, which must reflect the increasing flexibility of fusion systems. This contribution thus proposes an approach, which relies on a network of self-descriptive intelligent sensor nodes, for the automatic design and update of sensor and information fusion systems. This article encompasses the fusion system configuration and adaptation as well as communication aspects. Manual interaction with the flexibly changing system is reduced to a minimum.

Outlier Detection for Sensor Systems (ODSS): A MATLAB Macro for Evaluating Microphone Sensor Data Quality.

PubMed

Vasta, Robert; Crandell, Ian; Millican, Anthony; House, Leanna; Smith, Eric

2017-10-13

Microphone sensor systems provide information that may be used for a variety of applications. Such systems generate large amounts of data. One concern is with microphone failure and unusual values that may be generated as part of the information collection process. This paper describes methods and a MATLAB graphical interface that provides rapid evaluation of microphone performance and identifies irregularities. The approach and interface are described. An application to a microphone array used in a wind tunnel is used to illustrate the methodology.

A Novel Multi-Sensor Environmental Perception Method Using Low-Rank Representation and a Particle Filter for Vehicle Reversing Safety

PubMed Central

Zhang, Zutao; Li, Yanjun; Wang, Fubing; Meng, Guanjun; Salman, Waleed; Saleem, Layth; Zhang, Xiaoliang; Wang, Chunbai; Hu, Guangdi; Liu, Yugang

2016-01-01

Environmental perception and information processing are two key steps of active safety for vehicle reversing. Single-sensor environmental perception cannot meet the need for vehicle reversing safety due to its low reliability. In this paper, we present a novel multi-sensor environmental perception method using low-rank representation and a particle filter for vehicle reversing safety. The proposed system consists of four main steps, namely multi-sensor environmental perception, information fusion, target recognition and tracking using low-rank representation and a particle filter, and vehicle reversing speed control modules. First of all, the multi-sensor environmental perception module, based on a binocular-camera system and ultrasonic range finders, obtains the distance data for obstacles behind the vehicle when the vehicle is reversing. Secondly, the information fusion algorithm using an adaptive Kalman filter is used to process the data obtained with the multi-sensor environmental perception module, which greatly improves the robustness of the sensors. Then the framework of a particle filter and low-rank representation is used to track the main obstacles. The low-rank representation is used to optimize an objective particle template that has the smallest L-1 norm. Finally, the electronic throttle opening and automatic braking is under control of the proposed vehicle reversing control strategy prior to any potential collisions, making the reversing control safer and more reliable. The final system simulation and practical testing results demonstrate the validity of the proposed multi-sensor environmental perception method using low-rank representation and a particle filter for vehicle reversing safety. PMID:27294931

A Novel Multi-Sensor Environmental Perception Method Using Low-Rank Representation and a Particle Filter for Vehicle Reversing Safety.

PubMed

Zhang, Zutao; Li, Yanjun; Wang, Fubing; Meng, Guanjun; Salman, Waleed; Saleem, Layth; Zhang, Xiaoliang; Wang, Chunbai; Hu, Guangdi; Liu, Yugang

2016-06-09

Environmental perception and information processing are two key steps of active safety for vehicle reversing. Single-sensor environmental perception cannot meet the need for vehicle reversing safety due to its low reliability. In this paper, we present a novel multi-sensor environmental perception method using low-rank representation and a particle filter for vehicle reversing safety. The proposed system consists of four main steps, namely multi-sensor environmental perception, information fusion, target recognition and tracking using low-rank representation and a particle filter, and vehicle reversing speed control modules. First of all, the multi-sensor environmental perception module, based on a binocular-camera system and ultrasonic range finders, obtains the distance data for obstacles behind the vehicle when the vehicle is reversing. Secondly, the information fusion algorithm using an adaptive Kalman filter is used to process the data obtained with the multi-sensor environmental perception module, which greatly improves the robustness of the sensors. Then the framework of a particle filter and low-rank representation is used to track the main obstacles. The low-rank representation is used to optimize an objective particle template that has the smallest L-1 norm. Finally, the electronic throttle opening and automatic braking is under control of the proposed vehicle reversing control strategy prior to any potential collisions, making the reversing control safer and more reliable. The final system simulation and practical testing results demonstrate the validity of the proposed multi-sensor environmental perception method using low-rank representation and a particle filter for vehicle reversing safety.

Effective Sensor Selection and Data Anomaly Detection for Condition Monitoring of Aircraft Engines

PubMed Central

Liu, Liansheng; Liu, Datong; Zhang, Yujie; Peng, Yu

2016-01-01

In a complex system, condition monitoring (CM) can collect the system working status. The condition is mainly sensed by the pre-deployed sensors in/on the system. Most existing works study how to utilize the condition information to predict the upcoming anomalies, faults, or failures. There is also some research which focuses on the faults or anomalies of the sensing element (i.e., sensor) to enhance the system reliability. However, existing approaches ignore the correlation between sensor selecting strategy and data anomaly detection, which can also improve the system reliability. To address this issue, we study a new scheme which includes sensor selection strategy and data anomaly detection by utilizing information theory and Gaussian Process Regression (GPR). The sensors that are more appropriate for the system CM are first selected. Then, mutual information is utilized to weight the correlation among different sensors. The anomaly detection is carried out by using the correlation of sensor data. The sensor data sets that are utilized to carry out the evaluation are provided by National Aeronautics and Space Administration (NASA) Ames Research Center and have been used as Prognostics and Health Management (PHM) challenge data in 2008. By comparing the two different sensor selection strategies, the effectiveness of selection method on data anomaly detection is proved. PMID:27136561

Effective Sensor Selection and Data Anomaly Detection for Condition Monitoring of Aircraft Engines.

PubMed

Liu, Liansheng; Liu, Datong; Zhang, Yujie; Peng, Yu

2016-04-29

In a complex system, condition monitoring (CM) can collect the system working status. The condition is mainly sensed by the pre-deployed sensors in/on the system. Most existing works study how to utilize the condition information to predict the upcoming anomalies, faults, or failures. There is also some research which focuses on the faults or anomalies of the sensing element (i.e., sensor) to enhance the system reliability. However, existing approaches ignore the correlation between sensor selecting strategy and data anomaly detection, which can also improve the system reliability. To address this issue, we study a new scheme which includes sensor selection strategy and data anomaly detection by utilizing information theory and Gaussian Process Regression (GPR). The sensors that are more appropriate for the system CM are first selected. Then, mutual information is utilized to weight the correlation among different sensors. The anomaly detection is carried out by using the correlation of sensor data. The sensor data sets that are utilized to carry out the evaluation are provided by National Aeronautics and Space Administration (NASA) Ames Research Center and have been used as Prognostics and Health Management (PHM) challenge data in 2008. By comparing the two different sensor selection strategies, the effectiveness of selection method on data anomaly detection is proved.

Infrastructure sensing.

PubMed

Soga, Kenichi; Schooling, Jennifer

2016-08-06

Design, construction, maintenance and upgrading of civil engineering infrastructure requires fresh thinking to minimize use of materials, energy and labour. This can only be achieved by understanding the performance of the infrastructure, both during its construction and throughout its design life, through innovative monitoring. Advances in sensor systems offer intriguing possibilities to radically alter methods of condition assessment and monitoring of infrastructure. In this paper, it is hypothesized that the future of infrastructure relies on smarter information; the rich information obtained from embedded sensors within infrastructure will act as a catalyst for new design, construction, operation and maintenance processes for integrated infrastructure systems linked directly with user behaviour patterns. Some examples of emerging sensor technologies for infrastructure sensing are given. They include distributed fibre-optics sensors, computer vision, wireless sensor networks, low-power micro-electromechanical systems, energy harvesting and citizens as sensors.

Infrastructure sensing

PubMed Central

Soga, Kenichi; Schooling, Jennifer

2016-01-01

Design, construction, maintenance and upgrading of civil engineering infrastructure requires fresh thinking to minimize use of materials, energy and labour. This can only be achieved by understanding the performance of the infrastructure, both during its construction and throughout its design life, through innovative monitoring. Advances in sensor systems offer intriguing possibilities to radically alter methods of condition assessment and monitoring of infrastructure. In this paper, it is hypothesized that the future of infrastructure relies on smarter information; the rich information obtained from embedded sensors within infrastructure will act as a catalyst for new design, construction, operation and maintenance processes for integrated infrastructure systems linked directly with user behaviour patterns. Some examples of emerging sensor technologies for infrastructure sensing are given. They include distributed fibre-optics sensors, computer vision, wireless sensor networks, low-power micro-electromechanical systems, energy harvesting and citizens as sensors. PMID:27499845

Utilizing Novel Non-traditional Sensor Tasking Approaches to Enhance the Space Situational Awareness Picture Maintained by the Space Surveillance Network

NASA Astrophysics Data System (ADS)

Herz, A.; Herz, E.; Center, K.; George, P.; Axelrad, P.; Mutschler, S.; Jones, B.

2016-09-01

The Space Surveillance Network (SSN) is tasked with the increasingly difficult mission of detecting, tracking, cataloging and identifying artificial objects orbiting the Earth, including active and inactive satellites, spent rocket bodies, and fragmented debris. Much of the architecture and operations of the SSN are limited and outdated. Efforts are underway to modernize some elements of the systems. Even so, the ability to maintain the best current Space Situational Awareness (SSA) picture and identify emerging events in a timely fashion could be significantly improved by leveraging non-traditional sensor sites. Orbit Logic, the University of Colorado and the University of Texas at Austin are developing an innovative architecture and operations concept to coordinate the tasking and observation information processing of non - traditional assets based on information-theoretic approaches. These confirmed tasking schedules and the resulting data can then be used to "inform" the SSN tasking process. The 'Heimdall Web' system is comprised of core tasking optimization components and accompanying Web interfaces within a secure, split architecture that will for the first time allow non-traditional sensors to support SSA and improve SSN tasking. Heimdall Web application components appropriately score/prioritize space catalog objects based on covariance, priority, observability, expected information gain, and probability of detect - then coordinate an efficient sensor observation schedule for non-SSN sensors contributing to the overall SSA picture maintained by the Joint Space Operations Center (JSpOC). The Heimdall Web Ops concept supports sensor participation levels of "Scheduled", "Tasked" and "Contributing". Scheduled and Tasked sensors are provided optimized observation schedules or object tracking lists from central algorithms, while Contributing sensors review and select from a list of "desired track objects". All sensors are "Web Enabled" for tasking and feedback, supplying observation schedules, confirmed observations and related data back to Heimdall Web to complete the feedback loop for the next scheduling iteration.

Bio-inspired multi-mode optic flow sensors for micro air vehicles

NASA Astrophysics Data System (ADS)

Park, Seokjun; Choi, Jaehyuk; Cho, Jihyun; Yoon, Euisik

2013-06-01

Monitoring wide-field surrounding information is essential for vision-based autonomous navigation in micro-air-vehicles (MAV). Our image-cube (iCube) module, which consists of multiple sensors that are facing different angles in 3-D space, can be applied to the wide-field of view optic flows estimation (μ-Compound eyes) and to attitude control (μ- Ocelli) in the Micro Autonomous Systems and Technology (MAST) platforms. In this paper, we report an analog/digital (A/D) mixed-mode optic-flow sensor, which generates both optic flows and normal images in different modes for μ- Compound eyes and μ-Ocelli applications. The sensor employs a time-stamp based optic flow algorithm which is modified from the conventional EMD (Elementary Motion Detector) algorithm to give an optimum partitioning of hardware blocks in analog and digital domains as well as adequate allocation of pixel-level, column-parallel, and chip-level signal processing. Temporal filtering, which may require huge hardware resources if implemented in digital domain, is remained in a pixel-level analog processing unit. The rest of the blocks, including feature detection and timestamp latching, are implemented using digital circuits in a column-parallel processing unit. Finally, time-stamp information is decoded into velocity from look-up tables, multiplications, and simple subtraction circuits in a chip-level processing unit, thus significantly reducing core digital processing power consumption. In the normal image mode, the sensor generates 8-b digital images using single slope ADCs in the column unit. In the optic flow mode, the sensor estimates 8-b 1-D optic flows from the integrated mixed-mode algorithm core and 2-D optic flows with an external timestamp processing, respectively.

Intelligent multi-sensor integrations

NASA Technical Reports Server (NTRS)

Volz, Richard A.; Jain, Ramesh; Weymouth, Terry

1989-01-01

Growth in the intelligence of space systems requires the use and integration of data from multiple sensors. Generic tools are being developed for extracting and integrating information obtained from multiple sources. The full spectrum is addressed for issues ranging from data acquisition, to characterization of sensor data, to adaptive systems for utilizing the data. In particular, there are three major aspects to the project, multisensor processing, an adaptive approach to object recognition, and distributed sensor system integration.

Towards a light-weight query engine for accessing health sensor data in a fall prevention system.

PubMed

Kreiner, Karl; Gossy, Christian; Drobics, Mario

2014-01-01

Connecting various sensors in sensor networks has become popular during the last decade. An important aspect next to storing and creating data is information access by domain experts, such as researchers, caretakers and physicians. In this work we present the design and prototypic implementation of a light-weight query engine using natural language processing for accessing health-related sensor data in a fall prevention system.

Energy Efficient Communication Using Relationships between Biological Signals for Ubiquitous Health Monitoring

NASA Astrophysics Data System (ADS)

Lee, Songjun; Na, Doosu; Koo, Bonmin

Wireless sensor networks with a star network topology are commonly applied for health monitoring systems. To determine the condition of a patient, sensor nodes are attached to the body to transmit the data to a coordinator. However, this process is inefficient because the coordinator is always communicating with each sensor node resulting in a data processing workload for the coordinator that becomes much greater than that of the sensor nodes. In this paper, a method is proposed to reduce the number of data transmissions from the sensor nodes to the coordinator by establishing a threshold for data from the biological signals to ensure that only relevant information is transmitted. This results in a dramatic reduction in power consumption throughout the entire network.

Focal-Plane Sensing-Processing: A Power-Efficient Approach for the Implementation of Privacy-Aware Networked Visual Sensors

PubMed Central

Fernández-Berni, Jorge; Carmona-Galán, Ricardo; del Río, Rocío; Kleihorst, Richard; Philips, Wilfried; Rodríguez-Vázquez, Ángel

2014-01-01

The capture, processing and distribution of visual information is one of the major challenges for the paradigm of the Internet of Things. Privacy emerges as a fundamental barrier to overcome. The idea of networked image sensors pervasively collecting data generates social rejection in the face of sensitive information being tampered by hackers or misused by legitimate users. Power consumption also constitutes a crucial aspect. Images contain a massive amount of data to be processed under strict timing requirements, demanding high-performance vision systems. In this paper, we describe a hardware-based strategy to concurrently address these two key issues. By conveying processing capabilities to the focal plane in addition to sensing, we can implement privacy protection measures just at the point where sensitive data are generated. Furthermore, such measures can be tailored for efficiently reducing the computational load of subsequent processing stages. As a proof of concept, a full-custom QVGA vision sensor chip is presented. It incorporates a mixed-signal focal-plane sensing-processing array providing programmable pixelation of multiple image regions in parallel. In addition to this functionality, the sensor exploits reconfigurability to implement other processing primitives, namely block-wise dynamic range adaptation, integral image computation and multi-resolution filtering. The proposed circuitry is also suitable to build a granular space, becoming the raw material for subsequent feature extraction and recognition of categorized objects. PMID:25195849

Focal-plane sensing-processing: a power-efficient approach for the implementation of privacy-aware networked visual sensors.

PubMed

Fernández-Berni, Jorge; Carmona-Galán, Ricardo; del Río, Rocío; Kleihorst, Richard; Philips, Wilfried; Rodríguez-Vázquez, Ángel

2014-08-19

The capture, processing and distribution of visual information is one of the major challenges for the paradigm of the Internet of Things. Privacy emerges as a fundamental barrier to overcome. The idea of networked image sensors pervasively collecting data generates social rejection in the face of sensitive information being tampered by hackers or misused by legitimate users. Power consumption also constitutes a crucial aspect. Images contain a massive amount of data to be processed under strict timing requirements, demanding high-performance vision systems. In this paper, we describe a hardware-based strategy to concurrently address these two key issues. By conveying processing capabilities to the focal plane in addition to sensing, we can implement privacy protection measures just at the point where sensitive data are generated. Furthermore, such measures can be tailored for efficiently reducing the computational load of subsequent processing stages. As a proof of concept, a full-custom QVGA vision sensor chip is presented. It incorporates a mixed-signal focal-plane sensing-processing array providing programmable pixelation of multiple image regions in parallel. In addition to this functionality, the sensor exploits reconfigurability to implement other processing primitives, namely block-wise dynamic range adaptation, integral image computation and multi-resolution filtering. The proposed circuitry is also suitable to build a granular space, becoming the raw material for subsequent feature extraction and recognition of categorized objects.

Advanced Image Processing Techniques for Maximum Information Recovery

DTIC Science & Technology

2006-11-01

0704-0188), 1215 Jefferson Davis Highway, Suite 1204, Arlington, VA 22202-4302. Respondents should be aware that notwithstanding any other provision...available information from an image. Some radio frequency and optical sensors collect large-scale sets of spatial imagery data whose content is often...Some radio frequency and optical sensors collect large- scale sets of spatial imagery data whose content is often obscured by fog, clouds, foliage

Georeferenced LiDAR 3D vine plantation map generation.

PubMed

Llorens, Jordi; Gil, Emilio; Llop, Jordi; Queraltó, Meritxell

2011-01-01

The use of electronic devices for canopy characterization has recently been widely discussed. Among such devices, LiDAR sensors appear to be the most accurate and precise. Information obtained with LiDAR sensors during reading while driving a tractor along a crop row can be managed and transformed into canopy density maps by evaluating the frequency of LiDAR returns. This paper describes a proposed methodology to obtain a georeferenced canopy map by combining the information obtained with LiDAR with that generated using a GPS receiver installed on top of a tractor. Data regarding the velocity of LiDAR measurements and UTM coordinates of each measured point on the canopy were obtained by applying the proposed transformation process. The process allows overlap of the canopy density map generated with the image of the intended measured area using Google Earth(®), providing accurate information about the canopy distribution and/or location of damage along the rows. This methodology was applied and tested on different vine varieties and crop stages in two important vine production areas in Spain. The results indicate that the georeferenced information obtained with LiDAR sensors appears to be an interesting tool with the potential to improve crop management processes.

A Soft Sensor for Bioprocess Control Based on Sequential Filtering of Metabolic Heat Signals

PubMed Central

Paulsson, Dan; Gustavsson, Robert; Mandenius, Carl-Fredrik

2014-01-01

Soft sensors are the combination of robust on-line sensor signals with mathematical models for deriving additional process information. Here, we apply this principle to a microbial recombinant protein production process in a bioreactor by exploiting bio-calorimetric methodology. Temperature sensor signals from the cooling system of the bioreactor were used for estimating the metabolic heat of the microbial culture and from that the specific growth rate and active biomass concentration were derived. By applying sequential digital signal filtering, the soft sensor was made more robust for industrial practice with cultures generating low metabolic heat in environments with high noise level. The estimated specific growth rate signal obtained from the three stage sequential filter allowed controlled feeding of substrate during the fed-batch phase of the production process. The biomass and growth rate estimates from the soft sensor were also compared with an alternative sensor probe and a capacitance on-line sensor, for the same variables. The comparison showed similar or better sensitivity and lower variability for the metabolic heat soft sensor suggesting that using permanent temperature sensors of a bioreactor is a realistic and inexpensive alternative for monitoring and control. However, both alternatives are easy to implement in a soft sensor, alone or in parallel. PMID:25264951

A soft sensor for bioprocess control based on sequential filtering of metabolic heat signals.

PubMed

Paulsson, Dan; Gustavsson, Robert; Mandenius, Carl-Fredrik

2014-09-26

Soft sensors are the combination of robust on-line sensor signals with mathematical models for deriving additional process information. Here, we apply this principle to a microbial recombinant protein production process in a bioreactor by exploiting bio-calorimetric methodology. Temperature sensor signals from the cooling system of the bioreactor were used for estimating the metabolic heat of the microbial culture and from that the specific growth rate and active biomass concentration were derived. By applying sequential digital signal filtering, the soft sensor was made more robust for industrial practice with cultures generating low metabolic heat in environments with high noise level. The estimated specific growth rate signal obtained from the three stage sequential filter allowed controlled feeding of substrate during the fed-batch phase of the production process. The biomass and growth rate estimates from the soft sensor were also compared with an alternative sensor probe and a capacitance on-line sensor, for the same variables. The comparison showed similar or better sensitivity and lower variability for the metabolic heat soft sensor suggesting that using permanent temperature sensors of a bioreactor is a realistic and inexpensive alternative for monitoring and control. However, both alternatives are easy to implement in a soft sensor, alone or in parallel.

Facility Monitoring: A Qualitative Theory for Sensor Fusion

NASA Technical Reports Server (NTRS)

Figueroa, Fernando

2001-01-01

Data fusion and sensor management approaches have largely been implemented with centralized and hierarchical architectures. Numerical and statistical methods are the most common data fusion methods found in these systems. Given the proliferation and low cost of processing power, there is now an emphasis on designing distributed and decentralized systems. These systems use analytical/quantitative techniques or qualitative reasoning methods for date fusion.Based on other work by the author, a sensor may be treated as a highly autonomous (decentralized) unit. Each highly autonomous sensor (HAS) is capable of extracting qualitative behaviours from its data. For example, it detects spikes, disturbances, noise levels, off-limit excursions, step changes, drift, and other typical measured trends. In this context, this paper describes a distributed sensor fusion paradigm and theory where each sensor in the system is a HAS. Hence, given the reach qualitative information from each HAS, a paradigm and formal definitions are given so that sensors and processes can reason and make decisions at the qualitative level. This approach to sensor fusion makes it possible the implementation of intuitive (effective) methods to monitor, diagnose, and compensate processes/systems and their sensors. This paradigm facilitates a balanced distribution of intelligence (code and/or hardware) to the sensor level, the process/system level, and a higher controller level. The primary application of interest is in intelligent health management of rocket engine test stands.

Smart fabrics: integrating fiber optic sensors and information networks.

PubMed

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.

A Passive Wireless Multi-Sensor SAW Technology Device and System Perspectives

PubMed Central

Malocha, Donald C.; Gallagher, Mark; Fisher, Brian; Humphries, James; Gallagher, Daniel; Kozlovski, Nikolai

2013-01-01

This paper will discuss a SAW passive, wireless multi-sensor system under development by our group for the past several years. The device focus is on orthogonal frequency coded (OFC) SAW sensors, which use both frequency diversity and pulse position reflectors to encode the device ID and will be briefly contrasted to other embodiments. A synchronous correlator transceiver is used for the hardware and post processing and correlation techniques of the received signal to extract the sensor information will be presented. Critical device and system parameters addressed include encoding, operational range, SAW device parameters, post-processing, and antenna-SAW device integration. A fully developed 915 MHz OFC SAW multi-sensor system is used to show experimental results. The system is based on a software radio approach that provides great flexibility for future enhancements and diverse sensor applications. Several different sensor types using the OFC SAW platform are shown. PMID:23666124

Selected examples of intelligent (micro) sensor systems: state-of-the-art and tendencies

NASA Astrophysics Data System (ADS)

Hauptmann, Peter R.

2006-03-01

The capability of intelligent sensors to have more intelligence built into them continues to drive their application in areas including automotive, aerospace and defense, industrial, intelligent house and wear, medical and homeland security. In principle it is difficult to overestimate the importance of intelligent (micro) sensors or sensor systems within advanced societies but one characteristic feature is the global market for sensors, which is now about 20 billion annually. Therefore sensors or sensor systems play a dominant role in many fields from the macro sensor in manufacturing industry down to the miniaturized sensor for medical applications. The diversity of sensors precludes a complete description of the state-of-the-art; selected examples will illustrate the current situation. MEMS (microelectromechanical systems) devices are of special interest in the context of micro sensor systems. In past the main requirements of a sensor were in terms of metrological performance. The electrical (or optical) signal produced by the sensor needed to match the measure relatively accurately. Such basic functionality is no longer sufficient. Data processing near the sensor, the extraction of more information than just the direct sensor information by signal analysis, system aspects and multi-sensor information are the new demands. A shifting can be observed away from aiming to design perfect single-function transducers and towards the utilization of system-based sensors as system components. In the ideal case such systems contain sensors, actuators and electronics. They can be realized in monolithic, hybrid or discrete form—which kind is used depends on the application. In this article the state-of-the-art of intelligent sensors or sensor systems is reviewed using selected examples. Future trends are deduced.

On-road anomaly detection by multimodal sensor analysis and multimedia processing

NASA Astrophysics Data System (ADS)

Orhan, Fatih; Eren, P. E.

2014-03-01

The use of smartphones in Intelligent Transportation Systems is gaining popularity, yet many challenges exist in developing functional applications. Due to the dynamic nature of transportation, vehicular social applications face complexities such as developing robust sensor management, performing signal and image processing tasks, and sharing information among users. This study utilizes a multimodal sensor analysis framework which enables the analysis of sensors in multimodal aspect. It also provides plugin-based analyzing interfaces to develop sensor and image processing based applications, and connects its users via a centralized application as well as to social networks to facilitate communication and socialization. With the usage of this framework, an on-road anomaly detector is being developed and tested. The detector utilizes the sensors of a mobile device and is able to identify anomalies such as hard brake, pothole crossing, and speed bump crossing. Upon such detection, the video portion containing the anomaly is automatically extracted in order to enable further image processing analysis. The detection results are shared on a central portal application for online traffic condition monitoring.

Secure Data Aggregation with Fully Homomorphic Encryption in Large-Scale Wireless Sensor Networks.

PubMed

Li, Xing; Chen, Dexin; Li, Chunyan; Wang, Liangmin

2015-07-03

With the rapid development of wireless communication technology, sensor technology, information acquisition and processing technology, sensor networks will finally have a deep influence on all aspects of people's lives. The battery resources of sensor nodes should be managed efficiently in order to prolong network lifetime in large-scale wireless sensor networks (LWSNs). Data aggregation represents an important method to remove redundancy as well as unnecessary data transmission and hence cut down the energy used in communication. As sensor nodes are deployed in hostile environments, the security of the sensitive information such as confidentiality and integrity should be considered. This paper proposes Fully homomorphic Encryption based Secure data Aggregation (FESA) in LWSNs which can protect end-to-end data confidentiality and support arbitrary aggregation operations over encrypted data. In addition, by utilizing message authentication codes (MACs), this scheme can also verify data integrity during data aggregation and forwarding processes so that false data can be detected as early as possible. Although the FHE increase the computation overhead due to its large public key size, simulation results show that it is implementable in LWSNs and performs well. Compared with other protocols, the transmitted data and network overhead are reduced in our scheme.

RESTFul based heterogeneous Geoprocessing workflow interoperation for Sensor Web Service

NASA Astrophysics Data System (ADS)

Yang, Chao; Chen, Nengcheng; Di, Liping

2012-10-01

Advanced sensors on board satellites offer detailed Earth observations. A workflow is one approach for designing, implementing and constructing a flexible and live link between these sensors' resources and users. It can coordinate, organize and aggregate the distributed sensor Web services to meet the requirement of a complex Earth observation scenario. A RESTFul based workflow interoperation method is proposed to integrate heterogeneous workflows into an interoperable unit. The Atom protocols are applied to describe and manage workflow resources. The XML Process Definition Language (XPDL) and Business Process Execution Language (BPEL) workflow standards are applied to structure a workflow that accesses sensor information and one that processes it separately. Then, a scenario for nitrogen dioxide (NO2) from a volcanic eruption is used to investigate the feasibility of the proposed method. The RESTFul based workflows interoperation system can describe, publish, discover, access and coordinate heterogeneous Geoprocessing workflows.

Structural action recognition in body sensor networks: distributed classification based on string matching.

PubMed

Ghasemzadeh, Hassan; Loseu, Vitali; Jafari, Roozbeh

2010-03-01

Mobile sensor-based systems are emerging as promising platforms for healthcare monitoring. An important goal of these systems is to extract physiological information about the subject wearing the network. Such information can be used for life logging, quality of life measures, fall detection, extraction of contextual information, and many other applications. Data collected by these sensor nodes are overwhelming, and hence, an efficient data processing technique is essential. In this paper, we present a system using inexpensive, off-the-shelf inertial sensor nodes that constructs motion transcripts from biomedical signals and identifies movements by taking collaboration between the nodes into consideration. Transcripts are built of motion primitives and aim to reduce the complexity of the original data. We then label each primitive with a unique symbol and generate a sequence of symbols, known as motion template, representing a particular action. This model leads to a distributed algorithm for action recognition using edit distance with respect to motion templates. The algorithm reduces the number of active nodes during every classification decision. We present our results using data collected from five normal subjects performing transitional movements. The results clearly illustrate the effectiveness of our framework. In particular, we obtain a classification accuracy of 84.13% with only one sensor node involved in the classification process.

Stress measurements in Kuzbass mines using photoelastic sensors

NASA Astrophysics Data System (ADS)

Schastlivtsev, E.

1996-06-01

The basic amount of known measurements of stressed state in front of development workings' faces was carried out with the use of hydraulic sensors, which give an information about principal stresses without their separation. Besides, the availability of pipe-line and cumbersome equipment make more complicated and sometimes impossible the process of stresses' measurements during works in mining process. In our opinion, the borehole and photoelastic sensors at high degree satisfy with the conditions of stresses' measurements in front of mining workings' faces. The principal idea of the method is in the usage of proper face advancing aiming the estimation of the field stresses in its neighborhood. Borehole and photoelastic sensors, fixed in the advanced boreholes, drilled from the active face react to the field change of stresses or deformation caused by working face advancing. While obtaining this information we may judge about the distribution of additional stresses in rock of face's neighborhood and concentration of stresses in front of face. The usage of cavity (because of face advancing) in the quality of disturbing influence in combination with the properties of ring photoelastic sensor to given an information about magnitude and direction of secondary principle stresses, permits us to obtain rather a simple and not labor consuming method of investigation of field additional stresses in the working's face neighborhood.

AOD furnace splash soft-sensor in the smelting process based on improved BP neural network

NASA Astrophysics Data System (ADS)

Ma, Haitao; Wang, Shanshan; Wu, Libin; Yu, Ying

2017-11-01

In view of argon oxygen refining low carbon ferrochrome production process, in the splash of smelting process as the research object, based on splash mechanism analysis in the smelting process , using multi-sensor information fusion and BP neural network modeling techniques is proposed in this paper, using the vibration signal, the audio signal and the flame image signal in the furnace as the characteristic signal of splash, the vibration signal, the audio signal and the flame image signal in the furnace integration and modeling, and reconstruct splash signal, realize the splash soft measurement in the smelting process, the simulation results show that the method can accurately forecast splash type in the smelting process, provide a new method of measurement for forecast splash in the smelting process, provide more accurate information to control splash.

Combustion Sensors: Gas Turbine Applications

NASA Technical Reports Server (NTRS)

Human, Mel

2002-01-01

This report documents efforts to survey the current research directions in sensor technology for gas turbine systems. The work is driven by the current and future requirements on system performance and optimization. Accurate real time measurements of velocities, pressure, temperatures, and species concentrations will be required for objectives such as combustion instability attenuation, pollutant reduction, engine health management, exhaust profile control via active control, etc. Changing combustor conditions - engine aging, flow path slagging, or rapid maneuvering - will require adaptive responses; the effectiveness of such will be only as good as the dynamic information available for processing. All of these issues point toward the importance of continued sensor development. For adequate control of the combustion process, sensor data must include information about the above mentioned quantities along with equivalence ratios and radical concentrations, and also include both temporal and spatial velocity resolution. Ultimately these devices must transfer from the laboratory to field installations, and thus must become low weight and cost, reliable and maintainable. A primary conclusion from this study is that the optics-based sensor science will be the primary diagnostic in future gas turbine technologies.

Control of three different continuous pharmaceutical manufacturing processes: Use of soft sensors.

PubMed

Rehrl, Jakob; Karttunen, Anssi-Pekka; Nicolaï, Niels; Hörmann, Theresa; Horn, Martin; Korhonen, Ossi; Nopens, Ingmar; De Beer, Thomas; Khinast, Johannes G

2018-05-30

One major advantage of continuous pharmaceutical manufacturing over traditional batch manufacturing is the possibility of enhanced in-process control, reducing out-of-specification and waste material by appropriate discharge strategies. The decision on material discharge can be based on the measurement of active pharmaceutical ingredient (API) concentration at specific locations in the production line via process analytic technology (PAT), e.g. near-infrared (NIR) spectrometers. The implementation of the PAT instruments is associated with monetary investment and the long term operation requires techniques avoiding sensor drifts. Therefore, our paper proposes a soft sensor approach for predicting the API concentration from the feeder data. In addition, this information can be used to detect sensor drift, or serve as a replacement/supplement of specific PAT equipment. The paper presents the experimental determination of the residence time distribution of selected unit operations in three different continuous processing lines (hot melt extrusion, direct compaction, wet granulation). The mathematical models describing the soft sensor are developed and parameterized. Finally, the suggested soft sensor approach is validated on the three mentioned, different continuous processing lines, demonstrating its versatility. Copyright © 2018 Elsevier B.V. All rights reserved.

Digital Image Processing Overview For Helmet Mounted Displays

NASA Astrophysics Data System (ADS)

Parise, Michael J.

1989-09-01

Digital image processing provides a means to manipulate an image and presents a user with a variety of display formats that are not available in the analog image processing environment. When performed in real time and presented on a Helmet Mounted Display, system capability and flexibility are greatly enhanced. The information content of a display can be increased by the addition of real time insets and static windows from secondary sensor sources, near real time 3-D imaging from a single sensor can be achieved, graphical information can be added, and enhancement techniques can be employed. Such increased functionality is generating a considerable amount of interest in the military and commercial markets. This paper discusses some of these image processing techniques and their applications.

Passive Sensors for Long Duration Internet of Things Networks.

PubMed

Pereira, Felisberto; Correia, Ricardo; Carvalho, Nuno Borges

2017-10-03

In this work, three different concepts are used to develop a fully passive sensor that is capable of measuring different types of data. The sensor was supplied by Wireless Power Transmission (WPT). Communication between the sensor and reader is established by a backscatter, and to ensure minimum energy consumption, low power techniques are used. In a simplistic way, the process starts by the transmission of two different waves by the reader to the sensor, one of which is used in power transmission and the other of which is used to communicate. Once the sensor is powered, the monitoring process starts. From the monitoring state, results from after processing are used to modulate the incoming wave, which is the information that is sent back from the reader to the tag. This new combination of technologies enables the possibility of using sensors without any cables or batteries to operate 340 cm from the reader. The developed prototype measures acceleration and temperature. However, it is scalable. This system enables a new generation of passive Internet of Things (IoT) devices.

Passive Sensors for Long Duration Internet of Things Networks

PubMed Central

Correia, Ricardo; Carvalho, Nuno Borges

2017-01-01

In this work, three different concepts are used to develop a fully passive sensor that is capable of measuring different types of data. The sensor was supplied by Wireless Power Transmission (WPT). Communication between the sensor and reader is established by a backscatter, and to ensure minimum energy consumption, low power techniques are used. In a simplistic way, the process starts by the transmission of two different waves by the reader to the sensor, one of which is used in power transmission and the other of which is used to communicate. Once the sensor is powered, the monitoring process starts. From the monitoring state, results from after processing are used to modulate the incoming wave, which is the information that is sent back from the reader to the tag. This new combination of technologies enables the possibility of using sensors without any cables or batteries to operate 340 cm from the reader. The developed prototype measures acceleration and temperature. However, it is scalable. This system enables a new generation of passive Internet of Things (IoT) devices. PMID:28972554

A Bionic Polarization Navigation Sensor and Its Calibration Method.

PubMed

Zhao, Huijie; Xu, Wujian

2016-08-03

The polarization patterns of skylight which arise due to the scattering of sunlight in the atmosphere can be used by many insects for deriving compass information. Inspired by insects' polarized light compass, scientists have developed a new kind of navigation method. One of the key techniques in this method is the polarimetric sensor which is used to acquire direction information from skylight. In this paper, a polarization navigation sensor is proposed which imitates the working principles of the polarization vision systems of insects. We introduce the optical design and mathematical model of the sensor. In addition, a calibration method based on variable substitution and non-linear curve fitting is proposed. The results obtained from the outdoor experiments provide support for the feasibility and precision of the sensor. The sensor's signal processing can be well described using our mathematical model. A relatively high degree of accuracy in polarization measurement can be obtained without any error compensation.

Utilization of extended bayesian networks in decision making under uncertainty

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

Van Eeckhout, Edward M; Leishman, Deborah A; Gibson, William L

2009-01-01

Bayesian network tool (called IKE for Integrated Knowledge Engine) has been developed to assess the probability of undesirable events. The tool allows indications and observables from sensors and/or intelligence to feed directly into hypotheses of interest, thus allowing one to quantify the probability and uncertainty of these events resulting from very disparate evidence. For example, the probability that a facility is processing nuclear fuel or assembling a weapon can be assessed by examining the processes required, establishing the observables that should be present, then assembling information from intelligence, sensors and other information sources related to the observables. IKE also hasmore » the capability to determine tasking plans, that is, prioritize which observable should be collected next to most quickly ascertain the 'true' state and drive the probability toward 'zero' or 'one.' This optimization capability is called 'evidence marshaling.' One example to be discussed is a denied facility monitoring situation; there is concern that certain process(es) are being executed at the site (due to some intelligence or other data). We will show how additional pieces of evidence will then ascertain with some degree of certainty the likelihood of this process(es) as each piece of evidence is obtained. This example shows how both intelligence and sensor data can be incorporated into the analysis. A second example involves real-time perimeter security. For this demonstration we used seismic, acoustic, and optical sensors linked back to IKE. We show how these sensors identified and assessed the likelihood of 'intruder' versus friendly vehicles.« less

Managed traffic evacuation using distributed sensor processing

NASA Astrophysics Data System (ADS)

Ramuhalli, Pradeep; Biswas, Subir

2005-05-01

This paper presents an integrated sensor network and distributed event processing architecture for managed in-building traffic evacuation during natural and human-caused disasters, including earthquakes, fire and biological/chemical terrorist attacks. The proposed wireless sensor network protocols and distributed event processing mechanisms offer a new distributed paradigm for improving reliability in building evacuation and disaster management. The networking component of the system is constructed using distributed wireless sensors for measuring environmental parameters such as temperature, humidity, and detecting unusual events such as smoke, structural failures, vibration, biological/chemical or nuclear agents. Distributed event processing algorithms will be executed by these sensor nodes to detect the propagation pattern of the disaster and to measure the concentration and activity of human traffic in different parts of the building. Based on this information, dynamic evacuation decisions are taken for maximizing the evacuation speed and minimizing unwanted incidents such as human exposure to harmful agents and stampedes near exits. A set of audio-visual indicators and actuators are used for aiding the automated evacuation process. In this paper we develop integrated protocols, algorithms and their simulation models for the proposed sensor networking and the distributed event processing framework. Also, efficient harnessing of the individually low, but collectively massive, processing abilities of the sensor nodes is a powerful concept behind our proposed distributed event processing algorithms. Results obtained through simulation in this paper are used for a detailed characterization of the proposed evacuation management system and its associated algorithmic components.

Proposed tethered unmanned aerial system for the detection of pollution entering the Chesapeake Bay area

NASA Astrophysics Data System (ADS)

Goodman, J.; McKay, J.; Evans, W.; Gadsden, S. Andrew

2016-05-01

This paper is based on a proposed unmanned aerial system platform that is to be outfitted with high-resolution sensors. The proposed system is to be tethered to a moveable ground station, which may be a research vessel or some form of ground vehicle (e.g., car, truck, or rover). The sensors include, at a minimum: camera, infrared sensor, thermal, normalized difference vegetation index (NDVI) camera, global positioning system (GPS), and a light-based radar (LIDAR). The purpose of this paper is to provide an overview of existing methods for pollution detection of failing septic systems, and to introduce the proposed system. Future work will look at the high-resolution data from the sensors and integrating the data through a process called information fusion. Typically, this process is done using the popular and well-published Kalman filter (or its nonlinear formulations, such as the extended Kalman filter). However, future work will look at using a new type of strategy based on variable structure estimation for the information fusion portion of the data processing. It is hypothesized that fusing data from the thermal and NDVI sensors will be more accurate and reliable for a multitude of applications, including the detection of pollution entering the Chesapeake Bay area.

Glomerular latency coding in artificial olfaction.

PubMed

Yamani, Jaber Al; Boussaid, Farid; Bermak, Amine; Martinez, Dominique

2011-01-01

Sensory perception results from the way sensory information is subsequently transformed in the brain. Olfaction is a typical example in which odor representations undergo considerable changes as they pass from olfactory receptor neurons (ORNs) to second-order neurons. First, many ORNs expressing the same receptor protein yet presenting heterogeneous dose-response properties converge onto individually identifiable glomeruli. Second, onset latency of glomerular activation is believed to play a role in encoding odor quality and quantity in the context of fast information processing. Taking inspiration from the olfactory pathway, we designed a simple yet robust glomerular latency coding scheme for processing gas sensor data. The proposed bio-inspired approach was evaluated using an in-house SnO(2) sensor array. Glomerular convergence was achieved by noting the possible analogy between receptor protein expressed in ORNs and metal catalyst used across the fabricated gas sensor array. Ion implantation was another technique used to account both for sensor heterogeneity and enhanced sensitivity. The response of the gas sensor array was mapped into glomerular latency patterns, whose rank order is concentration-invariant. Gas recognition was achieved by simply looking for a "match" within a library of spatio-temporal spike fingerprints. Because of its simplicity, this approach enables the integration of sensing and processing onto a single-chip.

Higher resolution satellite remote sensing and the impact on image mapping

USGS Publications Warehouse

Watkins, Allen H.; Thormodsgard, June M.

1987-01-01

Recent advances in spatial, spectral, and temporal resolution of civil land remote sensing satellite data are presenting new opportunities for image mapping applications. The U.S. Geological Survey's experimental satellite image mapping program is evolving toward larger scale image map products with increased information content as a result of improved image processing techniques and increased resolution. Thematic mapper data are being used to produce experimental image maps at 1:100,000 scale that meet established U.S. and European map accuracy standards. Availability of high quality, cloud-free, 30-meter ground resolution multispectral data from the Landsat thematic mapper sensor, along with 10-meter ground resolution panchromatic and 20-meter ground resolution multispectral data from the recently launched French SPOT satellite, present new cartographic and image processing challenges.The need to fully exploit these higher resolution data increases the complexity of processing the images into large-scale image maps. The removal of radiometric artifacts and noise prior to geometric correction can be accomplished by using a variety of image processing filters and transforms. Sensor modeling and image restoration techniques allow maximum retention of spatial and radiometric information. An optimum combination of spectral information and spatial resolution can be obtained by merging different sensor types. These processing techniques are discussed and examples are presented.

Information integration and diagnosis analysis of equipment status and production quality for machining process

NASA Astrophysics Data System (ADS)

Zan, Tao; Wang, Min; Hu, Jianzhong

2010-12-01

Machining status monitoring technique by multi-sensors can acquire and analyze the machining process information to implement abnormity diagnosis and fault warning. Statistical quality control technique is normally used to distinguish abnormal fluctuations from normal fluctuations through statistical method. In this paper by comparing the advantages and disadvantages of the two methods, the necessity and feasibility of integration and fusion is introduced. Then an approach that integrates multi-sensors status monitoring and statistical process control based on artificial intelligent technique, internet technique and database technique is brought forward. Based on virtual instrument technique the author developed the machining quality assurance system - MoniSysOnline, which has been used to monitoring the grinding machining process. By analyzing the quality data and AE signal information of wheel dressing process the reason of machining quality fluctuation has been obtained. The experiment result indicates that the approach is suitable for the status monitoring and analyzing of machining process.

Smart Networked Elements in Support of ISHM

NASA Technical Reports Server (NTRS)

Oostdyk, Rebecca; Mata, Carlos; Perotti, Jose M.

2008-01-01

At the core of ISHM is the ability to extract information and knowledge from raw data. Conventional data acquisition systems sample and convert physical measurements to engineering units, which higher-level systems use to derive health and information about processes and systems. Although health management is essential at the top level, there are considerable advantages to implementing health-related functions at the sensor level. The distribution of processing to lower levels reduces bandwidth requirements, enhances data fusion, and improves the resolution for detection and isolation of failures in a system, subsystem, component, or process. The Smart Networked Element (SNE) has been developed to implement intelligent functions and algorithms at the sensor level in support of ISHM.

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.

Methods of use for sensor based fluid detection devices

NASA Technical Reports Server (NTRS)

Lewis, Nathan S. (Inventor)

2001-01-01

Methods of use and devices for detecting analyte in fluid. A system for detecting an analyte in a fluid is described comprising a substrate having a sensor comprising a first organic material and a second organic material where the sensor has a response to permeation by an analyte. A detector is operatively associated with the sensor. Further, a fluid delivery appliance is operatively associated with the sensor. The sensor device has information storage and processing equipment, which is operably connected with the device. This device compares a response from the detector with a stored ideal response to detect the presence of analyte. An integrated system for detecting an analyte in a fluid is also described where the sensing device, detector, information storage and processing device, and fluid delivery device are incorporated in a substrate. Methods for use for the above system are also described where the first organic material and a second organic material are sensed and the analyte is detected with a detector operatively associated with the sensor. The method provides for a device, which delivers fluid to the sensor and measures the response of the sensor with the detector. Further, the response is compared to a stored ideal response for the analyte to determine the presence of the analyte. In different embodiments, the fluid measured may be a gaseous fluid, a liquid, or a fluid extracted from a solid. Methods of fluid delivery for each embodiment are accordingly provided.

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

PubMed Central

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

2017-01-01

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

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

PubMed

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

2017-11-25

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

Integrated intelligent sensor for the textile industry

NASA Astrophysics Data System (ADS)

Peltie, Philippe; David, Dominique

1996-08-01

A new sensor has been developed for pantyhose inspection. Unlike a first complete inspection machine devoted to post- manufacturing control of the whole panty, this sensor will be directly integrated on currently existing manufacturing machines, and will combine advantages of miniaturization is to design an intelligent, compact and very cheap product, which should be integrated without requiring any modifications of host machines. The sensor part was designed to achieve closed acquisition, and various solutions have been explored to maintain adequate depth of field. The illumination source will be integrated in the device. The processing part will include correction facilities and electronic processing. Finally, high-level information will be output in order to interface directly with the manufacturing machine automate.

A Study on Group Key Agreement in Sensor Network Environments Using Two-Dimensional Arrays

PubMed Central

Jang, Seung-Jae; Lee, Young-Gu; Lee, Kwang-Hyung; Kim, Tai-Hoon; Jun, Moon-Seog

2011-01-01

These days, with the emergence of the concept of ubiquitous computing, sensor networks that collect, analyze and process all the information through the sensors have become of huge interest. However, sensor network technology fundamentally has wireless communication infrastructure as its foundation and thus has security weakness and limitations such as low computing capacity, power supply limitations and price. In this paper, and considering the characteristics of the sensor network environment, we propose a group key agreement method using a keyset pre-distribution of two-dimension arrays that should minimize the exposure of key and personal information. The key collision problems are resolved by utilizing a polygonal shape’s center of gravity. The method shows that calculating a polygonal shape’s center of gravity only requires a very small amount of calculations from the users. The simple calculation not only increases the group key generation efficiency, but also enhances the sense of security by protecting information between nodes. PMID:22164072

Two Analyte Calibration From The Transient Response Of Potentiometric Sensors Employed With The SIA Technique

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

Cartas, Raul; Mimendia, Aitor; Valle, Manel del

2009-05-23

Calibration models for multi-analyte electronic tongues have been commonly built using a set of sensors, at least one per analyte under study. Complex signals recorded with these systems are formed by the sensors' responses to the analytes of interest plus interferents, from which a multivariate response model is then developed. This work describes a data treatment method for the simultaneous quantification of two species in solution employing the signal from a single sensor. The approach used here takes advantage of the complex information recorded with one electrode's transient after insertion of sample for building the calibration models for both analytes.more » The departure information from the electrode was firstly processed by discrete wavelet for transforming the signals to extract useful information and reduce its length, and then by artificial neural networks for fitting a model. Two different potentiometric sensors were used as study case for simultaneously corroborating the effectiveness of the approach.« less

Review of Portable and Low-Cost Sensors for the Ambient Air Monitoring of Benzene and Other Volatile Organic Compounds

PubMed Central

Kok, Gertjan; Persijn, Stefan; Sauerwald, Tilman

2017-01-01

This article presents a literature review of sensors for the monitoring of benzene in ambient air and other volatile organic compounds. Combined with information provided by stakeholders, manufacturers and literature, the review considers commercially available sensors, including PID-based sensors, semiconductor (resistive gas sensors) and portable on-line measuring devices as for example sensor arrays. The bibliographic collection includes the following topics: sensor description, field of application at fixed sites, indoor and ambient air monitoring, range of concentration levels and limit of detection in air, model descriptions of the phenomena involved in the sensor detection process, gaseous interference selectivity of sensors in complex VOC matrix, validation data in lab experiments and under field conditions. PMID:28657595

Review of Portable and Low-Cost Sensors for the Ambient Air Monitoring of Benzene and Other Volatile Organic Compounds.

PubMed

Spinelle, Laurent; Gerboles, Michel; Kok, Gertjan; Persijn, Stefan; Sauerwald, Tilman

2017-06-28

This article presents a literature review of sensors for the monitoring of benzene in ambient air and other volatile organic compounds. Combined with information provided by stakeholders, manufacturers and literature, the review considers commercially available sensors, including PID-based sensors, semiconductor (resistive gas sensors) and portable on-line measuring devices as for example sensor arrays. The bibliographic collection includes the following topics: sensor description, field of application at fixed sites, indoor and ambient air monitoring, range of concentration levels and limit of detection in air, model descriptions of the phenomena involved in the sensor detection process, gaseous interference selectivity of sensors in complex VOC matrix, validation data in lab experiments and under field conditions.

Real-time physiological monitoring with distributed networks of sensors and object-oriented programming techniques

NASA Astrophysics Data System (ADS)

Wiesmann, William P.; Pranger, L. Alex; Bogucki, Mary S.

1998-05-01

Remote monitoring of physiologic data from individual high- risk workers distributed over time and space is a considerable challenge. This is often due to an inadequate capability to accurately integrate large amounts of data into usable information in real time. In this report, we have used the vertical and horizontal organization of the 'fireground' as a framework to design a distributed network of sensors. In this system, sensor output is linked through a hierarchical object oriented programing process to accurately interpret physiological data, incorporate these data into a synchronous model and relay processed data, trends and predictions to members of the fire incident command structure. There are several unique aspects to this approach. The first includes a process to account for variability in vital parameter values for each individual's normal physiologic response by including an adaptive network in each data process. This information is used by the model in an iterative process to baseline a 'normal' physiologic response to a given stress for each individual and to detect deviations that indicate dysfunction or a significant insult. The second unique capability of the system orders the information for each user including the subject, local company officers, medical personnel and the incident commanders. Information can be retrieved and used for training exercises and after action analysis. Finally this system can easily be adapted to existing communication and processing links along with incorporating the best parts of current models through the use of object oriented programming techniques. These modern software techniques are well suited to handling multiple data processes independently over time in a distributed network.

Digital seismo-acoustic signal processing aboard a wireless sensor platform

NASA Astrophysics Data System (ADS)

Marcillo, O.; Johnson, J. B.; Lorincz, K.; Werner-Allen, G.; Welsh, M.

2006-12-01

We are developing a low power, low-cost wireless sensor array to conduct real-time signal processing of earthquakes at active volcanoes. The sensor array, which integrates data from both seismic and acoustic sensors, is based on Moteiv TMote Sky wireless sensor nodes (www.moteiv.com). The nodes feature a Texas Instruments MSP430 microcontroller, 48 Kbytes of program memory, 10 Kbytes of static RAM, 1 Mbyte of external flash memory, and a 2.4-GHz Chipcon CC2420 IEEE 802.15.4 radio. The TMote Sky is programmed in TinyOS. Basic signal processing occurs on an array of three peripheral sensor nodes. These nodes are tied into a dedicated GPS receiver node, which is focused on time synchronization, and a central communications node, which handles data integration and additional processing. The sensor nodes incorporate dual 12-bit digitizers sampling a seismic sensor and a pressure transducer at 100 samples per second. The wireless capabilities of the system allow flexible array geometry, with a maximum aperture of 200m. We have already developed the digital signal processing routines on board the Moteiv Tmote sensor nodes. The developed routines accomplish Real-time Seismic-Amplitude Measurement (RSAM), Seismic Spectral- Amplitude Measurement (SSAM), and a user-configured Short Term Averaging / Long Term Averaging (STA LTA ratio), which is used to calculate first arrivals. The processed data from individual nodes are transmitted back to a central node, where additional processing may be performed. Such processing will include back azimuth determination and other wave field analyses. Future on-board signal processing will focus on event characterization utilizing pattern recognition and spectral characterization. The processed data is intended as low bandwidth information which can be transmitted periodically and at low cost through satellite telemetry to a web server. The processing is limited by the computational capabilities (RAM, ROM) of the nodes. Nevertheless, we envision this product to be a useful tool for assessing the state of unrest at remote volcanoes.

Monitoring technology

NASA Technical Reports Server (NTRS)

Stevenson, William A. (Inventor)

1989-01-01

A process for infrared spectroscopic monitoring of insitu compositional changes in a polymeric material comprises the steps of providing an elongated infrared radiation transmitting fiber that has a transmission portion and a sensor portion, embedding the sensor portion in the polymeric material to be monitored, subjecting the polymeric material to a processing sequence, applying a beam of infrared radiation to the fiber for transmission through the transmitting portion to the sensor portion for modification as a function of properties of the polymeric material, monitoring the modified infrared radiation spectra as the polymeric material is being subjected to the processing sequence to obtain kinetic data on changes in the polymeric material during the processing sequence, and adjusting the processing sequence as a function of the kinetic data provided by the modified infrared radiation spectra information.

Monitoring technology

NASA Technical Reports Server (NTRS)

Stevenson, William A. (Inventor)

1992-01-01

A process for infrared spectroscopic monitoring of insitu compositional changes in a polymeric material comprises the steps of providing an elongated infrared radiation transmitting fiber that has a transmission portion and a sensor portion, embedding the sensor portion in the polymeric material to be monitored, subjecting the polymeric material to a processing sequence, applying a beam of infrared radiation to the fiber for transmission through the transmitting portion to the sensor portion for modification as a function of properties of the polymeric material, monitoring the modified infrared radiation spectra as the polymeric material is being subjected to the processing sequence to obtain kinetic data on changes in the polymeric material during the processing sequence, and adjusting the processing sequence as a function of the kinetic data provided by the modified infrared radiation spectra information.

A source number estimation method for single optical fiber sensor

NASA Astrophysics Data System (ADS)

Hu, Junpeng; Huang, Zhiping; Su, Shaojing; Zhang, Yimeng; Liu, Chunwu

2015-10-01

The single-channel blind source separation (SCBSS) technique makes great significance in many fields, such as optical fiber communication, sensor detection, image processing and so on. It is a wide range application to realize blind source separation (BSS) from a single optical fiber sensor received data. The performance of many BSS algorithms and signal process methods will be worsened with inaccurate source number estimation. Many excellent algorithms have been proposed to deal with the source number estimation in array signal process which consists of multiple sensors, but they can not be applied directly to the single sensor condition. This paper presents a source number estimation method dealing with the single optical fiber sensor received data. By delay process, this paper converts the single sensor received data to multi-dimension form. And the data covariance matrix is constructed. Then the estimation algorithms used in array signal processing can be utilized. The information theoretic criteria (ITC) based methods, presented by AIC and MDL, Gerschgorin's disk estimation (GDE) are introduced to estimate the source number of the single optical fiber sensor's received signal. To improve the performance of these estimation methods at low signal noise ratio (SNR), this paper make a smooth process to the data covariance matrix. By the smooth process, the fluctuation and uncertainty of the eigenvalues of the covariance matrix are reduced. Simulation results prove that ITC base methods can not estimate the source number effectively under colored noise. The GDE method, although gets a poor performance at low SNR, but it is able to accurately estimate the number of sources with colored noise. The experiments also show that the proposed method can be applied to estimate the source number of single sensor received data.

Detection and analysis of emitted radiation for advanced monitoring and control of combustors

NASA Astrophysics Data System (ADS)

Ballester, J.; Sanz, A.; Hernandez, R.; Smolarz, A.

2005-09-01

The permanent optimization of combustion equipment could provide very important benefits in terms of efficiency, reliability and reduced pollution. However, current capabilities for monitoring and control of industrial flames are very limited; the lack of reliable diagnostic techniques is, most probably, the main obstacle to achieve those goals. Novel instrumentation systems based on the processing of the radiation emitted by the flames could help greatly to fill this gap, as radiation signals are known to contain very rich information about flame properties Optical sensors offer the benefit of being selective, rapid and able to gather data from extremely hostile environments. Passive optical sensors offer the further advantages of simplicity and low cost. With the rapidly growing capability of sensor hardware, there is an increased interest and need to develop data interpretation strategies that will allow optical flame emission data to be converted into meaningful combustor state information. The present work describes new results achieved on the use of optical sensors for the development of advanced monitoring systems of lean-premixed flames representative of gas turbine combustors. Different complementary signals have been analyzed: broad band emission using a Si photodiode, a narrow band around 310 nm measured with a photomultiplier and measurement of UV+VIS emission spectra. The signals have been processed using both conventional and advanced methods. The results obtained demonstrate that optical sensors can yield useful, instantaneous information on the actual flame properties, not available with the sensors currently used in practical combustion systems.

3-D Imaging Systems for Agricultural Applications—A Review

PubMed Central

Vázquez-Arellano, Manuel; Griepentrog, Hans W.; Reiser, David; Paraforos, Dimitris S.

2016-01-01

Efficiency increase of resources through automation of agriculture requires more information about the production process, as well as process and machinery status. Sensors are necessary for monitoring the status and condition of production by recognizing the surrounding structures such as objects, field structures, natural or artificial markers, and obstacles. Currently, three dimensional (3-D) sensors are economically affordable and technologically advanced to a great extent, so a breakthrough is already possible if enough research projects are commercialized. The aim of this review paper is to investigate the state-of-the-art of 3-D vision systems in agriculture, and the role and value that only 3-D data can have to provide information about environmental structures based on the recent progress in optical 3-D sensors. The structure of this research consists of an overview of the different optical 3-D vision techniques, based on the basic principles. Afterwards, their application in agriculture are reviewed. The main focus lays on vehicle navigation, and crop and animal husbandry. The depth dimension brought by 3-D sensors provides key information that greatly facilitates the implementation of automation and robotics in agriculture. PMID:27136560

A New Dusts Sensor for Cultural Heritage Applications Based on Image Processing

PubMed Central

Proietti, Andrea; Leccese, Fabio; Caciotta, Maurizio; Morresi, Fabio; Santamaria, Ulderico; Malomo, Carmela

2014-01-01

In this paper, we propose a new sensor for the detection and analysis of dusts (seen as powders and fibers) in indoor environments, especially designed for applications in the field of Cultural Heritage or in other contexts where the presence of dust requires special care (surgery, clean rooms, etc.). The presented system relies on image processing techniques (enhancement, noise reduction, segmentation, metrics analysis) and it allows obtaining both qualitative and quantitative information on the accumulation of dust. This information aims to identify the geometric and topological features of the elements of the deposit. The curators can use this information in order to design suitable prevention and maintenance actions for objects and environments. The sensor consists of simple and relatively cheap tools, based on a high-resolution image acquisition system, a preprocessing software to improve the captured image and an analysis algorithm for the feature extraction and the classification of the elements of the dust deposit. We carried out some tests in order to validate the system operation. These tests were performed within the Sistine Chapel in the Vatican Museums, showing the good performance of the proposed sensor in terms of execution time and classification accuracy. PMID:24901977

Interactive information processing for NASA's mesoscale analysis and space sensor program

NASA Technical Reports Server (NTRS)

Parker, K. G.; Maclean, L.; Reavis, N.; Wilson, G.; Hickey, J. S.; Dickerson, M.; Karitani, S.; Keller, D.

1985-01-01

The Atmospheric Sciences Division (ASD) of the Systems Dynamics Laboratory at NASA's Marshall Space Flight Center (MSFC) is currently involved in interactive information processing for the Mesoscale Analysis and Space Sensor (MASS) program. Specifically, the ASD is engaged in the development and implementation of new space-borne remote sensing technology to observe and measure mesoscale atmospheric processes. These space measurements and conventional observational data are being processed together to gain an improved understanding of the mesoscale structure and the dynamical evolution of the atmosphere relative to cloud development and precipitation processes. To satisfy its vast data processing requirements, the ASD has developed a Researcher Computer System consiting of three primary computer systems which provides over 20 scientists with a wide range of capabilities for processing and displaying a large volumes of remote sensing data. Each of the computers performs a specific function according to its unique capabilities.

Automated information-analytical system for thunderstorm monitoring and early warning alarms using modern physical sensors and information technologies with elements of artificial intelligence

NASA Astrophysics Data System (ADS)

Boldyreff, Anton S.; Bespalov, Dmitry A.; Adzhiev, Anatoly Kh.

2017-05-01

Methods of artificial intelligence are a good solution for weather phenomena forecasting. They allow to process a large amount of diverse data. Recirculation Neural Networks is implemented in the paper for the system of thunderstorm events prediction. Large amounts of experimental data from lightning sensors and electric field mills networks are received and analyzed. The average recognition accuracy of sensor signals is calculated. It is shown that Recirculation Neural Networks is a promising solution in the forecasting of thunderstorms and weather phenomena, characterized by the high efficiency of the recognition elements of the sensor signals, allows to compress images and highlight their characteristic features for subsequent recognition.

Image processing techniques and applications to the Earth Resources Technology Satellite program

NASA Technical Reports Server (NTRS)

Polge, R. J.; Bhagavan, B. K.; Callas, L.

1973-01-01

The Earth Resources Technology Satellite system is studied, with emphasis on sensors, data processing requirements, and image data compression using the Fast Fourier and Hadamard transforms. The ERTS-A system and the fundamentals of remote sensing are discussed. Three user applications (forestry, crops, and rangelands) are selected and their spectral signatures are described. It is shown that additional sensors are needed for rangeland management. An on-board information processing system is recommended to reduce the amount of data transmitted.

Do leaf-cutter ants Atta colombica obtain their magnetic sensors from soil?

USDA-ARS?s Scientific Manuscript database

How animals sense, process and use magnetic information has remained largely elusive. In insects, ferromagnetic particles are candidates for a magnetic sensor. Recent studies suggest that ferromagnetic minerals from soil can be incorporated into the antennae of the migratory ant Pachycondola margina...

An innovative nanophotonic information processing concept implementing cogent micro/nanosensors for space robotics

NASA Astrophysics Data System (ADS)

Santoli, Salvatore

2013-02-01

Cogent sensors, defined as sensors that are capable of performing the transformation of raw data into information, are shown to be of the essence for realization of the long sought-after autonomous robots for space applications. A strongly miniaturized integration of sensing and information processing systems is needed for cogent sensors designed for autonomous sensing—information processing (IP)—actuating behavior. It is shown that the recently developed field of quantum holography (QH), stemming from geometric quantization of any holographic processes through the Heisenberg Group (G) and deeply different, as stressed in detail, from other meanings of "quantum holography" in the literature, supplies the nanophotonic tools for designing and assembling an associative memory (AM) as the brain implementing such strong cogency. An AM is designed through a free-space interconnected large planar multilayer architecture of quantum well-based two-port neurons implementing a shift register on the manifold of G, and whose input consists of photonic holograms from high frequency pulsed microlasers in the infrared band of em or em-transduced outside signals. The optoelectronics as relative, integrated into a hybrid chip involving photonic detectors, microlasers and electronic components for the clock control system, would allow cycle times as short as 30 ns with the large spatial bandwidth available in photonics. IP through QH concerns the encoding and decoding of holographic interference patterns, not of mere binary digital logical (syntactic) information. Accordingly, QH defines on the G's manifold an IP paradigm where information as experimental knowledge is processed; i.e., IP concerns both syntax and semantics. It is shown that such QH-neural brain would cogently deal with spurious signals as random noise that would be caused to die out on the way to the intended target through parallel massive and real-time IP.

Improved GSO Optimized ESN Soft-Sensor Model of Flotation Process Based on Multisource Heterogeneous Information Fusion

PubMed Central

Wang, Jie-sheng; Han, Shuang; Shen, Na-na

2014-01-01

For predicting the key technology indicators (concentrate grade and tailings recovery rate) of flotation process, an echo state network (ESN) based fusion soft-sensor model optimized by the improved glowworm swarm optimization (GSO) algorithm is proposed. Firstly, the color feature (saturation and brightness) and texture features (angular second moment, sum entropy, inertia moment, etc.) based on grey-level co-occurrence matrix (GLCM) are adopted to describe the visual characteristics of the flotation froth image. Then the kernel principal component analysis (KPCA) method is used to reduce the dimensionality of the high-dimensional input vector composed by the flotation froth image characteristics and process datum and extracts the nonlinear principal components in order to reduce the ESN dimension and network complex. The ESN soft-sensor model of flotation process is optimized by the GSO algorithm with congestion factor. Simulation results show that the model has better generalization and prediction accuracy to meet the online soft-sensor requirements of the real-time control in the flotation process. PMID:24982935

Lateral position detection and control for friction stir systems

DOEpatents

Fleming, Paul; Lammlein, David; Cook, George E.; Wilkes, Don Mitchell; Strauss, Alvin M.; Delapp, David; Hartman, Daniel A.

2010-12-14

A friction stir system for processing at least a first workpiece includes a spindle actuator coupled to a rotary tool comprising a rotating member for contacting and processing the first workpiece. A detection system is provided for obtaining information related to a lateral alignment of the rotating member. The detection system comprises at least one sensor for measuring a force experienced by the rotary tool or a parameter related to the force experienced by the rotary tool during processing, wherein the sensor provides sensor signals. A signal processing system is coupled to receive and analyze the sensor signals and determine a lateral alignment of the rotating member relative to a selected lateral position, a selected path, or a direction to decrease a lateral distance relative to the selected lateral position or selected path. In one embodiment, the friction stir system can be embodied as a closed loop tracking system, such as a robot-based tracked friction stir welding (FSW) or friction stir processing (FSP) system.

A Molecular Sensor To Characterize Arenavirus Envelope Glycoprotein Cleavage by Subtilisin Kexin Isozyme 1/Site 1 Protease.

PubMed

Oppliger, Joel; da Palma, Joel Ramos; Burri, Dominique J; Bergeron, Eric; Khatib, Abdel-Majid; Spiropoulou, Christina F; Pasquato, Antonella; Kunz, Stefan

2016-01-15

Arenaviruses are emerging viruses including several causative agents of severe hemorrhagic fevers in humans. The advent of next-generation sequencing technology has greatly accelerated the discovery of novel arenavirus species. However, for many of these viruses, only genetic information is available, and their zoonotic disease potential remains unknown. During the arenavirus life cycle, processing of the viral envelope glycoprotein precursor (GPC) by the cellular subtilisin kexin isozyme 1 (SKI-1)/site 1 protease (S1P) is crucial for productive infection. The ability of newly emerging arenaviruses to hijack human SKI-1/S1P appears, therefore, to be a requirement for efficient zoonotic transmission and human disease potential. Here we implement a newly developed cell-based molecular sensor for SKI-1/S1P to characterize the processing of arenavirus GPC-derived target sequences by human SKI-1/S1P in a quantitative manner. We show that only nine amino acids flanking the putative cleavage site are necessary and sufficient to accurately recapitulate the efficiency and subcellular location of arenavirus GPC processing. In a proof of concept, our sensor correctly predicts efficient processing of the GPC of the newly emergent pathogenic Lujo virus by human SKI-1/S1P and defines the exact cleavage site. Lastly, we employed our sensor to show efficient GPC processing of a panel of pathogenic and nonpathogenic New World arenaviruses, suggesting that GPC cleavage represents no barrier for zoonotic transmission of these pathogens. Our SKI-1/S1P sensor thus represents a rapid and robust test system for assessment of the processing of putative cleavage sites derived from the GPCs of newly discovered arenavirus by the SKI-1/S1P of humans or any other species, based solely on sequence information. Arenaviruses are important emerging human pathogens that can cause severe hemorrhagic fevers with high mortality in humans. A crucial step in productive arenavirus infection of human cells is the processing of the viral envelope glycoprotein by the cellular subtilisin kexin isozyme 1 (SKI-1)/site 1 protease (S1P). In order to break the species barrier during zoonotic transmission and cause severe disease in humans, newly emerging arenaviruses must be able to hijack human SKI-1/S1P efficiently. Here we implement a newly developed cell-based molecular sensor for human SKI-1/S1P to characterize the processing of arenavirus glycoproteins in a quantitative manner. We further use our sensor to correctly predict efficient processing of the glycoprotein of the newly emergent pathogenic Lujo virus by human SKI-1/S1P. Our sensor thus represents a rapid and robust test system with which to assess whether the glycoprotein of any newly emerging arenavirus can be efficiently processed by human SKI-1/S1P, based solely on sequence information. Copyright © 2015, American Society for Microbiology. All Rights Reserved.

Cosmic non-TEM radiation and synthetic feed array sensor system in ASIC mixed signal technology

NASA Astrophysics Data System (ADS)

Centureli, F.; Scotti, G.; Tommasino, P.; Trifiletti, A.; Romano, F.; Cimmino, R.; Saitto, A.

2014-08-01

The paper deals with the opportunity to introduce "Not strictly TEM waves" Synthetic detection Method (NTSM), consisting in a Three Axis Digital Beam Processing (3ADBP), to enhance the performances of radio telescope and sensor systems. Current Radio Telescopes generally use the classic 3D "TEM waves" approximation Detection Method, which consists in a linear tomography process (Single or Dual axis beam forming processing) neglecting the small z component. The Synthetic FEED ARRAY three axis Sensor SYSTEM is an innovative technique using a synthetic detection of the generic "NOT strictly TEM Waves radiation coming from the Cosmo, which processes longitudinal component of Angular Momentum too. Than the simultaneous extraction from radiation of both the linear and quadratic information component, may reduce the complexity to reconstruct the Early Universe in the different requested scales. This next order approximation detection of the observed cosmologic processes, may improve the efficacy of the statistical numerical model used to elaborate the same information acquired. The present work focuses on detection of such waves at carrier frequencies in the bands ranging from LF to MMW. The work shows in further detail the new generation of on line programmable and reconfigurable Mixed Signal ASIC technology that made possible the innovative Synthetic Sensor. Furthermore the paper shows the ability of such technique to increase the Radio Telescope Array Antenna performances.

Tasking and sharing sensing assets using controlled natural language

NASA Astrophysics Data System (ADS)

Preece, Alun; Pizzocaro, Diego; Braines, David; Mott, David

2012-06-01

We introduce an approach to representing intelligence, surveillance, and reconnaissance (ISR) tasks at a relatively high level in controlled natural language. We demonstrate that this facilitates both human interpretation and machine processing of tasks. More specically, it allows the automatic assignment of sensing assets to tasks, and the informed sharing of tasks between collaborating users in a coalition environment. To enable automatic matching of sensor types to tasks, we created a machine-processable knowledge representation based on the Military Missions and Means Framework (MMF), and implemented a semantic reasoner to match task types to sensor types. We combined this mechanism with a sensor-task assignment procedure based on a well-known distributed protocol for resource allocation. In this paper, we re-formulate the MMF ontology in Controlled English (CE), a type of controlled natural language designed to be readable by a native English speaker whilst representing information in a structured, unambiguous form to facilitate machine processing. We show how CE can be used to describe both ISR tasks (for example, detection, localization, or identication of particular kinds of object) and sensing assets (for example, acoustic, visual, or seismic sensors, mounted on motes or unmanned vehicles). We show how these representations enable an automatic sensor-task assignment process. Where a group of users are cooperating in a coalition, we show how CE task summaries give users in the eld a high-level picture of ISR coverage of an area of interest. This allows them to make ecient use of sensing resources by sharing tasks.

A New Multi-Sensor Track Fusion Architecture for Multi-Sensor Information Integration

DTIC Science & Technology

2004-09-01

NUMBER 5b. GRANT NUMBER 5c. PROGRAM ELEMENT NUMBER 6. AUTHOR(S) 5d. PROJECT NUMBER 5e. TASK NUMBER 5f. WORK UNIT NUMBER 7. PERFORMING ORGANIZATION ...NAME(S) AND ADDRESS(ES) Lockheed Martin Aeronautical Systems Company,Marietta,GA,3063 8. PERFORMING ORGANIZATION REPORT NUMBER 9. SPONSORING...tracking process and degrades the track accuracy. ARCHITECHTURE OF MULTI-SENSOR TRACK FUSION MODEL The Alpha

An Improved Multi-Sensor Fusion Navigation Algorithm Based on the Factor Graph

PubMed Central

Zeng, Qinghua; Chen, Weina; Liu, Jianye; Wang, Huizhe

2017-01-01

An integrated navigation system coupled with additional sensors can be used in the Micro Unmanned Aerial Vehicle (MUAV) applications because the multi-sensor information is redundant and complementary, which can markedly improve the system accuracy. How to deal with the information gathered from different sensors efficiently is an important problem. The fact that different sensors provide measurements asynchronously may complicate the processing of these measurements. In addition, the output signals of some sensors appear to have a non-linear character. In order to incorporate these measurements and calculate a navigation solution in real time, the multi-sensor fusion algorithm based on factor graph is proposed. The global optimum solution is factorized according to the chain structure of the factor graph, which allows for a more general form of the conditional probability density. It can convert the fusion matter into connecting factors defined by these measurements to the graph without considering the relationship between the sensor update frequency and the fusion period. An experimental MUAV system has been built and some experiments have been performed to prove the effectiveness of the proposed method. PMID:28335570

An Improved Multi-Sensor Fusion Navigation Algorithm Based on the Factor Graph.

PubMed

Zeng, Qinghua; Chen, Weina; Liu, Jianye; Wang, Huizhe

2017-03-21

An integrated navigation system coupled with additional sensors can be used in the Micro Unmanned Aerial Vehicle (MUAV) applications because the multi-sensor information is redundant and complementary, which can markedly improve the system accuracy. How to deal with the information gathered from different sensors efficiently is an important problem. The fact that different sensors provide measurements asynchronously may complicate the processing of these measurements. In addition, the output signals of some sensors appear to have a non-linear character. In order to incorporate these measurements and calculate a navigation solution in real time, the multi-sensor fusion algorithm based on factor graph is proposed. The global optimum solution is factorized according to the chain structure of the factor graph, which allows for a more general form of the conditional probability density. It can convert the fusion matter into connecting factors defined by these measurements to the graph without considering the relationship between the sensor update frequency and the fusion period. An experimental MUAV system has been built and some experiments have been performed to prove the effectiveness of the proposed method.

Secure Data Aggregation with Fully Homomorphic Encryption in Large-Scale Wireless Sensor Networks

PubMed Central

Li, Xing; Chen, Dexin; Li, Chunyan; Wang, Liangmin

2015-01-01

With the rapid development of wireless communication technology, sensor technology, information acquisition and processing technology, sensor networks will finally have a deep influence on all aspects of people’s lives. The battery resources of sensor nodes should be managed efficiently in order to prolong network lifetime in large-scale wireless sensor networks (LWSNs). Data aggregation represents an important method to remove redundancy as well as unnecessary data transmission and hence cut down the energy used in communication. As sensor nodes are deployed in hostile environments, the security of the sensitive information such as confidentiality and integrity should be considered. This paper proposes Fully homomorphic Encryption based Secure data Aggregation (FESA) in LWSNs which can protect end-to-end data confidentiality and support arbitrary aggregation operations over encrypted data. In addition, by utilizing message authentication codes (MACs), this scheme can also verify data integrity during data aggregation and forwarding processes so that false data can be detected as early as possible. Although the FHE increase the computation overhead due to its large public key size, simulation results show that it is implementable in LWSNs and performs well. Compared with other protocols, the transmitted data and network overhead are reduced in our scheme. PMID:26151208

Precise nanoliter fluid handling system with integrated high-speed flow sensor.

PubMed

Haber, Carsten; Boillat, Marc; van der Schoot, Bart

2005-04-01

A system for accurate low-volume delivery of liquids in the micro- to nanoliter range makes use of an integrated miniature flow sensor as part of an intelligent feedback control loop driving a micro-solenoid valve. The flow sensor is hydraulically connected with the pressurized system liquid in the dispensing channel and located downstream from the pressure source, above the solenoid valve. The sensor operates in a differential mode and responds in real-time to the internal flow-pulse resulting from the brief opening interval of the solenoid valve leading to a rapid ejection of a fluid droplet. The integral of the flow-pulse delivered by the sensor is directly proportional to the volume of the ejected droplet from the nozzle. The quantitative information is utilized to provide active control of the effectively dispensed or aspirated volume by adjusting the solenoid valve accordingly. This process significantly enhances the precision of the fluid delivery. The system furthermore compensates automatically for any changes in the viscosity of the dispensed liquid. The data delivered by the flow sensor can be saved and backtracked in order to confirm and validate the aspiration and dispensing process in its entirety. The collected dispense information can be used for quality control assessments and automatically be made part of an electronic record.

Optimal full motion video registration with rigorous error propagation

NASA Astrophysics Data System (ADS)

Dolloff, John; Hottel, Bryant; Doucette, Peter; Theiss, Henry; Jocher, Glenn

2014-06-01

Optimal full motion video (FMV) registration is a crucial need for the Geospatial community. It is required for subsequent and optimal geopositioning with simultaneous and reliable accuracy prediction. An overall approach being developed for such registration is presented that models relevant error sources in terms of the expected magnitude and correlation of sensor errors. The corresponding estimator is selected based on the level of accuracy of the a priori information of the sensor's trajectory and attitude (pointing) information, in order to best deal with non-linearity effects. Estimator choices include near real-time Kalman Filters and batch Weighted Least Squares. Registration solves for corrections to the sensor a priori information for each frame. It also computes and makes available a posteriori accuracy information, i.e., the expected magnitude and correlation of sensor registration errors. Both the registered sensor data and its a posteriori accuracy information are then made available to "down-stream" Multi-Image Geopositioning (MIG) processes. An object of interest is then measured on the registered frames and a multi-image optimal solution, including reliable predicted solution accuracy, is then performed for the object's 3D coordinates. This paper also describes a robust approach to registration when a priori information of sensor attitude is unavailable. It makes use of structure-from-motion principles, but does not use standard Computer Vision techniques, such as estimation of the Essential Matrix which can be very sensitive to noise. The approach used instead is a novel, robust, direct search-based technique.

HIRIS (High-Resolution Imaging Spectrometer: Science opportunities for the 1990s. Earth observing system. Volume 2C: Instrument panel report

NASA Technical Reports Server (NTRS)

1987-01-01

The high-resolution imaging spectrometer (HIRIS) is an Earth Observing System (EOS) sensor developed for high spatial and spectral resolution. It can acquire more information in the 0.4 to 2.5 micrometer spectral region than any other sensor yet envisioned. Its capability for critical sampling at high spatial resolution makes it an ideal complement to the MODIS (moderate-resolution imaging spectrometer) and HMMR (high-resolution multifrequency microwave radiometer), lower resolution sensors designed for repetitive coverage. With HIRIS it is possible to observe transient processes in a multistage remote sensing strategy for Earth observations on a global scale. The objectives, science requirements, and current sensor design of the HIRIS are discussed along with the synergism of the sensor with other EOS instruments and data handling and processing requirements.

Active Multimodal Sensor System for Target Recognition and Tracking

PubMed Central

Zhang, Guirong; Zou, Zhaofan; Liu, Ziyue; Mao, Jiansen

2017-01-01

High accuracy target recognition and tracking systems using a single sensor or a passive multisensor set are susceptible to external interferences and exhibit environmental dependencies. These difficulties stem mainly from limitations to the available imaging frequency bands, and a general lack of coherent diversity of the available target-related data. This paper proposes an active multimodal sensor system for target recognition and tracking, consisting of a visible, an infrared, and a hyperspectral sensor. The system makes full use of its multisensor information collection abilities; furthermore, it can actively control different sensors to collect additional data, according to the needs of the real-time target recognition and tracking processes. This level of integration between hardware collection control and data processing is experimentally shown to effectively improve the accuracy and robustness of the target recognition and tracking system. PMID:28657609

Wireless Body Sensor Network for low-power motion-tolerant synchronized vital sign measurement.

PubMed

Volmer, Achim; Orglmeister, Reinhold

2008-01-01

Prophylaxis and rehabilitation of cardiovascular disease require the development of biosignal acquisition and processing devices that are capable of supporting patients in their everyday life. This paper presents a Body Sensor Network (BSN) for use in Personal Healthcare applications. It consists of miniaturized sensor modules for electrocardiogram (ECG), photoplethysmogram (PPG) and phonocardiography (PCG) which are wirelessly connected with a coordinator to collect the data. Each sensor module is combined with a tri-axis accelerometer for patient's posture and activity measurement. As it is possible to extract further information about the health state by fusioning data of different biosensors, the wireless link based on IEEE 802.15.4 was extended by a synchronisation mechanism enabling synchronous sampling of the individual sensors. An adaptive application of algorithms for signal pre-processing and analysis allows the reduction of the transferred data.

Trust metrics in information fusion

NASA Astrophysics Data System (ADS)

Blasch, Erik

2014-05-01

Trust is an important concept for machine intelligence and is not consistent across many applications. In this paper, we seek to understand trust from a variety of factors: humans, sensors, communications, intelligence processing algorithms and human-machine displays of information. In modeling the various aspects of trust, we provide an example from machine intelligence that supports the various attributes of measuring trust such as sensor accuracy, communication timeliness, machine processing confidence, and display throughput to convey the various attributes that support user acceptance of machine intelligence results. The example used is fusing video and text whereby an analyst needs trust information in the identified imagery track. We use the proportional conflict redistribution rule as an information fusion technique that handles conflicting data from trusted and mistrusted sources. The discussion of the many forms of trust explored in the paper seeks to provide a systems-level design perspective for information fusion trust quantification.

Decentralized system identification using stochastic subspace identification on wireless smart sensor networks

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.

Human Movement Recognition Based on the Stochastic Characterisation of Acceleration Data

PubMed Central

Munoz-Organero, Mario; Lotfi, Ahmad

2016-01-01

Human activity recognition algorithms based on information obtained from wearable sensors are successfully applied in detecting many basic activities. Identified activities with time-stationary features are characterised inside a predefined temporal window by using different machine learning algorithms on extracted features from the measured data. Better accuracy, precision and recall levels could be achieved by combining the information from different sensors. However, detecting short and sporadic human movements, gestures and actions is still a challenging task. In this paper, a novel algorithm to detect human basic movements from wearable measured data is proposed and evaluated. The proposed algorithm is designed to minimise computational requirements while achieving acceptable accuracy levels based on characterising some particular points in the temporal series obtained from a single sensor. The underlying idea is that this algorithm would be implemented in the sensor device in order to pre-process the sensed data stream before sending the information to a central point combining the information from different sensors to improve accuracy levels. Intra- and inter-person validation is used for two particular cases: single step detection and fall detection and classification using a single tri-axial accelerometer. Relevant results for the above cases and pertinent conclusions are also presented. PMID:27618063

Applying Sensor-Based Technology to Improve Construction Safety Management.

PubMed

Zhang, Mingyuan; Cao, Tianzhuo; Zhao, Xuefeng

2017-08-11

Construction sites are dynamic and complicated systems. The movement and interaction of people, goods and energy make construction safety management extremely difficult. Due to the ever-increasing amount of information, traditional construction safety management has operated under difficult circumstances. As an effective way to collect, identify and process information, sensor-based technology is deemed to provide new generation of methods for advancing construction safety management. It makes the real-time construction safety management with high efficiency and accuracy a reality and provides a solid foundation for facilitating its modernization, and informatization. Nowadays, various sensor-based technologies have been adopted for construction safety management, including locating sensor-based technology, vision-based sensing and wireless sensor networks. This paper provides a systematic and comprehensive review of previous studies in this field to acknowledge useful findings, identify the research gaps and point out future research directions.

A Bionic Polarization Navigation Sensor and Its Calibration Method

PubMed Central

Zhao, Huijie; Xu, Wujian

2016-01-01

The polarization patterns of skylight which arise due to the scattering of sunlight in the atmosphere can be used by many insects for deriving compass information. Inspired by insects’ polarized light compass, scientists have developed a new kind of navigation method. One of the key techniques in this method is the polarimetric sensor which is used to acquire direction information from skylight. In this paper, a polarization navigation sensor is proposed which imitates the working principles of the polarization vision systems of insects. We introduce the optical design and mathematical model of the sensor. In addition, a calibration method based on variable substitution and non-linear curve fitting is proposed. The results obtained from the outdoor experiments provide support for the feasibility and precision of the sensor. The sensor’s signal processing can be well described using our mathematical model. A relatively high degree of accuracy in polarization measurement can be obtained without any error compensation. PMID:27527171

Applying Sensor-Based Technology to Improve Construction Safety Management

PubMed Central

Zhang, Mingyuan; Cao, Tianzhuo; Zhao, Xuefeng

2017-01-01

Construction sites are dynamic and complicated systems. The movement and interaction of people, goods and energy make construction safety management extremely difficult. Due to the ever-increasing amount of information, traditional construction safety management has operated under difficult circumstances. As an effective way to collect, identify and process information, sensor-based technology is deemed to provide new generation of methods for advancing construction safety management. It makes the real-time construction safety management with high efficiency and accuracy a reality and provides a solid foundation for facilitating its modernization, and informatization. Nowadays, various sensor-based technologies have been adopted for construction safety management, including locating sensor-based technology, vision-based sensing and wireless sensor networks. This paper provides a systematic and comprehensive review of previous studies in this field to acknowledge useful findings, identify the research gaps and point out future research directions. PMID:28800061

Hierarchical adaptation scheme for multiagent data fusion and resource management in situation analysis

NASA Astrophysics Data System (ADS)

Benaskeur, Abder R.; Roy, Jean

2001-08-01

Sensor Management (SM) has to do with how to best manage, coordinate and organize the use of sensing resources in a manner that synergistically improves the process of data fusion. Based on the contextual information, SM develops options for collecting further information, allocates and directs the sensors towards the achievement of the mission goals and/or tunes the parameters for the realtime improvement of the effectiveness of the sensing process. Conscious of the important role that SM has to play in modern data fusion systems, we are currently studying advanced SM Concepts that would help increase the survivability of the current Halifax and Iroquois Class ships, as well as their possible future upgrades. For this purpose, a hierarchical scheme has been proposed for data fusion and resource management adaptation, based on the control theory and within the process refinement paradigm of the JDL data fusion model, and taking into account the multi-agent model put forward by the SASS Group for the situation analysis process. The novelty of this work lies in the unified framework that has been defined for tackling the adaptation of both the fusion process and the sensor/weapon management.

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

Real-Time Wireless Data Acquisition System

NASA Technical Reports Server (NTRS)

Valencia, Emilio J.; Perotti, Jose; Lucena, Angel; Mata, Carlos

2007-01-01

Current and future aerospace requirements demand the creation of a new breed of sensing devices, with emphasis on reduced weight, power consumption, and physical size. This new generation of sensors must possess a high degree of intelligence to provide critical data efficiently and in real-time. Intelligence will include self-calibration, self-health assessment, and pre-processing of raw data at the sensor level. Most of these features are already incorporated in the Wireless Sensors Network (SensorNet(TradeMark)), developed by the Instrumentation Group at Kennedy Space Center (KSC). A system based on the SensorNet(TradeMark) architecture consists of data collection point(s) called Central Stations (CS) and intelligent sensors called Remote Stations (RS) where one or more CSs can be accommodated depending on the specific application. The CS's major function is to establish communications with the Remote Stations and to poll each RS for data and health information. The CS also collects, stores and distributes these data to the appropriate systems requiring the information. The system has the ability to perform point-to-point, multi-point and relay mode communications with an autonomous self-diagnosis of each communications link. Upon detection of a communication failure, the system automatically reconfigures to establish new communication paths. These communication paths are automatically and autonomously selected as the best paths by the system based on the existing operating environment. The data acquisition system currently under development at KSC consists of the SensorNet(TradeMark) wireless sensors as the remote stations and the central station called the Radio Frequency Health Node (RFHN). The RFF1N is the central station which remotely communicates with the SensorNet(TradeMark) sensors to control them and to receive data. The system's salient feature is the ability to provide deterministic sensor data with accurate time stamps for both time critical and non-time critical applications. Current wireless standards such as Zigbee(TradeMark) and Bluetooth(Registered TradeMark) do not have these capabilities and can not meet the needs that are provided by the SensorNet technology. Additionally, the system has the ability to automatically reconfigure the wireless communication link to a secondary frequency if interference is encountered and can autonomously search for a sensor that was perceived to be lost using the relay capabilities of the sensors and the secondary frequency. The RFHN and the SensorNet designs are based on modular architectures that allow for future increases in capability and the ability to expand or upgrade with relative ease. The RFHN and SensorNet sensors .can also perform data processing which forms a distributed processing architecture allowing the system to pass along information rather than just sending "raw data points" to the next higher level system. With a relatively small size, weight and power consumption, this system has the potential for both spacecraft and aircraft applications as well as ground applications that require time critical data.

Numerical modelling of distributed vibration sensor based on phase-sensitive OTDR

NASA Astrophysics Data System (ADS)

Masoudi, A.; Newson, T. P.

2017-04-01

A Distributed Vibration Sensor Based on Phase-Sensitive OTDR is numerically modeled. The advantage of modeling the building blocks of the sensor individually and combining the blocks to analyse the behavior of the sensing system is discussed. It is shown that the numerical model can accurately imitate the response of the experimental setup to dynamic perturbations a signal processing procedure similar to that used to extract the phase information from sensing setup.

Sensor Systems for Space Life Sciences

NASA Technical Reports Server (NTRS)

Somps, Chris J.; Hines, John W.; Connolly, John P. (Technical Monitor)

1995-01-01

Sensors 2000! (S2K!) is a NASA Ames Research Center engineering initiative designed to provide biosensor and bio-instrumentation systems technology expertise to NASA's life sciences spaceflight programs. S2K! covers the full spectrum of sensor technology applications, ranging from spaceflight hardware design and fabrication to advanced technology development, transfer and commercialization. S2K! is currently developing sensor systems for space biomedical applications on BION (a Russian biosatellite focused on Rhesus Monkey physiology) and NEUROLAB (a Space Shuttle flight devoted to neuroscience). It's Advanced Technology Development-Biosensors (ATD-B) project focuses efforts in five principle areas: biotelemetry Systems, chemical and biological sensors, physiological sensors, advanced instrumentation architectures, and data and information management. Technologies already developed and tested included, application-specific sensors, preamplifier hybrids, modular programmable signal conditioners, power conditioning and distribution systems, and a fully implantable dual channel biotelemeter. Systems currently under development include a portable receiver system compatible with an off-the-shelf analog biotelemeter, a 4 channel digital biotelemetry system which monitors pH, a multichannel, g-processor based PCM biotelemetry system, and hand-held personal monitoring systems. S2K! technology easily lends itself to telescience and telemedicine applications as a front-end measurement and data acquisition device, suitable for obtaining and configuring physiological information, and processing that information under control from a remote location.

A Distributed Architecture for Tsunami Early Warning and Collaborative Decision-support in Crises

NASA Astrophysics Data System (ADS)

Moßgraber, J.; Middleton, S.; Hammitzsch, M.; Poslad, S.

2012-04-01

The presentation will describe work on the system architecture that is being developed in the EU FP7 project TRIDEC on "Collaborative, Complex and Critical Decision-Support in Evolving Crises". The challenges for a Tsunami Early Warning System (TEWS) are manifold and the success of a system depends crucially on the system's architecture. A modern warning system following a system-of-systems approach has to integrate various components and sub-systems such as different information sources, services and simulation systems. Furthermore, it has to take into account the distributed and collaborative nature of warning systems. In order to create an architecture that supports the whole spectrum of a modern, distributed and collaborative warning system one must deal with multiple challenges. Obviously, one cannot expect to tackle these challenges adequately with a monolithic system or with a single technology. Therefore, a system architecture providing the blueprints to implement the system-of-systems approach has to combine multiple technologies and architectural styles. At the bottom layer it has to reliably integrate a large set of conventional sensors, such as seismic sensors and sensor networks, buoys and tide gauges, and also innovative and unconventional sensors, such as streams of messages from social media services. At the top layer it has to support collaboration on high-level decision processes and facilitates information sharing between organizations. In between, the system has to process all data and integrate information on a semantic level in a timely manner. This complex communication follows an event-driven mechanism allowing events to be published, detected and consumed by various applications within the architecture. Therefore, at the upper layer the event-driven architecture (EDA) aspects are combined with principles of service-oriented architectures (SOA) using standards for communication and data exchange. The most prominent challenges on this layer include providing a framework for information integration on a syntactic and semantic level, leveraging distributed processing resources for a scalable data processing platform, and automating data processing and decision support workflows.

A highly scalable information system as extendable framework solution for medical R&D projects.

PubMed

Holzmüller-Laue, Silke; Göde, Bernd; Stoll, Regina; Thurow, Kerstin

2009-01-01

For research projects in preventive medicine a flexible information management is needed that offers a free planning and documentation of project specific examinations. The system should allow a simple, preferably automated data acquisition from several distributed sources (e.g., mobile sensors, stationary diagnostic systems, questionnaires, manual inputs) as well as an effective data management, data use and analysis. An information system fulfilling these requirements has been developed at the Center for Life Science Automation (celisca). This system combines data of multiple investigations and multiple devices and displays them on a single screen. The integration of mobile sensor systems for comfortable, location-independent capture of time-based physiological parameter and the possibility of observation of these measurements directly by this system allow new scenarios. The web-based information system presented in this paper is configurable by user interfaces. It covers medical process descriptions, operative process data visualizations, a user-friendly process data processing, modern online interfaces (data bases, web services, XML) as well as a comfortable support of extended data analysis with third-party applications.

Microelectromechanical Systems

NASA Technical Reports Server (NTRS)

Gabriel, Kaigham J.

1995-01-01

Micro-electromechanical systems (MEMS) is an enabling technology that merges computation and communication with sensing and actuation to change the way people and machines interact with the physical world. MEMS is a manufacturing technology that will impact widespread applications including: miniature inertial measurement measurement units for competent munitions and personal navigation; distributed unattended sensors; mass data storage devices; miniature analytical instruments; embedded pressure sensors; non-invasive biomedical sensors; fiber-optics components and networks; distributed aerodynamic control; and on-demand structural strength. The long term goal of ARPA's MEMS program is to merge information processing with sensing and actuation to realize new systems and strategies for both perceiving and controlling systems, processes, and the environment. The MEMS program has three major thrusts: advanced devices and processes, system design, and infrastructure.

Cluster Cooperation in Wireless-Powered Sensor Networks: Modeling and Performance Analysis.

PubMed

Zhang, Chao; Zhang, Pengcheng; Zhang, Weizhan

2017-09-27

A wireless-powered sensor network (WPSN) consisting of one hybrid access point (HAP), a near cluster and the corresponding far cluster is investigated in this paper. These sensors are wireless-powered and they transmit information by consuming the harvested energy from signal ejected by the HAP. Sensors are able to harvest energy as well as store the harvested energy. We propose that if sensors in near cluster do not have their own information to transmit, acting as relays, they can help the sensors in a far cluster to forward information to the HAP in an amplify-and-forward (AF) manner. We use a finite Markov chain to model the dynamic variation process of the relay battery, and give a general analyzing model for WPSN with cluster cooperation. Though the model, we deduce the closed-form expression for the outage probability as the metric of this network. Finally, simulation results validate the start point of designing this paper and correctness of theoretical analysis and show how parameters have an effect on system performance. Moreover, it is also known that the outage probability of sensors in far cluster can be drastically reduced without sacrificing the performance of sensors in near cluster if the transmit power of HAP is fairly high. Furthermore, in the aspect of outage performance of far cluster, the proposed scheme significantly outperforms the direct transmission scheme without cooperation.

Cluster Cooperation in Wireless-Powered Sensor Networks: Modeling and Performance Analysis

PubMed Central

Zhang, Chao; Zhang, Pengcheng; Zhang, Weizhan

2017-01-01

A wireless-powered sensor network (WPSN) consisting of one hybrid access point (HAP), a near cluster and the corresponding far cluster is investigated in this paper. These sensors are wireless-powered and they transmit information by consuming the harvested energy from signal ejected by the HAP. Sensors are able to harvest energy as well as store the harvested energy. We propose that if sensors in near cluster do not have their own information to transmit, acting as relays, they can help the sensors in a far cluster to forward information to the HAP in an amplify-and-forward (AF) manner. We use a finite Markov chain to model the dynamic variation process of the relay battery, and give a general analyzing model for WPSN with cluster cooperation. Though the model, we deduce the closed-form expression for the outage probability as the metric of this network. Finally, simulation results validate the start point of designing this paper and correctness of theoretical analysis and show how parameters have an effect on system performance. Moreover, it is also known that the outage probability of sensors in far cluster can be drastically reduced without sacrificing the performance of sensors in near cluster if the transmit power of HAP is fairly high. Furthermore, in the aspect of outage performance of far cluster, the proposed scheme significantly outperforms the direct transmission scheme without cooperation. PMID:28953231

Causal simulation and sensor planning in predictive monitoring

NASA Technical Reports Server (NTRS)

Doyle, Richard J.

1989-01-01

Two issues are addressed which arise in the task of detecting anomalous behavior in complex systems with numerous sensor channels: how to adjust alarm thresholds dynamically, within the changing operating context of the system, and how to utilize sensors selectively, so that nominal operation can be verified reliably without processing a prohibitive amount of sensor data. The approach involves simulation of a causal model of the system, which provides information on expected sensor values, and on dependencies between predicted events, useful in assessing the relative importance of events so that sensor resources can be allocated effectively. The potential applicability of this work to the execution monitoring of robot task plans is briefly discussed.

Revealing the properties of oils from their dissolved hydrocarbon compounds in water with an integrated sensor array system.

PubMed

Qi, Xiubin; Crooke, Emma; Ross, Andrew; Bastow, Trevor P; Stalvies, Charlotte

2011-09-21

This paper presents a system and method developed to identify a source oil's characteristic properties by testing the oil's dissolved components in water. Through close examination of the oil dissolution process in water, we hypothesise that when oil is in contact with water, the resulting oil-water extract, a complex hydrocarbon mixture, carries the signature property information of the parent oil. If the dominating differences in compositions between such extracts of different oils can be identified, this information could guide the selection of various sensors, capable of capturing such chemical variations. When used as an array, such a sensor system can be used to determine parent oil information from the oil-water extract. To test this hypothesis, 22 oils' water extracts were prepared and selected dominant hydrocarbons analyzed with Gas Chromatography-Mass Spectrometry (GC-MS); the subsequent Principal Component Analysis (PCA) indicates that the major difference between the extract solutions is the relative concentration between the volatile mono-aromatics and fluorescent polyaromatics. An integrated sensor array system that is composed of 3 volatile hydrocarbon sensors and 2 polyaromatic hydrocarbon sensors was built accordingly to capture the major and subtle differences of these extracts. It was tested by exposure to a total of 110 water extract solutions diluted from the 22 extracts. The sensor response data collected from the testing were processed with two multivariate analysis tools to reveal information retained in the response patterns of the arrayed sensors: by conducting PCA, we were able to demonstrate the ability to qualitatively identify and distinguish different oil samples from their sensor array response patterns. When a supervised PCA, Linear Discriminate Analysis (LDA), was applied, even quantitative classification can be achieved: the multivariate model generated from the LDA achieved 89.7% of successful classification of the type of the oil samples. By grouping the samples based on the level of viscosity and density we were able to reveal the correlation between the oil extracts' sensor array responses and their original oils' feature properties. The equipment and method developed in this study have promising potential to be readily applied in field studies and marine surveys for oil exploration or oil spill monitoring.

Advances in biologically inspired on/near sensor processing

NASA Astrophysics Data System (ADS)

McCarley, Paul L.

1999-07-01

As electro-optic sensors increase in size and frame rate, the data transfer and digital processing resource requirements also increase. In many missions, the spatial area of interest is but a small fraction of the available field of view. Choosing the right region of interest, however, is a challenge and still requires an enormous amount of downstream digital processing resources. In order to filter this ever-increasing amount of data, we look at how nature solves the problem. The Advanced Guidance Division of the Munitions Directorate, Air Force Research Laboratory at Elgin AFB, Florida, has been pursuing research in the are of advanced sensor and image processing concepts based on biologically inspired sensory information processing. A summary of two 'neuromorphic' processing efforts will be presented along with a seeker system concept utilizing this innovative technology. The Neuroseek program is developing a 256 X 256 2-color dual band IRFPA coupled to an optimized silicon CMOS read-out and processing integrated circuit that provides simultaneous full-frame imaging in MWIR/LWIR wavebands along with built-in biologically inspired sensor image processing functions. Concepts and requirements for future such efforts will also be discussed.

Large Scale Environmental Monitoring through Integration of Sensor and Mesh Networks.

PubMed

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.

An Efficient Location Verification Scheme for Static Wireless Sensor Networks.

PubMed

Kim, In-Hwan; Kim, Bo-Sung; Song, JooSeok

2017-01-24

In wireless sensor networks (WSNs), the accuracy of location information is vital to support many interesting applications. Unfortunately, sensors have difficulty in estimating their location when malicious sensors attack the location estimation process. Even though secure localization schemes have been proposed to protect location estimation process from attacks, they are not enough to eliminate the wrong location estimations in some situations. The location verification can be the solution to the situations or be the second-line defense. The problem of most of the location verifications is the explicit involvement of many sensors in the verification process and requirements, such as special hardware, a dedicated verifier and the trusted third party, which causes more communication and computation overhead. In this paper, we propose an efficient location verification scheme for static WSN called mutually-shared region-based location verification (MSRLV), which reduces those overheads by utilizing the implicit involvement of sensors and eliminating several requirements. In order to achieve this, we use the mutually-shared region between location claimant and verifier for the location verification. The analysis shows that MSRLV reduces communication overhead by 77% and computation overhead by 92% on average, when compared with the other location verification schemes, in a single sensor verification. In addition, simulation results for the verification of the whole network show that MSRLV can detect the malicious sensors by over 90% when sensors in the network have five or more neighbors.

An Efficient Location Verification Scheme for Static Wireless Sensor Networks

PubMed Central

Kim, In-hwan; Kim, Bo-sung; Song, JooSeok

2017-01-01

In wireless sensor networks (WSNs), the accuracy of location information is vital to support many interesting applications. Unfortunately, sensors have difficulty in estimating their location when malicious sensors attack the location estimation process. Even though secure localization schemes have been proposed to protect location estimation process from attacks, they are not enough to eliminate the wrong location estimations in some situations. The location verification can be the solution to the situations or be the second-line defense. The problem of most of the location verifications is the explicit involvement of many sensors in the verification process and requirements, such as special hardware, a dedicated verifier and the trusted third party, which causes more communication and computation overhead. In this paper, we propose an efficient location verification scheme for static WSN called mutually-shared region-based location verification (MSRLV), which reduces those overheads by utilizing the implicit involvement of sensors and eliminating several requirements. In order to achieve this, we use the mutually-shared region between location claimant and verifier for the location verification. The analysis shows that MSRLV reduces communication overhead by 77% and computation overhead by 92% on average, when compared with the other location verification schemes, in a single sensor verification. In addition, simulation results for the verification of the whole network show that MSRLV can detect the malicious sensors by over 90% when sensors in the network have five or more neighbors. PMID:28125007

A Model for Field Deployment of Wireless Sensor Networks (WSNs) within the Domain of Microclimate Habitat Monitoring

ERIC Educational Resources Information Center

Sanborn, Mark

2011-01-01

Wireless sensor networks (WSNs) represent a class of miniaturized information systems designed to monitor physical environments. These smart monitoring systems form collaborative networks utilizing autonomous sensing, data-collection, and processing to provide real-time analytics of observed environments. As a fundamental research area in…

Energy efficient wireless sensor network for structural health monitoring using distributed embedded piezoelectric transducers

NASA Astrophysics Data System (ADS)

Li, Peng; Olmi, Claudio; Song, Gangbing

2010-04-01

Piezoceramic based transducers are widely researched and used for structural health monitoring (SHM) systems due to the piezoceramic material's inherent advantage of dual sensing and actuation. Wireless sensor network (WSN) technology benefits from advances made in piezoceramic based structural health monitoring systems, allowing easy and flexible installation, low system cost, and increased robustness over wired system. However, piezoceramic wireless SHM systems still faces some drawbacks, one of these is that the piezoceramic based SHM systems require relatively high computational capabilities to calculate damage information, however, battery powered WSN sensor nodes have strict power consumption limitation and hence limited computational power. On the other hand, commonly used centralized processing networks require wireless sensors to transmit all data back to the network coordinator for analysis. This signal processing procedure can be problematic for piezoceramic based SHM applications as it is neither energy efficient nor robust. In this paper, we aim to solve these problems with a distributed wireless sensor network for piezoceramic base structural health monitoring systems. Three important issues: power system, waking up from sleep impact detection, and local data processing, are addressed to reach optimized energy efficiency. Instead of sweep sine excitation that was used in the early research, several sine frequencies were used in sequence to excite the concrete structure. The wireless sensors record the sine excitations and compute the time domain energy for each sine frequency locally to detect the energy change. By comparing the data of the damaged concrete frame with the healthy data, we are able to find out the damage information of the concrete frame. A relative powerful wireless microcontroller was used to carry out the sampling and distributed data processing in real-time. The distributed wireless network dramatically reduced the data transmission between wireless sensor and the wireless coordinator, which in turn reduced the power consumption of the overall system.

EDITORIAL: Industrial Process Tomography

NASA Astrophysics Data System (ADS)

Anton Johansen, Geir; Wang, Mi

2008-09-01

There has been tremendous development within measurement science and technology over the past couple of decades. New sensor technologies and compact versatile signal recovery electronics are continuously expanding the limits of what can be measured and the accuracy with which this can be done. Miniaturization of sensors and the use of nanotechnology push these limits further. Also, thanks to powerful and cost-effective computer systems, sophisticated measurement and reconstruction algorithms previously only accessible in advanced laboratories are now available for in situ online measurement systems. The process industries increasingly require more process-related information, motivated by key issues such as improved process control, process utilization and process yields, ultimately driven by cost-effectiveness, quality assurance, environmental and safety demands. Industrial process tomography methods have taken advantage of the general progress in measurement science, and aim at providing more information, both quantitatively and qualitatively, on multiphase systems and their dynamics. The typical approach for such systems has been to carry out one local or bulk measurement and assume that this is representative of the whole system. In some cases, this is sufficient. However, there are many complex systems where the component distribution varies continuously and often unpredictably in space and time. The foundation of industrial tomography is to conduct several measurements around the periphery of a multiphase process, and use these measurements to unravel the cross-sectional distribution of the process components in time and space. This information is used in the design and optimization of industrial processes and process equipment, and also to improve the accuracy of multiphase system measurements in general. In this issue we are proud to present a selection of the 145 papers presented at the 5th World Congress on Industrial Process Tomography in Bergen, September 2007. Interestingly, x-ray technologies, one of the first imaging modalities available, keep on moving the limits on both spatial and temporal measurement resolution; experimental results of less than 100 nm and several thousand frames/s are reported, respectively. Important progress is demonstrated in research and development on sensor technologies and algorithms for data processing and image reconstruction, including unconventional sensor design and adaptation of the sensors to the application in question. The number of applications to which tomographic methods are applied is steadily increasing, and results obtained in a representative selection of applications are included. As guest editors we would like express our appreciation and thanks to all authors who have contributed and to IOP staff for excellent collaboration in the process of finalizing this special feature.

Information-based self-organization of sensor nodes of a sensor network

DOEpatents

Ko, Teresa H [Castro Valley, CA; Berry, Nina M [Tracy, CA

2011-09-20

A sensor node detects a plurality of information-based events. The sensor node determines whether at least one other sensor node is an information neighbor of the sensor node based on at least a portion of the plurality of information-based events. The information neighbor has an overlapping field of view with the sensor node. The sensor node sends at least one communication to the at least one other sensor node that is an information neighbor of the sensor node in response to at least one information-based event of the plurality of information-based events.

A Prototype Land Information Sensor Web: Design, Implementation and Implication for the SMAP Mission

NASA Astrophysics Data System (ADS)

Su, H.; Houser, P.; Tian, Y.; Geiger, J. K.; Kumar, S. V.; Gates, L.

2009-12-01

Land Surface Model (LSM) predictions are regular in time and space, but these predictions are influenced by errors in model structure, input variables, parameters and inadequate treatment of sub-grid scale spatial variability. Consequently, LSM predictions are significantly improved through observation constraints made in a data assimilation framework. Several multi-sensor satellites are currently operating which provide multiple global observations of the land surface, and its related near-atmospheric properties. However, these observations are not optimal for addressing current and future land surface environmental problems. To meet future earth system science challenges, NASA will develop constellations of smart satellites in sensor web configurations which provide timely on-demand data and analysis to users, and can be reconfigured based on the changing needs of science and available technology. A sensor web is more than a collection of satellite sensors. That means a sensor web is a system composed of multiple platforms interconnected by a communication network for the purpose of performing specific observations and processing data required to support specific science goals. Sensor webs can eclipse the value of disparate sensor components by reducing response time and increasing scientific value, especially when the two-way interaction between the model and the sensor web is enabled. The study of a prototype Land Information Sensor Web (LISW) is sponsored by NASA, trying to integrate the Land Information System (LIS) in a sensor web framework which allows for optimal 2-way information flow that enhances land surface modeling using sensor web observations, and in turn allows sensor web reconfiguration to minimize overall system uncertainty. This prototype is based on a simulated interactive sensor web, which is then used to exercise and optimize the sensor web modeling interfaces. The Land Information Sensor Web Service-Oriented Architecture (LISW-SOA) has been developed and it is the very first sensor web framework developed especially for the land surface studies. Synthetic experiments based on the LISW-SOA and the virtual sensor web provide a controlled environment in which to examine the end-to-end performance of the prototype, the impact of various sensor web design trade-offs and the eventual value of sensor webs for a particular prediction or decision support. In this paper, the design, implementation of the LISW-SOA and the implication for the Soil Moisture Active and Passive (SMAP) mission is presented. Particular attention is focused on examining the relationship between the economic investment on a sensor web (space and air borne, ground based) and the accuracy of the model predicted soil moisture, which can be achieved by using such sensor observations. The Study of Virtual Land Information Sensor Web (LISW) is expected to provide some necessary a priori knowledge for designing and deploying the next generation Global Earth Observing System of systems (GEOSS).

Cochlea-inspired sensing node for compressive sensing

NASA Astrophysics Data System (ADS)

Peckens, Courtney A.; Lynch, Jerome P.

2013-04-01

While sensing technologies for structural monitoring applications have made significant advances over the last several decades, there is still room for improvement in terms of computational efficiency, as well as overall energy consumption. The biological nervous system can offer a potential solution to address these current deficiencies. The nervous system is capable of sensing and aggregating information about the external environment through very crude processing units known as neurons. Neurons effectively communicate in an extremely condensed format by encoding information into binary electrical spike trains, thereby reducing the amount of raw information sent throughout a neural network. Due to its unique signal processing capabilities, the mammalian cochlea and its interaction with the biological nervous system is of particular interest for devising compressive sensing strategies for dynamic engineered systems. The cochlea uses a novel method of place theory and frequency decomposition, thereby allowing for rapid signal processing within the nervous system. In this study, a low-power sensing node is proposed that draws inspiration from the mechanisms employed by the cochlea and the biological nervous system. As such, the sensor is able to perceive and transmit a compressed representation of the external stimulus with minimal distortion. Each sensor represents a basic building block, with function similar to the neuron, and can form a network with other sensors, thus enabling a system that can convey input stimulus in an extremely condensed format. The proposed sensor is validated through a structural monitoring application of a single degree of freedom structure excited by seismic ground motion.

An energy-efficient and secure hybrid algorithm for wireless sensor networks using a mobile data collector

NASA Astrophysics Data System (ADS)

Dayananda, Karanam Ravichandran; Straub, Jeremy

2017-05-01

This paper proposes a new hybrid algorithm for security, which incorporates both distributed and hierarchal approaches. It uses a mobile data collector (MDC) to collect information in order to save energy of sensor nodes in a wireless sensor network (WSN) as, in most networks, these sensor nodes have limited energy. Wireless sensor networks are prone to security problems because, among other things, it is possible to use a rogue sensor node to eavesdrop on or alter the information being transmitted. To prevent this, this paper introduces a security algorithm for MDC-based WSNs. A key use of this algorithm is to protect the confidentiality of the information sent by the sensor nodes. The sensor nodes are deployed in a random fashion and form group structures called clusters. Each cluster has a cluster head. The cluster head collects data from the other nodes using the time-division multiple access protocol. The sensor nodes send their data to the cluster head for transmission to the base station node for further processing. The MDC acts as an intermediate node between the cluster head and base station. The MDC, using its dynamic acyclic graph path, collects the data from the cluster head and sends it to base station. This approach is useful for applications including warfighting, intelligent building and medicine. To assess the proposed system, the paper presents a comparison of its performance with other approaches and algorithms that can be used for similar purposes.

Barrow real-time sea ice mass balance data: ingestion, processing, dissemination and archival of multi-sensor data

NASA Astrophysics Data System (ADS)

Grimes, J.; Mahoney, A. R.; Heinrichs, T. A.; Eicken, H.

2012-12-01

Sensor data can be highly variable in nature and also varied depending on the physical quantity being observed, sensor hardware and sampling parameters. The sea ice mass balance site (MBS) operated in Barrow by the University of Alaska Fairbanks (http://seaice.alaska.edu/gi/observatories/barrow_sealevel) is a multisensor platform consisting of a thermistor string, air and water temperature sensors, acoustic altimeters above and below the ice and a humidity sensor. Each sensor has a unique specification and configuration. The data from multiple sensors are combined to generate sea ice data products. For example, ice thickness is calculated from the positions of the upper and lower ice surfaces, which are determined using data from downward-looking and upward-looking acoustic altimeters above and below the ice, respectively. As a data clearinghouse, the Geographic Information Network of Alaska (GINA) processes real time data from many sources, including the Barrow MBS. Doing so requires a system that is easy to use, yet also offers the flexibility to handle data from multisensor observing platforms. In the case of the Barrow MBS, the metadata system needs to accommodate the addition of new and retirement of old sensors from year to year as well as instrument configuration changes caused by, for example, spring melt or inquisitive polar bears. We also require ease of use for both administrators and end users. Here we present the data and processing steps of using sensor data system powered by the NoSQL storage engine, MongoDB. The system has been developed to ingest, process, disseminate and archive data from the Barrow MBS. Storing sensor data in a generalized format, from many different sources, is a challenging task, especially for traditional SQL databases with a set schema. MongoDB is a NoSQL (not only SQL) database that does not require a fixed schema. There are several advantages using this model over the traditional relational database management system (RDBMS) model databases. The lack of a required schema allows flexibility in how the data can be ingested into the database. For example, MongoDB imposes no restrictions on field names. For researchers using the system, this means that the name they have chosen for the sensor is carried through the database, any processing, and to the final output helping to preserve data integrity. Also, MongoDB allows the data to be pushed to it dynamically meaning that field attributes can be defined at the point of ingestion. This allows any sensor data to be ingested as a document and for this functionality to be transferred to the user interface, allowing greater adaptability to different use-case scenarios. In presenting the MondoDB data system being developed for the Barrow MBS, we demonstrate the versatility of this approach and its suitability as the foundation of a Barrow node of the Arctic Observing Network. Authors Jason Grimes - Geographic Information Network of Alaska - jason@gina.alaska.edu Andy Mahony - Geophysical Institute - mahoney@gi.alaska.edu Hajo Eiken - Geophysical Institute - Hajo.Eicken@gi.alaska.edu Tom Heinrichs - Geographic Information Network of Alaska - Tom.Heinrichs@alaska.edu

Fusion of 3D laser scanner and depth images for obstacle recognition in mobile applications

NASA Astrophysics Data System (ADS)

Budzan, Sebastian; Kasprzyk, Jerzy

2016-02-01

The problem of obstacle detection and recognition or, generally, scene mapping is one of the most investigated problems in computer vision, especially in mobile applications. In this paper a fused optical system using depth information with color images gathered from the Microsoft Kinect sensor and 3D laser range scanner data is proposed for obstacle detection and ground estimation in real-time mobile systems. The algorithm consists of feature extraction in the laser range images, processing of the depth information from the Kinect sensor, fusion of the sensor information, and classification of the data into two separate categories: road and obstacle. Exemplary results are presented and it is shown that fusion of information gathered from different sources increases the effectiveness of the obstacle detection in different scenarios, and it can be used successfully for road surface mapping.

Smart Sensors' Role in Integrated System Health Management

NASA Technical Reports Server (NTRS)

Perotti, Jose M.; Mata, Carlos

2005-01-01

During the last decade, there has been a major effort in the aerospace industry to reduce the cost per pond of payload and become competitive in the international market. Competition from Europe, Japan, and China has reduced this cost to almost a third from 1990 to 2000. This cost has leveled in recent years to an average price of around $12,000/pound of payload. One of NASA's goals is to promote the development of technologies to reduce this cost by a factor of 10 or more Exploration of space, specially manned exploration missions, involves very complex launch and flight vehicles, associated ground support systems, and extensive human support during all phases of the mission. When considering the Space Shuttle Program, we can see that vehicle and ground support systems' processing, operation, and maintenance represent a large percentage of the program cost and time. Reducing operating, processing and maintenance costs will greatly reduce the cost of Exploration programs. The Integrated System Health Management (ISHM) concept is one of the technologies that will help reduce these operating, processing and maintenance costs. ISHM is an integrated health monitoring system applicable to both flight and ground systems. It automatically and autonomously acquires information from sensors and actuators and processes that information using the ISHM-embedded knowledge. As a result, it establishes the health of the system based on the acquired information and its prior knowledge. When this concept is fully implemented, ISHM systems shall be able to perform failure prediction and remediation before actual hard failures occurs, preventing its costly consequences. Data sources, sensors, and their associated data acquisition systems, constitute the foundation of the system. A smart sensing architecture is required to support the acquisition of reliable, high quality data, required by the ISHM. A thorough definition of the smart sensor architectures, their embedded diagnostic agents, and communication protocols need to be established and standardized to allow the embedding and exchange of health information among sensors and ISHM. This workshop is aimed to foster the exchange of ideas and lessons learned between government, industry and academia to aid in the establishment of ISHM (and smart sensors) standards and guidelines as well as to identify present technology gaps that will have to be overcome to successfully achieve this goal.

Ground Penetrating Radar as a Contextual Sensor for Multi-Sensor Radiological Characterisation

PubMed Central

Ukaegbu, Ikechukwu K.; Gamage, Kelum A. A.

2017-01-01

Radioactive sources exist in environments or contexts that influence how they are detected and localised. For instance, the context of a moving source is different from a stationary source because of the effects of motion. The need to incorporate this contextual information in the radiation detection and localisation process has necessitated the integration of radiological and contextual sensors. The benefits of the successful integration of both types of sensors is well known and widely reported in fields such as medical imaging. However, the integration of both types of sensors has also led to innovative solutions to challenges in characterising radioactive sources in non-medical applications. This paper presents a review of such recent applications. It also identifies that these applications mostly use visual sensors as contextual sensors for characterising radiation sources. However, visual sensors cannot retrieve contextual information about radioactive wastes located in opaque environments encountered at nuclear sites, e.g., underground contamination. Consequently, this paper also examines ground-penetrating radar (GPR) as a contextual sensor for characterising this category of wastes and proposes several ways of integrating data from GPR and radiological sensors. Finally, it demonstrates combined GPR and radiation imaging for three-dimensional localisation of contamination in underground pipes using radiation transport and GPR simulations. PMID:28387706

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

Mou, J.I.; King, C.

The focus of this study is to develop a sensor fused process modeling and control methodology to model, assess, and then enhance the performance of a hexapod machine for precision product realization. Deterministic modeling technique was used to derive models for machine performance assessment and enhancement. Sensor fusion methodology was adopted to identify the parameters of the derived models. Empirical models and computational algorithms were also derived and implemented to model, assess, and then enhance the machine performance. The developed sensor fusion algorithms can be implemented on a PC-based open architecture controller to receive information from various sensors, assess themore » status of the process, determine the proper action, and deliver the command to actuators for task execution. This will enhance a hexapod machine`s capability to produce workpieces within the imposed dimensional tolerances.« less

A hybrid artificial neural network as a software sensor for optimal control of a wastewater treatment process.

PubMed

Choi, D J; Park, H

2001-11-01

For control and automation of biological treatment processes, lack of reliable on-line sensors to measure water quality parameters is one of the most important problems to overcome. Many parameters cannot be measured directly with on-line sensors. The accuracy of existing hardware sensors is also not sufficient and maintenance problems such as electrode fouling often cause trouble. This paper deals with the development of software sensor techniques that estimate the target water quality parameter from other parameters using the correlation between water quality parameters. We focus our attention on the preprocessing of noisy data and the selection of the best model feasible to the situation. Problems of existing approaches are also discussed. We propose a hybrid neural network as a software sensor inferring wastewater quality parameter. Multivariate regression, artificial neural networks (ANN), and a hybrid technique that combines principal component analysis as a preprocessing stage are applied to data from industrial wastewater processes. The hybrid ANN technique shows an enhancement of prediction capability and reduces the overfitting problem of neural networks. The result shows that the hybrid ANN technique can be used to extract information from noisy data and to describe the nonlinearity of complex wastewater treatment processes.

35-GHz radar sensor for automotive collision avoidance

NASA Astrophysics Data System (ADS)

Zhang, Jun

1999-07-01

This paper describes the development of a radar sensor system used for automotive collision avoidance. Because the heavy truck may have great larger radar cross section than a motorcyclist has, the radar receiver may have a large dynamic range. And multi-targets at different speed may confuse the echo spectrum causing the ambiguity between range and speed of target. To get more information about target and background and to adapt to the large dynamic range and multi-targets, a frequency modulated and pseudo- random binary sequences phase modulated continuous wave radar system is described. The analysis of this double- modulation system is given. A high-speed signal processing and data processing component are used to process and combine the data and information from echo at different direction and at every moment.

PTC and Partner Products in the Creation of a Hurricane Wind Sensor

NASA Technical Reports Server (NTRS)

Randazzo, John; Voska, N. (Technical Monitor)

2002-01-01

This viewgraph presentation provides information on the development of a wind sensor for use during hurricanes. The objectives of this presentation are: (1) Educate the user unfamiliar with the modules as to what is available/lacking; (2) Share where some changes could be made; (3) Look at alternative approaches made possible by new releases/modules; (4) Use feedback to improve processes/approaches. The current pad wind sensors are cup-and-vane type anemometers.

Multisensor Fusion for Change Detection

NASA Astrophysics Data System (ADS)

Schenk, T.; Csatho, B.

2005-12-01

Combining sensors that record different properties of a 3-D scene leads to complementary and redundant information. If fused properly, a more robust and complete scene description becomes available. Moreover, fusion facilitates automatic procedures for object reconstruction and modeling. For example, aerial imaging sensors, hyperspectral scanning systems, and airborne laser scanning systems generate complementary data. We describe how data from these sensors can be fused for such diverse applications as mapping surface erosion and landslides, reconstructing urban scenes, monitoring urban land use and urban sprawl, and deriving velocities and surface changes of glaciers and ice sheets. An absolute prerequisite for successful fusion is a rigorous co-registration of the sensors involved. We establish a common 3-D reference frame by using sensor invariant features. Such features are caused by the same object space phenomena and are extracted in multiple steps from the individual sensors. After extracting, segmenting and grouping the features into more abstract entities, we discuss ways on how to automatically establish correspondences. This is followed by a brief description of rigorous mathematical models suitable to deal with linear and area features. In contrast to traditional, point-based registration methods, lineal and areal features lend themselves to a more robust and more accurate registration. More important, the chances to automate the registration process increases significantly. The result of the co-registration of the sensors is a unique transformation between the individual sensors and the object space. This makes spatial reasoning of extracted information more versatile; reasoning can be performed in sensor space or in 3-D space where domain knowledge about features and objects constrains reasoning processes, reduces the search space, and helps to make the problem well-posed. We demonstrate the feasibility of the proposed multisensor fusion approach with detecting surface elevation changes on the Byrd Glacier, Antarctica, with aerial imagery from 1980s and ICESat laser altimetry data from 2003-05. Change detection from such disparate data sets is an intricate fusion problem, beginning with sensor alignment, and on to reasoning with spatial information as to where changes occurred and to what extent.

Embedded Acoustic Sensor Array for Engine Fan Noise Source Diagnostic Test: Feasibility of Noise Telemetry via Wireless Smart Sensors

NASA Technical Reports Server (NTRS)

Zaman, Afroz; Bauch, Matthew; Raible, Daniel

2011-01-01

Aircraft engines have evolved into a highly complex system to meet ever-increasing demands. The evolution of engine technologies has primarily been driven by fuel efficiency, reliability, as well as engine noise concerns. One of the sources of engine noise is pressure fluctuations that are induced on the stator vanes. These local pressure fluctuations, once produced, propagate and coalesce with the pressure waves originating elsewhere on the stator to form a spinning pressure pattern. Depending on the duct geometry, air flow, and frequency of fluctuations, these spinning pressure patterns are self-sustaining and result in noise which eventually radiate to the far-field from engine. To investigate the nature of vane pressure fluctuations and the resulting engine noise, unsteady pressure signatures from an array of embedded acoustic sensors are recorded as a part of vane noise source diagnostics. Output time signatures from these sensors are routed to a control and data processing station adding complexity to the system and cable loss to the measured signal. "Smart" wireless sensors have data processing capability at the sensor locations which further increases the potential of wireless sensors. Smart sensors can process measured data locally and transmit only the important information through wireless communication. The aim of this wireless noise telemetry task was to demonstrate a single acoustic sensor wireless link for unsteady pressure measurement, and thus, establish the feasibility of distributed smart sensors scheme for aircraft engine vane surface unsteady pressure data transmission and characterization.

Design of smart home sensor visualizations for older adults.

PubMed

Le, Thai; Reeder, Blaine; Chung, Jane; Thompson, Hilaire; Demiris, George

2014-01-01

Smart home sensor systems provide a valuable opportunity to continuously and unobtrusively monitor older adult wellness. However, the density of sensor data can be challenging to visualize, especially for an older adult consumer with distinct user needs. We describe the design of sensor visualizations informed by interviews with older adults. The goal of the visualizations is to present sensor activity data to an older adult consumer audience that supports both longitudinal detection of trends and on-demand display of activity details for any chosen day. The design process is grounded through participatory design with older adult interviews during a six-month pilot sensor study. Through a secondary analysis of interviews, we identified the visualization needs of older adults. We incorporated these needs with cognitive perceptual visualization guidelines and the emotional design principles of Norman to develop sensor visualizations. We present a design of sensor visualization that integrate both temporal and spatial components of information. The visualization supports longitudinal detection of trends while allowing the viewer to view activity within a specific date. Appropriately designed visualizations for older adults not only provide insight into health and wellness, but also are a valuable resource to promote engagement within care.

Design of smart home sensor visualizations for older adults.

PubMed

Le, Thai; Reeder, Blaine; Chung, Jane; Thompson, Hilaire; Demiris, George

2014-07-24

Smart home sensor systems provide a valuable opportunity to continuously and unobtrusively monitor older adult wellness. However, the density of sensor data can be challenging to visualize, especially for an older adult consumer with distinct user needs. We describe the design of sensor visualizations informed by interviews with older adults. The goal of the visualizations is to present sensor activity data to an older adult consumer audience that supports both longitudinal detection of trends and on-demand display of activity details for any chosen day. The design process is grounded through participatory design with older adult interviews during a six-month pilot sensor study. Through a secondary analysis of interviews, we identified the visualization needs of older adults. We incorporated these needs with cognitive perceptual visualization guidelines and the emotional design principles of Norman to develop sensor visualizations. We present a design of sensor visualization that integrate both temporal and spatial components of information. The visualization supports longitudinal detection of trends while allowing the viewer to view activity within a specific date.CONCLUSIONS: Appropriately designed visualizations for older adults not only provide insight into health and wellness, but also are a valuable resource to promote engagement within care.

Social Media in Crisis Management and Forensic Disaster Analysis

NASA Astrophysics Data System (ADS)

Dittrich, André; Lucas, Christian

2014-05-01

Today, modern sensors or sensor networks provide good quality measurements for the observation of large-scale emergencies as a result of natural disasters. Mostly however, only at certain points in their respective locations and for a very limited number of measurement parameters (e.g. seismograph) and not over the entire course of a disaster event. The proliferation of different social media application (e.g. Twitter, Facebook, Google+, etc.), yields the possibility to use the resulting data as a free and fast supplement or complement to traditional monitoring techniques. In particular, these new channels can serve for rapid detection, for information gathering for emergency protection and for information dissemination. Thus, each user of these networks represents a so-called virtual sensor ('social sensor'), whose eyewitness account can be important for understanding the situation on the ground. The advantages of these social sensors are the high mobility, the versatility of the parameters that can be captured (text, images, videos, etc.) as well as the rapid spread of information. Due to the subjective characteristics however, the data often show different quality and quantity. Against this background, it is essential for an application in crisis management to reasonably (pre-)process the data from social media. Hence, fully-automated processes are used which adequately filter and structure the enormous amount of information and associate it with an event, respectively, a geographic location. This is done through statistical monitoring of the volume of messages (Twitter) in different geographic regions of the world. In combination with a frequency analysis with respect to disaster-relevant terms (in 43 languages), thematic as well as spatio-temporal clustering, an initial assessment regarding the severity and extent of the detected event, its classification and (spatio-temporal) localization can be achieved. This detection in real time (2-5 minutes) thus allows gathering first responder reports or eyewitness reports, which can provide important information for a first situation analysis for the various officials and volunteers, especially in case of large-scale emergencies. Eventually, this can be used in combination with conventional sensors and information sources to conduct a detailed forensic disaster analysis of an event.

Smart Toys Designed for Detecting Developmental Delays

PubMed Central

Rivera, Diego; García, Antonio; Alarcos, Bernardo; Velasco, Juan R.; Ortega, José Eugenio; Martínez-Yelmo, Isaías

2016-01-01

In this paper, we describe the design considerations and implementation of a smart toy system, a technology for supporting the automatic recording and analysis for detecting developmental delays recognition when children play using the smart toy. To achieve this goal, we take advantage of the current commercial sensor features (reliability, low consumption, easy integration, etc.) to develop a series of sensor-based low-cost devices. Specifically, our prototype system consists of a tower of cubes augmented with wireless sensing capabilities and a mobile computing platform that collect the information sent from the cubes allowing the later analysis by childhood development professionals in order to verify a normal behaviour or to detect a potential disorder. This paper presents the requirements of the toy and discusses our choices in toy design, technology used, selected sensors, process to gather data from the sensors and generate information that will help in the decision-making and communication of the information to the collector system. In addition, we also describe the play activities the system supports. PMID:27879626

Smart Toys Designed for Detecting Developmental Delays.

PubMed

Rivera, Diego; García, Antonio; Alarcos, Bernardo; Velasco, Juan R; Ortega, José Eugenio; Martínez-Yelmo, Isaías

2016-11-20

In this paper, we describe the design considerations and implementation of a smart toy system, a technology for supporting the automatic recording and analysis for detecting developmental delays recognition when children play using the smart toy. To achieve this goal, we take advantage of the current commercial sensor features (reliability, low consumption, easy integration, etc.) to develop a series of sensor-based low-cost devices. Specifically, our prototype system consists of a tower of cubes augmented with wireless sensing capabilities and a mobile computing platform that collect the information sent from the cubes allowing the later analysis by childhood development professionals in order to verify a normal behaviour or to detect a potential disorder. This paper presents the requirements of the toy and discusses our choices in toy design, technology used, selected sensors, process to gather data from the sensors and generate information that will help in the decision-making and communication of the information to the collector system. In addition, we also describe the play activities the system supports.

A three-dimensional laser vibration measurement technology realized on five laser beam and its calibration

NASA Astrophysics Data System (ADS)

Li, Lu-Ke; Zhang, Shen-Feng

2018-03-01

Put forward a kind of three-dimensional vibration information technology of vibrating object by the mean of five laser beam of He-Ne laser, and with the help of three-way sensor, measure the three-dimensional laser vibration developed by above mentioned technology. The technology based on the Doppler principle of interference and signal demodulation technology, get the vibration information of the object, through the algorithm processing, extract the three-dimensional vibration information of space objects, and can achieve the function of angle calibration of five beam in the space, which avoid the effects of the mechanical installation error, greatly improve the accuracy of measurement. With the help of a & B K4527 contact three axis sensor, measure and calibrate three-dimensional laser vibrometer, which ensure the accuracy of the measurement data. Summarize the advantages and disadvantages of contact and non-contact sensor, and analysis the future development trends of the sensor industry.

MASM: a market architecture for sensor management in distributed sensor networks

NASA Astrophysics Data System (ADS)

Viswanath, Avasarala; Mullen, Tracy; Hall, David; Garga, Amulya

2005-03-01

Rapid developments in sensor technology and its applications have energized research efforts towards devising a firm theoretical foundation for sensor management. Ubiquitous sensing, wide bandwidth communications and distributed processing provide both opportunities and challenges for sensor and process control and optimization. Traditional optimization techniques do not have the ability to simultaneously consider the wildly non-commensurate measures involved in sensor management in a single optimization routine. Market-oriented programming provides a valuable and principled paradigm to designing systems to solve this dynamic and distributed resource allocation problem. We have modeled the sensor management scenario as a competitive market, wherein the sensor manager holds a combinatorial auction to sell the various items produced by the sensors and the communication channels. However, standard auction mechanisms have been found not to be directly applicable to the sensor management domain. For this purpose, we have developed a specialized market architecture MASM (Market architecture for Sensor Management). In MASM, the mission manager is responsible for deciding task allocations to the consumers and their corresponding budgets and the sensor manager is responsible for resource allocation to the various consumers. In addition to having a modified combinatorial winner determination algorithm, MASM has specialized sensor network modules that address commensurability issues between consumers and producers in the sensor network domain. A preliminary multi-sensor, multi-target simulation environment has been implemented to test the performance of the proposed system. MASM outperformed the information theoretic sensor manager in meeting the mission objectives in the simulation experiments.

Information adaptive system of NEEDS. [of NASA End to End Data System

NASA Technical Reports Server (NTRS)

Howle, W. M., Jr.; Kelly, W. L.

1979-01-01

The NASA End-to-End Data System (NEEDS) program was initiated by NASA to improve significantly the state of the art in acquisition, processing, and distribution of space-acquired data for the mid-1980s and beyond. The information adaptive system (IAS) is a program element under NEEDS Phase II which addresses sensor specific processing on board the spacecraft. The IAS program is a logical first step toward smart sensors, and IAS developments - particularly the system components and key technology improvements - are applicable to future smart efforts. The paper describes the design goals and functional elements of the IAS. In addition, the schedule for IAS development and demonstration is discussed.

Design and implementation of non-linear image processing functions for CMOS image sensor

NASA Astrophysics Data System (ADS)

Musa, Purnawarman; Sudiro, Sunny A.; Wibowo, Eri P.; Harmanto, Suryadi; Paindavoine, Michel

2012-11-01

Today, solid state image sensors are used in many applications like in mobile phones, video surveillance systems, embedded medical imaging and industrial vision systems. These image sensors require the integration in the focal plane (or near the focal plane) of complex image processing algorithms. Such devices must meet the constraints related to the quality of acquired images, speed and performance of embedded processing, as well as low power consumption. To achieve these objectives, low-level analog processing allows extracting the useful information in the scene directly. For example, edge detection step followed by a local maxima extraction will facilitate the high-level processing like objects pattern recognition in a visual scene. Our goal was to design an intelligent image sensor prototype achieving high-speed image acquisition and non-linear image processing (like local minima and maxima calculations). For this purpose, we present in this article the design and test of a 64×64 pixels image sensor built in a standard CMOS Technology 0.35 μm including non-linear image processing. The architecture of our sensor, named nLiRIC (non-Linear Rapid Image Capture), is based on the implementation of an analog Minima/Maxima Unit. This MMU calculates the minimum and maximum values (non-linear functions), in real time, in a 2×2 pixels neighbourhood. Each MMU needs 52 transistors and the pitch of one pixel is 40×40 mu m. The total area of the 64×64 pixels is 12.5mm2. Our tests have shown the validity of the main functions of our new image sensor like fast image acquisition (10K frames per second), minima/maxima calculations in less then one ms.

Acoustic Source Localization via Time Difference of Arrival Estimation for Distributed Sensor Networks Using Tera-Scale Optical Core Devices

DOE PAGES

Imam, Neena; Barhen, Jacob

2009-01-01

For real-time acoustic source localization applications, one of the primary challenges is the considerable growth in computational complexity associated with the emergence of ever larger, active or passive, distributed sensor networks. These sensors rely heavily on battery-operated system components to achieve highly functional automation in signal and information processing. In order to keep communication requirements minimal, it is desirable to perform as much processing on the receiver platforms as possible. However, the complexity of the calculations needed to achieve accurate source localization increases dramatically with the size of sensor arrays, resulting in substantial growth of computational requirements that cannot bemore » readily met with standard hardware. One option to meet this challenge builds upon the emergence of digital optical-core devices. The objective of this work was to explore the implementation of key building block algorithms used in underwater source localization on the optical-core digital processing platform recently introduced by Lenslet Inc. This demonstration of considerably faster signal processing capability should be of substantial significance to the design and innovation of future generations of distributed sensor networks.« less

Development of a Three Dimensional Wireless Sensor Network for Terrain-Climate Research in Remote Mountainous Environments

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.

Integrated Air Surveillance Concept of Operations

DTIC Science & Technology

2011-11-01

information, intelligence, weather data, and other situational awareness-related information. 4.2.4 Shared Services Automated processing of sensor and...other surveillance information will occur through shared services , accessible through an enterprise network infrastructure, that provide for collecting...also be provided, such as information discovery and translation. The IS architecture effort will identify specific shared services . Shared

A hybrid system identification methodology for wireless structural health monitoring systems based on dynamic substructuring

NASA Astrophysics Data System (ADS)

Dragos, Kosmas; Smarsly, Kay

2016-04-01

System identification has been employed in numerous structural health monitoring (SHM) applications. Traditional system identification methods usually rely on centralized processing of structural response data to extract information on structural parameters. However, in wireless SHM systems the centralized processing of structural response data introduces a significant communication bottleneck. Exploiting the merits of decentralization and on-board processing power of wireless SHM systems, many system identification methods have been successfully implemented in wireless sensor networks. While several system identification approaches for wireless SHM systems have been proposed, little attention has been paid to obtaining information on the physical parameters (e.g. stiffness, damping) of the monitored structure. This paper presents a hybrid system identification methodology suitable for wireless sensor networks based on the principles of component mode synthesis (dynamic substructuring). A numerical model of the monitored structure is embedded into the wireless sensor nodes in a distributed manner, i.e. the entire model is segmented into sub-models, each embedded into one sensor node corresponding to the substructure the sensor node is assigned to. The parameters of each sub-model are estimated by extracting local mode shapes and by applying the equations of the Craig-Bampton method on dynamic substructuring. The proposed methodology is validated in a laboratory test conducted on a four-story frame structure to demonstrate the ability of the methodology to yield accurate estimates of stiffness parameters. Finally, the test results are discussed and an outlook on future research directions is provided.

Issues and challenges in resource management and its interaction with levels 2/3 fusion with applications to real-world problems: an annotated perspective

NASA Astrophysics Data System (ADS)

Blasch, Erik; Kadar, Ivan; Hintz, Kenneth; Biermann, Joachim; Chong, Chee-Yee; Salerno, John; Das, Subrata

2007-04-01

Resource management (or process refinement) is critical for information fusion operations in that users, sensors, and platforms need to be informed, based on mission needs, on how to collect, process, and exploit data. To meet these growing concerns, a panel session was conducted at the International Society of Information Fusion Conference in 2006 to discuss the various issues surrounding the interaction of Resource Management with Level 2/3 Situation and Threat Assessment. This paper briefly consolidates the discussion of the invited panel panelists. The common themes include: (1) Addressing the user in system management, sensor control, and knowledge based information collection (2) Determining a standard set of fusion metrics for optimization and evaluation based on the application (3) Allowing dynamic and adaptive updating to deliver timely information needs and information rates (4) Optimizing the joint objective functions at all information fusion levels based on decision-theoretic analysis (5) Providing constraints from distributed resource mission planning and scheduling; and (6) Defining L2/3 situation entity definitions for knowledge discovery, modeling, and information projection

Combining engineered cell-sensors with multi-agent systems to realize smart environment

NASA Astrophysics Data System (ADS)

Chen, Mei

2013-03-01

The connection of everything in a sensory and an intelligent way is a pursuit in smart environment. This paper introduces the engineered cell-sensors into the multi-agent systems to realize the smart environment. The seamless interface with the natural environment and strong information-processing ability of cell with the achievements of synthetic biology make the construction of engineered cell-sensors possible. However, the engineered cell-sensors are only simple-functional and unreliable computational entities. Therefore how to combine engineered cell-sensors with digital device is a key problem in order to realize the smart environment. We give the abstract structure and interaction modes of the engineered cell-sensors in order to introduce engineered cell-sensors into multi-agent systems. We believe that the introduction of engineered cell-sensors will push forward the development of the smart environment.

Reactor protection system with automatic self-testing and diagnostic

DOEpatents

Gaubatz, Donald C.

1996-01-01

A reactor protection system having four divisions, with quad redundant sensors for each scram parameter providing input to four independent microprocessor-based electronic chassis. Each electronic chassis acquires the scram parameter data from its own sensor, digitizes the information, and then transmits the sensor reading to the other three electronic chassis via optical fibers. To increase system availability and reduce false scrams, the reactor protection system employs two levels of voting on a need for reactor scram. The electronic chassis perform software divisional data processing, vote 2/3 with spare based upon information from all four sensors, and send the divisional scram signals to the hardware logic panel, which performs a 2/4 division vote on whether or not to initiate a reactor scram. Each chassis makes a divisional scram decision based on data from all sensors. Automatic detection and discrimination against failed sensors allows the reactor protection system to automatically enter a known state when sensor failures occur. Cross communication of sensor readings allows comparison of four theoretically "identical" values. This permits identification of sensor errors such as drift or malfunction. A diagnostic request for service is issued for errant sensor data. Automated self test and diagnostic monitoring, sensor input through output relay logic, virtually eliminate the need for manual surveillance testing. This provides an ability for each division to cross-check all divisions and to sense failures of the hardware logic.

Reactor protection system with automatic self-testing and diagnostic

DOEpatents

Gaubatz, D.C.

1996-12-17

A reactor protection system is disclosed having four divisions, with quad redundant sensors for each scram parameter providing input to four independent microprocessor-based electronic chassis. Each electronic chassis acquires the scram parameter data from its own sensor, digitizes the information, and then transmits the sensor reading to the other three electronic chassis via optical fibers. To increase system availability and reduce false scrams, the reactor protection system employs two levels of voting on a need for reactor scram. The electronic chassis perform software divisional data processing, vote 2/3 with spare based upon information from all four sensors, and send the divisional scram signals to the hardware logic panel, which performs a 2/4 division vote on whether or not to initiate a reactor scram. Each chassis makes a divisional scram decision based on data from all sensors. Automatic detection and discrimination against failed sensors allows the reactor protection system to automatically enter a known state when sensor failures occur. Cross communication of sensor readings allows comparison of four theoretically ``identical`` values. This permits identification of sensor errors such as drift or malfunction. A diagnostic request for service is issued for errant sensor data. Automated self test and diagnostic monitoring, sensor input through output relay logic, virtually eliminate the need for manual surveillance testing. This provides an ability for each division to cross-check all divisions and to sense failures of the hardware logic. 16 figs.

Working group organizational meeting

NASA Technical Reports Server (NTRS)

1982-01-01

Scene radiation and atmospheric effects, mathematical pattern recognition and image analysis, information evaluation and utilization, and electromagnetic measurements and signal handling are considered. Research issues in sensors and signals, including radar (SAR) reflectometry, SAR processing speed, registration, including overlay of SAR and optical imagery, entire system radiance calibration, and lack of requirements for both sensors and systems, etc. were discussed.

Diameter sensors for tree-length harvesting systems

Treesearch

T.P. McDonald; Robert B. Rummer; T.E. Grift

2003-01-01

Most cut-to-length (CTL) harvesters provide sensors for measuring diameter of trees as they are cut and processed. Among other uses, this capability provides a data collection tool for marketing of logs in real time. Logs can be sorted and stacked based on up-to-date market information, then transportation systems optimized to route wood to proper destinations at...

Gossip and Distributed Kalman Filtering: Weak Consensus Under Weak Detectability

NASA Astrophysics Data System (ADS)

Kar, Soummya; Moura, José M. F.

2011-04-01

The paper presents the gossip interactive Kalman filter (GIKF) for distributed Kalman filtering for networked systems and sensor networks, where inter-sensor communication and observations occur at the same time-scale. The communication among sensors is random; each sensor occasionally exchanges its filtering state information with a neighbor depending on the availability of the appropriate network link. We show that under a weak distributed detectability condition: 1. the GIKF error process remains stochastically bounded, irrespective of the instability properties of the random process dynamics; and 2. the network achieves \\emph{weak consensus}, i.e., the conditional estimation error covariance at a (uniformly) randomly selected sensor converges in distribution to a unique invariant measure on the space of positive semi-definite matrices (independent of the initial state.) To prove these results, we interpret the filtered states (estimates and error covariances) at each node in the GIKF as stochastic particles with local interactions. We analyze the asymptotic properties of the error process by studying as a random dynamical system the associated switched (random) Riccati equation, the switching being dictated by a non-stationary Markov chain on the network graph.

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

Sreedharan, Priya

The sudden release of toxic contaminants that reach indoor spaces can be hazardousto building occupants. To respond effectively, the contaminant release must be quicklydetected and characterized to determine unobserved parameters, such as release locationand strength. Characterizing the release requires solving an inverse problem. Designinga robust real-time sensor system that solves the inverse problem is challenging becausethe fate and transport of contaminants is complex, sensor information is limited andimperfect, and real-time estimation is computationally constrained.This dissertation uses a system-level approach, based on a Bayes Monte Carloframework, to develop sensor-system design concepts and methods. I describe threeinvestigations that explore complex relationships amongmore » sensors, network architecture,interpretation algorithms, and system performance. The investigations use data obtainedfrom tracer gas experiments conducted in a real building. The influence of individual sensor characteristics on the sensor-system performance for binary-type contaminant sensors is analyzed. Performance tradeoffs among sensor accuracy, threshold level and response time are identified; these attributes could not be inferred without a system-level analysis. For example, more accurate but slower sensors are found to outperform less accurate but faster sensors. Secondly, I investigate how the sensor-system performance can be understood in terms of contaminant transport processes and the model representation that is used to solve the inverse problem. The determination of release location and mass are shown to be related to and constrained by transport and mixing time scales. These time scales explain performance differences among different sensor networks. For example, the effect of longer sensor response times is comparably less for releases with longer mixing time scales. The third investigation explores how information fusion from heterogeneous sensors may improve the sensor-system performance and offset the need for more contaminant sensors. Physics- and algorithm-based frameworks are presented for selecting and fusing information from noncontaminant sensors. The frameworks are demonstrated with door-position sensors, which are found to be more useful in natural airflow conditions, but which cannot compensate for poor placement of contaminant sensors. The concepts and empirical findings have the potential to help in the design of sensor systems for more complex building systems. The research has broader relevance to additional environmental monitoring problems, fault detection and diagnostics, and system design.« less

Improving travel information products via robust estimation techniques : final report, March 2009.

DOT National Transportation Integrated Search

2009-03-01

Traffic-monitoring systems, such as those using loop detectors, are prone to coverage gaps, arising from sensor noise, processing errors and : transmission problems. Such gaps adversely affect the accuracy of Advanced Traveler Information Systems. Th...

Color Restoration of RGBN Multispectral Filter Array Sensor Images Based on Spectral Decomposition.

PubMed

Park, Chulhee; Kang, Moon Gi

2016-05-18

A multispectral filter array (MSFA) image sensor with red, green, blue and near-infrared (NIR) filters is useful for various imaging applications with the advantages that it obtains color information and NIR information simultaneously. Because the MSFA image sensor needs to acquire invisible band information, it is necessary to remove the IR cut-offfilter (IRCF). However, without the IRCF, the color of the image is desaturated by the interference of the additional NIR component of each RGB color channel. To overcome color degradation, a signal processing approach is required to restore natural color by removing the unwanted NIR contribution to the RGB color channels while the additional NIR information remains in the N channel. Thus, in this paper, we propose a color restoration method for an imaging system based on the MSFA image sensor with RGBN filters. To remove the unnecessary NIR component in each RGB color channel, spectral estimation and spectral decomposition are performed based on the spectral characteristics of the MSFA sensor. The proposed color restoration method estimates the spectral intensity in NIR band and recovers hue and color saturation by decomposing the visible band component and the NIR band component in each RGB color channel. The experimental results show that the proposed method effectively restores natural color and minimizes angular errors.

Color Restoration of RGBN Multispectral Filter Array Sensor Images Based on Spectral Decomposition

PubMed Central

Park, Chulhee; Kang, Moon Gi

2016-01-01

A multispectral filter array (MSFA) image sensor with red, green, blue and near-infrared (NIR) filters is useful for various imaging applications with the advantages that it obtains color information and NIR information simultaneously. Because the MSFA image sensor needs to acquire invisible band information, it is necessary to remove the IR cut-offfilter (IRCF). However, without the IRCF, the color of the image is desaturated by the interference of the additional NIR component of each RGB color channel. To overcome color degradation, a signal processing approach is required to restore natural color by removing the unwanted NIR contribution to the RGB color channels while the additional NIR information remains in the N channel. Thus, in this paper, we propose a color restoration method for an imaging system based on the MSFA image sensor with RGBN filters. To remove the unnecessary NIR component in each RGB color channel, spectral estimation and spectral decomposition are performed based on the spectral characteristics of the MSFA sensor. The proposed color restoration method estimates the spectral intensity in NIR band and recovers hue and color saturation by decomposing the visible band component and the NIR band component in each RGB color channel. The experimental results show that the proposed method effectively restores natural color and minimizes angular errors. PMID:27213381

Guidelines for spaceborne microwave remote sensors

NASA Technical Reports Server (NTRS)

Litman, V.; Nicholas, J.

1982-01-01

A handbook was developed to provide information and support to the spaceborne remote sensing and frequency management communities: to guide sensor developers in the choice of frequencies; to advise regulators on sensor technology needs and sharing potential; to present sharing analysis models and, through example, methods for determining sensor sharing feasibility; to introduce developers to the regulatory process; to create awareness of proper assignment procedures; to present sensor allocations; and to provide guidelines on the use and limitations of allocated bands. Controlling physical factors and user requirements and the regulatory environment are discussed. Sensor frequency allocation achievable performance and usefulness are reviewed. Procedures for national and international registration, the use of non-allocated bands and steps for obtaining new frequency allocations, and procedures for reporting interference are also discussed.

Design and Parametric Study of the Magnetic Sensor for Position Detection in Linear Motor Based on Nonlinear Parametric Model Order Reduction

PubMed Central

Paul, Sarbajit; Chang, Junghwan

2017-01-01

This paper presents a design approach for a magnetic sensor module to detect mover position using the proper orthogonal decomposition-dynamic mode decomposition (POD-DMD)-based nonlinear parametric model order reduction (PMOR). The parameterization of the sensor module is achieved by using the multipolar moment matching method. Several geometric variables of the sensor module are considered while developing the parametric study. The operation of the sensor module is based on the principle of the airgap flux density distribution detection by the Hall Effect IC. Therefore, the design objective is to achieve a peak flux density (PFD) greater than 0.1 T and total harmonic distortion (THD) less than 3%. To fulfill the constraint conditions, the specifications for the sensor module is achieved by using POD-DMD based reduced model. The POD-DMD based reduced model provides a platform to analyze the high number of design models very fast, with less computational burden. Finally, with the final specifications, the experimental prototype is designed and tested. Two different modes, 90° and 120° modes respectively are used to obtain the position information of the linear motor mover. The position information thus obtained are compared with that of the linear scale data, used as a reference signal. The position information obtained using the 120° mode has a standard deviation of 0.10 mm from the reference linear scale signal, whereas the 90° mode position signal shows a deviation of 0.23 mm from the reference. The deviation in the output arises due to the mechanical tolerances introduced into the specification during the manufacturing process. This provides a scope for coupling the reliability based design optimization in the design process as a future extension. PMID:28671580

Land mine detection using multispectral image fusion

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

Clark, G.A.; Sengupta, S.K.; Aimonetti, W.D.

1995-03-29

Our system fuses information contained in registered images from multiple sensors to reduce the effects of clutter and improve the ability to detect surface and buried land mines. The sensor suite currently consists of a camera that acquires images in six bands (400nm, 500nm, 600nm, 700nm, 800nm and 900nm). Past research has shown that it is extremely difficult to distinguish land mines from background clutter in images obtained from a single sensor. It is hypothesized, however, that information fused from a suite of various sensors is likely to provide better detection reliability, because the suite of sensors detects a varietymore » of physical properties that are more separable in feature space. The materials surrounding the mines can include natural materials (soil, rocks, foliage, water, etc.) and some artifacts. We use a supervised learning pattern recognition approach to detecting the metal and plastic land mines. The overall process consists of four main parts: Preprocessing, feature extraction, feature selection, and classification. These parts are used in a two step process to classify a subimage. We extract features from the images, and use feature selection algorithms to select only the most important features according to their contribution to correct detections. This allows us to save computational complexity and determine which of the spectral bands add value to the detection system. The most important features from the various sensors are fused using a supervised learning pattern classifier (the probabilistic neural network). We present results of experiments to detect land mines from real data collected from an airborne platform, and evaluate the usefulness of fusing feature information from multiple spectral bands.« less

Design and Parametric Study of the Magnetic Sensor for Position Detection in Linear Motor Based on Nonlinear Parametric model order reduction.

PubMed

Paul, Sarbajit; Chang, Junghwan

2017-07-01

This paper presents a design approach for a magnetic sensor module to detect mover position using the proper orthogonal decomposition-dynamic mode decomposition (POD-DMD)-based nonlinear parametric model order reduction (PMOR). The parameterization of the sensor module is achieved by using the multipolar moment matching method. Several geometric variables of the sensor module are considered while developing the parametric study. The operation of the sensor module is based on the principle of the airgap flux density distribution detection by the Hall Effect IC. Therefore, the design objective is to achieve a peak flux density (PFD) greater than 0.1 T and total harmonic distortion (THD) less than 3%. To fulfill the constraint conditions, the specifications for the sensor module is achieved by using POD-DMD based reduced model. The POD-DMD based reduced model provides a platform to analyze the high number of design models very fast, with less computational burden. Finally, with the final specifications, the experimental prototype is designed and tested. Two different modes, 90° and 120° modes respectively are used to obtain the position information of the linear motor mover. The position information thus obtained are compared with that of the linear scale data, used as a reference signal. The position information obtained using the 120° mode has a standard deviation of 0.10 mm from the reference linear scale signal, whereas the 90° mode position signal shows a deviation of 0.23 mm from the reference. The deviation in the output arises due to the mechanical tolerances introduced into the specification during the manufacturing process. This provides a scope for coupling the reliability based design optimization in the design process as a future extension.

SWE-based Observation Data Delivery from the Instrument to the User - Sensor Web Technology in the NeXOS Project

NASA Astrophysics Data System (ADS)

Jirka, Simon; del Rio, Joaquin; Toma, Daniel; Martinez, Enoc; Delory, Eric; Pearlman, Jay; Rieke, Matthes; Stasch, Christoph

2017-04-01

The rapidly evolving technology for building Web-based (spatial) information infrastructures and Sensor Webs, there are new opportunities to improve the process how ocean data is collected and managed. A central element in this development is the suite of Sensor Web Enablement (SWE) standards specified by the Open Geospatial Consortium (OGC). This framework of standards comprises on the one hand data models as well as formats for measurement data (ISO/OGC Observations and Measurement, O&M) and metadata describing measurement processes and sensors (OGC Sensor Model Language, SensorML). On the other hand the SWE standards comprise (Web service) interface specifications for pull-based access to observation data (OGC Sensor Observation Service, SOS) and for controlling or configuring sensors (OGC Sensor Planning Service, SPS). Also within the European INSPIRE framework the SWE standards play an important role as the SOS is the recommended download service interface for O&M-encoded observation data sets. In the context of the EU-funded Oceans of Tomorrow initiative the NeXOS (Next generation, Cost-effective, Compact, Multifunctional Web Enabled Ocean Sensor Systems Empowering Marine, Maritime and Fisheries Management) project is developing a new generation of in-situ sensors that make use of the SWE standards to facilitate the data publication process and the integration into Web based information infrastructures. This includes the development of a dedicated firmware for instruments and sensor platforms (SEISI, Smart Electronic Interface for Sensors and Instruments) maintained by the Universitat Politècnica de Catalunya (UPC). Among other features, SEISI makes use of OGC SWE standards such OGC-PUCK, to enable a plug-and-play mechanism for sensors based on SensorML encoded metadata. Thus, if a new instrument is attached to a SEISI-based platform, it automatically configures the connection to these instruments, automatically generated data files compliant with the ISO/OGC Observations and Measurements standard and initiates the data transmission into the NeXOS Sensor Web infrastructure. Besides these platform-related developments, NeXOS has realised the full path of data transmission from the sensor to the end user application. The conceptual architecture design is implemented by a series of open source SWE software packages provided by 52°North. This comprises especially different SWE server components (i.e. OGC Sensor Observation Service), tools for data visualisation (e.g. the 52°North Helgoland SOS viewer), and an editor for providing SensorML-based metadata (52°North smle). As a result, NeXOS has demonstrated how the SWE standards help to improve marine observation data collection. Within this presentation, we will present the experiences and findings of the NeXOS project and will provide recommendation for future work directions.

Overview of the Smart Network Element Architecture and Recent Innovations

NASA Technical Reports Server (NTRS)

Perotti, Jose M.; Mata, Carlos T.; Oostdyk, Rebecca L.

2008-01-01

In industrial environments, system operators rely on the availability and accuracy of sensors to monitor processes and detect failures of components and/or processes. The sensors must be networked in such a way that their data is reported to a central human interface, where operators are tasked with making real-time decisions based on the state of the sensors and the components that are being monitored. Incorporating health management functions at this central location aids the operator by automating the decision-making process to suggest, and sometimes perform, the action required by current operating conditions. Integrated Systems Health Management (ISHM) aims to incorporate data from many sources, including real-time and historical data and user input, and extract information and knowledge from that data to diagnose failures and predict future failures of the system. By distributing health management processing to lower levels of the architecture, there is less bandwidth required for ISHM, enhanced data fusion, make systems and processes more robust, and improved resolution for the detection and isolation of failures in a system, subsystem, component, or process. The Smart Network Element (SNE) has been developed at NASA Kennedy Space Center to perform intelligent functions at sensors and actuators' level in support of ISHM.

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.

A Force-Sensing System on Legs for Biomimetic Hexapod Robots Interacting with Unstructured Terrain

PubMed Central

Wu, Rui; Li, Changle; Zang, Xizhe; Zhang, Xuehe; Jin, Hongzhe; Zhao, Jie

2017-01-01

The tiger beetle can maintain its stability by controlling the interaction force between its legs and an unstructured terrain while it runs. The biomimetic hexapod robot mimics a tiger beetle, and a comprehensive force sensing system combined with certain algorithms can provide force information that can help the robot understand the unstructured terrain that it interacts with. This study introduces a complicated leg force sensing system for a hexapod robot that is the same for all six legs. First, the layout and configuration of sensing system are designed according to the structure and sizes of legs. Second, the joint toque sensors, 3-DOF foot-end force sensor and force information processing module are designed, and the force sensor performance parameters are tested by simulations and experiments. Moreover, a force sensing system is implemented within the robot control architecture. Finally, the experimental evaluation of the leg force sensor system on the hexapod robot is discussed and the performance of the leg force sensor system is verified. PMID:28654003

Multiple Two-Way Time Message Exchange (TTME) Time Synchronization for Bridge Monitoring Wireless Sensor Networks

PubMed Central

Shi, Fanrong; Tuo, Xianguo; Yang, Simon X.; Li, Huailiang; Shi, Rui

2017-01-01

Wireless sensor networks (WSNs) have been widely used to collect valuable information in Structural Health Monitoring (SHM) of bridges, using various sensors, such as temperature, vibration and strain sensors. Since multiple sensors are distributed on the bridge, accurate time synchronization is very important for multi-sensor data fusion and information processing. Based on shape of the bridge, a spanning tree is employed to build linear topology WSNs and achieve time synchronization in this paper. Two-way time message exchange (TTME) and maximum likelihood estimation (MLE) are employed for clock offset estimation. Multiple TTMEs are proposed to obtain a subset of TTME observations. The time out restriction and retry mechanism are employed to avoid the estimation errors that are caused by continuous clock offset and software latencies. The simulation results show that the proposed algorithm could avoid the estimation errors caused by clock drift and minimize the estimation error due to the large random variable delay jitter. The proposed algorithm is an accurate and low complexity time synchronization algorithm for bridge health monitoring. PMID:28471418

Multiple Two-Way Time Message Exchange (TTME) Time Synchronization for Bridge Monitoring Wireless Sensor Networks.

PubMed

Shi, Fanrong; Tuo, Xianguo; Yang, Simon X; Li, Huailiang; Shi, Rui

2017-05-04

Wireless sensor networks (WSNs) have been widely used to collect valuable information in Structural Health Monitoring (SHM) of bridges, using various sensors, such as temperature, vibration and strain sensors. Since multiple sensors are distributed on the bridge, accurate time synchronization is very important for multi-sensor data fusion and information processing. Based on shape of the bridge, a spanning tree is employed to build linear topology WSNs and achieve time synchronization in this paper. Two-way time message exchange (TTME) and maximum likelihood estimation (MLE) are employed for clock offset estimation. Multiple TTMEs are proposed to obtain a subset of TTME observations. The time out restriction and retry mechanism are employed to avoid the estimation errors that are caused by continuous clock offset and software latencies. The simulation results show that the proposed algorithm could avoid the estimation errors caused by clock drift and minimize the estimation error due to the large random variable delay jitter. The proposed algorithm is an accurate and low complexity time synchronization algorithm for bridge health monitoring.

Radiation detection and situation management by distributed sensor networks

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

Jan, Frigo; Mielke, Angela; Cai, D Michael

Detection of radioactive materials in an urban environment usually requires large, portal-monitor-style radiation detectors. However, this may not be a practical solution in many transport scenarios. Alternatively, a distributed sensor network (DSN) could complement portal-style detection of radiological materials through the implementation of arrays of low cost, small heterogeneous sensors with the ability to detect the presence of radioactive materials in a moving vehicle over a specific region. In this paper, we report on the use of a heterogeneous, wireless, distributed sensor network for traffic monitoring in a field demonstration. Through wireless communications, the energy spectra from different radiation detectorsmore » are combined to improve the detection confidence. In addition, the DSN exploits other sensor technologies and algorithms to provide additional information about the vehicle, such as its speed, location, class (e.g. car, truck), and license plate number. The sensors are in-situ and data is processed in real-time at each node. Relevant information from each node is sent to a base station computer which is used to assess the movement of radioactive materials.« less

Sensors Applications, Volume 4, Sensors for Automotive Applications

NASA Astrophysics Data System (ADS)

Marek, Jiri; Trah, Hans-Peter; Suzuki, Yasutoshi; Yokomori, Iwao

2003-07-01

An international team of experts from the leading companies in this field gives a detailed picture of existing as well as future applications. They discuss in detail current technologies, design and construction concepts, market considerations and commercial developments. Topics covered include vehicle safety, fuel consumption, air conditioning, emergency control, traffic control systems, and electronic guidance using radar and video. Meeting the growing need for comprehensive information on the capabilities, potentials and limitations of modern sensor systems, Sensors Applications is a book series covering the use of sophisticated technologies and materials for the creation of advanced sensors and their implementation in the key areas process monitoring, building control, health care, automobiles, aerospace, environmental technology and household appliances.

Analysis of real-time reservoir monitoring : reservoirs, strategies, & modeling.

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

Mani, Seethambal S.; van Bloemen Waanders, Bart Gustaaf; Cooper, Scott Patrick

2006-11-01

The project objective was to detail better ways to assess and exploit intelligent oil and gas field information through improved modeling, sensor technology, and process control to increase ultimate recovery of domestic hydrocarbons. To meet this objective we investigated the use of permanent downhole sensors systems (Smart Wells) whose data is fed real-time into computational reservoir models that are integrated with optimized production control systems. The project utilized a three-pronged approach (1) a value of information analysis to address the economic advantages, (2) reservoir simulation modeling and control optimization to prove the capability, and (3) evaluation of new generation sensormore » packaging to survive the borehole environment for long periods of time. The Value of Information (VOI) decision tree method was developed and used to assess the economic advantage of using the proposed technology; the VOI demonstrated the increased subsurface resolution through additional sensor data. Our findings show that the VOI studies are a practical means of ascertaining the value associated with a technology, in this case application of sensors to production. The procedure acknowledges the uncertainty in predictions but nevertheless assigns monetary value to the predictions. The best aspect of the procedure is that it builds consensus within interdisciplinary teams The reservoir simulation and modeling aspect of the project was developed to show the capability of exploiting sensor information both for reservoir characterization and to optimize control of the production system. Our findings indicate history matching is improved as more information is added to the objective function, clearly indicating that sensor information can help in reducing the uncertainty associated with reservoir characterization. Additional findings and approaches used are described in detail within the report. The next generation sensors aspect of the project evaluated sensors and packaging survivability issues. Our findings indicate that packaging represents the most significant technical challenge associated with application of sensors in the downhole environment for long periods (5+ years) of time. These issues are described in detail within the report. The impact of successful reservoir monitoring programs and coincident improved reservoir management is measured by the production of additional oil and gas volumes from existing reservoirs, revitalization of nearly depleted reservoirs, possible re-establishment of already abandoned reservoirs, and improved economics for all cases. Smart Well monitoring provides the means to understand how a reservoir process is developing and to provide active reservoir management. At the same time it also provides data for developing high-fidelity simulation models. This work has been a joint effort with Sandia National Laboratories and UT-Austin's Bureau of Economic Geology, Department of Petroleum and Geosystems Engineering, and the Institute of Computational and Engineering Mathematics.« less

Video image processing to create a speed sensor

DOT National Transportation Integrated Search

1999-11-01

Image processing has been applied to traffic analysis in recent years, with different goals. In the report, a new approach is presented for extracting vehicular speed information, given a sequence of real-time traffic images. We extract moving edges ...

Parallel multi-join query optimization algorithm for distributed sensor network in the internet of things

NASA Astrophysics Data System (ADS)

Zheng, Yan

2015-03-01

Internet of things (IoT), focusing on providing users with information exchange and intelligent control, attracts a lot of attention of researchers from all over the world since the beginning of this century. IoT is consisted of large scale of sensor nodes and data processing units, and the most important features of IoT can be illustrated as energy confinement, efficient communication and high redundancy. With the sensor nodes increment, the communication efficiency and the available communication band width become bottle necks. Many research work is based on the instance which the number of joins is less. However, it is not proper to the increasing multi-join query in whole internet of things. To improve the communication efficiency between parallel units in the distributed sensor network, this paper proposed parallel query optimization algorithm based on distribution attributes cost graph. The storage information relations and the network communication cost are considered in this algorithm, and an optimized information changing rule is established. The experimental result shows that the algorithm has good performance, and it would effectively use the resource of each node in the distributed sensor network. Therefore, executive efficiency of multi-join query between different nodes could be improved.

Health Monitoring for Airframe Structural Characterization

NASA Technical Reports Server (NTRS)

Munns, Thomas E.; Kent, Renee M.; Bartolini, Antony; Gause, Charles B.; Borinski, Jason W.; Dietz, Jason; Elster, Jennifer L.; Boyd, Clark; Vicari, Larry; Ray, Asok;

Designing and Securing an Event Processing System for Smart Spaces

ERIC Educational Resources Information Center

Li, Zang

2011-01-01

Smart spaces, or smart environments, represent the next evolutionary development in buildings, banking, homes, hospitals, transportation systems, industries, cities, and government automation. By riding the tide of sensor and event processing technologies, the smart environment captures and processes information about its surroundings as well as…

Development of a belt-type wearable sensor system with multi-function for home health care

NASA Astrophysics Data System (ADS)

Ban, Yunho; Choi, Samjin; Jiang, Zhongwei; Park, Chanwon

2005-12-01

Some reports show that the physiological information measured in hospital is not enough without the one measured in home. The physiological information monitored in home, therefore, is strongly required recently. The goal of this research is to develop a wearable and tractable sensor system for detecting biomedical signals such as cardiac rhythm, respiration, body movement, and percentage of body fat (%BF) and for home health care. A belt type sensor for this purpose is developed, which consists of sensing materials of PVDF film and conductive fabrics. Also several data processing techniques, such as the discrete wavelet transform, cross correlation and adaptive filtering method, were introduced to eliminate noises and base wandering and to extract the specified components. The ECG and respiration signals obtained by the proposed belt type sensor system gave good agreements with commercial medical system. Furthermore, the body fat (%BF) measurement based on the four-electrode BIA was also built in the belt sensor. The body fat was calculated by measuring the body impedance from the belt type sensor and compared with the predicted %BF measured by the commercial adipometer (TBF-607). The results validated also the efficiency of the belt type sensor system.

Large Scale Environmental Monitoring through Integration of Sensor and Mesh Networks

PubMed Central

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

Attitude ground support system for the solar maximum mission spacecraft

NASA Technical Reports Server (NTRS)

Nair, G.

1980-01-01

The SMM attitude ground support system (AGSS) supports the acquisition of spacecraft roll attitude reference, performs the in-flight calibration of the attitude sensor complement, supports onboard control autonomy via onboard computer data base updates, and monitors onboard computer (OBC) performance. Initial roll attitude acquisition is accomplished by obtaining a coarse 3 axis attitude estimate from magnetometer and Sun sensor data and subsequently refining it by processing data from the fixed head star trackers. In-flight calibration of the attitude sensor complement is achieved by processing data from a series of slew maneuvers designed to maximize the observability and accuracy of the appropriate alignments and biases. To ensure autonomy of spacecraft operation, the AGSS selects guide stars and computes sensor occultation information for uplink to the OBC. The onboard attitude control performance is monitored on the ground through periodic attitude determination and processing of OBC data in downlink telemetry. In general, the control performance has met mission requirements. However, software and hardware problems have resulted in sporadic attitude reference losses.

Sensor feature fusion for detecting buried objects

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

Clark, G.A.; Sengupta, S.K.; Sherwood, R.J.

1993-04-01

Given multiple registered images of the earth`s surface from dual-band sensors, our system fuses information from the sensors to reduce the effects of clutter and improve the ability to detect buried or surface target sites. The sensor suite currently includes two sensors (5 micron and 10 micron wavelengths) and one ground penetrating radar (GPR) of the wide-band pulsed synthetic aperture type. We use a supervised teaming pattern recognition approach to detect metal and plastic land mines buried in soil. The overall process consists of four main parts: Preprocessing, feature extraction, feature selection, and classification. These parts are used in amore » two step process to classify a subimage. Thee first step, referred to as feature selection, determines the features of sub-images which result in the greatest separability among the classes. The second step, image labeling, uses the selected features and the decisions from a pattern classifier to label the regions in the image which are likely to correspond to buried mines. We extract features from the images, and use feature selection algorithms to select only the most important features according to their contribution to correct detections. This allows us to save computational complexity and determine which of the sensors add value to the detection system. The most important features from the various sensors are fused using supervised teaming pattern classifiers (including neural networks). We present results of experiments to detect buried land mines from real data, and evaluate the usefulness of fusing feature information from multiple sensor types, including dual-band infrared and ground penetrating radar. The novelty of the work lies mostly in the combination of the algorithms and their application to the very important and currently unsolved operational problem of detecting buried land mines from an airborne standoff platform.« less

Navigation system for a mobile robot with a visual sensor using a fish-eye lens

NASA Astrophysics Data System (ADS)

Kurata, Junichi; Grattan, Kenneth T. V.; Uchiyama, Hironobu

1998-02-01

Various position sensing and navigation systems have been proposed for the autonomous control of mobile robots. Some of these systems have been installed with an omnidirectional visual sensor system that proved very useful in obtaining information on the environment around the mobile robot for position reckoning. In this article, this type of navigation system is discussed. The sensor is composed of one TV camera with a fish-eye lens, using a reference target on a ceiling and hybrid image processing circuits. The position of the robot, with respect to the floor, is calculated by integrating the information obtained from a visual sensor and a gyroscope mounted in the mobile robot, and the use of a simple algorithm based on PTP control for guidance is discussed. An experimental trial showed that the proposed system was both valid and useful for the navigation of an indoor vehicle.

Sensor/Response Coordination In A Tactical Self-Protection System

NASA Astrophysics Data System (ADS)

Steinberg, Alan N.

1988-08-01

This paper describes a model for integrating information acquisition functions into a response planner within a tactical self-defense system. This model may be used in defining requirements in such applications for sensor systems and for associated processing and control functions. The goal of information acquisition in a self-defense system is generally not that of achieving the best possible estimate of the threat environment; but rather to provide resolution of that environment sufficient to support response decisions. We model the information acquisition problem as that of achieving a partition among possible world states such that the final partition maps into the system's repertoire of possible responses.

Sensor Fusion of Gaussian Mixtures for Ballistic Target Tracking in the Re-Entry Phase

PubMed Central

Lu, Kelin; Zhou, Rui

2016-01-01

A sensor fusion methodology for the Gaussian mixtures model is proposed for ballistic target tracking with unknown ballistic coefficients. To improve the estimation accuracy, a track-to-track fusion architecture is proposed to fuse tracks provided by the local interacting multiple model filters. During the fusion process, the duplicate information is removed by considering the first order redundant information between the local tracks. With extensive simulations, we show that the proposed algorithm improves the tracking accuracy in ballistic target tracking in the re-entry phase applications. PMID:27537883

Enhanced image capture through fusion

NASA Technical Reports Server (NTRS)

Burt, Peter J.; Hanna, Keith; Kolczynski, Raymond J.

1993-01-01

Image fusion may be used to combine images from different sensors, such as IR and visible cameras, to obtain a single composite with extended information content. Fusion may also be used to combine multiple images from a given sensor to form a composite image in which information of interest is enhanced. We present a general method for performing image fusion and show that this method is effective for diverse fusion applications. We suggest that fusion may provide a powerful tool for enhanced image capture with broad utility in image processing and computer vision.

Sensor Fusion of Gaussian Mixtures for Ballistic Target Tracking in the Re-Entry Phase.

PubMed

Lu, Kelin; Zhou, Rui

2016-08-15

A sensor fusion methodology for the Gaussian mixtures model is proposed for ballistic target tracking with unknown ballistic coefficients. To improve the estimation accuracy, a track-to-track fusion architecture is proposed to fuse tracks provided by the local interacting multiple model filters. During the fusion process, the duplicate information is removed by considering the first order redundant information between the local tracks. With extensive simulations, we show that the proposed algorithm improves the tracking accuracy in ballistic target tracking in the re-entry phase applications.

Applications of the DOE/NASA wind turbine engineering information system

NASA Technical Reports Server (NTRS)

Neustadter, H. E.; Spera, D. A.

1981-01-01

A statistical analysis of data obtained from the Technology and Engineering Information Systems was made. The systems analyzed consist of the following elements: (1) sensors which measure critical parameters (e.g., wind speed and direction, output power, blade loads and component vibrations); (2) remote multiplexing units (RMUs) on each wind turbine which frequency-modulate, multiplex and transmit sensor outputs; (3) on-site instrumentation to record, process and display the sensor output; and (4) statistical analysis of data. Two examples of the capabilities of these systems are presented. The first illustrates the standardized format for application of statistical analysis to each directly measured parameter. The second shows the use of a model to estimate the variability of the rotor thrust loading, which is a derived parameter.

Privacy-preserving discovery of topic-based events from social sensor signals: an experimental study on Twitter.

PubMed

Nguyen, Duc T; Jung, Jai E

2014-01-01

Social network services (e.g., Twitter and Facebook) can be regarded as social sensors which can capture a number of events in the society. Particularly, in terms of time and space, various smart devices have improved the accessibility to the social network services. In this paper, we present a social software platform to detect a number of meaningful events from information diffusion patterns on such social network services. The most important feature is to process the social sensor signal for understanding social events and to support users to share relevant information along the social links. The platform has been applied to fetch and cluster tweets from Twitter into relevant categories to reveal hot topics.

Adaptive Sampling of Time Series During Remote Exploration

NASA Technical Reports Server (NTRS)

Thompson, David R.

2012-01-01

This work deals with the challenge of online adaptive data collection in a time series. A remote sensor or explorer agent adapts its rate of data collection in order to track anomalous events while obeying constraints on time and power. This problem is challenging because the agent has limited visibility (all its datapoints lie in the past) and limited control (it can only decide when to collect its next datapoint). This problem is treated from an information-theoretic perspective, fitting a probabilistic model to collected data and optimizing the future sampling strategy to maximize information gain. The performance characteristics of stationary and nonstationary Gaussian process models are compared. Self-throttling sensors could benefit environmental sensor networks and monitoring as well as robotic exploration. Explorer agents can improve performance by adjusting their data collection rate, preserving scarce power or bandwidth resources during uninteresting times while fully covering anomalous events of interest. For example, a remote earthquake sensor could conserve power by limiting its measurements during normal conditions and increasing its cadence during rare earthquake events. A similar capability could improve sensor platforms traversing a fixed trajectory, such as an exploration rover transect or a deep space flyby. These agents can adapt observation times to improve sample coverage during moments of rapid change. An adaptive sampling approach couples sensor autonomy, instrument interpretation, and sampling. The challenge is addressed as an active learning problem, which already has extensive theoretical treatment in the statistics and machine learning literature. A statistical Gaussian process (GP) model is employed to guide sample decisions that maximize information gain. Nonsta tion - ary (e.g., time-varying) covariance relationships permit the system to represent and track local anomalies, in contrast with current GP approaches. Most common GP models are stationary, e.g., the covariance relationships are time-invariant. In such cases, information gain is independent of previously collected data, and the optimal solution can always be computed in advance. Information-optimal sampling of a stationary GP time series thus reduces to even spacing, and such models are not appropriate for tracking localized anomalies. Additionally, GP model inference can be computationally expensive.

Helicopter synthetic vision based DVE processing for all phases of flight

NASA Astrophysics Data System (ADS)

O'Brien, Patrick; Baughman, David C.; Wallace, H. Bruce

2013-05-01

Helicopters experience nearly 10 times the accident rate of fixed wing platforms, due largely to the nature of their mission, frequently requiring operations in close proximity to terrain and obstacles. Degraded visual environments (DVE), including brownout or whiteout conditions generated by rotor downwash, result in loss of situational awareness during the most critical phase of flight, and contribute significantly to this accident rate. Considerable research into sensor and system solutions to address DVE has been conducted in recent years; however, the promise of a Synthetic Vision Avionics Backbone (SVAB) extends far beyond DVE, enabling improved situational awareness and mission effectiveness during all phases of flight and in all visibility conditions. The SVAB fuses sensor information with high resolution terrain databases and renders it in synthetic vision format for display to the crew. Honeywell was awarded the DARPA MFRF Technical Area 2 contract in 2011 to develop an SVAB1. This work includes creation of a common sensor interface, development of SVAB hardware and software, and flight demonstration on a Black Hawk helicopter. A "sensor agnostic" SVAB allows platform and mission diversity with efficient upgrade path, even while research continues into new and improved sensors for use in DVE conditions. Through careful integration of multiple sources of information such as sensors, terrain and obstacle databases, mission planning information, and aircraft state information, operations in all conditions and phases of flight can be enhanced. This paper describes the SVAB and its functionality resulting from the DARPA contract as well as Honeywell RD investment.

A neuro-inspired spike-based PID motor controller for multi-motor robots with low cost FPGAs.

PubMed

Jimenez-Fernandez, Angel; Jimenez-Moreno, Gabriel; Linares-Barranco, Alejandro; Dominguez-Morales, Manuel J; Paz-Vicente, Rafael; Civit-Balcells, Anton

2012-01-01

In this paper we present a neuro-inspired spike-based close-loop controller written in VHDL and implemented for FPGAs. This controller has been focused on controlling a DC motor speed, but only using spikes for information representation, processing and DC motor driving. It could be applied to other motors with proper driver adaptation. This controller architecture represents one of the latest layers in a Spiking Neural Network (SNN), which implements a bridge between robotics actuators and spike-based processing layers and sensors. The presented control system fuses actuation and sensors information as spikes streams, processing these spikes in hard real-time, implementing a massively parallel information processing system, through specialized spike-based circuits. This spike-based close-loop controller has been implemented into an AER platform, designed in our labs, that allows direct control of DC motors: the AER-Robot. Experimental results evidence the viability of the implementation of spike-based controllers, and hardware synthesis denotes low hardware requirements that allow replicating this controller in a high number of parallel controllers working together to allow a real-time robot control.

A Neuro-Inspired Spike-Based PID Motor Controller for Multi-Motor Robots with Low Cost FPGAs

PubMed Central

Jimenez-Fernandez, Angel; Jimenez-Moreno, Gabriel; Linares-Barranco, Alejandro; Dominguez-Morales, Manuel J.; Paz-Vicente, Rafael; Civit-Balcells, Anton

2012-01-01

In this paper we present a neuro-inspired spike-based close-loop controller written in VHDL and implemented for FPGAs. This controller has been focused on controlling a DC motor speed, but only using spikes for information representation, processing and DC motor driving. It could be applied to other motors with proper driver adaptation. This controller architecture represents one of the latest layers in a Spiking Neural Network (SNN), which implements a bridge between robotics actuators and spike-based processing layers and sensors. The presented control system fuses actuation and sensors information as spikes streams, processing these spikes in hard real-time, implementing a massively parallel information processing system, through specialized spike-based circuits. This spike-based close-loop controller has been implemented into an AER platform, designed in our labs, that allows direct control of DC motors: the AER-Robot. Experimental results evidence the viability of the implementation of spike-based controllers, and hardware synthesis denotes low hardware requirements that allow replicating this controller in a high number of parallel controllers working together to allow a real-time robot control. PMID:22666004

Minimizing Input-to-Output Latency in Virtual Environment

NASA Technical Reports Server (NTRS)

Adelstein, Bernard D.; Ellis, Stephen R.; Hill, Michael I.

2009-01-01

A method and apparatus were developed to minimize latency (time delay ) in virtual environment (VE) and other discrete- time computer-base d systems that require real-time display in response to sensor input s. Latency in such systems is due to the sum of the finite time requi red for information processing and communication within and between sensors, software, and displays.

Automated Welding System

NASA Technical Reports Server (NTRS)

Bayless, E. O.; Lawless, K. G.; Kurgan, C.; Nunes, A. C.; Graham, B. F.; Hoffman, D.; Jones, C. S.; Shepard, R.

1993-01-01

Fully automated variable-polarity plasma arc VPPA welding system developed at Marshall Space Flight Center. System eliminates defects caused by human error. Integrates many sensors with mathematical model of the weld and computer-controlled welding equipment. Sensors provide real-time information on geometry of weld bead, location of weld joint, and wire-feed entry. Mathematical model relates geometry of weld to critical parameters of welding process.

Integrating Sensor-Collected Intelligence

DTIC Science & Technology

2008-11-01

collecting, processing, data storage and fusion, and the dissemination of information collected by Intelligence, Surveillance, and Reconnaissance (ISR...Grid – Bandwidth Expansion (GIG-BE) program) to provide the capability to transfer data from sensors to accessible storage and satellite and airborne...based ISR is much more fragile. There was a purposeful drawdown of these systems following the Cold War and modernization programs were planned to

Design Principles for Rapid Prototyping Forces Sensors using 3D Printing.

PubMed

Kesner, Samuel B; Howe, Robert D

2011-07-21

Force sensors provide critical information for robot manipulators, manufacturing processes, and haptic interfaces. Commercial force sensors, however, are generally not adapted to specific system requirements, resulting in sensors with excess size, cost, and fragility. To overcome these issues, 3D printers can be used to create components for the quick and inexpensive development of force sensors. Limitations of this rapid prototyping technology, however, require specialized design principles. In this paper, we discuss techniques for rapidly developing simple force sensors, including selecting and attaching metal flexures, using inexpensive and simple displacement transducers, and 3D printing features to aid in assembly. These design methods are illustrated through the design and fabrication of a miniature force sensor for the tip of a robotic catheter system. The resulting force sensor prototype can measure forces with an accuracy of as low as 2% of the 10 N measurement range.

Development of a Dynamic Web Mapping Service for Vegetation Productivity Using Earth Observation and in situ Sensors in a Sensor Web Based Approach

PubMed Central

Kooistra, Lammert; Bergsma, Aldo; Chuma, Beatus; de Bruin, Sytze

2009-01-01

This paper describes the development of a sensor web based approach which combines earth observation and in situ sensor data to derive typical information offered by a dynamic web mapping service (WMS). A prototype has been developed which provides daily maps of vegetation productivity for the Netherlands with a spatial resolution of 250 m. Daily available MODIS surface reflectance products and meteorological parameters obtained through a Sensor Observation Service (SOS) were used as input for a vegetation productivity model. This paper presents the vegetation productivity model, the sensor data sources and the implementation of the automated processing facility. Finally, an evaluation is made of the opportunities and limitations of sensor web based approaches for the development of web services which combine both satellite and in situ sensor sources. PMID:22574019

The multi-queue model applied to random access protocol

NASA Astrophysics Data System (ADS)

Fan, Xinlong

2013-03-01

The connection of everything in a sensory and an intelligent way is a pursuit in smart environment. This paper introduces the engineered cell-sensors into the multi-agent systems to realize the smart environment. The seamless interface with the natural environment and strong information-processing ability of cell with the achievements of synthetic biology make the construction of engineered cell-sensors possible. However, the engineered cell-sensors are only simple-functional and unreliable computational entities. Therefore how to combine engineered cell-sensors with digital device is a key problem in order to realize the smart environment. We give the abstract structure and interaction modes of the engineered cell-sensors in order to introduce engineered cell-sensors into multi-agent systems. We believe that the introduction of engineered cell-sensors will push forward the development of the smart environment.

Common Criteria related security design patterns--validation on the intelligent sensor example designed for mine environment.

PubMed

Bialas, Andrzej

2010-01-01

The paper discusses the security issues of intelligent sensors that are able to measure and process data and communicate with other information technology (IT) devices or systems. Such sensors are often used in high risk applications. To improve their robustness, the sensor systems should be developed in a restricted way to provide them with assurance. One of assurance creation methodologies is Common Criteria (ISO/IEC 15408), used for IT products and systems. The contribution of the paper is a Common Criteria compliant and pattern-based method for the intelligent sensors security development. The paper concisely presents this method and its evaluation for the sensor detecting methane in a mine, focusing on the security problem of the intelligent sensor definition and solution. The aim of the validation is to evaluate and improve the introduced method.

Assessment Study on Sensors and Automation in the Industries of the Future. Reports on Industrial Controls, Information Processing, Automation, and Robotics

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

Bennett, Bonnie; Boddy, Mark; Doyle, Frank

This report presents the results of an expert study to identify research opportunities for Sensors & Automation, a sub-program of the U.S. Department of Energy (DOE) Industrial Technologies Program (ITP). The research opportunities are prioritized by realizable energy savings. The study encompasses the technology areas of industrial controls, information processing, automation, and robotics. These areas have been central areas of focus of many Industries of the Future (IOF) technology roadmaps. This report identifies opportunities for energy savings as a direct result of advances in these areas and also recognizes indirect means of achieving energy savings, such as product quality improvement,more » productivity improvement, and reduction of recycle.« less

Wireless Sensor Networks for Developmental and Flight Instrumentation

NASA Technical Reports Server (NTRS)

Alena, Richard; Figueroa, Fernando; Becker, Jeffrey; Foster, Mark; Wang, Ray; Gamudevelli, Suman; Studor, George

2011-01-01

Wireless sensor networks (WSN) based on the IEEE 802.15.4 Personal Area Network and ZigBee Pro 2007 standards are finding increasing use in home automation and smart energy markets providing a framework for interoperable software. The Wireless Connections in Space Project, funded by the NASA Engineering and Safety Center, is developing technology, metrics and requirements for next-generation spacecraft avionics incorporating wireless data transport. The team from Stennis Space Center and Mobitrum Corporation, working under a NASA SBIR grant, has developed techniques for embedding plug-and-play software into ZigBee WSN prototypes implementing the IEEE 1451 Transducer Electronic Datasheet (TEDS) standard. The TEDS provides meta-information regarding sensors such as serial number, calibration curve and operational status. Incorporation of TEDS into wireless sensors leads directly to building application level software that can recognize sensors at run-time, dynamically instantiating sensors as they are added or removed. The Ames Research Center team has been experimenting with this technology building demonstration prototypes for on-board health monitoring. Innovations in technology, software and process can lead to dramatic improvements for managing sensor systems applied to Developmental and Flight Instrumentation (DFI) aboard aerospace vehicles. A brief overview of the plug-and-play ZigBee WSN technology is presented along with specific targets for application within the aerospace DFI market. The software architecture for the sensor nodes incorporating the TEDS information is described along with the functions of the Network Capable Gateway processor which bridges 802.15.4 PAN to the TCP/IP network. Client application software connects to the Gateway and is used to display TEDS information and real-time sensor data values updated every few seconds, incorporating error detection and logging to help measure performance and reliability in relevant target environments. Test results from our prototype WSN running the Mobitrum software system are summarized and the implications to the scalability and reliability for DFI applications are discussed. Our demonstration system, incorporating sensors for life support system and structural health monitoring is described along with test results obtained by running the demonstration prototype in relevant environments such as the Wireless Habitat Testbed at Johnson Space Center in Houston. An operations concept for improved sensor process flow from design to flight test is outlined specific to the areas of Environmental Control and Life Support System performance characterization and structural health monitoring of human-rated spacecraft. This operations concept will be used to highlight the areas where WSN technology, particularly plug-and-play software based on IEEE 1451, can improve the current process, resulting in significant reductions in the technical effort, overall cost and schedule for providing DFI capability for future spacecraft. RELEASED -

Vision communications based on LED array and imaging sensor

NASA Astrophysics Data System (ADS)

Yoo, Jong-Ho; Jung, Sung-Yoon

2012-11-01

In this paper, we propose a brand new communication concept, called as "vision communication" based on LED array and image sensor. This system consists of LED array as a transmitter and digital device which include image sensor such as CCD and CMOS as receiver. In order to transmit data, the proposed communication scheme simultaneously uses the digital image processing and optical wireless communication scheme. Therefore, the cognitive communication scheme is possible with the help of recognition techniques used in vision system. By increasing data rate, our scheme can use LED array consisting of several multi-spectral LEDs. Because arranged each LED can emit multi-spectral optical signal such as visible, infrared and ultraviolet light, the increase of data rate is possible similar to WDM and MIMO skills used in traditional optical and wireless communications. In addition, this multi-spectral capability also makes it possible to avoid the optical noises in communication environment. In our vision communication scheme, the data packet is composed of Sync. data and information data. Sync. data is used to detect the transmitter area and calibrate the distorted image snapshots obtained by image sensor. By making the optical rate of LED array be same with the frame rate (frames per second) of image sensor, we can decode the information data included in each image snapshot based on image processing and optical wireless communication techniques. Through experiment based on practical test bed system, we confirm the feasibility of the proposed vision communications based on LED array and image sensor.

Remote Sensing: A valuable tool in the Forest Service decision making process. [in Utah

NASA Technical Reports Server (NTRS)

Stanton, F. L.

1975-01-01

Forest Service studies for integrating remotely sensed data into existing information systems highlight a need to: (1) re-examine present methods of collecting and organizing data, (2) develop an integrated information system for rapidly processing and interpreting data, (3) apply existing technological tools in new ways, and (4) provide accurate and timely information for making right management decisions. The Forest Service developed an integrated information system using remote sensors, microdensitometers, computer hardware and software, and interactive accessories. Their efforts substantially reduce the time it takes for collecting and processing data.

An integrated optical sensor for GMAW feedback control

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

Taylor, P.L.; Watkins, A.D.; Larsen, E.D.

1992-08-01

The integrated optical sensor (IOS) is a multifunction feedback control sensor for arc welding, that is computer automated and independent of significant operator interaction. It is based on three major ``off-the-shelf`` components: a charged coupled device (CCD) camera, a diode laser, and a processing computer. The sensor head is compact and lightweight to avoid interference with weld head mobility, hardened to survive the harsh operating environment, and free of specialized cooling and power requirements. The sensor is positioned behind the GMAW torch and measures weld pool position and width, standoff distance, and postweld centerline cooling rate. Weld pool position andmore » width are used in a feedback loop, by the weld controller, to track the weld pool relative to the weld joint, thus allowing compensation for such phenomena as arc blow. Sensor stand off distance is used in a feedback loop to control the contact tip to base metal distance during the welding process. Cooling rate information is used to infer the final metallurgical state of the weld bead and heat affected zone, thereby providing a means of controlling post weld mechanical properties.« less

An integrated optical sensor for GMAW feedback control

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

Taylor, P.L.; Watkins, A.D.; Larsen, E.D.

1992-01-01

The integrated optical sensor (IOS) is a multifunction feedback control sensor for arc welding, that is computer automated and independent of significant operator interaction. It is based on three major off-the-shelf'' components: a charged coupled device (CCD) camera, a diode laser, and a processing computer. The sensor head is compact and lightweight to avoid interference with weld head mobility, hardened to survive the harsh operating environment, and free of specialized cooling and power requirements. The sensor is positioned behind the GMAW torch and measures weld pool position and width, standoff distance, and postweld centerline cooling rate. Weld pool position andmore » width are used in a feedback loop, by the weld controller, to track the weld pool relative to the weld joint, thus allowing compensation for such phenomena as arc blow. Sensor stand off distance is used in a feedback loop to control the contact tip to base metal distance during the welding process. Cooling rate information is used to infer the final metallurgical state of the weld bead and heat affected zone, thereby providing a means of controlling post weld mechanical properties.« less

Fuzzy Logic Based Autonomous Parallel Parking System with Kalman Filtering

NASA Astrophysics Data System (ADS)

Panomruttanarug, Benjamas; Higuchi, Kohji

This paper presents an emulation of fuzzy logic control schemes for an autonomous parallel parking system in a backward maneuver. There are four infrared sensors sending the distance data to a microcontroller for generating an obstacle-free parking path. Two of them mounted on the front and rear wheels on the parking side are used as the inputs to the fuzzy rules to calculate a proper steering angle while backing. The other two attached to the front and rear ends serve for avoiding collision with other cars along the parking space. At the end of parking processes, the vehicle will be in line with other parked cars and positioned in the middle of the free space. Fuzzy rules are designed based upon a wall following process. Performance of the infrared sensors is improved using Kalman filtering. The design method needs extra information from ultrasonic sensors. Starting from modeling the ultrasonic sensor in 1-D state space forms, one makes use of the infrared sensor as a measurement to update the predicted values. Experimental results demonstrate the effectiveness of sensor improvement.

Feasibility of an anticipatory noncontact precrash restraint actuation system

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

Kercel, S.W.; Dress, W.B.

1995-12-31

The problem of providing an electronic warning of an impending crash to a precrash restraint system a fraction of a second before physical contact differs from more widely explored problems, such as providing several seconds of crash warning to a driver. One approach to precrash restraint sensing is to apply anticipatory system theory. This consists of nested simplified models of the system to be controlled and of the system`s environment. It requires sensory information to describe the ``current state`` of the system and the environment. The models use the sensory data to make a faster-than-real-time prediction about the near future.more » Anticipation theory is well founded but rarely used. A major problem is to extract real-time current-state information from inexpensive sensors. Providing current-state information to the nested models is the weakest element of the system. Therefore, sensors and real-time processing of sensor signals command the most attention in an assessment of system feasibility. This paper describes problem definition, potential ``showstoppers,`` and ways to overcome them. It includes experiments showing that inexpensive radar is a practical sensing element. It considers fast and inexpensive algorithms to extract information from sensor data.« less

A Forest Fire Sensor Web Concept with UAVSAR

NASA Astrophysics Data System (ADS)

Lou, Y.; Chien, S.; Clark, D.; Doubleday, J.; Muellerschoen, R.; Zheng, Y.

2008-12-01

We developed a forest fire sensor web concept with a UAVSAR-based smart sensor and onboard automated response capability that will allow us to monitor fire progression based on coarse initial information provided by an external source. This autonomous disturbance detection and monitoring system combines the unique capabilities of imaging radar with high throughput onboard processing technology and onboard automated response capability based on specific science algorithms. In this forest fire sensor web scenario, a fire is initially located by MODIS/RapidFire or a ground-based fire observer. This information is transmitted to the UAVSAR onboard automated response system (CASPER). CASPER generates a flight plan to cover the alerted fire area and executes the flight plan. The onboard processor generates the fuel load map from raw radar data, used with wind and elevation information, predicts the likely fire progression. CASPER then autonomously alters the flight plan to track the fire progression, providing this information to the fire fighting team on the ground. We can also relay the precise fire location to other remote sensing assets with autonomous response capability such as Earth Observation-1 (EO-1)'s hyper-spectral imager to acquire the fire data.

Machine processing of remotely sensed data; Proceedings of the Conference, Purdue University, West Lafayette, Ind., October 16-18, 1973

NASA Technical Reports Server (NTRS)

1973-01-01

Topics discussed include the management and processing of earth resources information, special-purpose processors for the machine processing of remotely sensed data, digital image registration by a mathematical programming technique, the use of remote-sensor data in land classification (in particular, the use of ERTS-1 multispectral scanning data), the use of remote-sensor data in geometrical transformations and mapping, earth resource measurement with the aid of ERTS-1 multispectral scanning data, the use of remote-sensor data in the classification of turbidity levels in coastal zones and in the identification of ecological anomalies, the problem of feature selection and the classification of objects in multispectral images, the estimation of proportions of certain categories of objects, and a number of special systems and techniques. Individual items are announced in this issue.

A stretchable strain sensor based on a metal nanoparticle thin film for human motion detection

NASA Astrophysics Data System (ADS)

Lee, Jaehwan; Kim, Sanghyeok; Lee, Jinjae; Yang, Daejong; Park, Byong Chon; Ryu, Seunghwa; Park, Inkyu

2014-09-01

Wearable strain sensors for human motion detection are being highlighted in various fields such as medical, entertainment and sports industry. In this paper, we propose a new type of stretchable strain sensor that can detect both tensile and compressive strains and can be fabricated by a very simple process. A silver nanoparticle (Ag NP) thin film patterned on the polydimethylsiloxane (PDMS) stamp by a single-step direct transfer process is used as the strain sensing material. The working principle is the change in the electrical resistance caused by the opening/closure of micro-cracks under mechanical deformation. The fabricated stretchable strain sensor shows highly sensitive and durable sensing performances in various tensile/compressive strains, long-term cyclic loading and relaxation tests. We demonstrate the applications of our stretchable strain sensors such as flexible pressure sensors and wearable human motion detection devices with high sensitivity, response speed and mechanical robustness.Wearable strain sensors for human motion detection are being highlighted in various fields such as medical, entertainment and sports industry. In this paper, we propose a new type of stretchable strain sensor that can detect both tensile and compressive strains and can be fabricated by a very simple process. A silver nanoparticle (Ag NP) thin film patterned on the polydimethylsiloxane (PDMS) stamp by a single-step direct transfer process is used as the strain sensing material. The working principle is the change in the electrical resistance caused by the opening/closure of micro-cracks under mechanical deformation. The fabricated stretchable strain sensor shows highly sensitive and durable sensing performances in various tensile/compressive strains, long-term cyclic loading and relaxation tests. We demonstrate the applications of our stretchable strain sensors such as flexible pressure sensors and wearable human motion detection devices with high sensitivity, response speed and mechanical robustness. Electronic supplementary information (ESI) available. See DOI: 10.1039/c4nr03295k

A Global Lake Ecological Observatory Network (GLEON) for synthesising high-frequency sensor data for validation of deterministic ecological models

USGS Publications Warehouse

David, Hamilton P; Carey, Cayelan C.; Arvola, Lauri; Arzberger, Peter; Brewer, Carol A.; Cole, Jon J; Gaiser, Evelyn; Hanson, Paul C.; Ibelings, Bas W; Jennings, Eleanor; Kratz, Tim K; Lin, Fang-Pang; McBride, Christopher G.; de Motta Marques, David; Muraoka, Kohji; Nishri, Ami; Qin, Boqiang; Read, Jordan S.; Rose, Kevin C.; Ryder, Elizabeth; Weathers, Kathleen C.; Zhu, Guangwei; Trolle, Dennis; Brookes, Justin D

2014-01-01

A Global Lake Ecological Observatory Network (GLEON; www.gleon.org) has formed to provide a coordinated response to the need for scientific understanding of lake processes, utilising technological advances available from autonomous sensors. The organisation embraces a grassroots approach to engage researchers from varying disciplines, sites spanning geographic and ecological gradients, and novel sensor and cyberinfrastructure to synthesise high-frequency lake data at scales ranging from local to global. The high-frequency data provide a platform to rigorously validate process- based ecological models because model simulation time steps are better aligned with sensor measurements than with lower-frequency, manual samples. Two case studies from Trout Bog, Wisconsin, USA, and Lake Rotoehu, North Island, New Zealand, are presented to demonstrate that in the past, ecological model outputs (e.g., temperature, chlorophyll) have been relatively poorly validated based on a limited number of directly comparable measurements, both in time and space. The case studies demonstrate some of the difficulties of mapping sensor measurements directly to model state variable outputs as well as the opportunities to use deviations between sensor measurements and model simulations to better inform process understanding. Well-validated ecological models provide a mechanism to extrapolate high-frequency sensor data in space and time, thereby potentially creating a fully 3-dimensional simulation of key variables of interest.

An integrated multi-sensor fusion-based deep feature learning approach for rotating machinery diagnosis

NASA Astrophysics Data System (ADS)

Liu, Jie; Hu, Youmin; Wang, Yan; Wu, Bo; Fan, Jikai; Hu, Zhongxu

2018-05-01

The diagnosis of complicated fault severity problems in rotating machinery systems is an important issue that affects the productivity and quality of manufacturing processes and industrial applications. However, it usually suffers from several deficiencies. (1) A considerable degree of prior knowledge and expertise is required to not only extract and select specific features from raw sensor signals, and but also choose a suitable fusion for sensor information. (2) Traditional artificial neural networks with shallow architectures are usually adopted and they have a limited ability to learn the complex and variable operating conditions. In multi-sensor-based diagnosis applications in particular, massive high-dimensional and high-volume raw sensor signals need to be processed. In this paper, an integrated multi-sensor fusion-based deep feature learning (IMSFDFL) approach is developed to identify the fault severity in rotating machinery processes. First, traditional statistics and energy spectrum features are extracted from multiple sensors with multiple channels and combined. Then, a fused feature vector is constructed from all of the acquisition channels. Further, deep feature learning with stacked auto-encoders is used to obtain the deep features. Finally, the traditional softmax model is applied to identify the fault severity. The effectiveness of the proposed IMSFDFL approach is primarily verified by a one-stage gearbox experimental platform that uses several accelerometers under different operating conditions. This approach can identify fault severity more effectively than the traditional approaches.

Falling Person Detection Using Multi-Sensor Signal Processing

NASA Astrophysics Data System (ADS)

Toreyin, B. Ugur; Soyer, A. Birey; Onaran, Ibrahim; Cetin, E. Enis

2007-12-01

Falls are one of the most important problems for frail and elderly people living independently. Early detection of falls is vital to provide a safe and active lifestyle for elderly. Sound, passive infrared (PIR) and vibration sensors can be placed in a supportive home environment to provide information about daily activities of an elderly person. In this paper, signals produced by sound, PIR and vibration sensors are simultaneously analyzed to detect falls. Hidden Markov Models are trained for regular and unusual activities of an elderly person and a pet for each sensor signal. Decisions of HMMs are fused together to reach a final decision.

An Autonomous Sensor System Architecture for Active Flow and Noise Control Feedback

NASA Technical Reports Server (NTRS)

Humphreys, William M, Jr.; Culliton, William G.

2008-01-01

Multi-channel sensor fusion represents a powerful technique to simply and efficiently extract information from complex phenomena. While the technique has traditionally been used for military target tracking and situational awareness, a study has been successfully completed that demonstrates that sensor fusion can be applied equally well to aerodynamic applications. A prototype autonomous hardware processor was successfully designed and used to detect in real-time the two-dimensional flow reattachment location generated by a simple separated-flow wind tunnel model. The success of this demonstration illustrates the feasibility of using autonomous sensor processing architectures to enhance flow control feedback signal generation.

Fully integrated wearable sensor arrays for multiplexed in situ perspiration analysis

DOE PAGES

Gao, Wei; Emaminejad, Sam; Nyein, Hnin Yin Yin; ...

2016-01-27

We report that wearable sensor technologies are essential to the realization of personalized medicine through continuously monitoring an individual’s state of health. Sampling human sweat, which is rich in physiological information13, could enable non-invasive monitoring. Previously reported sweat-based and other noninvasive biosensors either can only monitor a single analyte at a time or lack on-site signal processing circuitry and sensor calibration mechanisms for accurate analysis of the physiological state14–18. Given the complexity of sweat secretion, simultaneous and multiplexed screening of target biomarkers is critical and requires full system integration to ensure the accuracy of measurements. Here we present a mechanicallymore » flexible and fully integrated (that is, no external analysis is needed) sensor array for multiplexed in situ perspiration analysis, which simultaneously and selectively measures sweat metabolites (such as glucose and lactate) and electrolytes (such as sodium and potassium ions), as well as the skin temperature (to calibrate the response of the sensors). Lastly, our work bridges the technological gap between signal transduction, conditioning (amplification and filtering), processing and wireless transmission in wearable biosensors by merging plasticbased sensors that interface with the skin with silicon integrated circuits consolidated on a flexible circuit board for complex signal processing.« less

Fully integrated wearable sensor arrays for multiplexed in situ perspiration analysis

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

Gao, Wei; Emaminejad, Sam; Nyein, Hnin Yin Yin

We report that wearable sensor technologies are essential to the realization of personalized medicine through continuously monitoring an individual’s state of health. Sampling human sweat, which is rich in physiological information13, could enable non-invasive monitoring. Previously reported sweat-based and other noninvasive biosensors either can only monitor a single analyte at a time or lack on-site signal processing circuitry and sensor calibration mechanisms for accurate analysis of the physiological state14–18. Given the complexity of sweat secretion, simultaneous and multiplexed screening of target biomarkers is critical and requires full system integration to ensure the accuracy of measurements. Here we present a mechanicallymore » flexible and fully integrated (that is, no external analysis is needed) sensor array for multiplexed in situ perspiration analysis, which simultaneously and selectively measures sweat metabolites (such as glucose and lactate) and electrolytes (such as sodium and potassium ions), as well as the skin temperature (to calibrate the response of the sensors). Lastly, our work bridges the technological gap between signal transduction, conditioning (amplification and filtering), processing and wireless transmission in wearable biosensors by merging plasticbased sensors that interface with the skin with silicon integrated circuits consolidated on a flexible circuit board for complex signal processing.« less

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

NASA Astrophysics Data System (ADS)

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

2003-12-01

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

Generic Sensor Data Fusion Services for Web-enabled Environmental Risk Management and Decision-Support Systems

NASA Astrophysics Data System (ADS)

Sabeur, Zoheir; Middleton, Stuart; Veres, Galina; Zlatev, Zlatko; Salvo, Nicola

2010-05-01

The advancement of smart sensor technology in the last few years has led to an increase in the deployment of affordable sensors for monitoring the environment around Europe. This is generating large amounts of sensor observation information and inevitably leading to problems about how to manage large volumes of data as well as making sense out the data for decision-making. In addition, the various European Directives (Water Framework Diectives, Bathing Water Directives, Habitat Directives, etc.. ) which regulate human activities in the environment and the INSPIRE Directive on spatial information management regulations have implicitely led the designated European Member States environment agencies and authorities to put in place new sensor monitoring infrastructure and share information about environmental regions under their statutory responsibilities. They will need to work cross border and collectively reach environmental quality standards. They will also need to regularly report to the EC on the quality of the environments of which they are responsible and make such information accessible to the members of the public. In recent years, early pioneering work on the design of service oriented architecture using sensor networks has been achieved. Information web-services infrastructure using existing data catalogues and web-GIS map services can now be enriched with the deployment of new sensor observation and data fusion and modelling services using OGC standards. The deployment of the new services which describe sensor observations and intelligent data-processing using data fusion techniques can now be implemented and provide added value information with spatial-temporal uncertainties to the next generation of decision support service systems. The new decision support service systems have become key to implement across Europe in order to comply with EU environmental regulations and INSPIRE. In this paper, data fusion services using OGC standards with sensor observation data streams are described in context of a geo-distributed service infrastructure specialising in multiple environmental risk management and decision-support. The sensor data fusion services are deployed and validated in two use cases. These are respectively concerned with: 1) Microbial risks forecast in bathing waters; and 2) Geohazards in urban zones during underground tunneling activities. This research was initiated in the SANY Integrated Project(www.sany-ip.org) and funded by the European Commission under the 6th Framework Programme.

SensorWeb 3G: Extending On-Orbit Sensor Capabilities to Enable Near Realtime User Configurability

NASA Technical Reports Server (NTRS)

Mandl, Daniel; Cappelaere, Pat; Frye, Stuart; Sohlberg, Rob; Ly, Vuong; Chien, Steve; Tran, Daniel; Davies, Ashley; Sullivan, Don; Ames, Troy;

Soft sensor development for Mooney viscosity prediction in rubber mixing process based on GMMDJITGPR algorithm

NASA Astrophysics Data System (ADS)

Yang, Kai; Chen, Xiangguang; Wang, Li; Jin, Huaiping

2017-01-01

In rubber mixing process, the key parameter (Mooney viscosity), which is used to evaluate the property of the product, can only be obtained with 4-6h delay offline. It is quite helpful for the industry, if the parameter can be estimate on line. Various data driven soft sensors have been used to prediction in the rubber mixing. However, it always not functions well due to the phase and nonlinear property in the process. The purpose of this paper is to develop an efficient soft sensing algorithm to solve the problem. Based on the proposed GMMD local sample selecting criterion, the phase information is extracted in the local modeling. Using the Gaussian local modeling method within Just-in-time (JIT) learning framework, nonlinearity of the process is well handled. Efficiency of the new method is verified by comparing the performance with various mainstream soft sensors, using the samples from real industrial rubber mixing process.

Dynamic Feed Control For Injection Molding

DOEpatents

Kazmer, David O.

1996-09-17

The invention provides methods and apparatus in which mold material flows through a gate into a mold cavity that defines the shape of a desired part. An adjustable valve is provided that is operable to change dynamically the effective size of the gate to control the flow of mold material through the gate. The valve is adjustable while the mold material is flowing through the gate into the mold cavity. A sensor is provided for sensing a process condition while the part is being molded. During molding, the valve is adjusted based at least in part on information from the sensor. In the preferred embodiment, the adjustable valve is controlled by a digital computer, which includes circuitry for acquiring data from the sensor, processing circuitry for computing a desired position of the valve based on the data from the sensor and a control data file containing target process conditions, and control circuitry for generating signals to control a valve driver to adjust the position of the valve. More complex embodiments include a plurality of gates, sensors, and controllable valves. Each valve is individually controllable so that process conditions corresponding to each gate can be adjusted independently. This allows for great flexibility in the control of injection molding to produce complex, high-quality parts.

Proposal of Self-Learning and Recognition System of Facial Expression

NASA Astrophysics Data System (ADS)

Ogawa, Yukihiro; Kato, Kunihito; Yamamoto, Kazuhiko

We describe realization of more complicated function by using the information acquired from some equipped unripe functions. The self-learning and recognition system of the human facial expression, which achieved under the natural relation between human and robot, are proposed. The robot with this system can understand human facial expressions and behave according to their facial expressions after the completion of learning process. The system modelled after the process that a baby learns his/her parents’ facial expressions. Equipping the robot with a camera the system can get face images and equipping the CdS sensors on the robot’s head the robot can get the information of human action. Using the information of these sensors, the robot can get feature of each facial expression. After self-learning is completed, when a person changed his facial expression in front of the robot, the robot operates actions under the relevant facial expression.

Wild life passer species recognition from a technical passage through data fusion of a wireless sensor network

NASA Astrophysics Data System (ADS)

Gazis, A.; Katsiri, E.

2017-09-01

This paper presents a Wireless Sensor Network (WSN) system which was created as a project about protecting wildlife using sensor networks following the assistance of the department of Electrical and Computer Engineering of the Democritus University of Thrace. An automated process was implemented, regarding the recognition of a passenger (ie human, wolf, bear, etc.) traversing a box-shaped underground passage, such as the ones located along main highways fusing Width, Height and Weight values. These were measured using low-cost distance (beam) and weight (S-type load) micro-sensors and stored in a central repository. Moreover, the information provided by the WSN was analyzed, via a variety of methods including a neural pattern recognition network as well as clustering algorithms, which were able to recognize the kind of passenger, with certainty scores over 90%. The main concern, regarding the future, is the evaluation of these passages in respect to their effectiveness, i.e. whether they are frequently utilized by animals. This information was further analysed by appropriate information systems, in order to provide insights about the effectiveness of such mitigation structures.

A magnetic/fluorometric bimodal sensor based on a carbon dots-MnO2 platform for glutathione detection

NASA Astrophysics Data System (ADS)

Xu, Yang; Chen, Xi; Chai, Ran; Xing, Chengfen; Li, Huanrong; Yin, Xue-Bo

2016-07-01

A novel magnetic/fluorometric bimodal sensor was built from carbon dots (CDs) and MnO2. The resulting sensor was sensitive to glutathione (GSH), leading to apparent enhancement of magnetic resonance (MR) and fluorescence signals along with visual changes. The bimodal detection strategy is based on the decomposition of the CDs-MnO2 through a redox reaction between GSH and MnO2. This process causes the transformation from non-MR-active MnO2 to MR-active Mn2+, and is accompanied by fluorescence restoration of CDs. Compared with a range of other CDs, the polyethylenimine (PEI) passivated CDs (denoted as pCDs) were suitable for detection due to their positive surface potential. Cross-validation between MR and fluorescence provided detailed information regarding the MnO2 reduction process, and revealed the three distinct stages of the redox process. Thus, the design of a CD-based sensor for the magnetic/fluorometric bimodal detection of GSH was emphasized for the first time. This platform showed a detection limit of 0.6 μM with a linear range of 1-200 μM in the fluorescence mode, while the MR mode exhibited a linear range of 5-200 μM and a GSH detection limit of 2.8 μM with a visible change being observed rapidly at 1 μM in the MR images. Furthermore, the introduction of the MR mode allowed the biothiols to be easily identified. The integration of CD fluorescence with an MR response was demonstrated to be promising for providing detailed information and discriminating power, and therefore extend the application of CDs in sensing and imaging.A novel magnetic/fluorometric bimodal sensor was built from carbon dots (CDs) and MnO2. The resulting sensor was sensitive to glutathione (GSH), leading to apparent enhancement of magnetic resonance (MR) and fluorescence signals along with visual changes. The bimodal detection strategy is based on the decomposition of the CDs-MnO2 through a redox reaction between GSH and MnO2. This process causes the transformation from non-MR-active MnO2 to MR-active Mn2+, and is accompanied by fluorescence restoration of CDs. Compared with a range of other CDs, the polyethylenimine (PEI) passivated CDs (denoted as pCDs) were suitable for detection due to their positive surface potential. Cross-validation between MR and fluorescence provided detailed information regarding the MnO2 reduction process, and revealed the three distinct stages of the redox process. Thus, the design of a CD-based sensor for the magnetic/fluorometric bimodal detection of GSH was emphasized for the first time. This platform showed a detection limit of 0.6 μM with a linear range of 1-200 μM in the fluorescence mode, while the MR mode exhibited a linear range of 5-200 μM and a GSH detection limit of 2.8 μM with a visible change being observed rapidly at 1 μM in the MR images. Furthermore, the introduction of the MR mode allowed the biothiols to be easily identified. The integration of CD fluorescence with an MR response was demonstrated to be promising for providing detailed information and discriminating power, and therefore extend the application of CDs in sensing and imaging. Electronic supplementary information (ESI) available. See DOI: 10.1039/c6nr03129c

Fault-tolerant reactor protection system

DOEpatents

Gaubatz, Donald C.

1997-01-01

A reactor protection system having four divisions, with quad redundant sensors for each scram parameter providing input to four independent microprocessor-based electronic chassis. Each electronic chassis acquires the scram parameter data from its own sensor, digitizes the information, and then transmits the sensor reading to the other three electronic chassis via optical fibers. To increase system availability and reduce false scrams, the reactor protection system employs two levels of voting on a need for reactor scram. The electronic chassis perform software divisional data processing, vote 2/3 with spare based upon information from all four sensors, and send the divisional scram signals to the hardware logic panel, which performs a 2/4 division vote on whether or not to initiate a reactor scram. Each chassis makes a divisional scram decision based on data from all sensors. Each division performs independently of the others (asynchronous operation). All communications between the divisions are asynchronous. Each chassis substitutes its own spare sensor reading in the 2/3 vote if a sensor reading from one of the other chassis is faulty or missing. Therefore the presence of at least two valid sensor readings in excess of a set point is required before terminating the output to the hardware logic of a scram inhibition signal even when one of the four sensors is faulty or when one of the divisions is out of service.

Fault-tolerant reactor protection system

DOEpatents

Gaubatz, D.C.

1997-04-15

A reactor protection system is disclosed having four divisions, with quad redundant sensors for each scram parameter providing input to four independent microprocessor-based electronic chassis. Each electronic chassis acquires the scram parameter data from its own sensor, digitizes the information, and then transmits the sensor reading to the other three electronic chassis via optical fibers. To increase system availability and reduce false scrams, the reactor protection system employs two levels of voting on a need for reactor scram. The electronic chassis perform software divisional data processing, vote 2/3 with spare based upon information from all four sensors, and send the divisional scram signals to the hardware logic panel, which performs a 2/4 division vote on whether or not to initiate a reactor scram. Each chassis makes a divisional scram decision based on data from all sensors. Each division performs independently of the others (asynchronous operation). All communications between the divisions are asynchronous. Each chassis substitutes its own spare sensor reading in the 2/3 vote if a sensor reading from one of the other chassis is faulty or missing. Therefore the presence of at least two valid sensor readings in excess of a set point is required before terminating the output to the hardware logic of a scram inhibition signal even when one of the four sensors is faulty or when one of the divisions is out of service. 16 figs.

Application of remote sensors in coastal zone observations

NASA Technical Reports Server (NTRS)

Caillat, J. M.; Elachi, C.; Brown, W. E., Jr.

1975-01-01

A review of processes taking place along coastlines and their biological consideration led to the determination of the elements which are required in the study of coastal structures and which are needed for better utilization of the resources from the oceans. The processes considered include waves, currents, and their influence on the erosion of coastal structures. Biological considerations include coastal fisheries, estuaries, and tidal marshes. Various remote sensors were analyzed for the information which they can provide and sites were proposed where a general ocean-observation plan could be tested.

Automating the Processing of Earth Observation Data

NASA Technical Reports Server (NTRS)

Golden, Keith; Pang, Wan-Lin; Nemani, Ramakrishna; Votava, Petr

2003-01-01

NASA s vision for Earth science is to build a "sensor web": an adaptive array of heterogeneous satellites and other sensors that will track important events, such as storms, and provide real-time information about the state of the Earth to a wide variety of customers. Achieving this vision will require automation not only in the scheduling of the observations but also in the processing of the resulting data. To address this need, we are developing a planner-based agent to automatically generate and execute data-flow programs to produce the requested data products.

Rodent wearable ultrasound system for wireless neural recording.

PubMed

Piech, David K; Kay, Joshua E; Boser, Bernhard E; Maharbiz, Michel M

2017-07-01

Advances in minimally-invasive, distributed biological interface nodes enable possibilities for networks of sensors and actuators to connect the brain with external devices. The recent development of the neural dust sensor mote has shown that utilizing ultrasound backscatter communication enables untethered sub-mm neural recording devices. These implanted sensor motes require a wearable external ultrasound interrogation device to enable in-vivo, freely-behaving neural interface experiments. However, minimizing the complexity and size of the implanted sensors shifts the power and processing burden to the external interrogator. In this paper, we present an ultrasound backscatter interrogator that supports real-time backscatter processing in a rodent-wearable, completely wireless device. We demonstrate a generic digital encoding scheme which is intended for transmitting neural information. The system integrates a front-end ultrasonic interface ASIC with off-the-shelf components to enable a highly compact ultrasound interrogation device intended for rodent neural interface experiments but applicable to other model systems.

Pedestrian recognition using automotive radar sensors

NASA Astrophysics Data System (ADS)

Bartsch, A.; Fitzek, F.; Rasshofer, R. H.

2012-09-01

The application of modern series production automotive radar sensors to pedestrian recognition is an important topic in research on future driver assistance systems. The aim of this paper is to understand the potential and limits of such sensors in pedestrian recognition. This knowledge could be used to develop next generation radar sensors with improved pedestrian recognition capabilities. A new raw radar data signal processing algorithm is proposed that allows deep insights into the object classification process. The impact of raw radar data properties can be directly observed in every layer of the classification system by avoiding machine learning and tracking. This gives information on the limiting factors of raw radar data in terms of classification decision making. To accomplish the very challenging distinction between pedestrians and static objects, five significant and stable object features from the spatial distribution and Doppler information are found. Experimental results with data from a 77 GHz automotive radar sensor show that over 95% of pedestrians can be classified correctly under optimal conditions, which is compareable to modern machine learning systems. The impact of the pedestrian's direction of movement, occlusion, antenna beam elevation angle, linear vehicle movement, and other factors are investigated and discussed. The results show that under real life conditions, radar only based pedestrian recognition is limited due to insufficient Doppler frequency and spatial resolution as well as antenna side lobe effects.

A different approach for the analysis of grapes: Using the skin as sensing element.

PubMed

Muñoz, Raquel; García-Hernández, Celia; Medina-Plaza, Cristina; García-Cabezón, Cristina; Fernández-Escudero, J A; Barajas, Enrique; Medrano, Germán; Rodriguez-Méndez, María Luz

2018-05-01

In this work, an alternative method to monitor the phenolic maturity of grapes was developed. In this approach, the skins of grapes were used to cover the surface of carbon paste electrodes and the voltammetric signals obtained with the skin-modified sensors were used to obtain information about the phenolic content of the skins. These sensors could easily detect differences in the phenolic composition of different Spanish varieties of grapes (Mencía, Prieto Picudo and Juan García). Moreover, sensors were able to monitor changes in the phenolic content throughout the ripening process from véraison until harvest. Using PLS-1 (Partial Least Squares), correlations were established between the voltammetric signals registered with the skin-modified sensors and the phenolic content measured by classical methods (Glories or Total Polyphenol Index). PLS-1 models provided additional information about Brix degree, density or sugar content, which usually used to establish the harvesting date. The quality of the correlations was influenced by the maturation process and the structural and mechanical skin properties. Thus the skin sensors fabricated with Juan García and Prieto Picudo grapes (that showed faster polyphenolic maturation and a higher amount of extractable polyphenols than Mencía), showed good correlations and therefore could be used to monitor the ripening. Copyright © 2018 Elsevier Ltd. All rights reserved.

Lightweight Sensor Authentication Scheme for Energy Efficiency in Ubiquitous Computing Environments.

PubMed

Lee, Jaeseung; Sung, Yunsick; Park, Jong Hyuk

2016-12-01

The Internet of Things (IoT) is the intelligent technologies and services that mutually communicate information between humans and devices or between Internet-based devices. In IoT environments, various device information is collected from the user for intelligent technologies and services that control the devices. Recently, wireless sensor networks based on IoT environments are being used in sectors as diverse as medicine, the military, and commerce. Specifically, sensor techniques that collect relevant area data via mini-sensors after distributing smart dust in inaccessible areas like forests or military zones have been embraced as the future of information technology. IoT environments that utilize smart dust are composed of the sensor nodes that detect data using wireless sensors and transmit the detected data to middle nodes. Currently, since the sensors used in these environments are composed of mini-hardware, they have limited memory, processing power, and energy, and a variety of research that aims to make the best use of these limited resources is progressing. This paper proposes a method to utilize these resources while considering energy efficiency, and suggests lightweight mutual verification and key exchange methods based on a hash function that has no restrictions on operation quantity, velocity, and storage space. This study verifies the security and energy efficiency of this method through security analysis and function evaluation, comparing with existing approaches. The proposed method has great value in its applicability as a lightweight security technology for IoT environments.

Lightweight Sensor Authentication Scheme for Energy Efficiency in Ubiquitous Computing Environments

PubMed Central

Lee, Jaeseung; Sung, Yunsick; Park, Jong Hyuk

2016-01-01

The Internet of Things (IoT) is the intelligent technologies and services that mutually communicate information between humans and devices or between Internet-based devices. In IoT environments, various device information is collected from the user for intelligent technologies and services that control the devices. Recently, wireless sensor networks based on IoT environments are being used in sectors as diverse as medicine, the military, and commerce. Specifically, sensor techniques that collect relevant area data via mini-sensors after distributing smart dust in inaccessible areas like forests or military zones have been embraced as the future of information technology. IoT environments that utilize smart dust are composed of the sensor nodes that detect data using wireless sensors and transmit the detected data to middle nodes. Currently, since the sensors used in these environments are composed of mini-hardware, they have limited memory, processing power, and energy, and a variety of research that aims to make the best use of these limited resources is progressing. This paper proposes a method to utilize these resources while considering energy efficiency, and suggests lightweight mutual verification and key exchange methods based on a hash function that has no restrictions on operation quantity, velocity, and storage space. This study verifies the security and energy efficiency of this method through security analysis and function evaluation, comparing with existing approaches. The proposed method has great value in its applicability as a lightweight security technology for IoT environments. PMID:27916962

Optimal rotation sequences for active perception

NASA Astrophysics Data System (ADS)

Nakath, David; Rachuy, Carsten; Clemens, Joachim; Schill, Kerstin

2016-05-01

One major objective of autonomous systems navigating in dynamic environments is gathering information needed for self localization, decision making, and path planning. To account for this, such systems are usually equipped with multiple types of sensors. As these sensors often have a limited field of view and a fixed orientation, the task of active perception breaks down to the problem of calculating alignment sequences which maximize the information gain regarding expected measurements. Action sequences that rotate the system according to the calculated optimal patterns then have to be generated. In this paper we present an approach for calculating these sequences for an autonomous system equipped with multiple sensors. We use a particle filter for multi- sensor fusion and state estimation. The planning task is modeled as a Markov decision process (MDP), where the system decides in each step, what actions to perform next. The optimal control policy, which provides the best action depending on the current estimated state, maximizes the expected cumulative reward. The latter is computed from the expected information gain of all sensors over time using value iteration. The algorithm is applied to a manifold representation of the joint space of rotation and time. We show the performance of the approach in a spacecraft navigation scenario where the information gain is changing over time, caused by the dynamic environment and the continuous movement of the spacecraft

Real-Time Digital Signal Processing Based on FPGAs for Electronic Skin Implementation †

PubMed Central

Ibrahim, Ali; Gastaldo, Paolo; Chible, Hussein; Valle, Maurizio

2017-01-01

Enabling touch-sensing capability would help appliances understand interaction behaviors with their surroundings. Many recent studies are focusing on the development of electronic skin because of its necessity in various application domains, namely autonomous artificial intelligence (e.g., robots), biomedical instrumentation, and replacement prosthetic devices. An essential task of the electronic skin system is to locally process the tactile data and send structured information either to mimic human skin or to respond to the application demands. The electronic skin must be fabricated together with an embedded electronic system which has the role of acquiring the tactile data, processing, and extracting structured information. On the other hand, processing tactile data requires efficient methods to extract meaningful information from raw sensor data. Machine learning represents an effective method for data analysis in many domains: it has recently demonstrated its effectiveness in processing tactile sensor data. In this framework, this paper presents the implementation of digital signal processing based on FPGAs for tactile data processing. It provides the implementation of a tensorial kernel function for a machine learning approach. Implementation results are assessed by highlighting the FPGA resource utilization and power consumption. Results demonstrate the feasibility of the proposed implementation when real-time classification of input touch modalities are targeted. PMID:28287448

Real-Time Digital Signal Processing Based on FPGAs for Electronic Skin Implementation.

PubMed

Ibrahim, Ali; Gastaldo, Paolo; Chible, Hussein; Valle, Maurizio

2017-03-10

Enabling touch-sensing capability would help appliances understand interaction behaviors with their surroundings. Many recent studies are focusing on the development of electronic skin because of its necessity in various application domains, namely autonomous artificial intelligence (e.g., robots), biomedical instrumentation, and replacement prosthetic devices. An essential task of the electronic skin system is to locally process the tactile data and send structured information either to mimic human skin or to respond to the application demands. The electronic skin must be fabricated together with an embedded electronic system which has the role of acquiring the tactile data, processing, and extracting structured information. On the other hand, processing tactile data requires efficient methods to extract meaningful information from raw sensor data. Machine learning represents an effective method for data analysis in many domains: it has recently demonstrated its effectiveness in processing tactile sensor data. In this framework, this paper presents the implementation of digital signal processing based on FPGAs for tactile data processing. It provides the implementation of a tensorial kernel function for a machine learning approach. Implementation results are assessed by highlighting the FPGA resource utilization and power consumption. Results demonstrate the feasibility of the proposed implementation when real-time classification of input touch modalities are targeted.

Design of an auto change mechanism and intelligent gripper for the space station

NASA Technical Reports Server (NTRS)

Dehoff, Paul H.; Naik, Dipak P.

1989-01-01

Robot gripping of objects in space is inherently demanding and dangerous and nowhere is this more clearly reflected than in the design of the robot gripper. An object which escapes the gripper in a micro g environment is launched not dropped. To prevent this, the gripper must have sensors and signal processing to determine that the object is properly grasped, e.g., grip points and gripping forces and, if not, to provide information to the robot to enable closed loop corrections to be made. The sensors and sensor strategies employed in the NASA/GSFC Split-Rail Parallel Gripper are described. Objectives and requirements are given followed by the design of the sensor suite, sensor fusion techniques and supporting algorithms.

Distributed resource allocation under communication constraints

NASA Astrophysics Data System (ADS)

Dodin, Pierre; Nimier, Vincent

2001-03-01

This paper deals with a study of the multi-sensor management problem for multi-target tracking. The collaboration between many sensors observing the same target means that they are able to fuse their data during the information process. Then one must take into account this possibility to compute the optimal association sensors-target at each step of time. In order to solve this problem for real large scale system, one must both consider the information aspect and the control aspect of the problem. To unify these problems, one possibility is to use a decentralized filtering algorithm locally driven by an assignment algorithm. The decentralized filtering algorithm we use in our model is the filtering algorithm of Grime, which relaxes the usual full-connected hypothesis. By full-connected, one means that the information in a full-connected system is totally distributed everywhere at the same moment, which is unacceptable for a real large scale system. We modelize the distributed assignment decision with the help of a greedy algorithm. Each sensor performs a global optimization, in order to estimate other information sets. A consequence of the relaxation of the full- connected hypothesis is that the sensors' information set are not the same at each step of time, producing an information dis- symmetry in the system. The assignment algorithm uses a local knowledge of this dis-symmetry. By testing the reactions and the coherence of the local assignment decisions of our system, against maneuvering targets, we show that it is still possible to manage with decentralized assignment control even though the system is not full-connected.

Interferometry-based free space communication and information processing

NASA Astrophysics Data System (ADS)

Arain, Muzammil Arshad

This dissertation studies, analyzes, and experimentally demonstrates the innovative use of interference phenomenon in the field of opto-electronic information processing and optical communications. A number of optical systems using interferometric techniques both in the optical and the electronic domains has been demonstrated in the filed of signal transmission and processing, optical metrology, defense, and physical sensors. Specifically it has been shown that the interference of waves in the form of holography can be exploited to realize a novel optical scanner called Code Multiplexed Optical Scanner (C-MOS). The C-MOS features large aperture, wide scan angles, 3-D beam control, no moving parts, and high beam scanning resolution. A C-MOS based free space optical transceiver for bi-directional communication has also been experimentally demonstrated. For high speed, large bandwidth, and high frequency operation, an optically implemented reconfigurable RF transversal filter design is presented that implements wide range of filtering algorithms. A number of techniques using heterodyne interferometry via acousto-optic device for optical path length measurements have been described. Finally, a whole new class of interferometric sensors for optical metrology and sensing applications is presented. A non-traditional interferometric output signal processing scheme has been developed. Applications include, for example, temperature sensors for harsh environments for a wide temperature range from room temperature to 1000°C.

Attacks and intrusion detection in wireless sensor networks of industrial SCADA systems

NASA Astrophysics Data System (ADS)

Kamaev, V. A.; Finogeev, A. G.; Finogeev, A. A.; Parygin, D. S.

2017-01-01

The effectiveness of automated process control systems (APCS) and supervisory control and data acquisition systems (SCADA) information security depends on the applied protection technologies of transport environment data transmission components. This article investigates the problems of detecting attacks in wireless sensor networks (WSN) of SCADA systems. As a result of analytical studies, the authors developed the detailed classification of external attacks and intrusion detection in sensor networks and brought a detailed description of attacking impacts on components of SCADA systems in accordance with the selected directions of attacks.

Transient plasma estimation: a noise cancelling/identification approach

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

Candy, J.V.; Casper, T.; Kane, R.

1985-03-01

The application of a noise cancelling technique to extract energy storage information from sensors occurring during fusion reactor experiments on the Tandem Mirror Experiment-Upgrade (TMX-U) at the Lawrence Livermore National Laboratory (LLNL) is examined. We show how this technique can be used to decrease the uncertainty in the corresponding sensor measurements used for diagnostics in both real-time and post-experimental environments. We analyze the performance of algorithm on the sensor data and discuss the various tradeoffs. The algorithm suggested is designed using SIG, an interactive signal processing package developed at LLNL.

Tracking and Classification of In-Air Hand Gesture Based on Thermal Guided Joint Filter.

PubMed

Kim, Seongwan; Ban, Yuseok; Lee, Sangyoun

2017-01-17

The research on hand gestures has attracted many image processing-related studies, as it intuitively conveys the intention of a human as it pertains to motional meaning. Various sensors have been used to exploit the advantages of different modalities for the extraction of important information conveyed by the hand gesture of a user. Although many works have focused on learning the benefits of thermal information from thermal cameras, most have focused on face recognition or human body detection, rather than hand gesture recognition. Additionally, the majority of the works that take advantage of multiple modalities (e.g., the combination of a thermal sensor and a visual sensor), usually adopting simple fusion approaches between the two modalities. As both thermal sensors and visual sensors have their own shortcomings and strengths, we propose a novel joint filter-based hand gesture recognition method to simultaneously exploit the strengths and compensate the shortcomings of each. Our study is motivated by the investigation of the mutual supplementation between thermal and visual information in low feature level for the consistent representation of a hand in the presence of varying lighting conditions. Accordingly, our proposed method leverages the thermal sensor's stability against luminance and the visual sensors textural detail, while complementing the low resolution and halo effect of thermal sensors and the weakness against illumination of visual sensors. A conventional region tracking method and a deep convolutional neural network have been leveraged to track the trajectory of a hand gesture and to recognize the hand gesture, respectively. Our experimental results show stability in recognizing a hand gesture against varying lighting conditions based on the contribution of the joint kernels of spatial adjacency and thermal range similarity.

Extraction of Qualitative Features from Sensor Data Using Windowed Fourier Transform

NASA Technical Reports Server (NTRS)

Amini, Abolfazl M.; Figueroa, Fenando

2003-01-01

In this paper, we use Matlab to model the health monitoring of a system through the information gathered from sensors. This implies assessment of the condition of the system components. Once a normal mode of operation is established any deviation from the normal behavior indicates a change. This change may be due to a malfunction of an element, a qualitative change, or a change due to a problem with another element in the network. For example, if one sensor indicates that the temperature in the tank has experienced a step change then a pressure sensor associated with the process in the tank should also experience a step change. The step up and step down as well as sensor disturbances are assumed to be exponential. An RC network is used to model the main process, which is step-up (charging), drift, and step-down (discharging). The sensor disturbances and spike are added while the system is in drift. The system is allowed to run for a period equal to three time constant of the main process before changes occur. Then each point of the signal is selected with a trailing data collected previously. Two trailing lengths of data are selected, one equal to two time constants of the main process and the other equal to two time constants of the sensor disturbance. Next, the DC is removed from each set of data and then the data are passed through a window followed by calculation of spectra for each set. In order to extract features the signal power, peak, and spectrum are plotted vs time. The results indicate distinct shapes corresponding to each process. The study is also carried out for a number of Gaussian distributed noisy cases.

Dimension Reduction of Multivariable Optical Emission Spectrometer Datasets for Industrial Plasma Processes

PubMed Central

Yang, Jie; McArdle, Conor; Daniels, Stephen

2014-01-01

A new data dimension-reduction method, called Internal Information Redundancy Reduction (IIRR), is proposed for application to Optical Emission Spectroscopy (OES) datasets obtained from industrial plasma processes. For example in a semiconductor manufacturing environment, real-time spectral emission data is potentially very useful for inferring information about critical process parameters such as wafer etch rates, however, the relationship between the spectral sensor data gathered over the duration of an etching process step and the target process output parameters is complex. OES sensor data has high dimensionality (fine wavelength resolution is required in spectral emission measurements in order to capture data on all chemical species involved in plasma reactions) and full spectrum samples are taken at frequent time points, so that dynamic process changes can be captured. To maximise the utility of the gathered dataset, it is essential that information redundancy is minimised, but with the important requirement that the resulting reduced dataset remains in a form that is amenable to direct interpretation of the physical process. To meet this requirement and to achieve a high reduction in dimension with little information loss, the IIRR method proposed in this paper operates directly in the original variable space, identifying peak wavelength emissions and the correlative relationships between them. A new statistic, Mean Determination Ratio (MDR), is proposed to quantify the information loss after dimension reduction and the effectiveness of IIRR is demonstrated using an actual semiconductor manufacturing dataset. As an example of the application of IIRR in process monitoring/control, we also show how etch rates can be accurately predicted from IIRR dimension-reduced spectral data. PMID:24451453

Process control of GMAW by detection of discontinuities in the molten weld pool

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

Carlson, N.M.; Kunerth, D.C.; Johnson, J.A.

1988-01-01

The use of ultrasonic sensors to detect discontinuities associated with the molten pool is one phase of a project to automate the welding process. In this work, ultrasonic sensors were used to interrogate the region around the molten/solid interface during gas metal arc welding (GMAW). The ultrasonic echoes from the interface and the molten pool provide information about the quality of the fusion zone and the molten pool. This information can be sent to a controller that can vary the welding parameters to correct the process. Previously ultrasonic shear waves were used to determine if the geometry of the molten/solidmore » interface was indicative of an acceptable weld. In this work, longitudinal waves were used to interrogate the molten weld pool for discontinuities. Unacceptable welding conditions that can result in porosity, incomplete penetration, or undercut were detected. 8 refs., 4 figs.« less

Lysine N[superscript zeta]-Decarboxylation Switch and Activation of the [beta]-Lactam Sensor Domain of BlaR1 Protein of Methicillin-resistant Staphylococcus aureus

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

Borbulevych, Oleg; Kumarasiri, Malika; Wilson, Brian

The integral membrane protein BlaR1 of methicillin-resistant Staphylococcus aureus senses the presence of {beta}-lactam antibiotics in the milieu and transduces the information to the cytoplasm, where the biochemical events that unleash induction of antibiotic resistance mechanisms take place. We report herein by two-dimensional and three-dimensional NMR experiments of the sensor domain of BlaR1 in solution and by determination of an x-ray structure for the apo protein that Lys-392 of the antibiotic-binding site is posttranslationally modified by N{sup {zeta}}-carboxylation. Additional crystallographic and NMR data reveal that on acylation of Ser-389 by antibiotics, Lys-392 experiences N{sup {zeta}}-decarboxylation. This unique process, termed themore » lysine N{sup {zeta}}-decarboxylation switch, arrests the sensor domain in the activated ('on') state, necessary for signal transduction and all the subsequent biochemical processes. We present structural information on how this receptor activation process takes place, imparting longevity to the antibiotic-receptor complex that is needed for the induction of the antibiotic-resistant phenotype in methicillin-resistant S. aureus.« less

The Human Factors of Sensor Fusion

DTIC Science & Technology

2008-05-01

tool in future military operations. 23 7. References Abdi, H. Neural Networks. In M. Lewis-Beck, A . Bryman , T. Futing (Eds), Encyclopedia for... a collection of information if it does not display a currently valid OMB control number. PLEASE DO NOT RETURN YOUR FORM TO THE ABOVE ADDRESS. 1...This report discusses select, cognitively based principles associated with the sensor fusion process. A review is made of the standard

Information theory analysis of sensor-array imaging systems for computer vision

NASA Technical Reports Server (NTRS)

Huck, F. O.; Fales, C. L.; Park, S. K.; Samms, R. W.; Self, M. O.

1983-01-01

Information theory is used to assess the performance of sensor-array imaging systems, with emphasis on the performance obtained with image-plane signal processing. By electronically controlling the spatial response of the imaging system, as suggested by the mechanism of human vision, it is possible to trade-off edge enhancement for sensitivity, increase dynamic range, and reduce data transmission. Computational results show that: signal information density varies little with large variations in the statistical properties of random radiance fields; most information (generally about 85 to 95 percent) is contained in the signal intensity transitions rather than levels; and performance is optimized when the OTF of the imaging system is nearly limited to the sampling passband to minimize aliasing at the cost of blurring, and the SNR is very high to permit the retrieval of small spatial detail from the extensively blurred signal. Shading the lens aperture transmittance to increase depth of field and using a regular hexagonal sensor-array instead of square lattice to decrease sensitivity to edge orientation also improves the signal information density up to about 30 percent at high SNRs.

Adding Semantics and OPM Ontology for the Provenance of Multi-sensor Merged Climate Data Records. Now What About Reproducibility?

NASA Astrophysics Data System (ADS)

Hua, H.; Wilson, B. D.; Manipon, G.; Pan, L.; Fetzer, E.

2011-12-01

Multi-decadal climate data records are critical to studying climate variability and change. These often also require merging data from multiple instruments such as those from NASA's A-Train that contain measurements covering a wide range of atmospheric conditions and phenomena. Multi-decadal climate data record of water vapor measurements from sensors on A-Train, operational weather, and other satellites are being assembled from existing data sources, or produced from well-established methods published in peer-reviewed literature. However, the immense volume and inhomogeneity of data often requires an "exploratory computing" approach to product generation where data is processed in a variety of different ways with varying algorithms, parameters, and code changes until an acceptable intermediate product is generated. This process is repeated until a desirable final merged product can be generated. Typically the production legacy is often lost due to the complexity of processing steps that were tried along the way. The data product information associated with source data, processing methods, parameters used, intermediate product outputs, and associated materials are often hidden in each of the trials and scattered throughout the processing system(s). We will discuss methods to help users better capture and explore the production legacy of the data, metadata, ancillary files, code, and computing environment changes used during the production of these merged and multi-sensor data products. By leveraging existing semantic and provenance tools, we can capture sufficient information to enable users to track, perform faceted searches, and visualize the provenance of the products and processing lineage. We will explore if sufficient provenance information can be captured to enable science reproducibility of these climate data records.

New virtual sonar and wireless sensor system concepts

NASA Astrophysics Data System (ADS)

Houston, B. H.; Bucaro, J. A.; Romano, A. J.

2004-05-01

Recently, exciting new sensor array concepts have been proposed which, if realized, could revolutionize how we approach surface mounted acoustic sensor systems for underwater vehicles. Two such schemes are so-called ``virtual sonar'' which is formulated around Helmholtz integral processing and ``wireless'' systems which transfer sensor information through radiated RF signals. The ``virtual sonar'' concept provides an interesting framework through which to combat the dilatory effects of the structure on surface mounted sensor systems including structure-borne vibration and variations in structure-backing impedance. The ``wireless'' concept would eliminate the necessity of a complex wiring or fiber-optic external network while minimizing vehicle penetrations. Such systems, however, would require a number of advances in sensor and RF waveguide technologies. In this presentation, we will discuss those sensor and sensor-related developments which are desired or required in order to make practical such new sensor system concepts, and we will present several underwater applications from the perspective of exploiting these new sonar concepts. [Work supported by ONR.

Common Criteria Related Security Design Patterns—Validation on the Intelligent Sensor Example Designed for Mine Environment

PubMed Central

Bialas, Andrzej

2010-01-01

The paper discusses the security issues of intelligent sensors that are able to measure and process data and communicate with other information technology (IT) devices or systems. Such sensors are often used in high risk applications. To improve their robustness, the sensor systems should be developed in a restricted way to provide them with assurance. One of assurance creation methodologies is Common Criteria (ISO/IEC 15408), used for IT products and systems. The contribution of the paper is a Common Criteria compliant and pattern-based method for the intelligent sensors security development. The paper concisely presents this method and its evaluation for the sensor detecting methane in a mine, focusing on the security problem of the intelligent sensor definition and solution. The aim of the validation is to evaluate and improve the introduced method. PMID:22399888

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.

Display device for indicating the value of a parameter in a process plant

DOEpatents

Scarola, Kenneth; Jamison, David S.; Manazir, Richard M.; Rescorl, Robert L.; Harmon, Daryl L.

1993-01-01

An advanced control room complex for a nuclear power plant, including a discrete indicator and alarm system (72) which is nuclear qualified for rapid response to changes in plant parameters and a component control system (64) which together provide a discrete monitoring and control capability at a panel (14-22, 26, 28) in the control room (10). A separate data processing system (70), which need not be nuclear qualified, provides integrated and overview information to the control room and to each panel, through CRTs (84) and a large, overhead integrated process status overview board (24). The discrete indicator and alarm system (72) and the data processing system (70) receive inputs from common plant sensors and validate the sensor outputs to arrive at a representative value of the parameter for use by the operator during both normal and accident conditions, thereby avoiding the need for him to assimilate data from each sensor individually. The integrated process status board (24) is at the apex of an information hierarchy that extends through four levels and provides access at each panel to the full display hierarchy. The control room panels are preferably of a modular construction, permitting the definition of inputs and outputs, the man machine interface, and the plant specific algorithms, to proceed in parallel with the fabrication of the panels, the installation of the equipment and the generic testing thereof.

Indicator system for a process plant control complex

DOEpatents

Scarola, Kenneth; Jamison, David S.; Manazir, Richard M.; Rescorl, Robert L.; Harmon, Daryl L.

1993-01-01

An advanced control room complex for a nuclear power plant, including a discrete indicator and alarm system (72) which is nuclear qualified for rapid response to changes in plant parameters and a component control system (64) which together provide a discrete monitoring and control capability at a panel (14-22, 26, 28) in the control room (10). A separate data processing system (70), which need not be nuclear qualified, provides integrated and overview information to the control room and to each panel, through CRTs (84) and a large, overhead integrated process status overview board (24). The discrete indicator and alarm system (72) and the data processing system (70) receive inputs from common plant sensors and validate the sensor outputs to arrive at a representative value of the parameter for use by the operator during both normal and accident conditions, thereby avoiding the need for him to assimilate data from each sensor individually. The integrated process status board (24) is at the apex of an information hierarchy that extends through four levels and provides access at each panel to the full display hierarchy. The control room panels are preferably of a modular construction, permitting the definition of inputs and outputs, the man machine interface, and the plant specific algorithms, to proceed in parallel with the fabrication of the panels, the installation of the equipment and the generic testing thereof.

An International Disaster Management SensorWeb Consisting of Space-based and Insitu Sensors

NASA Astrophysics Data System (ADS)

Mandl, D.; Frye, S. W.; Policelli, F. S.; Cappelaere, P. G.

2009-12-01

For the past year, NASA along with partners consisting of the United Nations Space-based Information for Disaster and Emergency Response (UN-SPIDER) office, the Canadian Space Agency, the Ukraine Space Research Institute (SRI), Taiwan National Space Program Office (NSPO) and in conjunction with the Committee on Earth Observing Satellite (CEOS) Working Group on Information Systems and Services (WGISS) have been conducting a pilot project to automate the process of obtaining sensor data for the purpose of flood management and emergency response. This includes experimenting with flood prediction models based on numerous meteorological satellites and a global hydrological model and then automatically triggering follow up high resolution satellite imagery with rapid delivery of data products. This presentation will provide a overview of the effort, recent accomplishments and future plans.

Sensor Characteristics Reference Guide

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

Cree, Johnathan V.; Dansu, A.; Fuhr, P.

The Buildings Technologies Office (BTO), within the U.S. Department of Energy (DOE), Office of Energy Efficiency and Renewable Energy (EERE), is initiating a new program in Sensor and Controls. The vision of this program is: • Buildings operating automatically and continuously at peak energy efficiency over their lifetimes and interoperating effectively with the electric power grid. • Buildings that are self-configuring, self-commissioning, self-learning, self-diagnosing, self-healing, and self-transacting to enable continuous peak performance. • Lower overall building operating costs and higher asset valuation. The overarching goal is to capture 30% energy savings by enhanced management of energy consuming assets and systemsmore » through development of cost-effective sensors and controls. One step in achieving this vision is the publication of this Sensor Characteristics Reference Guide. The purpose of the guide is to inform building owners and operators of the current status, capabilities, and limitations of sensor technologies. It is hoped that this guide will aid in the design and procurement process and result in successful implementation of building sensor and control systems. DOE will also use this guide to identify research priorities, develop future specifications for potential market adoption, and provide market clarity through unbiased information« less

On the Design of Attitude-Heading Reference Systems Using the Allan Variance.

PubMed

Hidalgo-Carrió, Javier; Arnold, Sascha; Poulakis, Pantelis

2016-04-01

The Allan variance is a method to characterize stochastic random processes. The technique was originally developed to characterize the stability of atomic clocks and has also been successfully applied to the characterization of inertial sensors. Inertial navigation systems (INS) can provide accurate results in a short time, which tend to rapidly degrade in longer time intervals. During the last decade, the performance of inertial sensors has significantly improved, particularly in terms of signal stability, mechanical robustness, and power consumption. The mass and volume of inertial sensors have also been significantly reduced, offering system-level design and accommodation advantages. This paper presents a complete methodology for the characterization and modeling of inertial sensors using the Allan variance, with direct application to navigation systems. Although the concept of sensor fusion is relatively straightforward, accurate characterization and sensor-information filtering is not a trivial task, yet they are essential for good performance. A complete and reproducible methodology utilizing the Allan variance, including all the intermediate steps, is described. An end-to-end (E2E) process for sensor-error characterization and modeling up to the final integration in the sensor-fusion scheme is explained in detail. The strength of this approach is demonstrated with representative tests on novel, high-grade inertial sensors. Experimental navigation results are presented from two distinct robotic applications: a planetary exploration rover prototype and an autonomous underwater vehicle (AUV).

Ontology Alignment Architecture for Semantic Sensor Web Integration

PubMed Central

Fernandez, Susel; Marsa-Maestre, Ivan; Velasco, Juan R.; Alarcos, Bernardo

2013-01-01

Sensor networks are a concept that has become very popular in data acquisition and processing for multiple applications in different fields such as industrial, medicine, home automation, environmental detection, etc. Today, with the proliferation of small communication devices with sensors that collect environmental data, semantic Web technologies are becoming closely related with sensor networks. The linking of elements from Semantic Web technologies with sensor networks has been called Semantic Sensor Web and has among its main features the use of ontologies. One of the key challenges of using ontologies in sensor networks is to provide mechanisms to integrate and exchange knowledge from heterogeneous sources (that is, dealing with semantic heterogeneity). Ontology alignment is the process of bringing ontologies into mutual agreement by the automatic discovery of mappings between related concepts. This paper presents a system for ontology alignment in the Semantic Sensor Web which uses fuzzy logic techniques to combine similarity measures between entities of different ontologies. The proposed approach focuses on two key elements: the terminological similarity, which takes into account the linguistic and semantic information of the context of the entity's names, and the structural similarity, based on both the internal and relational structure of the concepts. This work has been validated using sensor network ontologies and the Ontology Alignment Evaluation Initiative (OAEI) tests. The results show that the proposed techniques outperform previous approaches in terms of precision and recall. PMID:24051523

Ontology alignment architecture for semantic sensor Web integration.

PubMed

Fernandez, Susel; Marsa-Maestre, Ivan; Velasco, Juan R; Alarcos, Bernardo

2013-09-18

Sensor networks are a concept that has become very popular in data acquisition and processing for multiple applications in different fields such as industrial, medicine, home automation, environmental detection, etc. Today, with the proliferation of small communication devices with sensors that collect environmental data, semantic Web technologies are becoming closely related with sensor networks. The linking of elements from Semantic Web technologies with sensor networks has been called Semantic Sensor Web and has among its main features the use of ontologies. One of the key challenges of using ontologies in sensor networks is to provide mechanisms to integrate and exchange knowledge from heterogeneous sources (that is, dealing with semantic heterogeneity). Ontology alignment is the process of bringing ontologies into mutual agreement by the automatic discovery of mappings between related concepts. This paper presents a system for ontology alignment in the Semantic Sensor Web which uses fuzzy logic techniques to combine similarity measures between entities of different ontologies. The proposed approach focuses on two key elements: the terminological similarity, which takes into account the linguistic and semantic information of the context of the entity's names, and the structural similarity, based on both the internal and relational structure of the concepts. This work has been validated using sensor network ontologies and the Ontology Alignment Evaluation Initiative (OAEI) tests. The results show that the proposed techniques outperform previous approaches in terms of precision and recall.

Demonstration of a roving-host wireless sensor network for rapid assessment monitoring of structural health

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.

Adaptive Sensing and Fusion of Multi-Sensor Data and Historical Information

DTIC Science & Technology

2009-11-06

integrate MTL and semi-supervised learning into a single framework , thereby exploiting two forms of contextual information. A key new objective of the...this report we integrate MTL and semi-supervised learning into a single framework , thereby exploiting two forms of contextual information. A key new...process [8], denoted as X ∼ BeP (B), where B is a measure on Ω. If B is continuous, X is a Poisson process with intensity B and can be constructed as X = N

An Experimental Study in Determining Energy Expenditure from Treadmill Walking using Hip-Worn Inertial Sensors

PubMed Central

Vathsangam, Harshvardhan; Emken, Adar; Schroeder, E. Todd; Spruijt-Metz, Donna; Sukhatme, Gaurav S.

2011-01-01

This paper describes an experimental study in estimating energy expenditure from treadmill walking using a single hip-mounted triaxial inertial sensor comprised of a triaxial accelerometer and a triaxial gyroscope. Typical physical activity characterization using accelerometer generated counts suffers from two drawbacks - imprecison (due to proprietary counts) and incompleteness (due to incomplete movement description). We address these problems in the context of steady state walking by directly estimating energy expenditure with data from a hip-mounted inertial sensor. We represent the cyclic nature of walking with a Fourier transform of sensor streams and show how one can map this representation to energy expenditure (as measured by V O2 consumption, mL/min) using three regression techniques - Least Squares Regression (LSR), Bayesian Linear Regression (BLR) and Gaussian Process Regression (GPR). We perform a comparative analysis of the accuracy of sensor streams in predicting energy expenditure (measured by RMS prediction accuracy). Triaxial information is more accurate than uniaxial information. LSR based approaches are prone to outlier sensitivity and overfitting. Gyroscopic information showed equivalent if not better prediction accuracy as compared to accelerometers. Combining accelerometer and gyroscopic information provided better accuracy than using either sensor alone. We also analyze the best algorithmic approach among linear and nonlinear methods as measured by RMS prediction accuracy and run time. Nonlinear regression methods showed better prediction accuracy but required an order of magnitude of run time. This paper emphasizes the role of probabilistic techniques in conjunction with joint modeling of triaxial accelerations and rotational rates to improve energy expenditure prediction for steady-state treadmill walking. PMID:21690001

Distance correction system for localization based on linear regression and smoothing in ambient intelligence display.

PubMed

Kim, Dae-Hee; Choi, Jae-Hun; Lim, Myung-Eun; Park, Soo-Jun

2008-01-01

This paper suggests the method of correcting distance between an ambient intelligence display and a user based on linear regression and smoothing method, by which distance information of a user who approaches to the display can he accurately output even in an unanticipated condition using a passive infrared VIR) sensor and an ultrasonic device. The developed system consists of an ambient intelligence display and an ultrasonic transmitter, and a sensor gateway. Each module communicates with each other through RF (Radio frequency) communication. The ambient intelligence display includes an ultrasonic receiver and a PIR sensor for motion detection. In particular, this system selects and processes algorithms such as smoothing or linear regression for current input data processing dynamically through judgment process that is determined using the previous reliable data stored in a queue. In addition, we implemented GUI software with JAVA for real time location tracking and an ambient intelligence display.

A signal processing framework for simultaneous detection of multiple environmental contaminants

NASA Astrophysics Data System (ADS)

Chakraborty, Subhadeep; Manahan, Michael P.; Mench, Matthew M.

2013-11-01

The possibility of large-scale attacks using chemical warfare agents (CWAs) has exposed the critical need for fundamental research enabling the reliable, unambiguous and early detection of trace CWAs and toxic industrial chemicals. This paper presents a unique approach for the identification and classification of simultaneously present multiple environmental contaminants by perturbing an electrochemical (EC) sensor with an oscillating potential for the extraction of statistically rich information from the current response. The dynamic response, being a function of the degree and mechanism of contamination, is then processed with a symbolic dynamic filter for the extraction of representative patterns, which are then classified using a trained neural network. The approach presented in this paper promises to extend the sensing power and sensitivity of these EC sensors by augmenting and complementing sensor technology with state-of-the-art embedded real-time signal processing capabilities.

Research on motor rotational speed measurement in regenerative braking system of electric vehicle

NASA Astrophysics Data System (ADS)

Pan, Chaofeng; Chen, Liao; Chen, Long; Jiang, Haobin; Li, Zhongxing; Wang, Shaohua

2016-01-01

Rotational speed signals acquisition and processing techniques are widely used in rotational machinery. In order to realized precise and real-time control of motor drive and regenerative braking process, rotational speed measurement techniques are needed in electric vehicles. Obtaining accurate motor rotational speed signal will contribute to the regenerative braking force control steadily and realized higher energy recovery rate. This paper aims to develop a method that provides instantaneous speed information in the form of motor rotation. It addresses principles of motor rotational speed measurement in the regenerative braking systems of electric vehicle firstly. The paper then presents ideal and actual Hall position sensor signals characteristics, the relation between the motor rotational speed and the Hall position sensor signals is revealed. Finally, Hall position sensor signals conditioning and processing circuit and program for motor rotational speed measurement have been carried out based on measurement error analysis.

Using multiple sensors for printed circuit board insertion

NASA Technical Reports Server (NTRS)

Sood, Deepak; Repko, Michael C.; Kelley, Robert B.

1989-01-01

As more and more activities are performed in space, there will be a greater demand placed on the information handling capacity of people who are to direct and accomplish these tasks. A promising alternative to full-time human involvement is the use of semi-autonomous, intelligent robot systems. To automate tasks such as assembly, disassembly, repair and maintenance, the issues presented by environmental uncertainties need to be addressed. These uncertainties are introduced by variations in the computed position of the robot at different locations in its work envelope, variations in part positioning, and tolerances of part dimensions. As a result, the robot system may not be able to accomplish the desired task without the help of sensor feedback. Measurements on the environment allow real time corrections to be made to the process. A design and implementation of an intelligent robot system which inserts printed circuit boards into a card cage are presented. Intelligent behavior is accomplished by coupling the task execution sequence with information derived from three different sensors: an overhead three-dimensional vision system, a fingertip infrared sensor, and a six degree of freedom wrist-mounted force/torque sensor.

A Reverse Localization Scheme for Underwater Acoustic Sensor Networks

PubMed Central

Moradi, Marjan; Rezazadeh, Javad; Ismail, Abdul Samad

2012-01-01

Underwater Wireless Sensor Networks (UWSNs) provide new opportunities to observe and predict the behavior of aquatic environments. In some applications like target tracking or disaster prevention, sensed data is meaningless without location information. In this paper, we propose a novel 3D centralized, localization scheme for mobile underwater wireless sensor network, named Reverse Localization Scheme or RLS in short. RLS is an event-driven localization method triggered by detector sensors for launching localization process. RLS is suitable for surveillance applications that require very fast reactions to events and could report the location of the occurrence. In this method, mobile sensor nodes report the event toward the surface anchors as soon as they detect it. They do not require waiting to receive location information from anchors. Simulation results confirm that the proposed scheme improves the energy efficiency and reduces significantly localization response time with a proper level of accuracy in terms of mobility model of water currents. Major contributions of this method lie on reducing the numbers of message exchange for localization, saving the energy and decreasing the average localization response time. PMID:22666034

A reverse localization scheme for underwater acoustic sensor networks.

PubMed

Moradi, Marjan; Rezazadeh, Javad; Ismail, Abdul Samad

2012-01-01

Underwater Wireless Sensor Networks (UWSNs) provide new opportunities to observe and predict the behavior of aquatic environments. In some applications like target tracking or disaster prevention, sensed data is meaningless without location information. In this paper, we propose a novel 3D centralized, localization scheme for mobile underwater wireless sensor network, named Reverse Localization Scheme or RLS in short. RLS is an event-driven localization method triggered by detector sensors for launching localization process. RLS is suitable for surveillance applications that require very fast reactions to events and could report the location of the occurrence. In this method, mobile sensor nodes report the event toward the surface anchors as soon as they detect it. They do not require waiting to receive location information from anchors. Simulation results confirm that the proposed scheme improves the energy efficiency and reduces significantly localization response time with a proper level of accuracy in terms of mobility model of water currents. Major contributions of this method lie on reducing the numbers of message exchange for localization, saving the energy and decreasing the average localization response time.

System for RFID-Enabled Information Collection

NASA Technical Reports Server (NTRS)

Kennedy, Timothy F. (Inventor); Fink, Patrick W. (Inventor); Lin, Gregory Y. (Inventor); Ngo, Phong H. (Inventor)

2017-01-01

A sensor and system provide for radio frequency identification (RFID)-enabled information collection. The sensor includes a ring-shaped element and an antenna. The ring-shaped element includes a conductive ring and an RFID integrated circuit. The antenna is spaced apart from the ring-shaped element and defines an electrically-conductive path commensurate in size and shape to at least a portion of the conductive ring. The system may include an interrogator for energizing the ring-shaped element and receiving a data transmission from the RFID integrated circuit that has been energized for further processing by a processor.

Passive Polarimetric Information Processing for Target Classification

NASA Astrophysics Data System (ADS)

Sadjadi, Firooz; Sadjadi, Farzad

Polarimetric sensing is an area of active research in a variety of applications. In particular, the use of polarization diversity has been shown to improve performance in automatic target detection and recognition. Within the diverse scope of polarimetric sensing, the field of passive polarimetric sensing is of particular interest. This chapter presents several new methods for gathering in formation using such passive techniques. One method extracts three-dimensional (3D) information and surface properties using one or more sensors. Another method extracts scene-specific algebraic expressions that remain unchanged under polariza tion transformations (such as along the transmission path to the sensor).

Characterizing Multiple Wireless Sensor Networks for Large-Scale Radio Tomography

DTIC Science & Technology

2015-03-01

with other transceivers over a wireless frequency. A base station transceiver collects the information and processes the information into something...or most other obstructions in between the two links [4]. A base station transceiver is connected to a processing computer to collect the RSS of each... transceivers at four different heights to create a Three-Dimensional (3-D) RTI network. Using shadowing- based RTI, this research demonstrated that RTI

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.

Implementing Operational Analytics using Big Data Technologies to Detect and Predict Sensor Anomalies

NASA Astrophysics Data System (ADS)

Coughlin, J.; Mital, R.; Nittur, S.; SanNicolas, B.; Wolf, C.; Jusufi, R.

2016-09-01

Operational analytics when combined with Big Data technologies and predictive techniques have been shown to be valuable in detecting mission critical sensor anomalies that might be missed by conventional analytical techniques. Our approach helps analysts and leaders make informed and rapid decisions by analyzing large volumes of complex data in near real-time and presenting it in a manner that facilitates decision making. It provides cost savings by being able to alert and predict when sensor degradations pass a critical threshold and impact mission operations. Operational analytics, which uses Big Data tools and technologies, can process very large data sets containing a variety of data types to uncover hidden patterns, unknown correlations, and other relevant information. When combined with predictive techniques, it provides a mechanism to monitor and visualize these data sets and provide insight into degradations encountered in large sensor systems such as the space surveillance network. In this study, data from a notional sensor is simulated and we use big data technologies, predictive algorithms and operational analytics to process the data and predict sensor degradations. This study uses data products that would commonly be analyzed at a site. This study builds on a big data architecture that has previously been proven valuable in detecting anomalies. This paper outlines our methodology of implementing an operational analytic solution through data discovery, learning and training of data modeling and predictive techniques, and deployment. Through this methodology, we implement a functional architecture focused on exploring available big data sets and determine practical analytic, visualization, and predictive technologies.

Dynamic Steering for Improved Sensor Autonomy and Catalogue Maintenance

NASA Astrophysics Data System (ADS)

Hobson, T.; Gordon, N.; Clarkson, I.; Rutten, M.; Bessell, T.

A number of international agencies endeavour to maintain catalogues of the man-made resident space objects (RSOs) currently orbiting the Earth. Such catalogues are primarily created to anticipate and avoid destructive collisions involving important space assets such as manned missions and active satellites. An agencys ability to achieve this objective is dependent on the accuracy, reliability and timeliness of the information used to update its catalogue. A primary means for gathering this information is by regularly making direct observations of the tens-of-thousands of currently detectable RSOs via networks of space surveillance sensors. But operational constraints sometimes prevent accurate and timely reacquisition of all known RSOs, which can cause them to become lost to the tracking system. Furthermore, when comprehensive acquisition of new objects does not occur, these objects, in addition to the lost RSOs, result in uncorrelated detections when next observed. Due to the rising number of space-missions and the introduction of newer, more capable space-sensors, the number of uncorrelated targets is at an all-time high. The process of differentiating uncorrelated detections caused by once-acquired now-lost RSOs from newly detected RSOs is a difficult and often labour intensive task. Current methods for overcoming this challenge focus on advancements in orbit propagation and object characterisation to improve prediction accuracy and target identification. In this paper, we describe a complementary approach that incorporates increased awareness of error and failed observations into the RSO tracking solution. Our methodology employs a technique called dynamic steering to improve the autonomy and capability of a space surveillance networks steerable sensors. By co-situating each sensor with a low-cost high-performance computer, the steerable sensor can quickly and intelligently decide how to steer itself. The sensor-system uses a dedicated parallel-processing architecture to enable it to compute a high-fidelity estimate of the targets prior state error distribution in real-time. Negative information, such as when an RSO is targeted for observation but it is not observed, is incorporated to improve the likelihood of reacquiring the target when attempting to observe the target in future. The sensor is consequently capable of improving its utility by planning each observation using a sensor steering solution that is informed by all prior attempts at observing the target. We describe the practical implementation of a single experimental sensor and offer the results of recent field trials. These trials involved reacquisition and constrained Initial Orbit Determination of RSOs, a number of months after prior observation and initial detection. Using the proposed approach, the system is capable of using targeting information that would be unusable by existing space surveillance networks. The system consequently offers a means of enhancing space surveillance for SSA via increased system capacity, a higher degree of autonomy and the ability to reacquire objects whose dynamics are insufficiently modelled to cue a conventional space surveillance system for observation and tracking.

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.

Resolving molecule-specific information in dynamic lipid membrane processes with multi-resonant infrared metasurfaces.

PubMed

Rodrigo, Daniel; Tittl, Andreas; Ait-Bouziad, Nadine; John-Herpin, Aurelian; Limaj, Odeta; Kelly, Christopher; Yoo, Daehan; Wittenberg, Nathan J; Oh, Sang-Hyun; Lashuel, Hilal A; Altug, Hatice

2018-06-04

A multitude of biological processes are enabled by complex interactions between lipid membranes and proteins. To understand such dynamic processes, it is crucial to differentiate the constituent biomolecular species and track their individual time evolution without invasive labels. Here, we present a label-free mid-infrared biosensor capable of distinguishing multiple analytes in heterogeneous biological samples with high sensitivity. Our technology leverages a multi-resonant metasurface to simultaneously enhance the different vibrational fingerprints of multiple biomolecules. By providing up to 1000-fold near-field intensity enhancement over both amide and methylene bands, our sensor resolves the interactions of lipid membranes with different polypeptides in real time. Significantly, we demonstrate that our label-free chemically specific sensor can analyze peptide-induced neurotransmitter cargo release from synaptic vesicle mimics. Our sensor opens up exciting possibilities for gaining new insights into biological processes such as signaling or transport in basic research as well as provides a valuable toolkit for bioanalytical and pharmaceutical applications.

Soft sensor modelling by time difference, recursive partial least squares and adaptive model updating

NASA Astrophysics Data System (ADS)

Fu, Y.; Yang, W.; Xu, O.; Zhou, L.; Wang, J.

2017-04-01

To investigate time-variant and nonlinear characteristics in industrial processes, a soft sensor modelling method based on time difference, moving-window recursive partial least square (PLS) and adaptive model updating is proposed. In this method, time difference values of input and output variables are used as training samples to construct the model, which can reduce the effects of the nonlinear characteristic on modelling accuracy and retain the advantages of recursive PLS algorithm. To solve the high updating frequency of the model, a confidence value is introduced, which can be updated adaptively according to the results of the model performance assessment. Once the confidence value is updated, the model can be updated. The proposed method has been used to predict the 4-carboxy-benz-aldehyde (CBA) content in the purified terephthalic acid (PTA) oxidation reaction process. The results show that the proposed soft sensor modelling method can reduce computation effectively, improve prediction accuracy by making use of process information and reflect the process characteristics accurately.

“Playing around” with Field-Effect Sensors on the Basis of EIS Structures, LAPS and ISFETs

PubMed Central

Schöning, Michael J.

2005-01-01

Microfabricated semiconductor devices are becoming increasingly relevant, also for the detection of biological and chemical quantities. Especially, the “marriage” of biomolecules and silicon technology often yields successful new sensor concepts. The fabrication techniques of such silicon-based chemical sensors and biosensors, respectively, will have a distinct impact in different fields of application such as medicine, food technology, environment, chemistry and biotechnology as well as information processing. Moreover, scientists and engineers are interested in the analytical benefits of miniaturised and microfabricated sensor devices. This paper gives a survey on different types of semiconductor-based field-effect structures that have been recently developed in our laboratory.

A Survey on Trust Management for Mobile Ad Hoc Networks

DTIC Science & Technology

2011-11-01

expects, trust is dangerous implying the possible betrayal of trust. In his comments on Lagerspetz’s book titled Trust: The Tacit Demand, Lahno [24...AODV Zouridaki et al. (2005 ) [79] (2006) [80] Secure routing Direct observation [79][80] Reputation by secondhand information [80] Packet dropping...areas of signal processing, wireless communications, sensor and mobile ad hoc networks. He is co-editor of the book Wireless Sensor Networks: Signal

Training Classifiers with Shadow Features for Sensor-Based Human Activity Recognition.

PubMed

Fong, Simon; Song, Wei; Cho, Kyungeun; Wong, Raymond; Wong, Kelvin K L

2017-02-27

In this paper, a novel training/testing process for building/using a classification model based on human activity recognition (HAR) is proposed. Traditionally, HAR has been accomplished by a classifier that learns the activities of a person by training with skeletal data obtained from a motion sensor, such as Microsoft Kinect. These skeletal data are the spatial coordinates (x, y, z) of different parts of the human body. The numeric information forms time series, temporal records of movement sequences that can be used for training a classifier. In addition to the spatial features that describe current positions in the skeletal data, new features called 'shadow features' are used to improve the supervised learning efficacy of the classifier. Shadow features are inferred from the dynamics of body movements, and thereby modelling the underlying momentum of the performed activities. They provide extra dimensions of information for characterising activities in the classification process, and thereby significantly improve the classification accuracy. Two cases of HAR are tested using a classification model trained with shadow features: one is by using wearable sensor and the other is by a Kinect-based remote sensor. Our experiments can demonstrate the advantages of the new method, which will have an impact on human activity detection research.

Training Classifiers with Shadow Features for Sensor-Based Human Activity Recognition

PubMed Central

Fong, Simon; Song, Wei; Cho, Kyungeun; Wong, Raymond; Wong, Kelvin K. L.

2017-01-01

In this paper, a novel training/testing process for building/using a classification model based on human activity recognition (HAR) is proposed. Traditionally, HAR has been accomplished by a classifier that learns the activities of a person by training with skeletal data obtained from a motion sensor, such as Microsoft Kinect. These skeletal data are the spatial coordinates (x, y, z) of different parts of the human body. The numeric information forms time series, temporal records of movement sequences that can be used for training a classifier. In addition to the spatial features that describe current positions in the skeletal data, new features called ‘shadow features’ are used to improve the supervised learning efficacy of the classifier. Shadow features are inferred from the dynamics of body movements, and thereby modelling the underlying momentum of the performed activities. They provide extra dimensions of information for characterising activities in the classification process, and thereby significantly improve the classification accuracy. Two cases of HAR are tested using a classification model trained with shadow features: one is by using wearable sensor and the other is by a Kinect-based remote sensor. Our experiments can demonstrate the advantages of the new method, which will have an impact on human activity detection research. PMID:28264470

Acoustic emission beamforming for enhanced damage detection

NASA Astrophysics Data System (ADS)

McLaskey, Gregory C.; Glaser, Steven D.; Grosse, Christian U.

2008-03-01

As civil infrastructure ages, the early detection of damage in a structure becomes increasingly important for both life safety and economic reasons. This paper describes the analysis procedures used for beamforming acoustic emission techniques as well as the promising results of preliminary experimental tests on a concrete bridge deck. The method of acoustic emission offers a tool for detecting damage, such as cracking, as it occurs on or in a structure. In order to gain meaningful information from acoustic emission analyses, the damage must be localized. Current acoustic emission systems with localization capabilities are very costly and difficult to install. Sensors must be placed throughout the structure to ensure that the damage is encompassed by the array. Beamforming offers a promising solution to these problems and permits the use of wireless sensor networks for acoustic emission analyses. Using the beamforming technique, the azmuthal direction of the location of the damage may be estimated by the stress waves impinging upon a small diameter array (e.g. 30mm) of acoustic emission sensors. Additional signal discrimination may be gained via array processing techniques such as the VESPA process. The beamforming approach requires no arrival time information and is based on very simple delay and sum beamforming algorithms which can be easily implemented on a wireless sensor or mote.

Pervasive Monitoring—An Intelligent Sensor Pod Approach for Standardised Measurement Infrastructures

PubMed Central

Resch, Bernd; Mittlboeck, Manfred; Lippautz, Michael

2010-01-01

Geo-sensor networks have traditionally been built up in closed monolithic systems, thus limiting trans-domain usage of real-time measurements. This paper presents the technical infrastructure of a standardised embedded sensing device, which has been developed in the course of the Live Geography approach. The sensor pod implements data provision standards of the Sensor Web Enablement initiative, including an event-based alerting mechanism and location-aware Complex Event Processing functionality for detection of threshold transgression and quality assurance. The goal of this research is that the resultant highly flexible sensing architecture will bring sensor network applications one step further towards the realisation of the vision of a “digital skin for planet earth”. The developed infrastructure can potentially have far-reaching impacts on sensor-based monitoring systems through the deployment of ubiquitous and fine-grained sensor networks. This in turn allows for the straight-forward use of live sensor data in existing spatial decision support systems to enable better-informed decision-making. PMID:22163537

Pervasive monitoring--an intelligent sensor pod approach for standardised measurement infrastructures.

PubMed

Resch, Bernd; Mittlboeck, Manfred; Lippautz, Michael

2010-01-01

Geo-sensor networks have traditionally been built up in closed monolithic systems, thus limiting trans-domain usage of real-time measurements. This paper presents the technical infrastructure of a standardised embedded sensing device, which has been developed in the course of the Live Geography approach. The sensor pod implements data provision standards of the Sensor Web Enablement initiative, including an event-based alerting mechanism and location-aware Complex Event Processing functionality for detection of threshold transgression and quality assurance. The goal of this research is that the resultant highly flexible sensing architecture will bring sensor network applications one step further towards the realisation of the vision of a "digital skin for planet earth". The developed infrastructure can potentially have far-reaching impacts on sensor-based monitoring systems through the deployment of ubiquitous and fine-grained sensor networks. This in turn allows for the straight-forward use of live sensor data in existing spatial decision support systems to enable better-informed decision-making.

Cross-layer protocol design for QoS optimization in real-time wireless sensor networks

NASA Astrophysics Data System (ADS)

Hortos, William S.

2010-04-01

The metrics of quality of service (QoS) for each sensor type in a wireless sensor network can be associated with metrics for multimedia that describe the quality of fused information, e.g., throughput, delay, jitter, packet error rate, information correlation, etc. These QoS metrics are typically set at the highest, or application, layer of the protocol stack to ensure that performance requirements for each type of sensor data are satisfied. Application-layer metrics, in turn, depend on the support of the lower protocol layers: session, transport, network, data link (MAC), and physical. The dependencies of the QoS metrics on the performance of the higher layers of the Open System Interconnection (OSI) reference model of the WSN protocol, together with that of the lower three layers, are the basis for a comprehensive approach to QoS optimization for multiple sensor types in a general WSN model. The cross-layer design accounts for the distributed power consumption along energy-constrained routes and their constituent nodes. Following the author's previous work, the cross-layer interactions in the WSN protocol are represented by a set of concatenated protocol parameters and enabling resource levels. The "best" cross-layer designs to achieve optimal QoS are established by applying the general theory of martingale representations to the parameterized multivariate point processes (MVPPs) for discrete random events occurring in the WSN. Adaptive control of network behavior through the cross-layer design is realized through the parametric factorization of the stochastic conditional rates of the MVPPs. The cross-layer protocol parameters for optimal QoS are determined in terms of solutions to stochastic dynamic programming conditions derived from models of transient flows for heterogeneous sensor data and aggregate information over a finite time horizon. Markov state processes, embedded within the complex combinatorial history of WSN events, are more computationally tractable and lead to simplifications for any simulated or analytical performance evaluations of the cross-layer designs.

Portable nuclear material detector and process

DOEpatents

Hofstetter, Kenneth J [Aiken, SC; Fulghum, Charles K [Aiken, SC; Harpring, Lawrence J [North Augusta, SC; Huffman, Russell K [Augusta, GA; Varble, Donald L [Evans, GA

2008-04-01

A portable, hand held, multi-sensor radiation detector is disclosed. The detection apparatus has a plurality of spaced sensor locations which are contained within a flexible housing. The detection apparatus, when suspended from an elevation, will readily assume a substantially straight, vertical orientation and may be used to monitor radiation levels from shipping containers. The flexible detection array can also assume a variety of other orientations to facilitate any unique container shapes or to conform to various physical requirements with respect to deployment of the detection array. The output of each sensor within the array is processed by at least one CPU which provides information in a usable form to a user interface. The user interface is used to provide the power requirements and operating instructions to the operational components within the detection array.

A New Cellular Architecture for Information Retrieval from Sensor Networks through Embedded Service and Security Protocols

PubMed Central

Shahzad, Aamir; Landry, René; Lee, Malrey; Xiong, Naixue; Lee, Jongho; Lee, Changhoon

2016-01-01

Substantial changes have occurred in the Information Technology (IT) sectors and with these changes, the demand for remote access to field sensor information has increased. This allows visualization, monitoring, and control through various electronic devices, such as laptops, tablets, i-Pads, PCs, and cellular phones. The smart phone is considered as a more reliable, faster and efficient device to access and monitor industrial systems and their corresponding information interfaces anywhere and anytime. This study describes the deployment of a protocol whereby industrial system information can be securely accessed by cellular phones via a Supervisory Control And Data Acquisition (SCADA) server. To achieve the study goals, proprietary protocol interconnectivity with non-proprietary protocols and the usage of interconnectivity services are considered in detail. They support the visualization of the SCADA system information, and the related operations through smart phones. The intelligent sensors are configured and designated to process real information via cellular phones by employing information exchange services between the proprietary protocol and non-proprietary protocols. SCADA cellular access raises the issue of security flaws. For these challenges, a cryptography-based security method is considered and deployed, and it could be considered as a part of a proprietary protocol. Subsequently, transmission flows from the smart phones through a cellular network. PMID:27314351

A New Cellular Architecture for Information Retrieval from Sensor Networks through Embedded Service and Security Protocols.

PubMed

Shahzad, Aamir; Landry, René; Lee, Malrey; Xiong, Naixue; Lee, Jongho; Lee, Changhoon

2016-06-14

Substantial changes have occurred in the Information Technology (IT) sectors and with these changes, the demand for remote access to field sensor information has increased. This allows visualization, monitoring, and control through various electronic devices, such as laptops, tablets, i-Pads, PCs, and cellular phones. The smart phone is considered as a more reliable, faster and efficient device to access and monitor industrial systems and their corresponding information interfaces anywhere and anytime. This study describes the deployment of a protocol whereby industrial system information can be securely accessed by cellular phones via a Supervisory Control And Data Acquisition (SCADA) server. To achieve the study goals, proprietary protocol interconnectivity with non-proprietary protocols and the usage of interconnectivity services are considered in detail. They support the visualization of the SCADA system information, and the related operations through smart phones. The intelligent sensors are configured and designated to process real information via cellular phones by employing information exchange services between the proprietary protocol and non-proprietary protocols. SCADA cellular access raises the issue of security flaws. For these challenges, a cryptography-based security method is considered and deployed, and it could be considered as a part of a proprietary protocol. Subsequently, transmission flows from the smart phones through a cellular network.

A New Approach for Combining Time-of-Flight and RGB Cameras Based on Depth-Dependent Planar Projective Transformations

PubMed Central

Salinas, Carlota; Fernández, Roemi; Montes, Héctor; Armada, Manuel

2015-01-01

Image registration for sensor fusion is a valuable technique to acquire 3D and colour information for a scene. Nevertheless, this process normally relies on feature-matching techniques, which is a drawback for combining sensors that are not able to deliver common features. The combination of ToF and RGB cameras is an instance that problem. Typically, the fusion of these sensors is based on the extrinsic parameter computation of the coordinate transformation between the two cameras. This leads to a loss of colour information because of the low resolution of the ToF camera, and sophisticated algorithms are required to minimize this issue. This work proposes a method for sensor registration with non-common features and that avoids the loss of colour information. The depth information is used as a virtual feature for estimating a depth-dependent homography lookup table (Hlut). The homographies are computed within sets of ground control points of 104 images. Since the distance from the control points to the ToF camera are known, the working distance of each element on the Hlut is estimated. Finally, two series of experimental tests have been carried out in order to validate the capabilities of the proposed method. PMID:26404315

Analysis of temperature influence on the informative parameters of single-coil eddy current sensors

NASA Astrophysics Data System (ADS)

Borovik, S. Yu.; Kuteynikova, M. M.; Sekisov, Yu. N.; Skobelev, O. P.

2017-07-01

This paper describes the study of temperature in the flowing part of a turbine on the informative parameters (equivalent inductances of primary windings of matching transformers) of single-coil eddy-current sensors with a sensitive element in the form of a conductor section, which are used as part of automation systems for testing gas-turbine engines. In this case, the objects of temperature influences are both sensors and controlled turbine blades. The existing model of electromagnetic interaction of a sensitive element with the end part of a controlled blade is used to obtain quantitative estimates of temperature changes of equivalent inductances of sensitive elements and primary windings of matching transformers. This model is also used to determine the corresponding changes of the informative parameter of the sensor in the process of experimental studies of temperature influences on it (in the absence of blades in the sensitive region). This paper also presents transformations in the form of relationships of informative parameters with radial and axial displacements at normal (20 °C) and nominal (1000 °C) temperatures, and their difference is used to determine the families of dominant functions of temperature, which characterize possible temperature errors for any radial and axial displacements in the ranges of their variation.

Evaluation of sensor arrays for engine oils using artificial oil alteration

NASA Astrophysics Data System (ADS)

Sen, Sedat; Schneidhofer, Christoph; Dörr, Nicole; Vellekoop, Michael J.

2011-06-01

With respect to varying operation conditions, only sensors directly installed in the engine can detect the current oil condition hence enabling to get the right time for the oil change. Usually, only one parameter is not sufficient to obtain reliable information about the current oil condition. For this reason, appropriate sensor principles were evaluated for the design of sensor arrays for the measurement of critical lubricant parameters. In this contribution, we report on the development of a sensor array for engine oils using laboratory analyses of used engine oils for the correlation with sensor signals. The sensor array comprises the measurement of conductivity, permittivity, viscosity and temperature as well as oil corrosiveness as a consequence of acidification of the lubricant. As a key method, rapid evaluation of the sensors was done by short term simulation of entire oil change intervals based on artificial oil alteration. Thereby, the compatibility of the sensor array to the lubricant and the oil deterioration during the artificial alteration process was observed by the sensors and confirmed by additional laboratory analyses of oil samples take.

Use of ebRIM-based CSW with sensor observation services for registry and discovery of remote-sensing observations

NASA Astrophysics Data System (ADS)

Chen, Nengcheng; Di, Liping; Yu, Genong; Gong, Jianya; Wei, Yaxing

2009-02-01

Recent advances in Sensor Web geospatial data capture, such as high-resolution in satellite imagery and Web-ready data processing and modeling technologies, have led to the generation of large numbers of datasets from real-time or near real-time observations and measurements. Finding which sensor or data complies with criteria such as specific times, locations, and scales has become a bottleneck for Sensor Web-based applications, especially remote-sensing observations. In this paper, an architecture for use of the integration Sensor Observation Service (SOS) with the Open Geospatial Consortium (OGC) Catalogue Service-Web profile (CSW) is put forward. The architecture consists of a distributed geospatial sensor observation service, a geospatial catalogue service based on the ebXML Registry Information Model (ebRIM), SOS search and registry middleware, and a geospatial sensor portal. The SOS search and registry middleware finds the potential SOS, generating data granule information and inserting the records into CSW. The contents and sequence of the services, the available observations, and the metadata of the observations registry are described. A prototype system is designed and implemented using the service middleware technology and a standard interface and protocol. The feasibility and the response time of registry and retrieval of observations are evaluated using a realistic Earth Observing-1 (EO-1) SOS scenario. Extracting information from SOS requires the same execution time as record generation for CSW. The average data retrieval response time in SOS+CSW mode is 17.6% of that of the SOS-alone mode. The proposed architecture has the more advantages of SOS search and observation data retrieval than the existing sensor Web enabled systems.

Multi-spectral image analysis for improved space object characterization

NASA Astrophysics Data System (ADS)

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

2009-08-01

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

Tracking and Classification of In-Air Hand Gesture Based on Thermal Guided Joint Filter

PubMed Central

Kim, Seongwan; Ban, Yuseok; Lee, Sangyoun

2017-01-01

The research on hand gestures has attracted many image processing-related studies, as it intuitively conveys the intention of a human as it pertains to motional meaning. Various sensors have been used to exploit the advantages of different modalities for the extraction of important information conveyed by the hand gesture of a user. Although many works have focused on learning the benefits of thermal information from thermal cameras, most have focused on face recognition or human body detection, rather than hand gesture recognition. Additionally, the majority of the works that take advantage of multiple modalities (e.g., the combination of a thermal sensor and a visual sensor), usually adopting simple fusion approaches between the two modalities. As both thermal sensors and visual sensors have their own shortcomings and strengths, we propose a novel joint filter-based hand gesture recognition method to simultaneously exploit the strengths and compensate the shortcomings of each. Our study is motivated by the investigation of the mutual supplementation between thermal and visual information in low feature level for the consistent representation of a hand in the presence of varying lighting conditions. Accordingly, our proposed method leverages the thermal sensor’s stability against luminance and the visual sensors textural detail, while complementing the low resolution and halo effect of thermal sensors and the weakness against illumination of visual sensors. A conventional region tracking method and a deep convolutional neural network have been leveraged to track the trajectory of a hand gesture and to recognize the hand gesture, respectively. Our experimental results show stability in recognizing a hand gesture against varying lighting conditions based on the contribution of the joint kernels of spatial adjacency and thermal range similarity. PMID:28106716

Sensor Network Demonstration for In Situ Decommissioning - 13332

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

Lagos, L.; Varona, J.; Awwad, A.

2013-07-01

Florida International University's (FIU's) Applied Research Center is currently supporting the Department of Energy's (DOE) Environmental Management Office of D and D and Facility Engineering program. FIU is supporting DOE's initiative to improve safety, reduce technical risks, and limit uncertainty within D and D operations by identifying technologies suitable to meet specific facility D and D requirements, assessing the readiness of those technologies for field deployment, and conducting feasibility studies and large scale demonstrations of promising technologies. During FY11, FIU collaborated with Savannah River National Laboratory in the development of an experimental test site for the demonstration of multiple sensormore » systems for potential use in the in situ decommissioning process. In situ decommissioning is a process in which the above ground portion of a facility is dismantled and removed, and the underground portion is filled with a cementious material such as grout. In such a scenario, the question remains on how to effectively monitor the structural health of the grout (cracking, flexing, and sinking), as well as track possible migration of contaminants within and out of the grouted monolith. The right types of sensors can aid personnel in better understanding the conditions within the entombed structure. Without sensors embedded in and around the monolith, it will be very difficult to estimate structural integrity and contaminant transport. Yet, to fully utilize the appropriate sensors and the provided data, their performance and reliability must be evaluated outside a laboratory setting. To this end, a large scale experimental setup and demonstration was conducted at FIU. In order to evaluate a large suite of sensor systems, FIU personnel designed and purchased a pre-cast concrete open-top cube, which served as a mock-up of an in situ DOE decommissioned facility. The inside of the cube measures 10 ft x 10 ft x 8 ft. In order to ensure that the individual sensors would be immobilized during the grout pouring activities, a set of nine sensor racks were designed. The 270 sensors provided by Idaho National Laboratory (INL), Mississippi State University (MSU), University of Houston (UH), and University of South Carolina (USC) were secured to these racks based on predetermined locations. Once sensor racks were installed inside the test cube, connected and debugged, approximately 32 cubic yards of special grout material was used to entomb the sensors. MSU provided and demonstrated four types of fiber loop ring-down (FLR) sensors for detection of water, temperature, cracks, and movement of fluids. INL provided and demonstrated time differenced 3D electrical resistivity tomography (ERT), advanced tensiometers for moisture content, and thermocouples for temperature measurements. University of Houston provided smart aggregate (SA) sensors, which detect crack severity and water presence. An additional UH sensor system demonstrated was a Fiber Bragg Grating (FBG) fiber optic system measuring strain, presence of water, and temperature. USC provided a system which measured acoustic emissions during cracking, as well as temperature and pH sensors. All systems were connected to a Sensor Remote Access System (SRAS) data networking and collection system designed, developed and provided by FIU. The purpose of SRAS was to collect and allow download of the raw sensor data from all the sensor system, as well as allow upload of the processed data and any analysis reports and graphs. All this information was made available to the research teams via the Deactivation and Decommissioning Knowledge Management and Information Tool (D and D KM-IT). As a current research effort, FIU is performing an energy analysis, and transferring several sensor systems to a Photovoltaic (PV) System to continuously monitor energy consumption parameters and overall power demands. Also, One final component of this research is focusing on developing an integrated data network to capture, log and analyze sensor system data in near real time from a single interface. FIU personnel and DOE Fellows monitored the progress and condition of the sensors for a period of six months. During this time, the sensors recorded data pertaining to strain, compression, temperature, crack detection, moisture presence, fluid mobility, shock resistance, monolith movement, and electrical resistivity. In addition, FIU regularly observed the curing process of the grout and documented the cube condition via the nine racks of sensors. The sensors held up throughout the curing process, withstood the natural elements for six months, and monitored the integrity of the grout. The large scale experiment and demonstration conducted at FIU was the first of its kind to demonstrate the feasibility of state of the art sensors for in situ decommissioning applications. These efforts successfully measured the durability, performance, and precision of the sensors in question as well as monitored and recorded the curing process of the selected grout material under natural environmental conditions. The current energy analysis work is resulting in data on the constraints placed by some of the sensor systems on a power network that requires high reliability and low losses. In addition, a sensor system demonstration has determined that it is feasible to develop an integrated data network where data can be accessed in near real-time from all systems, thereby allowing for larger-scale integrated system testing to be performed. Information collected during the execution of this research project will aid decision makers in the identification of sensors to be used in nuclear facilities selected for in situ decommissioning. (authors)« less

Inflight and Preflight Detection of Pitot Tube Anomalies

NASA Technical Reports Server (NTRS)

Mitchell, Darrell W.

2014-01-01

The health and integrity of aircraft sensors play a critical role in aviation safety. Inaccurate or false readings from these sensors can lead to improper decision making, resulting in serious and sometimes fatal consequences. This project demonstrated the feasibility of using advanced data analysis techniques to identify anomalies in Pitot tubes resulting from blockage such as icing, moisture, or foreign objects. The core technology used in this project is referred to as noise analysis because it relates sensors' response time to the dynamic component (noise) found in the signal of these same sensors. This analysis technique has used existing electrical signals of Pitot tube sensors that result from measured processes during inflight conditions and/or induced signals in preflight conditions to detect anomalies in the sensor readings. Analysis and Measurement Services Corporation (AMS Corp.) has routinely used this technology to determine the health of pressure transmitters in nuclear power plants. The application of this technology for the detection of aircraft anomalies is innovative. Instead of determining the health of process monitoring at a steady-state condition, this technology will be used to quickly inform the pilot when an air-speed indication becomes faulty under any flight condition as well as during preflight preparation.

Novel compact panomorph lens based vision system for monitoring around a vehicle

NASA Astrophysics Data System (ADS)

Thibault, Simon

2008-04-01

Automotive applications are one of the largest vision-sensor market segments and one of the fastest growing ones. The trend to use increasingly more sensors in cars is driven both by legislation and consumer demands for higher safety and better driving experiences. Awareness of what directly surrounds a vehicle affects safe driving and manoeuvring of a vehicle. Consequently, panoramic 360° Field of View imaging can contributes most to the perception of the world around the driver than any other sensors. However, to obtain a complete vision around the car, several sensor systems are necessary. To solve this issue, a customized imaging system based on a panomorph lens will provide the maximum information for the drivers with a reduced number of sensors. A panomorph lens is a hemispheric wide angle anamorphic lens with enhanced resolution in predefined zone of interest. Because panomorph lenses are optimized to a custom angle-to-pixel relationship, vision systems provide ideal image coverage that reduces and optimizes the processing. We present various scenarios which may benefit from the use of a custom panoramic sensor. We also discuss the technical requirements of such vision system. Finally we demonstrate how the panomorph based visual sensor is probably one of the most promising ways to fuse many sensors in one. For example, a single panoramic sensor on the front of a vehicle could provide all necessary information for assistance in crash avoidance, lane tracking, early warning, park aids, road sign detection, and various video monitoring views.

Sensing Models and Sensor Network Architectures for Transport Infrastructure Monitoring in Smart Cities

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.

Time-Of-Flight Camera, Optical Tracker and Computed Tomography in Pairwise Data Registration.

PubMed

Pycinski, Bartlomiej; Czajkowska, Joanna; Badura, Pawel; Juszczyk, Jan; Pietka, Ewa

2016-01-01

A growing number of medical applications, including minimal invasive surgery, depends on multi-modal or multi-sensors data processing. Fast and accurate 3D scene analysis, comprising data registration, seems to be crucial for the development of computer aided diagnosis and therapy. The advancement of surface tracking system based on optical trackers already plays an important role in surgical procedures planning. However, new modalities, like the time-of-flight (ToF) sensors, widely explored in non-medical fields are powerful and have the potential to become a part of computer aided surgery set-up. Connection of different acquisition systems promises to provide a valuable support for operating room procedures. Therefore, the detailed analysis of the accuracy of such multi-sensors positioning systems is needed. We present the system combining pre-operative CT series with intra-operative ToF-sensor and optical tracker point clouds. The methodology contains: optical sensor set-up and the ToF-camera calibration procedures, data pre-processing algorithms, and registration technique. The data pre-processing yields a surface, in case of CT, and point clouds for ToF-sensor and marker-driven optical tracker representation of an object of interest. An applied registration technique is based on Iterative Closest Point algorithm. The experiments validate the registration of each pair of modalities/sensors involving phantoms of four various human organs in terms of Hausdorff distance and mean absolute distance metrics. The best surface alignment was obtained for CT and optical tracker combination, whereas the worst for experiments involving ToF-camera. The obtained accuracies encourage to further develop the multi-sensors systems. The presented substantive discussion concerning the system limitations and possible improvements mainly related to the depth information produced by the ToF-sensor is useful for computer aided surgery developers.

Localization Using Visual Odometry and a Single Downward-Pointing Camera

NASA Technical Reports Server (NTRS)

Swank, Aaron J.

2012-01-01

Stereo imaging is a technique commonly employed for vision-based navigation. For such applications, two images are acquired from different vantage points and then compared using transformations to extract depth information. The technique is commonly used in robotics for obstacle avoidance or for Simultaneous Localization And Mapping, (SLAM). Yet, the process requires a number of image processing steps and therefore tends to be CPU-intensive, which limits the real-time data rate and use in power-limited applications. Evaluated here is a technique where a monocular camera is used for vision-based odometry. In this work, an optical flow technique with feature recognition is performed to generate odometry measurements. The visual odometry sensor measurements are intended to be used as control inputs or measurements in a sensor fusion algorithm using low-cost MEMS based inertial sensors to provide improved localization information. Presented here are visual odometry results which demonstrate the challenges associated with using ground-pointing cameras for visual odometry. The focus is for rover-based robotic applications for localization within GPS-denied environments.

Particle Filter-Based Recursive Data Fusion With Sensor Indexing for Large Core Neutron Flux Estimation

NASA Astrophysics Data System (ADS)

Tamboli, Prakash Kumar; Duttagupta, Siddhartha P.; Roy, Kallol

2017-06-01

We introduce a sequential importance sampling particle filter (PF)-based multisensor multivariate nonlinear estimator for estimating the in-core neutron flux distribution for pressurized heavy water reactor core. Many critical applications such as reactor protection and control rely upon neutron flux information, and thus their reliability is of utmost importance. The point kinetic model based on neutron transport conveniently explains the dynamics of nuclear reactor. The neutron flux in the large core loosely coupled reactor is sensed by multiple sensors measuring point fluxes located at various locations inside the reactor core. The flux values are coupled to each other through diffusion equation. The coupling facilitates redundancy in the information. It is shown that multiple independent data about the localized flux can be fused together to enhance the estimation accuracy to a great extent. We also propose the sensor anomaly handling feature in multisensor PF to maintain the estimation process even when the sensor is faulty or generates data anomaly.

Airborne sensors for detecting large marine debris at sea.

PubMed

Veenstra, Timothy S; Churnside, James H

2012-01-01

The human eye is an excellent, general-purpose airborne sensor for detecting marine debris larger than 10 cm on or near the surface of the water. Coupled with the human brain, it can adjust for light conditions and sea-surface roughness, track persistence, differentiate color and texture, detect change in movement, and combine all of the available information to detect and identify marine debris. Matching this performance with computers and sensors is difficult at best. However, there are distinct advantages over the human eye and brain that sensors and computers can offer such as the ability to use finer spectral resolution, to work outside the spectral range of human vision, to control the illumination, to process the information in ways unavailable to the human vision system, to provide a more objective and reproducible result, to operate from unmanned aircraft, and to provide a permanent record that can be used for later analysis. Copyright © 2010 Elsevier Ltd. All rights reserved.

TwitterSensing: An Event-Based Approach for Wireless Sensor Networks Optimization Exploiting Social Media in Smart City Applications

PubMed Central

2018-01-01

Modern cities are subject to periodic or unexpected critical events, which may bring economic losses or even put people in danger. When some monitoring systems based on wireless sensor networks are deployed, sensing and transmission configurations of sensor nodes may be adjusted exploiting the relevance of the considered events, but efficient detection and classification of events of interest may be hard to achieve. In Smart City environments, several people spontaneously post information in social media about some event that is being observed and such information may be mined and processed for detection and classification of critical events. This article proposes an integrated approach to detect and classify events of interest posted in social media, notably in Twitter, and the assignment of sensing priorities to source nodes. By doing so, wireless sensor networks deployed in Smart City scenarios can be optimized for higher efficiency when monitoring areas under the influence of the detected events. PMID:29614060

TwitterSensing: An Event-Based Approach for Wireless Sensor Networks Optimization Exploiting Social Media in Smart City Applications.

PubMed

Costa, Daniel G; Duran-Faundez, Cristian; Andrade, Daniel C; Rocha-Junior, João B; Peixoto, João Paulo Just

2018-04-03

Modern cities are subject to periodic or unexpected critical events, which may bring economic losses or even put people in danger. When some monitoring systems based on wireless sensor networks are deployed, sensing and transmission configurations of sensor nodes may be adjusted exploiting the relevance of the considered events, but efficient detection and classification of events of interest may be hard to achieve. In Smart City environments, several people spontaneously post information in social media about some event that is being observed and such information may be mined and processed for detection and classification of critical events. This article proposes an integrated approach to detect and classify events of interest posted in social media, notably in Twitter , and the assignment of sensing priorities to source nodes. By doing so, wireless sensor networks deployed in Smart City scenarios can be optimized for higher efficiency when monitoring areas under the influence of the detected events.

A Multi-Agent System Architecture for Sensor Networks

PubMed Central

Fuentes-Fernández, Rubén; Guijarro, María; Pajares, Gonzalo

2009-01-01

The design of the control systems for sensor networks presents important challenges. Besides the traditional problems about how to process the sensor data to obtain the target information, engineers need to consider additional aspects such as the heterogeneity and high number of sensors, and the flexibility of these networks regarding topologies and the sensors in them. Although there are partial approaches for resolving these issues, their integration relies on ad hoc solutions requiring important development efforts. In order to provide an effective approach for this integration, this paper proposes an architecture based on the multi-agent system paradigm with a clear separation of concerns. The architecture considers sensors as devices used by an upper layer of manager agents. These agents are able to communicate and negotiate services to achieve the required functionality. Activities are organized according to roles related with the different aspects to integrate, mainly sensor management, data processing, communication and adaptation to changes in the available devices and their capabilities. This organization largely isolates and decouples the data management from the changing network, while encouraging reuse of solutions. The use of the architecture is facilitated by a specific modelling language developed through metamodelling. A case study concerning a generic distributed system for fire fighting illustrates the approach and the comparison with related work. PMID:22303172

A multi-agent system architecture for sensor networks.

PubMed

Fuentes-Fernández, Rubén; Guijarro, María; Pajares, Gonzalo

2009-01-01

The design of the control systems for sensor networks presents important challenges. Besides the traditional problems about how to process the sensor data to obtain the target information, engineers need to consider additional aspects such as the heterogeneity and high number of sensors, and the flexibility of these networks regarding topologies and the sensors in them. Although there are partial approaches for resolving these issues, their integration relies on ad hoc solutions requiring important development efforts. In order to provide an effective approach for this integration, this paper proposes an architecture based on the multi-agent system paradigm with a clear separation of concerns. The architecture considers sensors as devices used by an upper layer of manager agents. These agents are able to communicate and negotiate services to achieve the required functionality. Activities are organized according to roles related with the different aspects to integrate, mainly sensor management, data processing, communication and adaptation to changes in the available devices and their capabilities. This organization largely isolates and decouples the data management from the changing network, while encouraging reuse of solutions. The use of the architecture is facilitated by a specific modelling language developed through metamodelling. A case study concerning a generic distributed system for fire fighting illustrates the approach and the comparison with related work.

Intelligent data processing of an ultrasonic sensor system for pattern recognition improvements

NASA Astrophysics Data System (ADS)

Na, Seung You; Park, Min-Sang; Hwang, Won-Gul; Kee, Chang-Doo

1999-05-01

Though conventional time-of-flight ultrasonic sensor systems are popular due to the advantages of low cost and simplicity, the usage of the sensors is rather narrowly restricted within object detection and distance readings. There is a strong need to enlarge the amount of environmental information for mobile applications to provide intelligent autonomy. Wide sectors of such neighboring object recognition problems can be satisfactorily handled with coarse vision data such as sonar maps instead of accurate laser or optic measurements. For the usage of object pattern recognition, ultrasonic senors have inherent shortcomings of poor directionality and specularity which result in low spatial resolution and indistinctiveness of object patterns. To resolve these problems an array of increased number of sensor elements has been used for large objects. In this paper we propose a method of sensor array system with improved recognition capability using electronic circuits accompanying the sensor array and neuro-fuzzy processing of data fusion. The circuit changes transmitter output voltages of array elements in several steps. Relying upon the known sensor characteristics, a set of different return signals from neighboring senors is manipulated to provide an enhanced pattern recognition in the aspects of inclination angle, size and shift as well as distance of objects. The results show improved resolution of the measurements for smaller targets.

Small craft ID criteria (N50/V50) for short wave infrared sensors in maritime security

NASA Astrophysics Data System (ADS)

Krapels, Keith; Driggers, Ronald G.; Larson, Paul; Garcia, Jose; Walden, Barry; Agheera, Sameer; Deaver, Dawne; Hixson, Jonathan; Boettcher, Evelyn

2008-04-01

The need for Anti-Terrorism and Force Protection (AT/FP), for both shore and sea platform protection, has resulted in a need for imager design and evaluation tools which can predict field performance against maritime asymmetric threats. In the design of tactical imaging systems for target acquisition, a discrimination criterion is required for successful sensor realization. It characterizes the difficulty of the task being performed by the observer and varies for different target sets. This criterion is used in both assessment of existing infrared sensor and in the design of new conceptual sensors. In this experiment, we collected 8 small craft signatures (military and civilian) in the short wave infrared (SWIR) band during the day. These signatures were processed to determine the targets' characteristic dimension and contrast. They were also processed to bandlimit the signature's spatial information content (simulating longer range) and a perception experiment was performed to determine the task difficulty (N50 and V50). The results are presented in this paper and can be used for maritime security imaging sensor design and evaluation.

Study of Aerospace Materials, Coatings, Adhesions and Processes. Aircraft Icing Processes. Volume 2.

DTIC Science & Technology

1984-09-14

la direccio’n del eje de la son - da. DATOS ELECTRICOS Rint’erna 20.26 . R(OC) =5.35 Q R(22 0 C).. 5.93 Q R(100 0 C) 7.43 . Roperacio’n... son las constantes de calibraci6n propias del sensor. 1INT A FN. de Informe I-231/S10/84.076Pg. . La temperatura de funcionamiento se deterrnin6 por l...funcionamiento del sensor, T la temperatura ambiente, la densidad y v la velocidad. A, B y n son las constantes de cal- z braci6n propias del

Importance of the spatial data and the sensor web in the ubiquitous computing area

NASA Astrophysics Data System (ADS)

Akçit, Nuhcan; Tomur, Emrah; Karslıoǧlu, Mahmut O.

2014-08-01

Spatial data has become a critical issue in recent years. In the past years, nearly more than three quarters of databases, were related directly or indirectly to locations referring to physical features, which constitute the relevant aspects. Spatial data is necessary to identify or calculate the relationships between spatial objects when using spatial operators in programs or portals. Originally, calculations were conducted using Geographic Information System (GIS) programs on local computers. Subsequently, through the Internet, they formed a geospatial web, which is integrated into a discoverable collection of geographically related web standards and key features, and constitutes a global network of geospatial data that employs the World Wide Web to process textual data. In addition, the geospatial web is used to gather spatial data producers, resources, and users. Standards also constitute a critical dimension in further globalizing the idea of the geospatial web. The sensor web is an example of the real time service that the geospatial web can provide. Sensors around the world collect numerous types of data. The sensor web is a type of sensor network that is used for visualizing, calculating, and analyzing collected sensor data. Today, people use smart devices and systems more frequently because of the evolution of technology and have more than one mobile device. The considerable number of sensors and different types of data that are positioned around the world have driven the production of interoperable and platform-independent sensor web portals. The focus of such production has been on further developing the idea of an interoperable and interdependent sensor web of all devices that share and collect information. The other pivotal idea consists of encouraging people to use and send data voluntarily for numerous purposes with the some level of credibility. The principal goal is to connect mobile and non-mobile device in the sensor web platform together to operate for serving and collecting information from people.

The SARVIEWS Project: Automated SAR Processing in Support of Operational Near Real-time Volcano Monitoring

NASA Astrophysics Data System (ADS)

Meyer, F. J.; Webley, P. W.; Dehn, J.; Arko, S. A.; McAlpin, D. B.; Gong, W.

2016-12-01

Volcanic eruptions are among the most significant hazards to human society, capable of triggering natural disasters on regional to global scales. In the last decade, remote sensing has become established in operational volcano monitoring. Centers like the Alaska Volcano Observatory rely heavily on remote sensing data from optical and thermal sensors to provide time-critical hazard information. Despite this high use of remote sensing data, the presence of clouds and a dependence on solar illumination often limit their impact on decision making. Synthetic Aperture Radar (SAR) systems are widely considered superior to optical sensors in operational monitoring situations, due to their weather and illumination independence. Still, the contribution of SAR to operational volcano monitoring has been limited in the past due to high data costs, long processing times, and low temporal sampling rates of most SAR systems. In this study, we introduce the automatic SAR processing system SARVIEWS, whose advanced data analysis and data integration techniques allow, for the first time, a meaningful integration of SAR into operational monitoring systems. We will introduce the SARVIEWS database interface that allows for automatic, rapid, and seamless access to the data holdings of the Alaska Satellite Facility. We will also present a set of processing techniques designed to automatically generate a set of SAR-based hazard products (e.g. change detection maps, interferograms, geocoded images). The techniques take advantage of modern signal processing and radiometric normalization schemes, enabling the combination of data from different geometries. Finally, we will show how SAR-based hazard information is integrated in existing multi-sensor decision support tools to enable joint hazard analysis with data from optical and thermal sensors. We will showcase the SAR processing system using a set of recent natural disasters (both earthquakes and volcanic eruptions) to demonstrate its robustness. We will also show the benefit of integrating SAR with data from other sensors to support volcano monitoring. For historic eruptions at Okmok and Augustine volcano, both located in the North Pacific, we will demonstrate that the addition of SAR can lead to a significant improvement in activity detection and eruption forecasting.

Design requirements for operational earth resources ground data processing

NASA Technical Reports Server (NTRS)

Baldwin, C. J.; Bradford, L. H.; Burnett, E. S.; Hutson, D. E.; Kinsler, B. A.; Kugle, D. R.; Webber, D. S.

1972-01-01

Realistic tradeoff data and evaluation techniques were studied that permit conceptual design of operational earth resources ground processing systems. Methodology for determining user requirements that utilize the limited information available from users is presented along with definitions of sensor capabilities projected into the shuttle/station era. A tentative method is presented for synthesizing candidate ground processing concepts.

Wildland fire management. Volume 2: Wildland fire control 1985-1995. [satellite information system for California fire problems

NASA Technical Reports Server (NTRS)

Saveker, D. R. (Editor)

1973-01-01

The preliminary design of a satellite plus computer earth resources information system is proposed for potential uses in fire prevention and control in the wildland fire community. Suggested are satellite characteristics, sensor characteristics, discrimination algorithms, data communication techniques, data processing requirements, display characteristics, and costs in achieving the integrated wildland fire information system.

Differential GNSS and Vision-Based Tracking to Improve Navigation Performance in Cooperative Multi-UAV Systems.

PubMed

Vetrella, Amedeo Rodi; Fasano, Giancarmine; Accardo, Domenico; Moccia, Antonio

2016-12-17

Autonomous navigation of micro-UAVs is typically based on the integration of low cost Global Navigation Satellite System (GNSS) receivers and Micro-Electro-Mechanical Systems (MEMS)-based inertial and magnetic sensors to stabilize and control the flight. The resulting navigation performance in terms of position and attitude accuracy may not suffice for other mission needs, such as the ones relevant to fine sensor pointing. In this framework, this paper presents a cooperative UAV navigation algorithm that allows a chief vehicle, equipped with inertial and magnetic sensors, a Global Positioning System (GPS) receiver, and a vision system, to improve its navigation performance (in real time or in the post processing phase) exploiting formation flying deputy vehicles equipped with GPS receivers. The focus is set on outdoor environments and the key concept is to exploit differential GPS among vehicles and vision-based tracking (DGPS/Vision) to build a virtual additional navigation sensor whose information is then integrated in a sensor fusion algorithm based on an Extended Kalman Filter. The developed concept and processing architecture are described, with a focus on DGPS/Vision attitude determination algorithm. Performance assessment is carried out on the basis of both numerical simulations and flight tests. In the latter ones, navigation estimates derived from the DGPS/Vision approach are compared with those provided by the onboard autopilot system of a customized quadrotor. The analysis shows the potential of the developed approach, mainly deriving from the possibility to exploit magnetic- and inertial-independent accurate attitude information.

Simultaneous measurement of sensor-protein dynamics and motility of a single cell by on-chip microcultivation system

PubMed Central

Inoue, Ippei; Shiomi, Daisuke; Kawagishi, Ikuro; Yasuda, Kenji

2004-01-01

Measurement of the correlation between sensor-protein expression, motility and environmental change is important for understanding the adaptation process of cells during their change of generation. We have developed a novel assay exploiting the on-chip cultivation system, which enabled us to observe the change of the localization of expressed sensor-protein and the motility for generations. Localization of the aspartate sensitive sensor protein at two poles in Escherichia coli decreased quickly after the aspartate was added into the cultivation medium. However, it took more than three generations for recovering the localization after the removal of aspartate from the medium. Moreover, the tumbling frequency was strongly related to the localization of the sensor protein in a cell. The results indicate that the change of the spatial localization of sensor protein, which was inherited for more than three generations, may contribute to cells, motility as the inheritable information. PMID:15119953

Atmospheric correction for hyperspectral ocean color sensors

NASA Astrophysics Data System (ADS)

Ibrahim, A.; Ahmad, Z.; Franz, B. A.; Knobelspiesse, K. D.

2017-12-01

NASA's heritage Atmospheric Correction (AC) algorithm for multi-spectral ocean color sensors is inadequate for the new generation of spaceborne hyperspectral sensors, such as NASA's first hyperspectral Ocean Color Instrument (OCI) onboard the anticipated Plankton, Aerosol, Cloud, ocean Ecosystem (PACE) satellite mission. The AC process must estimate and remove the atmospheric path radiance contribution due to the Rayleigh scattering by air molecules and by aerosols from the measured top-of-atmosphere (TOA) radiance. Further, it must also compensate for the absorption by atmospheric gases and correct for reflection and refraction of the air-sea interface. We present and evaluate an improved AC for hyperspectral sensors beyond the heritage approach by utilizing the additional spectral information of the hyperspectral sensor. The study encompasses a theoretical radiative transfer sensitivity analysis as well as a practical application of the Hyperspectral Imager for the Coastal Ocean (HICO) and the Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) sensors.

Multisatellite attitude determination/optical aspect bias determination (MSAD/OABIAS) system description and operating guide. Volume 3: Operating guide

NASA Technical Reports Server (NTRS)

Joseph, M.; Keat, J.; Liu, K. S.; Plett, M. E.; Shear, M. A.; Shinohara, T.; Wertz, J. R.

1983-01-01

The Multisatellite Attitude Determination/Optical Aspect Bias Determination (MSAD/OABIAS) System, designed to determine spin axis orientation and biases in the alignment or performance of optical or infrared horizon sensors and Sun sensors used for spacecraft attitude determination, is described. MSAD/OABIAS uses any combination of eight observation models to process data from a single onboard horizon sensor and Sun sensor to determine simultaneously the two components of the attitude of the spacecraft, the initial phase of the Sun sensor, the spin rate, seven sensor biases, and the orbital in-track error associated with the spacecraft ephemeris information supplied to the system. In addition, the MSAD/OABIAS system provides a data simulator for system and performance testing, an independent deterministic attitude system for preprocessing and independent testing of biases determined, and a multipurpose data prediction and comparison system.

Development of esMOCA RULA, Motion Capture Instrumentation for RULA Assessment

NASA Astrophysics Data System (ADS)

Akhmad, S.; Arendra, A.

2018-01-01

The purpose of this research is to build motion capture instrumentation using sensors fusion accelerometer and gyroscope to assist in RULA assessment. Data processing of sensor orientation is done in every sensor node by digital motion processor. Nine sensors are placed in the upper limb of operator subject. Development of kinematics model is done with Simmechanic Simulink. This kinematics model receives streaming data from sensors via wireless sensors network. The output of the kinematics model is the relative angular angle between upper limb members and visualized on the monitor. This angular information is compared to the look-up table of the RULA worksheet and gives the RULA score. The assessment result of the instrument is compared with the result of the assessment by rula assessors. To sum up, there is no significant difference of assessment by the instrument with an assessment by an assessor.

Multisatellite attitude determination/optical aspect bias determination (MSAD/OABIAS) system description and operating guide. Volume 1: Introduction and analysis

NASA Technical Reports Server (NTRS)

Joseph, M.; Ket, J. E.; Liu, K. S.; Plett, M. E.; Shear, M. A.; Shinohara, T.; Wertz, J. R.

1983-01-01

The Multisatellite Attitude Determination/Optical Aspect Bias Determination (MSAD/OABIAS) System, designed to determine spin axis orientation and biases in the alignment or performance of optical or infrared horizon sensors and Sun sensors used for spacecraft attitude determination is described. MSAD/OABIAS uses any combination of eight observation models to process data from a single onboard horizon sensor and Sun sensor to determine simultaneously the two components of the attitude of the spacecraft, the initial phase of the Sun sensor, the spin rate, seven sensor biases, and the orbital in-track error associated with the spacecraft ephemeris information supplied to the system. In addition, the MSAD/OABIAS System provides a data simulator for system and performance testing, an independent deterministic attitude system for preprocessing and independent testing of biases determined, and a multipurpose data prediction and comparison system.

Smart spectroscopy sensors: II. Narrow-band laser systems

NASA Astrophysics Data System (ADS)

Matharoo, Inderdeep; Peshko, Igor

2013-03-01

This paper describes the principles of operation of a miniature multifunctional optical sensory system based on laser technology and spectroscopic principles of analysis. The operation of the system as a remote oxygen sensor has been demonstrated. The multi-component alarm sensor has been designed to recognise gases and to measure gas concentration (O2, CO2, CO, CH4, N2O, C2H2, HI, OH radicals and H2O vapour, including semi-heavy water), temperature, pressure, humidity, and background radiation from the environment. Besides gas sensing, the same diode lasers are used for range-finding and to provide sensor self-calibration. The complete system operates as an inhomogeneous sensory network: the laser sensors are capable of using information received from environmental sensors for improving accuracy and reliability of gas concentration measurement. The sources of measurement errors associated with hardware and algorithms of operation and data processing have been analysed in detail.

Electric fish as natural models for technical sensor systems

NASA Astrophysics Data System (ADS)

von der Emde, Gerhard; Bousack, Herbert; Huck, Christina; Mayekar, Kavita; Pabst, Michael; Zhang, Yi

2009-05-01

Instead of vision, many animals use alternative senses for object detection. Weakly electric fish employ "active electrolocation", during which they discharge an electric organ emitting electrical current pulses (electric organ discharges, EOD). Local EODs are sensed by electroreceptors in the fish's skin, which respond to changes of the signal caused by nearby objects. Fish can gain information about attributes of an object, such as size, shape, distance, and complex impedance. When close to the fish, each object projects an 'electric image' onto the fish's skin. In order to get information about an object, the fish has to analyze the object's electric image by sampling its voltage distribution with the electroreceptors. We now know a great deal about the mechanisms the fish use to gain information about objects in their environment. Inspired by the remarkable capabilities of weakly electric fish in detecting and recognizing objects with their electric sense, we are designing technical sensor systems that can solve similar sensing problems. We applied the principles of active electrolocation to devices that produce electrical current pulses in water and simultaneously sense local current densities. Depending on the specific task, sensors can be designed which detect an object, localize it in space, determine its distance, and measure certain object properties such as material properties, thickness, or material faults. We present first experiments and FEM simulations on the optimal sensor arrangement regarding the sensor requirements e. g. localization of objects or distance measurements. Different methods of the sensor read-out and signal processing are compared.

Fast Measurement and Reconstruction of Large Workpieces with Freeform Surfaces by Combining Local Scanning and Global Position Data

PubMed Central

Chen, Zhe; Zhang, Fumin; Qu, Xinghua; Liang, Baoqiu

2015-01-01

In this paper, we propose a new approach for the measurement and reconstruction of large workpieces with freeform surfaces. The system consists of a handheld laser scanning sensor and a position sensor. The laser scanning sensor is used to acquire the surface and geometry information, and the position sensor is utilized to unify the scanning sensors into a global coordinate system. The measurement process includes data collection, multi-sensor data fusion and surface reconstruction. With the multi-sensor data fusion, errors accumulated during the image alignment and registration process are minimized, and the measuring precision is significantly improved. After the dense accurate acquisition of the three-dimensional (3-D) coordinates, the surface is reconstructed using a commercial software piece, based on the Non-Uniform Rational B-Splines (NURBS) surface. The system has been evaluated, both qualitatively and quantitatively, using reference measurements provided by a commercial laser scanning sensor. The method has been applied for the reconstruction of a large gear rim and the accuracy is up to 0.0963 mm. The results prove that this new combined method is promising for measuring and reconstructing the large-scale objects with complex surface geometry. Compared with reported methods of large-scale shape measurement, it owns high freedom in motion, high precision and high measurement speed in a wide measurement range. PMID:26091396

A Review on Sensor, Signal, and Information Processing Algorithms (PREPRINT)

DTIC Science & Technology

2010-01-01

processing [214], ambi- guity surface averaging [215], optimum uncertain field tracking, and optimal minimum variance track - before - detect [216]. In [217, 218...2) (2001) 739–746. [216] S. L. Tantum, L. W. Nolte, J. L. Krolik, K. Harmanci, The performance of matched-field track - before - detect methods using

Integrated Sensing and Processing (ISP) Phase II: Demonstration and Evaluation for Distributed Sensor Netowrks and Missile Seeker Systems

DTIC Science & Technology

2007-02-28

Shah, D. Waagen, H. Schmitt, S. Bellofiore, A. Spanias, and D. Cochran, 32nd International Conference on Acoustics, Speech , and Signal Processing...Information Exploitation Office kNN k-Nearest Neighbor LEAN Laplacian Eigenmap Adaptive Neighbor LIP Linear Integer Programming ISP

The Cloud2SM Project

NASA Astrophysics Data System (ADS)

Crinière, Antoine; Dumoulin, Jean; Mevel, Laurent; Andrade-Barosso, Guillermo; Simonin, Matthieu

2015-04-01

From the past decades the monitoring of civil engineering structure became a major field of research and development process in the domains of modelling and integrated instrumentation. This increasing of interest can be attributed in part to the need of controlling the aging of such structures and on the other hand to the need to optimize maintenance costs. From this standpoint the project Cloud2SM (Cloud architecture design for Structural Monitoring with in-line Sensors and Models tasking), has been launched to develop a robust information system able to assess the long term monitoring of civil engineering structures as well as interfacing various sensors and data. The specificity of such architecture is to be based on the notion of data processing through physical or statistical models. Thus the data processing, whether material or mathematical, can be seen here as a resource of the main architecture. The project can be divided in various items: -The sensors and their measurement process: Those items provide data to the main architecture and can embed storage or computational resources. Dependent of onboard capacity and the amount of data generated it can be distinguished heavy and light sensors. - The storage resources: Based on the cloud concept this resource can store at least two types of data, raw data and processed ones. - The computational resources: This item includes embedded "pseudo real time" resources as the dedicated computer cluster or computational resources. - The models: Used for the conversion of raw data to meaningful data. Those types of resources inform the system of their needs they can be seen as independents blocks of the system. - The user interface: This item can be divided in various HMI to assess maintaining operation on the sensors or pop-up some information to the user. - The demonstrators: The structures themselves. This project follows previous research works initiated in the European project ISTIMES [1]. It includes the infrared thermal monitoring of civil engineering structures [2-3] and/or the vibration monitoring of such structures [4-5]. The chosen architecture is based on the OGC standard in order to ensure the interoperability between the various measurement systems. This concept is extended to the notion of physical models. The last but not the least main objective of this project is to explore the feasibility and the reliability to deploy mathematical models and process a large amount of data using the GPGPU capacity of a dedicated computational cluster, while studying OGC standardization to those technical concepts. References [1] M. Proto et al., « Transport Infrastructure surveillance and Monitoring by Electromagnetic Sensing: the ISTIMES project », Journal Sensors, Sensors 2010, 10(12), 10620-10639; doi:10.3390/s101210620, December 2010. [2] J. Dumoulin, A. Crinière, R. Averty ," Detection and thermal characterization of the inner structure of the "Musmeci" bridge deck by infrared thermography monitoring ",Journal of Geophysics and Engineering, Volume 10, Number 2, 17 pages ,November 2013, IOP Science, doi:10.1088/1742-2132/10/6/064003. [3] J Dumoulin and V Boucher; "Infrared thermography system for transport infrastructures survey with inline local atmospheric parameter measurements and offline model for radiation attenuation evaluations," J. Appl. Remote Sens., 8(1), 084978 (2014). doi:10.1117/1.JRS.8.084978. [4] V. Le Cam, M. Doehler, M. Le Pen, L. Mevel. "Embedded modal analysis algorithms on the smart wireless sensor platform PEGASE", In Proc. 9th International Workshop on Structural Health Monitoring, Stanford, CA, USA, 2013. [5] M. Zghal, L. Mevel, P. Del Moral, "Modal parameter estimation using interacting Kalman filter", Mechanical Systems and Signal Processing, 2014.

Volumetric Forest Change Detection Through Vhr Satellite Imagery

NASA Astrophysics Data System (ADS)

Akca, Devrim; Stylianidis, Efstratios; Smagas, Konstantinos; Hofer, Martin; Poli, Daniela; Gruen, Armin; Sanchez Martin, Victor; Altan, Orhan; Walli, Andreas; Jimeno, Elisa; Garcia, Alejandro

2016-06-01

Quick and economical ways of detecting of planimetric and volumetric changes of forest areas are in high demand. A research platform, called FORSAT (A satellite processing platform for high resolution forest assessment), was developed for the extraction of 3D geometric information from VHR (very-high resolution) imagery from satellite optical sensors and automatic change detection. This 3D forest information solution was developed during a Eurostars project. FORSAT includes two main units. The first one is dedicated to the geometric and radiometric processing of satellite optical imagery and 2D/3D information extraction. This includes: image radiometric pre-processing, image and ground point measurement, improvement of geometric sensor orientation, quasiepipolar image generation for stereo measurements, digital surface model (DSM) extraction by using a precise and robust image matching approach specially designed for VHR satellite imagery, generation of orthoimages, and 3D measurements in single images using mono-plotting and in stereo images as well as triplets. FORSAT supports most of the VHR optically imagery commonly used for civil applications: IKONOS, OrbView - 3, SPOT - 5 HRS, SPOT - 5 HRG, QuickBird, GeoEye-1, WorldView-1/2, Pléiades 1A/1B, SPOT 6/7, and sensors of similar type to be expected in the future. The second unit of FORSAT is dedicated to 3D surface comparison for change detection. It allows users to import digital elevation models (DEMs), align them using an advanced 3D surface matching approach and calculate the 3D differences and volume changes between epochs. To this end our 3D surface matching method LS3D is being used. FORSAT is a single source and flexible forest information solution with a very competitive price/quality ratio, allowing expert and non-expert remote sensing users to monitor forests in three and four dimensions from VHR optical imagery for many forest information needs. The capacity and benefits of FORSAT have been tested in six case studies located in Austria, Cyprus, Spain, Switzerland and Turkey, using optical data from different sensors and with the purpose to monitor forest with different geometric characteristics. The validation run on Cyprus dataset is reported and commented.

A Gap-Filling Procedure for Hydrologic Data Based on Kalman Filtering and Expectation Maximization: Application to Data from the Wireless Sensor Networks of the Sierra Nevada

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.

Indicator system for advanced nuclear plant control complex

DOEpatents

Scarola, Kenneth; Jamison, David S.; Manazir, Richard M.; Rescorl, Robert L.; Harmon, Daryl L.

1993-01-01

An advanced control room complex for a nuclear power plant, including a discrete indicator and alarm system (72) which is nuclear qualified for rapid response to changes in plant parameters and a component control system (64) which together provide a discrete monitoring and control capability at a panel (14-22, 26, 28) in the control room (10). A separate data processing system (70), which need not be nuclear qualified, provides integrated and overview information to the control room and to each panel, through CRTs (84) and a large, overhead integrated process status overview board (24). The discrete indicator and alarm system (72) and the data processing system (70) receive inputs from common plant sensors and validate the sensor outputs to arrive at a representative value of the parameter for use by the operator during both normal and accident conditions, thereby avoiding the need for him to assimilate data from each sensor individually. The integrated process status board (24) is at the apex of an information hierarchy that extends through four levels and provides access at each panel to the full display hierarchy. The control room panels are preferably of a modular construction, permitting the definition of inputs and outputs, the man machine interface, and the plant specific algorithms, to proceed in parallel with the fabrication of the panels, the installation of the equipment and the generic testing thereof.

Console for a nuclear control complex

DOEpatents

Scarola, Kenneth; Jamison, David S.; Manazir, Richard M.; Rescorl, Robert L.; Harmon, Daryl L.

1993-01-01

An advanced control room complex for a nuclear power plant, including a discrete indicator and alarm system (72) which is nuclear qualified for rapid response to changes in plant parameters and a component control system (64) which together provide a discrete monitoring and control capability at a panel (14-22, 26, 28) in the control room (10). A separate data processing system (70), which need not be nuclear qualified, provides integrated and overview information to the control room and to each panel, through CRTs (84) and a large, overhead integrated process status overview board (24). The discrete indicator and alarm system (72) and the data processing system (70) receive inputs from common plant sensors and validate the sensor outputs to arrive at a representative value of the parameter for use by the operator during both normal and accident conditions, thereby avoiding the need for him to assimilate data from each sensor individually. The integrated process status board (24) is at the apex of an information hierarchy that extends through four levels and provides access at each panel to the full display hierarchy. The control room panels are preferably of a modular construction, permitting the definition of inputs and outputs, the man machine interface, and the plant specific algorithms, to proceed in parallel with the fabrication of the panels, the installation of the equipment and the generic testing thereof.

Alarm system for a nuclear control complex

DOEpatents

Scarola, Kenneth; Jamison, David S.; Manazir, Richard M.; Rescorl, Robert L.; Harmon, Daryl L.

1994-01-01

An advanced control room complex for a nuclear power plant, including a discrete indicator and alarm system (72) which is nuclear qualified for rapid response to changes in plant parameters and a component control system (64) which together provide a discrete monitoring and control capability at a panel (14-22, 26, 28) in the control room (10). A separate data processing system (70), which need not be nuclear qualified, provides integrated and overview information to the control room and to each panel, through CRTs (84) and a large, overhead integrated process status overview board (24). The discrete indicator and alarm system (72) and the data processing system (70) receive inputs from common plant sensors and validate the sensor outputs to arrive at a representative value of the parameter for use by the operator during both normal and accident conditions, thereby avoiding the need for him to assimilate data from each sensor individually. The integrated process status board (24) is at the apex of an information hierarchy that extends through four levels and provides access at each panel to the full display hierarchy. The control room panels are preferably of a modular construction, permitting the definition of inputs and outputs, the man machine interface, and the plant specific algorithms, to proceed in parallel with the fabrication of the panels, the installation of the equipment and the generic testing thereof.

Method of installing a control room console in a nuclear power plant

DOEpatents

Scarola, Kenneth; Jamison, David S.; Manazir, Richard M.; Rescorl, Robert L.; Harmon, Daryl L.

1994-01-01

An advanced control room complex for a nuclear power plant, including a discrete indicator and alarm system (72) which is nuclear qualified for rapid response to changes in plant parameters and a component control system (64) which together provide a discrete monitoring and control capability at a panel (14-22, 26, 28) in the control room (10). A separate data processing system (70), which need not be nuclear qualified, provides integrated and overview information to the control room and to each panel, through CRTs (84) and a large, overhead integrated process status overview board (24). The discrete indicator and alarm system (72) and the data processing system (70) receive inputs from common plant sensors and validate the sensor outputs to arrive at a representative value of the parameter for use by the operator during both normal and accident conditions, thereby avoiding the need for him to assimilate data from each sensor individually. The integrated process status board (24) is at the apex of an information hierarchy that extends through four levels and provides access at each panel to the full display hierarchy. The control room panels are preferably of a modular construction, permitting the definition of inputs and outputs, the man machine interface, and the plant specific algorithms, to proceed in parallel with the fabrication of the panels, the installation of the equipment and the generic testing thereof.

Advanced nuclear plant control complex

DOEpatents

Scarola, Kenneth; Jamison, David S.; Manazir, Richard M.; Rescorl, Robert L.; Harmon, Daryl L.

1993-01-01

An advanced control room complex for a nuclear power plant, including a discrete indicator and alarm system (72) which is nuclear qualified for rapid response to changes in plant parameters and a component control system (64) which together provide a discrete monitoring and control capability at a panel (14-22, 26, 28) in the control room (10). A separate data processing system (70), which need not be nuclear qualified, provides integrated and overview information to the control room and to each panel, through CRTs (84) and a large, overhead integrated process status overview board (24). The discrete indicator and alarm system (72) and the data processing system (70) receive inputs from common plant sensors and validate the sensor outputs to arrive at a representative value of the parameter for use by the operator during both normal and accident conditions, thereby avoiding the need for him to assimilate data from each sensor individually. The integrated process status board (24) is at the apex of an information hierarchy that extends through four levels and provides access at each panel to the full display hierarchy. The control room panels are preferably of a modular construction, permitting the definition of inputs and outputs, the man machine interface, and the plant specific algorithms, to proceed in parallel with the fabrication of the panels, the installation of the equipment and the generic testing thereof.

Advanced nuclear plant control room complex

DOEpatents

Scarola, Kenneth; Jamison, David S.; Manazir, Richard M.; Rescorl, Robert L.; Harmon, Daryl L.

1993-01-01

An advanced control room complex for a nuclear power plant, including a discrete indicator and alarm system (72) which is nuclear qualified for rapid response to changes in plant parameters and a component control system (64) which together provide a discrete monitoring and control capability at a panel (14-22, 26, 28) in the control room (10). A separate data processing system (70), which need not be nuclear qualified, provides integrated and overview information to the control room and to each panel, through CRTs (84) and a large, overhead integrated process status overview board (24). The discrete indicator and alarm system (72) and the data processing system (70) receive inputs from common plant sensors and validate the sensor outputs to arrive at a representative value of the parameter for use by the operator during both normal and accident conditions, thereby avoiding the need for him to assimilate data from each sensor individually. The integrated process status board (24) is at the apex of an information hierarchy that extends through four levels and provides access at each panel to the full display hierarchy. The control room panels are preferably of a modular construction, permitting the definition of inputs and outputs, the man machine interface, and the plant specific algorithms, to proceed in parallel with the fabrication of the panels, the installation of the equipment and the generic testing thereof.

Frequency-feature based antistrong-disturbance signal processing method and system for vortex flowmeter with single sensor

NASA Astrophysics Data System (ADS)

Xu, Ke-Jun; Luo, Qing-Lin; Wang, Gang; Liu, San-Shan; Kang, Yi-Bo

2010-07-01

Digital signal processing methods have been applied to vortex flowmeter for extracting the useful information from noisy output of the vortex flow sensor. But these approaches are unavailable when the power of the mechanical vibration noise is larger than that of the vortex flow signal. In order to solve this problem, an antistrong-disturbance signal processing method is proposed based on frequency features of the vortex flow signal and mechanical vibration noise for the vortex flowmeter with single sensor. The frequency bandwidth of the vortex flow signal is different from that of the mechanical vibration noise. The autocorrelation function can represent bandwidth features of the signal and noise. The output of the vortex flow sensor is processed by the spectrum analysis, filtered by bandpass filters, and calculated by autocorrelation function at the fixed delaying time and at τ =0 to obtain ratios. The frequency corresponding to the minimal ratio is regarded as the vortex flow frequency. With an ultralow-power microcontroller, a digital signal processing system is developed to implement the antistrong-disturbance algorithm, and at the same time to ensure low-power and two-wire mode for meeting the requirement of process instrumentation. The water flow-rate calibration and vibration test experiments are conducted, and the experimental results show that both the algorithm and system are effective.

Frequency-feature based antistrong-disturbance signal processing method and system for vortex flowmeter with single sensor.

PubMed

Xu, Ke-Jun; Luo, Qing-Lin; Wang, Gang; Liu, San-Shan; Kang, Yi-Bo

2010-07-01

Digital signal processing methods have been applied to vortex flowmeter for extracting the useful information from noisy output of the vortex flow sensor. But these approaches are unavailable when the power of the mechanical vibration noise is larger than that of the vortex flow signal. In order to solve this problem, an antistrong-disturbance signal processing method is proposed based on frequency features of the vortex flow signal and mechanical vibration noise for the vortex flowmeter with single sensor. The frequency bandwidth of the vortex flow signal is different from that of the mechanical vibration noise. The autocorrelation function can represent bandwidth features of the signal and noise. The output of the vortex flow sensor is processed by the spectrum analysis, filtered by bandpass filters, and calculated by autocorrelation function at the fixed delaying time and at tau=0 to obtain ratios. The frequency corresponding to the minimal ratio is regarded as the vortex flow frequency. With an ultralow-power microcontroller, a digital signal processing system is developed to implement the antistrong-disturbance algorithm, and at the same time to ensure low-power and two-wire mode for meeting the requirement of process instrumentation. The water flow-rate calibration and vibration test experiments are conducted, and the experimental results show that both the algorithm and system are effective.

An approach for representing sensor data to validate alerts in Ambient Assisted Living.

PubMed

Muñoz, Andrés; Serrano, Emilio; Villa, Ana; Valdés, Mercedes; Botía, Juan A

2012-01-01

The mainstream of research in Ambient Assisted Living (AAL) is devoted to developing intelligent systems for processing the data collected through artificial sensing. Besides, there are other elements that must be considered to foster the adoption of AAL solutions in real environments. In this paper we focus on the problem of designing interfaces among caregivers and AAL systems. We present an alert management tool that supports carers in their task of validating alarms raised by the system. It generates text-based explanations--obtained through an argumentation process--of the causes leading to alarm activation along with graphical sensor information and 3D models, thus offering complementary types of information. Moreover, a guideline to use the tool when validating alerts is also provided. Finally, the functionality of the proposed tool is demonstrated through two real cases of alert.

System-Level Design of a 64-Channel Low Power Neural Spike Recording Sensor.

PubMed

Delgado-Restituto, Manuel; Rodriguez-Perez, Alberto; Darie, Angela; Soto-Sanchez, Cristina; Fernandez-Jover, Eduardo; Rodriguez-Vazquez, Angel

2017-04-01

This paper reports an integrated 64-channel neural spike recording sensor, together with all the circuitry to process and configure the channels, process the neural data, transmit via a wireless link the information and receive the required instructions. Neural signals are acquired, filtered, digitized and compressed in the channels. Additionally, each channel implements an auto-calibration algorithm which individually configures the transfer characteristics of the recording site. The system has two transmission modes; in one case the information captured by the channels is sent as uncompressed raw data; in the other, feature vectors extracted from the detected neural spikes are released. Data streams coming from the channels are serialized by the embedded digital processor. Experimental results, including in vivo measurements, show that the power consumption of the complete system is lower than 330 μW.

The Contribution of GIS to Display and Analyze the Water Quality Data Collected by a Wireless Sensor Network: Case of Bouregreg Catchment, Morocco

NASA Astrophysics Data System (ADS)

Boubakri, S.; Rhinane, H.

2017-11-01

The monitoring of water quality is, in most cases, managed in the laboratory and not on real time bases. Besides this process being lengthy, it doesn't provide the required specifications to describe the evolution of the quality parameters that are of interest. This study presents the integration of Geographic Information Systems (GIS) with wireless sensor networks (WSN) aiming to create a system able to detect the parameters like temperature, salinity and conductivity in a Moroccan catchment scale and transmit information to the support station. This Information is displayed and evaluated in a GIS using maps and spatial dashboard to monitor the water quality in real time.

A Survey on Trust Management for Mobile Ad Hoc Networks

DTIC Science & Technology

2010-07-01

betrayal of trust. In his comments on Lagerspetz’s book titled Trust: The Tacit Demand, Lahno [24] describes the author’s view on trust as a moral...extension of AODV Zouridaki et al. (2005 ) [79] (2006) [80] Secure routing Direct observation [79][80] Reputation by secondhand information [80...the broad areas of signal processing, wireless communications, sensor and mobile ad hoc networks. He is co-editor of the book Wireless Sensor Networks

Sensory Information Processing

DTIC Science & Technology

1977-04-01

deblurred image is shown in Figure lUb. This result, with no sensor noise , shows a good representation of the original double star. The orientation of the...which we Page 21 performed to test the theory and to provide an indication of the effects of sensor noise on the performances of these procedures...34^-^^^^-^-^ Page 37 2 Labeyrie has shown experimentally that<|S(u)| > has useful signal-to- noise ratio out to the diffraction limit of the telescope. Korff

Novel wireless sensor system for dynamic characterization of borehole heat exchangers.

PubMed

Martos, Julio; Montero, Álvaro; Torres, José; Soret, Jesús; Martínez, Guillermo; García-Olcina, Raimundo

2011-01-01

The design and field test of a novel sensor system based in autonomous wireless sensors to measure the temperature of the heat transfer fluid along a borehole heat exchanger (BHE) is presented. The system, by means of two special valves, inserts and extracts miniaturized wireless sensors inside the pipes of the borehole, which are carried by the thermal fluid. Each sensor is embedded in a small sphere of just 25 mm diameter and 8 gr weight, containing a transceiver, a microcontroller, a temperature sensor and a power supply. A wireless data processing unit transmits to the sensors the acquisition configuration before the measurements, and also downloads the temperature data measured by the sensor along its way through the BHE U-tube. This sensor system is intended to improve the conventional thermal response test (TRT) and it allows the collection of information about the thermal characteristics of the geological structure of subsurface and its influence in borehole thermal behaviour, which in turn, facilitates the implementation of TRTs in a more cost-effective and reliable way.

MAGID-II: a next-generation magnetic unattended ground sensor (UGS)

NASA Astrophysics Data System (ADS)

Walter, Paul A.; Mauriello, Fred; Huber, Philip

2012-06-01

A next generation magnetic sensor is being developed at L-3 Communications, Communication Systems East to enhance the ability of Army and Marine Corps unattended ground sensor (UGS) systems to detect and track targets on the battlefield. This paper describes a magnetic sensor that provides superior detection range for both armed personnel and vehicle targets, at a reduced size, weight, and level of power consumption (SWAP) over currently available magnetic sensors. The design integrates the proven technology of a flux gate magnetometer combined with advanced digital signal processing algorithms to provide the warfighter with a rapidly deployable, extremely low false-alarm-rate sensor. This new sensor improves on currently available magnetic UGS systems by providing not only target detection and direction information, but also a magnetic disturbance readout, indicating the size of the target. The sensor integrates with Government Off-the-Shelf (GOTS) systems such as the United States Army's Battlefield Anti-Intrusion System (BAIS) and the United States Marine Corps Tactical Remote Sensor System (TRSS). The system has undergone testing by the US Marine Corps, as well as extensive company testing. Results from these field tests are given.

Novel Wireless Sensor System for Dynamic Characterization of Borehole Heat Exchangers

PubMed Central

Martos, Julio; Montero, Álvaro; Torres, José; Soret, Jesús; Martínez, Guillermo; García-Olcina, Raimundo

2011-01-01

The design and field test of a novel sensor system based in autonomous wireless sensors to measure the temperature of the heat transfer fluid along a borehole heat exchanger (BHE) is presented. The system, by means of two specials valves, inserts and extracts miniaturized wireless sensors inside the pipes of the borehole, which are carried by the thermal fluid. Each sensor is embedded in a small sphere of just 25 mm diameter and 8 gr weight, containing a transceiver, a microcontroller, a temperature sensor and a power supply. A wireless data processing unit transmits to the sensors the acquisition configuration before the measurements, and also downloads the temperature data measured by the sensor along its way through the BHE U-tube. This sensor system is intended to improve the conventional thermal response test (TRT) and it allows the collection of information about the thermal characteristics of the geological structure of subsurface and its influence in borehole thermal behaviour, which in turn, facilitates the implementation of TRTs in a more cost-effective and reliable way. PMID:22164005

Hybrid online sensor error detection and functional redundancy for systems with time-varying parameters.

PubMed

Feng, Jianyuan; Turksoy, Kamuran; Samadi, Sediqeh; Hajizadeh, Iman; Littlejohn, Elizabeth; Cinar, Ali

2017-12-01

Supervision and control systems rely on signals from sensors to receive information to monitor the operation of a system and adjust manipulated variables to achieve the control objective. However, sensor performance is often limited by their working conditions and sensors may also be subjected to interference by other devices. Many different types of sensor errors such as outliers, missing values, drifts and corruption with noise may occur during process operation. A hybrid online sensor error detection and functional redundancy system is developed to detect errors in online signals, and replace erroneous or missing values detected with model-based estimates. The proposed hybrid system relies on two techniques, an outlier-robust Kalman filter (ORKF) and a locally-weighted partial least squares (LW-PLS) regression model, which leverage the advantages of automatic measurement error elimination with ORKF and data-driven prediction with LW-PLS. The system includes a nominal angle analysis (NAA) method to distinguish between signal faults and large changes in sensor values caused by real dynamic changes in process operation. The performance of the system is illustrated with clinical data continuous glucose monitoring (CGM) sensors from people with type 1 diabetes. More than 50,000 CGM sensor errors were added to original CGM signals from 25 clinical experiments, then the performance of error detection and functional redundancy algorithms were analyzed. The results indicate that the proposed system can successfully detect most of the erroneous signals and substitute them with reasonable estimated values computed by functional redundancy system.

Monitoring corrosion in reinforced concrete structures

NASA Astrophysics Data System (ADS)

Kung, Peter; Comanici, Maria I.

2014-06-01

Many defects can cause deterioration and cracks in concrete; these are results of poor concrete mix, poor workmanship, inadequate design, shrinkage, chemical and environmental attack, physical or mechanical damage, and corrosion of reinforcing steel (RS). We want to develop a suite of sensors and systems that can detect that corrosion is taking place in RS and inform owners how serious the problem is. By understanding the stages of the corrosion process, we can develop special a sensor that detects each transition. First, moisture ingress can be monitored by a fiber optics humidity sensor, then ingress of Chloride, which acts as a catalyst and accelerates the corrosion process by converting iron into ferrous compounds. We need a fiber optics sensor which can quantify Chloride ingress over time. Converting ferric to ferrous causes large volume expansion and cracks. Such pressure build-up can be detected by a fiber optic pressure sensor. Finally, cracks emit acoustic waves, which can be detected by a high frequency sensor made with phase-shifted gratings. This paper will discuss the progress in our development of these special sensors and also our plan for a field test by the end of 2014. We recommend that we deploy these sensors by visually inspecting the affected area and by identifying locations of corrosion; then, work with the designers to identify spots that would compromise the integrity of the structure; finally, drill a small hole in the concrete and insert these sensors. Interrogation can be done at fixed intervals with a portable unit.

Development of a fusion approach selection tool

NASA Astrophysics Data System (ADS)

Pohl, C.; Zeng, Y.

2015-06-01

During the last decades number and quality of available remote sensing satellite sensors for Earth observation has grown significantly. The amount of available multi-sensor images along with their increased spatial and spectral resolution provides new challenges to Earth scientists. With a Fusion Approach Selection Tool (FAST) the remote sensing community would obtain access to an optimized and improved image processing technology. Remote sensing image fusion is a mean to produce images containing information that is not inherent in the single image alone. In the meantime the user has access to sophisticated commercialized image fusion techniques plus the option to tune the parameters of each individual technique to match the anticipated application. This leaves the operator with an uncountable number of options to combine remote sensing images, not talking about the selection of the appropriate images, resolution and bands. Image fusion can be a machine and time-consuming endeavour. In addition it requires knowledge about remote sensing, image fusion, digital image processing and the application. FAST shall provide the user with a quick overview of processing flows to choose from to reach the target. FAST will ask for available images, application parameters and desired information to process this input to come out with a workflow to quickly obtain the best results. It will optimize data and image fusion techniques. It provides an overview on the possible results from which the user can choose the best. FAST will enable even inexperienced users to use advanced processing methods to maximize the benefit of multi-sensor image exploitation.

Use of Pattern Classification Algorithms to Interpret Passive and Active Data Streams from a Walking-Speed Robotic Sensor Platform

NASA Astrophysics Data System (ADS)

Dieckman, Eric Allen

In order to perform useful tasks for us, robots must have the ability to notice, recognize, and respond to objects and events in their environment. This requires the acquisition and synthesis of information from a variety of sensors. Here we investigate the performance of a number of sensor modalities in an unstructured outdoor environment, including the Microsoft Kinect, thermal infrared camera, and coffee can radar. Special attention is given to acoustic echolocation measurements of approaching vehicles, where an acoustic parametric array propagates an audible signal to the oncoming target and the Kinect microphone array records the reflected backscattered signal. Although useful information about the target is hidden inside the noisy time domain measurements, the Dynamic Wavelet Fingerprint process (DWFP) is used to create a time-frequency representation of the data. A small-dimensional feature vector is created for each measurement using an intelligent feature selection process for use in statistical pattern classification routines. Using our experimentally measured data from real vehicles at 50 m, this process is able to correctly classify vehicles into one of five classes with 94% accuracy. Fully three-dimensional simulations allow us to study the nonlinear beam propagation and interaction with real-world targets to improve classification results.

Dispersion of Heat Flux Sensors Manufactured in Silicon Technology.

PubMed

Ziouche, Katir; Lejeune, Pascale; Bougrioua, Zahia; Leclercq, Didier

2016-06-09

In this paper, we focus on the dispersion performances related to the manufacturing process of heat flux sensors realized in CMOS (Complementary metal oxide semi-conductor) compatible 3-in technology. In particular, we have studied the performance dispersion of our sensors and linked these to the physical characteristics of dispersion of the materials used. This information is mandatory to ensure low-cost manufacturing and especially to reduce production rejects during the fabrication process. The results obtained show that the measured sensitivity of the sensors is in the range 3.15 to 6.56 μV/(W/m²), associated with measured resistances ranging from 485 to 675 kΩ. The dispersions correspond to a Gaussian-type distribution with more than 90% determined around average sensitivity S e ¯ = 4.5 µV/(W/m²) and electrical resistance R ¯ = 573.5 kΩ within the interval between the average and, more or less, twice the relative standard deviation.

Embedded spectroscopic fiber sensor for on-line arc-welding analysis.

PubMed

Mirapeix, Jesús; Cobo, Adolfo; Quintela, Antonio; López-Higuera, José-Miguel

2007-06-01

A new fiber sensor system designed for spectroscopic analysis and on-line quality assurance of arc-welding processes is presented here. Although several different approaches have been considered for the optical capture of plasma emission in arc-welding processes, they tend to be invasive and make use of optical devices such as collimators or photodiodes. The solution proposed here is based on the arrangement of an optical fiber, which is used at the same time as the optical capturing device and also to deliver the optical information to a spectrometer, embedded within an arc-welding torch. It will be demonstrated that, by using the shielding gas as a protection for the fiber end, the plasma light emission is efficiently collected, forming a sensor system completely transparent and noninvasive for the welding operator. The feasibility of the proposed sensor designed to be used as the input optics of a welding quality-assurance system based on plasma spectroscopy will be demonstrated by means of several welding tests.

A Machine Learning Approach to Pedestrian Detection for Autonomous Vehicles Using High-Definition 3D Range Data

PubMed Central

Navarro, Pedro J.; Fernández, Carlos; Borraz, Raúl; Alonso, Diego

2016-01-01

This article describes an automated sensor-based system to detect pedestrians in an autonomous vehicle application. Although the vehicle is equipped with a broad set of sensors, the article focuses on the processing of the information generated by a Velodyne HDL-64E LIDAR sensor. The cloud of points generated by the sensor (more than 1 million points per revolution) is processed to detect pedestrians, by selecting cubic shapes and applying machine vision and machine learning algorithms to the XY, XZ, and YZ projections of the points contained in the cube. The work relates an exhaustive analysis of the performance of three different machine learning algorithms: k-Nearest Neighbours (kNN), Naïve Bayes classifier (NBC), and Support Vector Machine (SVM). These algorithms have been trained with 1931 samples. The final performance of the method, measured a real traffic scenery, which contained 16 pedestrians and 469 samples of non-pedestrians, shows sensitivity (81.2%), accuracy (96.2%) and specificity (96.8%). PMID:28025565

Non-contact capacitance based image sensing method and system

DOEpatents

Novak, James L.; Wiczer, James J.

1995-01-01

A system and a method is provided for imaging desired surfaces of a workpiece. A sensor having first and second sensing electrodes which are electrically isolated from the workpiece is positioned above and in proximity to the desired surfaces of the workpiece. An electric field is developed between the first and second sensing electrodes of the sensor in response to input signals being applied thereto and capacitance signals are developed which are indicative of any disturbances in the electric field as a result of the workpiece. An image signal of the workpiece may be developed by processing the capacitance signals. The image signals may provide necessary control information to a machining device for machining the desired surfaces of the workpiece in processes such as deburring or chamfering. Also, the method and system may be used to image dimensions of weld pools on a workpiece and surfaces of glass vials. The sensor may include first and second preview sensors used to determine the feed rate of a workpiece with respect to the machining device.

Non-contact capacitance based image sensing method and system

DOEpatents

Novak, James L.; Wiczer, James J.

1994-01-01

A system and a method for imaging desired surfaces of a workpiece. A sensor having first and second sensing electrodes which are electrically isolated from the workpiece is positioned above and in proximity to the desired surfaces of the workpiece. An electric field is developed between the first and second sensing electrodes of the sensor in response to input signals being applied thereto and capacitance signals are developed which are indicative of any disturbances in the electric field as a result of the workpiece. An image signal of the workpiece may be developed by processing the capacitance signals. The image signals may provide necessary control information to a machining device for machining the desired surfaces of the workpiece in processes such as deburring or chamfering. Also, the method and system may be used to image dimensions of weld pools on a workpiece and surfaces of glass vials. The sensor may include first and second preview sensors used to determine the feed rate of a workpiece with respect to the machining device.

A Machine Learning Approach to Pedestrian Detection for Autonomous Vehicles Using High-Definition 3D Range Data.

PubMed

Navarro, Pedro J; Fernández, Carlos; Borraz, Raúl; Alonso, Diego

2016-12-23

This article describes an automated sensor-based system to detect pedestrians in an autonomous vehicle application. Although the vehicle is equipped with a broad set of sensors, the article focuses on the processing of the information generated by a Velodyne HDL-64E LIDAR sensor. The cloud of points generated by the sensor (more than 1 million points per revolution) is processed to detect pedestrians, by selecting cubic shapes and applying machine vision and machine learning algorithms to the XY, XZ, and YZ projections of the points contained in the cube. The work relates an exhaustive analysis of the performance of three different machine learning algorithms: k-Nearest Neighbours (kNN), Naïve Bayes classifier (NBC), and Support Vector Machine (SVM). These algorithms have been trained with 1931 samples. The final performance of the method, measured a real traffic scenery, which contained 16 pedestrians and 469 samples of non-pedestrians, shows sensitivity (81.2%), accuracy (96.2%) and specificity (96.8%).

A Platform Architecture for Sensor Data Processing and Verification in Buildings

ERIC Educational Resources Information Center

Ortiz, Jorge Jose

2013-01-01

This thesis examines the state of the art of building information systems and evaluates their architecture in the context of emerging technologies and applications for deep analysis of the built environment. We observe that modern building information systems are difficult to extend, do not provide general services for application development, do…

Use of MCIDAS as an earth science information systems tool

NASA Technical Reports Server (NTRS)

Goodman, H. Michael; Karitani, Shogo; Parker, Karen G.; Stooksbury, Laura M.; Wilson, Gregory S.

1988-01-01

The application of the man computer interactive data access system (MCIDAS) to information processing is examined. The computer systems that interface with the MCIDAS are discussed. Consideration is given to the computer networking of MCIDAS, data base archival, and the collection and distribution of real-time special sensor microwave/imager data.

Steel reinforcement corrosion detection with coaxial cable sensors

NASA Astrophysics Data System (ADS)

Muchaidze, Iana; Pommerenke, David; Chen, Genda

2011-04-01

Corrosion processes in the steel reinforced structures can result in structural deficiency and with time create a threat to human lives. Millions of dollars are lost each year because of corrosion. According to the U. S. Federal Highway Administration (FHWA) the average annual cost of corrosion in the infrastructure sector by the end of 2002 was estimated to be $22.6 billion. Timely remediation/retrofit and effective maintenance can extend the structure's live span for much less expense. Thus the considerable effort should be done to deploy corrosion monitoring techniques to have realistic information on the location and the severity of damage. Nowadays commercially available techniques for corrosion monitoring require costly equipment and certain interpretational skills. In addition, none of them is designed for the real time quality assessment. In this study the crack sensor developed at Missouri University of Science and Technology is proposed as a distributed sensor for real time corrosion monitoring. Implementation of this technology may ease the pressure on the bridge owners restrained with the federal budget by allowing the timely remediation with the minimal financial and labor expenses. The sensor is instrumented in such a way that the location of any discontinuity developed along its length can be easily detected. When the sensor is placed in immediate vicinity to the steel reinforcement it is subjected to the same chemical process as the steel reinforcement. And corrosion pitting is expected to develop on the sensor exactly at the same location as in the rebar. Thus it is expected to be an effective tool for active corrosion zones detection within reinforced concrete (RC) members. A series of laboratory tests were conducted to validate the effectiveness of the proposed methodology. Nine sensors were manufactured and placed in the artificially created corrosive environment and observed over the time. To induce accelerated corrosion 3% and 5% NaCL solutions were used. Based on the test results, the proposed/corrosion distributed sensor is capable of delivering fairly accurate information on the location of a discontinuity along the sensor caused by corrosion pitting. Forensic study was also conducted to validate the concept. In order to test the sensors in real live condition, 27 sensors were prepared to be placed into RC beams. The beams will be subjected to corrosive environment. After that the sensors will be monitored over the time for signs of corrosion.

Single-snapshot 2D color measurement by plenoptic imaging system

NASA Astrophysics Data System (ADS)

Masuda, Kensuke; Yamanaka, Yuji; Maruyama, Go; Nagai, Sho; Hirai, Hideaki; Meng, Lingfei; Tosic, Ivana

2014-03-01

Plenoptic cameras enable capture of directional light ray information, thus allowing applications such as digital refocusing, depth estimation, or multiband imaging. One of the most common plenoptic camera architectures contains a microlens array at the conventional image plane and a sensor at the back focal plane of the microlens array. We leverage the multiband imaging (MBI) function of this camera and develop a single-snapshot, single-sensor high color fidelity camera. Our camera is based on a plenoptic system with XYZ filters inserted in the pupil plane of the main lens. To achieve high color measurement precision of this system, we perform an end-to-end optimization of the system model that includes light source information, object information, optical system information, plenoptic image processing and color estimation processing. Optimized system characteristics are exploited to build an XYZ plenoptic colorimetric camera prototype that achieves high color measurement precision. We describe an application of our colorimetric camera to color shading evaluation of display and show that it achieves color accuracy of ΔE<0.01.

Exponential Modelling for Mutual-Cohering of Subband Radar Data

NASA Astrophysics Data System (ADS)

Siart, U.; Tejero, S.; Detlefsen, J.

2005-05-01

Increasing resolution and accuracy is an important issue in almost any type of radar sensor application. However, both resolution and accuracy are strongly related to the available signal bandwidth and energy that can be used. Nowadays, often several sensors operating in different frequency bands become available on a sensor platform. It is an attractive goal to use the potential of advanced signal modelling and optimization procedures by making proper use of information stemming from different frequency bands at the RF signal level. An important prerequisite for optimal use of signal energy is coherence between all contributing sensors. Coherent multi-sensor platforms are greatly expensive and are thus not available in general. This paper presents an approach for accurately estimating object radar responses using subband measurements at different RF frequencies. An exponential model approach allows to compensate for the lack of mutual coherence between independently operating sensors. Mutual coherence is recovered from the a-priori information that both sensors have common scattering centers in view. Minimizing the total squared deviation between measured data and a full-range exponential signal model leads to more accurate pole angles and pole magnitudes compared to single-band optimization. The model parameters (range and magnitude of point scatterers) after this full-range optimization process are also more accurate than the parameters obtained from a commonly used super-resolution procedure (root-MUSIC) applied to the non-coherent subband data.

The Shale Hills Sensorium for Embedded Sensors, Simulation, & Visualization: A Prototype for Land-Vegetation-Atmosphere Interactions

NASA Astrophysics Data System (ADS)

Duffy, C.

2008-12-01

The future of environmental observing systems will utilize embedded sensor networks with continuous real- time measurement of hydrologic, atmospheric, biogeochemical, and ecological variables across diverse terrestrial environments. Embedded environmental sensors, benefitting from advances in information sciences, networking technology, materials science, computing capacity, and data synthesis methods, are undergoing revolutionary change. It is now possible to field spatially-distributed, multi-node sensor networks that provide density and spatial coverage previously accessible only via numerical simulation. At the same time, computational tools are advancing rapidly to the point where it is now possible to simulate the physical processes controlling individual parcels of water and solutes through the complete terrestrial water cycle. Our goal for the Penn State Critical Zone Observatory is to apply environmental sensor arrays, integrated hydrologic models, and state-of-the-art visualization deployed and coordinated at a testbed within the Penn State Experimental Forest. The Shale Hills Hydro_Sensorium prototype proposed here is designed to observe land-atmosphere interactions in four-dimensional (space and time). The term Hydro_Sensorium implies the totality of physical sensors, models and visualization tools that allow us to perceive the detailed space and time complexities of the water and energy cycle for a watershed or river basin for all physical states and fluxes (groundwater, soil moisture, temperature, streamflow, latent heat, snowmelt, chemistry, isotopes etc.). This research will ultimately catalyze the study of complex interactions between the land surface, subsurface, biological and atmospheric systems over a broad range of scales. The sensor array would be real-time and fully controllable by remote users for "computational steering" and data fusion. Presently fully-coupled physical models are being developed that link the atmosphere-land-vegetation-subsurface system into a fully-coupled distributed system. During the last 5 years the Penn State Integrated Hydrologic Modeling System has been under development as an open-source community modeling project funded by NSF EAR/GEO and NSF CBET/ENG. PIHM represents a strategy for the formulation and solution of fully-coupled process equations at the watershed and river basin scales, and includes a tightly coupled GIS tool for data handling, domain decomposition, optimal unstructured grid generation, and model parameterization. The sensor and simulation system has the following elements: 1) extensive, spatially-distributed, non- invasive, smart sensor networks to gather massive geologic, hydrologic, and geochemical data; 2) stochastic information fusion methods; 3) spatially-explicit multiphysics models/solutions of the land-vegetation- atmosphere system; and 4) asynchronous, parallel/distributed, adaptive algorithms for rapidly simulating the states of a basin at high resolution, 5) signal processing tools for data mining and parameter estimation, and 6) visualization tools. The prototype proposed sensor array and simulation system proposed here will offer a coherent new approach to environmental predictions with a fully integrated observing system design. We expect that the Shale Hills Hydro_Sensorium may provide the needed synthesis of information and conceptualization necessary to advance predictive understanding in complex hydrologic systems.

Detection of cylinder unbalance from Bayesian inference combining cylinder pressure and vibration block measurement in a Diesel engine

NASA Astrophysics Data System (ADS)

Nguyen, Emmanuel; Antoni, Jerome; Grondin, Olivier

2009-12-01

In the automotive industry, the necessary reduction of pollutant emission for new Diesel engines requires the control of combustion events. This control is efficient provided combustion parameters such as combustion occurrence and combustion energy are relevant. Combustion parameters are traditionally measured from cylinder pressure sensors. However this kind of sensor is expensive and has a limited lifetime. Thus this paper proposes to use only one cylinder pressure on a multi-cylinder engine and to extract combustion parameters from the other cylinders with low cost knock sensors. Knock sensors measure the vibration circulating on the engine block, hence they do not all contain the information on the combustion processes, but they are also contaminated by other mechanical noises that disorder the signal. The question is how to combine the information coming from one cylinder pressure and knock sensors to obtain the most relevant combustion parameters in all engine cylinders. In this paper, the issue is addressed trough the Bayesian inference formalism. In that cylinder where a cylinder pressure sensor is mounted, combustion parameters will be measured directly. In the other cylinders, they will be measured indirectly from Bayesian inference. Experimental results obtained on a four cylinder Diesel engine demonstrate the effectiveness of the proposed algorithm toward that purpose.

A Novel Health Evaluation Strategy for Multifunctional Self-Validating Sensors

PubMed Central

Shen, Zhengguang; Wang, Qi

2013-01-01

The performance evaluation of sensors is very important in actual application. In this paper, a theory based on multi-variable information fusion is studied to evaluate the health level of multifunctional sensors. A novel conception of health reliability degree (HRD) is defined to indicate a quantitative health level, which is different from traditional so-called qualitative fault diagnosis. To evaluate the health condition from both local and global perspectives, the HRD of a single sensitive component at multiple time points and the overall multifunctional sensor at a single time point are defined, respectively. The HRD methodology is emphasized by using multi-variable data fusion technology coupled with a grey comprehensive evaluation method. In this method, to acquire the distinct importance of each sensitive unit and the sensitivity of different time points, the information entropy and analytic hierarchy process method are used, respectively. In order to verify the feasibility of the proposed strategy, a health evaluating experimental system for multifunctional self-validating sensors was designed. The five different health level situations have been discussed. Successful results show that the proposed method is feasible, the HRD could be used to quantitatively indicate the health level and it does have a fast response to the performance changes of multifunctional sensors. PMID:23291576

Structural health monitoring using smart optical fiber sensors

NASA Astrophysics Data System (ADS)

Davies, Heddwyn; Everall, Lorna A.; Gallon, Andrew M.

2001-04-01

This paper describes the potential of a smart monitoring system, incorporating optical fiber sensing techniques, to provide important structural information to designers and users alike. This technology has application in all areas including aerospace, civil, maritime and automotive engineering. In order to demonstrate the capability of the sensing system it has been installed in a 35 m free-standing carbon fiber yacht mast, where a complete optical network of strain and temperature sensors were embedded into a composite mast and boom during lay-up. The system was able to monitor the behavior of the composite rig through a range of handling conditions and the resulting strain information could be used by engineers to improve the structural design process. The optical strain sensor system comprises of three main components: the sensor network, the opto-electronic data acquisition unit (OFSSS) and the external PC which acts as a data log and display. Embedded fiber optic sensors have wide ranging application for structural load monitoring. Due to their small size, optical fiber sensors can be readily embedded into composite materials. Other advantages include their immediate multiplexing capability and immunity to electromagnetic interference. The capability of this system has been demonstrated within the maritime environment, but can be adapted for any application.

Wearable sensor systems for infants.

PubMed

Zhu, Zhihua; Liu, Tao; Li, Guangyi; Li, Tong; Inoue, Yoshio

2015-02-05

Continuous health status monitoring of infants is achieved with the development and fusion of wearable sensing technologies, wireless communication techniques and a low energy-consumption microprocessor with high performance data processing algorithms. As a clinical tool applied in the constant monitoring of physiological parameters of infants, wearable sensor systems for infants are able to transmit the information obtained inside an infant's body to clinicians or parents. Moreover, such systems with integrated sensors can perceive external threats such as falling or drowning and warn parents immediately. Firstly, the paper reviews some available wearable sensor systems for infants; secondly, we introduce the different modules of the framework in the sensor systems; lastly, the methods and techniques applied in the wearable sensor systems are summarized and discussed. The latest research and achievements have been highlighted in this paper and the meaningful applications in healthcare and behavior analysis are also presented. Moreover, we give a lucid perspective of the development of wearable sensor systems for infants in the future.

Wearable Sensor Systems for Infants

PubMed Central

Zhu, Zhihua; Liu, Tao; Li, Guangyi; Li, Tong; Inoue, Yoshio

2015-01-01

Continuous health status monitoring of infants is achieved with the development and fusion of wearable sensing technologies, wireless communication techniques and a low energy-consumption microprocessor with high performance data processing algorithms. As a clinical tool applied in the constant monitoring of physiological parameters of infants, wearable sensor systems for infants are able to transmit the information obtained inside an infant's body to clinicians or parents. Moreover, such systems with integrated sensors can perceive external threats such as falling or drowning and warn parents immediately. Firstly, the paper reviews some available wearable sensor systems for infants; secondly, we introduce the different modules of the framework in the sensor systems; lastly, the methods and techniques applied in the wearable sensor systems are summarized and discussed. The latest research and achievements have been highlighted in this paper and the meaningful applications in healthcare and behavior analysis are also presented. Moreover, we give a lucid perspective of the development of wearable sensor systems for infants in the future. PMID:25664432

Modelling the influence of noise of the image sensor for blood cells recognition in computer microscopy

NASA Astrophysics Data System (ADS)

Nikitaev, V. G.; Nagornov, O. V.; Pronichev, A. N.; Polyakov, E. V.; Dmitrieva, V. V.

2017-12-01

The first stage of diagnostics of blood cancer is the analysis of blood smears. The application of decision-making support systems would reduce the subjectivity of the diagnostic process and avoid errors, resulting in often irreversible changes in the patient's condition. In this regard, the solution of this problem requires the use of modern technology. One of the tools of the program classification of blood cells are texture features, and the task of finding informative among them is promising. The paper investigates the effect of noise of the image sensor to informative texture features with application of methods of mathematical modelling.

Health-Enabled Smart Sensor Fusion Technology

NASA Technical Reports Server (NTRS)

Wang, Ray

2012-01-01

A process was designed to fuse data from multiple sensors in order to make a more accurate estimation of the environment and overall health in an intelligent rocket test facility (IRTF), to provide reliable, high-confidence measurements for a variety of propulsion test articles. The object of the technology is to provide sensor fusion based on a distributed architecture. Specifically, the fusion technology is intended to succeed in providing health condition monitoring capability at the intelligent transceiver, such as RF signal strength, battery reading, computing resource monitoring, and sensor data reading. The technology also provides analytic and diagnostic intelligence at the intelligent transceiver, enhancing the IEEE 1451.x-based standard for sensor data management and distributions, as well as providing appropriate communications protocols to enable complex interactions to support timely and high-quality flow of information among the system elements.

Use of EO-1 Hyperion Data for Inter-Sensor Calibration of Vegetation Indices

NASA Technical Reports Server (NTRS)

Huete, Alfredo; Miura, Tomoaki; Kim, HoJin; Yoshioka, Hiroki

2004-01-01

Numerous satellite sensor systems useful in terrestrial Earth observation and monitoring have recently been launched and their derived products are increasingly being used in regional and global vegetation studies. The increasing availability of multiple sensors offer much opportunity for vegetation studies aimed at understanding the terrestrial carbon cycle, climate change, and land cover conversions. Potential applications include improved multiresolution characterization of the surface (scaling); improved optical-geometric characterization of vegetation canopies; improved assessments of surface phenology and ecosystem seasonal dynamics; and improved maintenance of long-term, inter-annual, time series data records. The Landsat series of sensors represent one group of sensors that have produced a long-term, archived data set of the Earth s surface, at fine resolution and since 1972, capable of being processed into useful information for global change studies (Hall et al., 1991).

Empowerment of Patients with Hypertension through BPM, IoT and Remote Sensing.

PubMed

Ruiz-Fernández, Daniel; Marcos-Jorquera, Diego; Gilart-Iglesias, Virgilio; Vives-Boix, Víctor; Ramírez-Navarro, Javier

2017-10-04

Hypertension affects one in five adults worldwide. Healthcare processes require interdisciplinary cooperation and coordination between medical teams, clinical processes, and patients. The lack of patients' empowerment and adherence to treatment makes necessary to integrate patients, data collecting devices and clinical processes. For this reason, in this paper we propose a model based on Business Process Management paradigm, together with a group of technologies, techniques and IT principles which increase the benefits of the paradigm. To achieve the proposed model, the clinical process of the hypertension is analyzed with the objective of detecting weaknesses and improving the process. Once the process is analyzed, an architecture that joins health devices and environmental sensors, together with an information system, has been developed. To test the architecture, a web system connected with health monitors and environment sensors, and with a mobile app have been implemented.

Empowerment of Patients with Hypertension through BPM, IoT and Remote Sensing

PubMed Central

Ramírez-Navarro, Javier

2017-01-01

Hypertension affects one in five adults worldwide. Healthcare processes require interdisciplinary cooperation and coordination between medical teams, clinical processes, and patients. The lack of patients’ empowerment and adherence to treatment makes necessary to integrate patients, data collecting devices and clinical processes. For this reason, in this paper we propose a model based on Business Process Management paradigm, together with a group of technologies, techniques and IT principles which increase the benefits of the paradigm. To achieve the proposed model, the clinical process of the hypertension is analyzed with the objective of detecting weaknesses and improving the process. Once the process is analyzed, an architecture that joins health devices and environmental sensors, together with an information system, has been developed. To test the architecture, a web system connected with health monitors and environment sensors, and with a mobile app have been implemented. PMID:28976940

Citizen-sensor-networks to confront government decision-makers: Two lessons from the Netherlands.

PubMed

Carton, Linda; Ache, Peter

2017-07-01

This paper presents one emerging social-technical innovation: The evolution of citizen-sensor-networks where citizens organize themselves from the 'bottom up', for the sake of confronting governance officials with measured information about environmental qualities. We have observed how citizen-sensor-networks have been initiated in the Netherlands in cases where official government monitoring and business organizations leave gaps. The formed citizen-sensor-networks collect information about issues that affect the local community in their quality-of-living. In particular, two community initiatives are described where the sensed environmental information, on noise pollution and gas-extraction induced earthquakes respectively, is published through networked geographic information methods. Both community initiatives pioneered in developing an approach that comprises the combined setting-up of sensor data flows, real-time map portals and community organization. Two particular cases are analyzed to trace the emergence and network operation of such 'networked geo-information tools' in practice: (1) The Groningen earthquake monitor, and (2) The Airplane Monitor Schiphol. In both cases, environmental 'externalities' of spatial-economic activities play an important role, having economic dimensions of national importance (e.g. gas extraction and national airport development) while simultaneously affecting the regional community with environmental consequences. The monitoring systems analyzed in this paper are established bottom-up, by citizens for citizens, to serve as 'information power' in dialogue with government institutions. The goal of this paper is to gain insight in how these citizen-sensor-networks come about: how the idea for establishing a sensor network originated, how their value gets recognized and adopted in the overall 'system of governance'; to what extent they bring countervailing power against vested interests and established discourses to the table and influence power-laden conflicts over environmental pressures; and whether or not they achieve (some form of) institutionalization and, ultimately, policy change. We find that the studied-citizen-sensor networks gain strength by uniting efforts and activities in crowdsourcing data, providing factual, 'objectivized data' or 'evidence' of the situation 'on the ground' on a matter of local community-wide concern. By filling an information need of the local community, a process of 'collective sense-making' combined with citizen empowerment could grow, which influenced societal discourse and challenged prevailing truth-claims of public institutions. In both cases similar, 'competing' web-portals were developed in response, both by the gas-extraction company and the airport. But with the citizen-sensor-networks alongside, we conclude there is a shift in power balance involved between government and affected communities, as the government no longer has information monopoly on environmental measurements. Copyright © 2017 Elsevier Ltd. All rights reserved.

On performing semantic queries in small devices

NASA Astrophysics Data System (ADS)

Costea, C.; Petrovan, A.; Neamţ, L.; Chiver, O.

2016-08-01

The sensors have a well-defined role in control or monitoring industrial processes; the data given by them can generate valuable information of the trend of the systems to which they belong, but to store a large volume of data and then analysis offline is not always practical. One solution is on-line analysis, preferably as close to the place where data have been generated (edge computing). An increasing amount of data generated by a growing number of devices connected to the Internet resulted in processing data sensors to the edge of the network, in a middle layer where smart entities should interoperate. Diversity of communication technologies outlined the idea of using intermediate devices such as gateways in sensor networks and for this reason the paper examines the functionality of a SPARQL endpoint in the Raspberry Pi device.

A Survey of Data Semantization in Internet of Things

PubMed Central

Shi, Feifei; Zhu, Tao

2018-01-01

With the development of Internet of Things (IoT), more and more sensors, actuators and mobile devices have been deployed into our daily lives. The result is that tremendous data are produced and it is urgent to dig out hidden information behind these volumous data. However, IoT data generated by multi-modal sensors or devices show great differences in formats, domains and types, which poses challenges for machines to process and understand. Therefore, adding semantics to Internet of Things becomes an overwhelming tendency. This paper provides a systematic review of data semantization in IoT, including its backgrounds, processing flows, prevalent techniques, applications, existing challenges and open issues. It surveys development status of adding semantics to IoT data, mainly referring to sensor data and points out current issues and challenges that are worth further study. PMID:29361772

A Survey of Data Semantization in Internet of Things.

PubMed

Shi, Feifei; Li, Qingjuan; Zhu, Tao; Ning, Huansheng

2018-01-22

With the development of Internet of Things (IoT), more and more sensors, actuators and mobile devices have been deployed into our daily lives. The result is that tremendous data are produced and it is urgent to dig out hidden information behind these volumous data. However, IoT data generated by multi-modal sensors or devices show great differences in formats, domains and types, which poses challenges for machines to process and understand. Therefore, adding semantics to Internet of Things becomes an overwhelming tendency. This paper provides a systematic review of data semantization in IoT, including its backgrounds, processing flows, prevalent techniques, applications, existing challenges and open issues. It surveys development status of adding semantics to IoT data, mainly referring to sensor data and points out current issues and challenges that are worth further study.

Methods and apparatuses for detection of radiation with semiconductor image sensors

DOEpatents

Cogliati, Joshua Joseph

2018-04-10

A semiconductor image sensor is repeatedly exposed to high-energy photons while a visible light obstructer is in place to block visible light from impinging on the sensor to generate a set of images from the exposures. A composite image is generated from the set of images with common noise substantially removed so the composite image includes image information corresponding to radiated pixels that absorbed at least some energy from the high-energy photons. The composite image is processed to determine a set of bright points in the composite image, each bright point being above a first threshold. The set of bright points is processed to identify lines with two or more bright points that include pixels therebetween that are above a second threshold and identify a presence of the high-energy particles responsive to a number of lines.

Integrating sensing across a broader spectrum to support homeland security

NASA Astrophysics Data System (ADS)

O'Brien, Thomas W.; Finkelstein, Marc

2003-08-01

All objects and activities give off energy in some part of the spectrum, may leave tell-tail signs from their previous activities (e.g., earth scaring or vapor trails), or leave information about relationships that they may have with other entities and activities (e.g., networks). Many of these phenomenologies are either not picked up by current stovepiped sensors, or the data supplied by those sensors are not fully exploited to properly observe them. In either case, new sensor data as well as the better exploitation of existing data could be used to provide, or at least cross cue or correlate with other sensor data to detect, identify, geolocate or track different kind of problems. Current sensors are often designed for specific purposes and are capable of sensing only limited parts of the spectrum. Significantly broadening the sensing spectrum will be an essential element of solving the emerging class of new "hard problems". There are many other observables available that could be exploited to assist in that process. Thus one could broaden the sensing to observe those phenomenologies associated with combustion effluents; thermal radiation; magnetic anomalies; seismic movement; acoustics; unintended electromagnetic emissions, changing weather conditions, logistics support indicators, debris trails; impressed observables (such as tagging); and others. What's needed is a disciplined, analytical process that can map observables to sensors, and ultimately to mission utility. The process, described in this SPIE presentation will address a specific example on the flow from the establishment of requirements to prosecutable observables, to objectives, to identification of sensors and assets, to the allocation of sensors and assets to observables, all based on optimizing mission utility.

Acoustic sensors in the helmet detect voice and physiology

NASA Astrophysics Data System (ADS)

Scanlon, Michael V.

2003-09-01

The Army Research Laboratory has developed body-contacting acoustic sensors that detect diverse physiological sounds such as heartbeats and breaths, high quality speech, and activity. These sensors use an acoustic impedance-matching gel contained in a soft, compliant pad to enhance the body borne sounds, yet significantly repel airborne noises due to an acoustic impedance mismatch. The signals from such a sensor can be used as a microphone with embedded physiology, or a dedicated digital signal processor can process packetized data to separate physiological parameters from voice, and log parameter trends for performance surveillance. Acoustic sensors were placed inside soldier helmets to monitor voice, physiology, activity, and situational awareness clues such as bullet shockwaves from sniper activity and explosions. The sensors were also incorporated into firefighter breathing masks, neck and wrist straps, and other protective equipment. Heart rate, breath rate, blood pressure, voice and activity can be derived from these sensors (reports at www.arl.army.mil/acoustics). Having numerous sensors at various locations provides a means for array processing to reduce motion artifacts, calculate pulse transit time for passive blood pressure measurement, and the origin of blunt/penetrating traumas such as ballistic wounding. These types of sensors give us the ability to monitor soldiers and civilian emergency first-responders in demanding environments, and provide vital signs information to assess their health status and how that person is interacting with the environment and mission at hand. The Objective Force Warrior, Scorpion, Land Warrior, Warrior Medic, and other military and civilian programs can potentially benefit from these sensors.

A cognitive information processing framework for distributed sensor networks

NASA Astrophysics Data System (ADS)

Wang, Feiyi; Qi, Hairong

2004-09-01

In this paper, we present a cognitive agent framework (CAF) based on swarm intelligence and self-organization principles, and demonstrate it through collaborative processing for target classification in sensor networks. The framework involves integrated designs to provide both cognitive behavior at the organization level to conquer complexity and reactive behavior at the individual agent level to retain simplicity. The design tackles various problems in the current information processing systems, including overly complex systems, maintenance difficulties, increasing vulnerability to attack, lack of capability to tolerate faults, and inability to identify and cope with low-frequency patterns. An important and distinguishing point of the presented work from classical AI research is that the acquired intelligence does not pertain to distinct individuals but to groups. It also deviates from multi-agent systems (MAS) due to sheer quantity of extremely simple agents we are able to accommodate, to the degree that some loss of coordination messages and behavior of faulty/compromised agents will not affect the collective decision made by the group.

Neuro-inspired smart image sensor: analog Hmax implementation

NASA Astrophysics Data System (ADS)

Paindavoine, Michel; Dubois, Jérôme; Musa, Purnawarman

2015-03-01

Neuro-Inspired Vision approach, based on models from biology, allows to reduce the computational complexity. One of these models - The Hmax model - shows that the recognition of an object in the visual cortex mobilizes V1, V2 and V4 areas. From the computational point of view, V1 corresponds to the area of the directional filters (for example Sobel filters, Gabor filters or wavelet filters). This information is then processed in the area V2 in order to obtain local maxima. This new information is then sent to an artificial neural network. This neural processing module corresponds to area V4 of the visual cortex and is intended to categorize objects present in the scene. In order to realize autonomous vision systems (consumption of a few milliwatts) with such treatments inside, we studied and realized in 0.35μm CMOS technology prototypes of two image sensors in order to achieve the V1 and V2 processing of Hmax model.

Immobilization of pH-sensitive CdTe Quantum Dots in a Poly(acrylate) Hydrogel for Microfluidic Applications

NASA Astrophysics Data System (ADS)

Franke, M.; Leubner, S.; Dubavik, A.; George, A.; Savchenko, T.; Pini, C.; Frank, P.; Melnikau, D.; Rakovich, Y.; Gaponik, N.; Eychmüller, A.; Richter, A.

2017-04-01

Microfluidic devices present the basis of modern life sciences and chemical information processing. To control the flow and to allow optical readout, a reliable sensor material that can be easily utilized for microfluidic systems is in demand. Here, we present a new optical readout system for pH sensing based on pH sensitive, photoluminescent glutathione capped cadmium telluride quantum dots that are covalently immobilized in a poly(acrylate) hydrogel. For an applicable pH sensing the generated hybrid material is integrated in a microfluidic sensor chip setup. The hybrid material not only allows in situ readout, but also possesses valve properties due to the swelling behavior of the poly(acrylate) hydrogel. In this work, the swelling property of the hybrid material is utilized in a microfluidic valve seat, where a valve opening process is demonstrated by a fluid flow change and in situ monitored by photoluminescence quenching. This discrete photoluminescence detection (ON/OFF) of the fluid flow change (OFF/ON) enables upcoming chemical information processing.

Smartphones in ecology and evolution: a guide for the app-rehensive.

PubMed

Teacher, Amber G F; Griffiths, David J; Hodgson, David J; Inger, Richard

2013-12-01

Smartphones and their apps (application software) are now used by millions of people worldwide and represent a powerful combination of sensors, information transfer, and computing power that deserves better exploitation by ecological and evolutionary researchers. We outline the development process for research apps, provide contrasting case studies for two new research apps, and scan the research horizon to suggest how apps can contribute to the rapid collection, interpretation, and dissemination of data in ecology and evolutionary biology. We emphasize that the usefulness of an app relies heavily on the development process, recommend that app developers are engaged with the process at the earliest possible stage, and commend efforts to create open-source software scaffolds on which customized apps can be built by nonexperts. We conclude that smartphones and their apps could replace many traditional handheld sensors, calculators, and data storage devices in ecological and evolutionary research. We identify their potential use in the high-throughput collection, analysis, and storage of complex ecological information.

Intelligent Transportation Systems (ITS) plan for Canada : en route to intelligent mobility

DOT National Transportation Integrated Search

1999-11-01

Intelligent Transportation Systems (ITS) include the application of advanced information processing, communications, sensor and control technologies and management strategies in an integrated manner to improve the functioning of the transportation sy...

Sensor Web for Spatio-Temporal Monitoring of a Hydrological Environment

NASA Technical Reports Server (NTRS)

Delin, K. A.; Jackson, S. P.; Johnson, D. W.; Burleigh, S. C.; Woodrow, R. R.; McAuley, M.; Britton, J. T.; Dohm, J. M.; Ferre, T. P. A.; Ip, Felipe

2004-01-01

The Sensor Web is a macroinstrument concept that allows for the spatio-temporal understanding of an environment through coordinated efforts between multiple numbers and types of sensing platforms, including, in its most general form, both orbital and terrestrial and both fixed and mobile. Each of these platforms, or pods, communicates within its local neighborhood and thus distributes information to the instrument as a whole. The result of sharing and continual processing of this information among all the Sensor Web elements will result in an information flow and a global perception of and reactive capability to the environment. As illustrated, the Sensor Web concept also allows for the recursive notion of a web of webs with individual distributed instruments possibly playing the role of a single node point on a larger Sensor Web instrument. In particular, the fusion of inexpensive, yet sophisticated, commercial technology from both the computation and telecommunication revolutions has enabled the development of practical, fielded, and embedded in situ systems that have been the focus of the NASA/JPL Sensor Webs Project (http://sensorwebs.jpl.nasa.gov/). These Sensor Webs are complete systems consisting of not only the pod elements that wirelessly communicate among themselves, but also interfacing and archiving software that allows for easy use by the end-user. Previous successful deployments have included environments as diverse as coastal regions, Antarctica, and desert areas. The Sensor Web has broad implications for Earth and planetary science and will revolutionize the way experiments and missions are conceived and performed. As part of our current efforts to develop a macrointelligence within the system, we have deployed a Sensor Web at the Central Avra Valley Storage and Recovery Project (CAVSARP) facility located west of Tucson, AZ. This particular site was selected because it is ideal for studying spatio-temporal phenomena and for providing a test site for more sophisticated hydrological studies in the future.

Methods and Apparatus for Autonomous Robotic Control

NASA Technical Reports Server (NTRS)

Gorshechnikov, Anatoly (Inventor); Livitz, Gennady (Inventor); Versace, Massimiliano (Inventor); Palma, Jesse (Inventor)

2017-01-01

Sensory processing of visual, auditory, and other sensor information (e.g., visual imagery, LIDAR, RADAR) is conventionally based on "stovepiped," or isolated processing, with little interactions between modules. Biological systems, on the other hand, fuse multi-sensory information to identify nearby objects of interest more quickly, more efficiently, and with higher signal-to-noise ratios. Similarly, examples of the OpenSense technology disclosed herein use neurally inspired processing to identify and locate objects in a robot's environment. This enables the robot to navigate its environment more quickly and with lower computational and power requirements.

Multivariate EMD and full spectrum based condition monitoring for rotating machinery

NASA Astrophysics Data System (ADS)

Zhao, Xiaomin; Patel, Tejas H.; Zuo, Ming J.

2012-02-01

Early assessment of machinery health condition is of paramount importance today. A sensor network with sensors in multiple directions and locations is usually employed for monitoring the condition of rotating machinery. Extraction of health condition information from these sensors for effective fault detection and fault tracking is always challenging. Empirical mode decomposition (EMD) is an advanced signal processing technology that has been widely used for this purpose. Standard EMD has the limitation in that it works only for a single real-valued signal. When dealing with data from multiple sensors and multiple health conditions, standard EMD faces two problems. First, because of the local and self-adaptive nature of standard EMD, the decomposition of signals from different sources may not match in either number or frequency content. Second, it may not be possible to express the joint information between different sensors. The present study proposes a method of extracting fault information by employing multivariate EMD and full spectrum. Multivariate EMD can overcome the limitations of standard EMD when dealing with data from multiple sources. It is used to extract the intrinsic mode functions (IMFs) embedded in raw multivariate signals. A criterion based on mutual information is proposed for selecting a sensitive IMF. A full spectral feature is then extracted from the selected fault-sensitive IMF to capture the joint information between signals measured from two orthogonal directions. The proposed method is first explained using simple simulated data, and then is tested for the condition monitoring of rotating machinery applications. The effectiveness of the proposed method is demonstrated through monitoring damage on the vane trailing edge of an impeller and rotor-stator rub in an experimental rotor rig.

Arc-welding quality assurance by means of embedded fiber sensor and spectral processing combining feature selection and neural networks

NASA Astrophysics Data System (ADS)

Mirapeix, J.; García-Allende, P. B.; Cobo, A.; Conde, O.; López-Higuera, J. M.

2007-07-01

A new spectral processing technique designed for its application in the on-line detection and classification of arc-welding defects is presented in this paper. A non-invasive fiber sensor embedded within a TIG torch collects the plasma radiation originated during the welding process. The spectral information is then processed by means of two consecutive stages. A compression algorithm is first applied to the data allowing real-time analysis. The selected spectral bands are then used to feed a classification algorithm, which will be demonstrated to provide an efficient weld defect detection and classification. The results obtained with the proposed technique are compared to a similar processing scheme presented in a previous paper, giving rise to an improvement in the performance of the monitoring system.

Advanced Land Imager Assessment System

NASA Technical Reports Server (NTRS)

Chander, Gyanesh; Choate, Mike; Christopherson, Jon; Hollaren, Doug; Morfitt, Ron; Nelson, Jim; Nelson, Shar; Storey, James; Helder, Dennis; Ruggles, Tim;

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.

Multiple frequency method for operating electrochemical sensors

DOEpatents

Martin, Louis P [San Ramon, CA

2012-05-15

A multiple frequency method for the operation of a sensor to measure a parameter of interest using calibration information including the steps of exciting the sensor at a first frequency providing a first sensor response, exciting the sensor at a second frequency providing a second sensor response, using the second sensor response at the second frequency and the calibration information to produce a calculated concentration of the interfering parameters, using the first sensor response at the first frequency, the calculated concentration of the interfering parameters, and the calibration information to measure the parameter of interest.

Advantages and Challenges in using Multi-Sensor Data for Studying Aerosols from Space

NASA Astrophysics Data System (ADS)

Leptoukh, Gregory

We are living now in the golden era of numerous sensors measuring aerosols from space, e.g., MODIS, MISR, MERIS, OMI, POLDER, etc. Data from multiple sensors provide a more complete coverage of physical phenomena than data from a single sensor. These sensors are rather different from each other, are sensitive to various parts of the atmosphere, use different aerosol models and treat surface differently when retrieving aerosols. However, they complement each other thus providing more information about spatial, vertical and temporal distribution of aerosols. In addition to differences in instrumentation, retrieval algorithms and calibration, there are quite substantial differences in processing algorithms from Level 0 up to Level 3 and 4. Some of these differences in processing steps, at times not well documented and not widely known by users, can lead to quite significant differences in final products. Without documenting all the steps leading to the final product, data users will not trust the data and/or may use data incorrectly. Data by themselves without quality assessment and provenance are not sufficient to make accurate scientific conclusions. In this paper we provide examples of striking differences between aerosol optical depth data from MODIS, MISR, and MERIS that can be attributed to differences in a certain threshold, aggregation methods, and the dataday definition. We talk about challenges in developing processing provenance. Also, we address issues of harmonization of data, quality and provenance that is needed to guide the multi-sensor data usage and avoid apples-to-oranges comparison and fusion.

A mobile unit for memory retrieval in daily life based on image and sensor processing

NASA Astrophysics Data System (ADS)

Takesumi, Ryuji; Ueda, Yasuhiro; Nakanishi, Hidenobu; Nakamura, Atsuyoshi; Kakimori, Nobuaki

2003-10-01

We developed a Mobile Unit which purpose is to support memory retrieval of daily life. In this paper, we describe the two characteristic factors of this unit. (1)The behavior classification with an acceleration sensor. (2)Extracting the difference of environment with image processing technology. In (1), By analyzing power and frequency of an acceleration sensor which turns to gravity direction, the one's activities can be classified using some techniques to walk, stay, and so on. In (2), By extracting the difference between the beginning scene and the ending scene of a stay scene with image processing, the result which is done by user is recognized as the difference of environment. Using those 2 techniques, specific scenes of daily life can be extracted, and important information at the change of scenes can be realized to record. Especially we describe the effect to support retrieving important things, such as a thing left behind and a state of working halfway.

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

NASA Astrophysics Data System (ADS)

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

2016-12-01

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

The advanced linked extended reconnaissance and targeting technology demonstration project

NASA Astrophysics Data System (ADS)

Cruickshank, James; de Villers, Yves; Maheux, Jean; Edwards, Mark; Gains, David; Rea, Terry; Banbury, Simon; Gauthier, Michelle

2007-06-01

The Advanced Linked Extended Reconnaissance & Targeting (ALERT) Technology Demonstration (TD) project is addressing key operational needs of the future Canadian Army's Surveillance and Reconnaissance forces by fusing multi-sensor and tactical data, developing automated processes, and integrating beyond line-of-sight sensing. We discuss concepts for displaying and fusing multi-sensor and tactical data within an Enhanced Operator Control Station (EOCS). The sensor data can originate from the Coyote's own visible-band and IR cameras, laser rangefinder, and ground-surveillance radar, as well as beyond line-of-sight systems such as a mini-UAV and unattended ground sensors. The authors address technical issues associated with the use of fully digital IR and day video cameras and discuss video-rate image processing developed to assist the operator to recognize poorly visible targets. Automatic target detection and recognition algorithms processing both IR and visible-band images have been investigated to draw the operator's attention to possible targets. The machine generated information display requirements are presented with the human factors engineering aspects of the user interface in this complex environment, with a view to establishing user trust in the automation. The paper concludes with a summary of achievements to date and steps to project completion.

Multi-frequency SAR, SSM/I and AVHRR derived geophysical information of the marginal ice zone

NASA Technical Reports Server (NTRS)

Shuchman, R. A.; Onstott, R. G.; Wackerman, C. C.; Russel, C. A.; Sutherland, L. L.; Johannessen, O. M.; Johannessen, J. A.; Sandven, S.; Gloerson, P.

1991-01-01

A description is given of the fusion of synthetic aperture radar (SAR), special sensor microwave imager (SSM/I), and NOAA Advanced Very High Resolution Radiometer (AVHRR) data to study arctic processes. These data were collected during the SIZEX/CEAREX experiments that occurred in the Greenland Sea in March of 1989. Detailed comparisons between the SAR, AVHRR, and SSM/I indicated: (1) The ice edge position was in agreement to within 25 km, (2) The SSM/I SAR total ice concentration compared favorably, however, the SSM/I significantly underpredicted the multiyear fraction, (3) Combining high resolution SAR with SSM/I can potentially map open water and new ice features in the marginal ice zone (MIZ) which cannot be mapped by the single sensors, and (4) The combination of all three sensors provides accurate ice information as well as sea surface temperature and wind speeds.

Querying and Extracting Timeline Information from Road Traffic Sensor Data

PubMed Central

Imawan, Ardi; Indikawati, Fitri Indra; Kwon, Joonho; Rao, Praveen

2016-01-01

The escalation of traffic congestion in urban cities has urged many countries to use intelligent transportation system (ITS) centers to collect historical traffic sensor data from multiple heterogeneous sources. By analyzing historical traffic data, we can obtain valuable insights into traffic behavior. Many existing applications have been proposed with limited analysis results because of the inability to cope with several types of analytical queries. In this paper, we propose the QET (querying and extracting timeline information) system—a novel analytical query processing method based on a timeline model for road traffic sensor data. To address query performance, we build a TQ-index (timeline query-index) that exploits spatio-temporal features of timeline modeling. We also propose an intuitive timeline visualization method to display congestion events obtained from specified query parameters. In addition, we demonstrate the benefit of our system through a performance evaluation using a Busan ITS dataset and a Seattle freeway dataset. PMID:27563900

The electrophotonic silicon biosensor

NASA Astrophysics Data System (ADS)

Juan-Colás, José; Parkin, Alison; Dunn, Katherine E.; Scullion, Mark G.; Krauss, Thomas F.; Johnson, Steven D.

2016-09-01

The emergence of personalized and stratified medicine requires label-free, low-cost diagnostic technology capable of monitoring multiple disease biomarkers in parallel. Silicon photonic biosensors combine high-sensitivity analysis with scalable, low-cost manufacturing, but they tend to measure only a single biomarker and provide no information about their (bio)chemical activity. Here we introduce an electrochemical silicon photonic sensor capable of highly sensitive and multiparameter profiling of biomarkers. Our electrophotonic technology consists of microring resonators optimally n-doped to support high Q resonances alongside electrochemical processes in situ. The inclusion of electrochemical control enables site-selective immobilization of different biomolecules on individual microrings within a sensor array. The combination of photonic and electrochemical characterization also provides additional quantitative information and unique insight into chemical reactivity that is unavailable with photonic detection alone. By exploiting both the photonic and the electrical properties of silicon, the sensor opens new modalities for sensing on the microscale.

Simulation of the hyperspectral data from multispectral data using Python programming language

NASA Astrophysics Data System (ADS)

Tiwari, Varun; Kumar, Vinay; Pandey, Kamal; Ranade, Rigved; Agarwal, Shefali

2016-04-01

Multispectral remote sensing (MRS) sensors have proved their potential in acquiring and retrieving information of Land Use Land (LULC) Cover features in the past few decades. These MRS sensor generally acquire data within limited broad spectral bands i.e. ranging from 3 to 10 number of bands. The limited number of bands and broad spectral bandwidth in MRS sensors becomes a limitation in detailed LULC studies as it is not capable of distinguishing spectrally similar LULC features. On the counterpart, fascinating detailed information available in hyperspectral (HRS) data is spectrally over determined and able to distinguish spectrally similar material of the earth surface. But presently the availability of HRS sensors is limited. This is because of the requirement of sensitive detectors and large storage capability, which makes the acquisition and processing cumbersome and exorbitant. So, there arises a need to utilize the available MRS data for detailed LULC studies. Spectral reconstruction approach is one of the technique used for simulating hyperspectral data from available multispectral data. In the present study, spectral reconstruction approach is utilized for the simulation of hyperspectral data using EO-1 ALI multispectral data. The technique is implemented using python programming language which is open source in nature and possess support for advanced imaging processing libraries and utilities. Over all 70 bands have been simulated and validated using visual interpretation, statistical and classification approach.

NASA Integrated Vehicle Health Management (NIVHM) A New Simulation Architecture. Part I; An Investigation

NASA Technical Reports Server (NTRS)

Sheppard, Gene

2005-01-01

The overall objective of this research is to explore the development of a new architecture for simulating a vehicle health monitoring system in support of NASA s on-going Integrated Vehicle Health Monitoring (IVHM) initiative. As discussed in NASA MSFC s IVHM workshop on June 29-July 1, 2004, a large number of sensors will be required for a robust IVHM system. The current simulation architecture is incapable of simulating the large number of sensors required for IVHM. Processing the data from the sensors into a format that a human operator can understand and assimilate in a timely manner will require a paradigm shift. Data from a single sensor is, at best, suspect and in order to overcome this deficiency, redundancy will be required for tomorrow s sensors. The sensor technology of tomorrow will allow for the placement of thousands of sensors per square inch. The major obstacle to overcome will then be how we can mitigate the torrent of data from raw sensor data to useful information to computer assisted decisionmaking.

Theoretical and experimental study of low-finesse extrinsic Fabry-Perot interferometric fiber optic sensors

NASA Astrophysics Data System (ADS)

Han, Ming

In this dissertation, detailed and systematic theoretical and experimental study of low-finesse extrinsic Fabry-Perot interferometric (EFPI) fiber optic sensors together with their signal processing methods for white-light systems are presented. The work aims to provide a better understanding of the operational principle of EFPI fiber optic sensors, and is useful and important in the design, optimization, fabrication and application of single mode fiber(SMF) EFPI (SMF-EFPI) and multimode fiber (MMF) EFPI (MMF-EFPI) sensor systems. The cases for SMF-EFPI and MMF-EFPI sensors are separately considered. In the analysis of SMF-EFPI sensors, the light transmitted in the fiber is approximated by a Gaussian beam and the obtained spectral transfer function of the sensors includes an extra phase shift due to the light coupling in the fiber end-face. This extra phase shift has not been addressed by previous researchers and is of great importance for high accuracy and high resolution signal processing of white-light SMF-EFPI systems. Fringe visibility degradation due to gap-length increase and sensor imperfections is studied. The results indicate that the fringe visibility of a SMF-EFPI sensor is relatively insensitive to the gap-length change and sensor imperfections. Based on the spectral fringe pattern predicated by the theory of SMF-EFPI sensors, a novel curve fitting signal processing method (Type 1 curve-fitting method) is presented for white-light SMF-EFPI sensor systems. Other spectral domain signal processing methods including the wavelength-tracking, the Type 2-3 curve fitting, Fourier transform, and two-point interrogation methods are reviewed and systematically analyzed. Experiments were carried out to compare the performances of these signal processing methods. The results have shown that the Type 1 curve fitting method achieves high accuracy, high resolution, large dynamic range, and the capability of absolute measurement at the same time, while others either have less resolution, or are not capable of absolute measurement. Previous mathematical models for MMF-EFPI sensors are all based on geometric optics; therefore their applications have many limitations. In this dissertation, a modal theory is developed that can be used in any situations and is more accurate. The mathematical description of the spectral fringes of MMF-EFPI sensors is obtained by the modal theory. Effect on the fringe visibility of system parameters, including the sensor head structure, the fiber parameters, and the mode power distribution in the MMF of the MMF-EFPI sensors, is analyzed. Experiments were carried out to validate the theory. Fundamental mechanism that causes the degradation of the fringe visibility in MMF-EFPI sensors are revealed. It is shown that, in some situations at which the fringe visibility is important and difficult to achieve, a simple method of launching the light into the MMF-EFPI sensor system from the output of a SMF could be used to improve the fringe visibility and to ease the fabrication difficulties of MMF-EFPI sensors. Signal processing methods that are well-understood in white-light SMF-EFPI sensor systems may exhibit new aspects when they are applied to white-light MMF-EFPI sensor systems. This dissertation reveals that the variations of mode power distribution (MPD) in the MMF could cause phase variations of the spectral fringes from a MMF-EFPI sensor and introduce measurement errors for a signal processing method in which the phase information is used. This MPD effect on the wavelength-tracking method in white-light MMF-EFPI sensors is theoretically analyzed. The fringe phases changes caused by MPD variations were experimentally observed and thus the MFD effect is validated.

Distributed data collection and supervision based on web sensor

NASA Astrophysics Data System (ADS)

He, Pengju; Dai, Guanzhong; Fu, Lei; Li, Xiangjun

2006-11-01

As a node in Internet/Intranet, web sensor has been promoted in recent years and wildly applied in remote manufactory, workshop measurement and control field. However, the conventional scheme can only support HTTP protocol, and the remote users supervise and control the collected data published by web in the standard browser because of the limited resource of the microprocessor in the sensor; moreover, only one node of data acquirement can be supervised and controlled in one instant therefore the requirement of centralized remote supervision, control and data process can not be satisfied in some fields. In this paper, the centralized remote supervision, control and data process by the web sensor are proposed and implemented by the principle of device driver program. The useless information of the every collected web page embedded in the sensor is filtered and the useful data is transmitted to the real-time database in the workstation, and different filter algorithms are designed for different sensors possessing independent web pages. Every sensor node has its own filter program of web, called "web data collection driver program", the collecting details are shielded, and the supervision, control and configuration software can be implemented by the call of web data collection driver program just like the use of the I/O driver program. The proposed technology can be applied in the data acquirement where relative low real-time is required.

High-speed limnology: using advanced sensors to investigate spatial variability in biogeochemistry and hydrology.

PubMed

Crawford, John T; Loken, Luke C; Casson, Nora J; Smith, Colin; Stone, Amanda G; Winslow, Luke A

2015-01-06

Advanced sensor technology is widely used in aquatic monitoring and research. Most applications focus on temporal variability, whereas spatial variability has been challenging to document. We assess the capability of water chemistry sensors embedded in a high-speed water intake system to document spatial variability. This new sensor platform continuously samples surface water at a range of speeds (0 to >45 km h(-1)) resulting in high-density, mesoscale spatial data. These novel observations reveal previously unknown variability in physical, chemical, and biological factors in streams, rivers, and lakes. By combining multiple sensors into one platform, we were able to detect terrestrial-aquatic hydrologic connections in a small dystrophic lake, to infer the role of main-channel vs backwater nutrient processing in a large river and to detect sharp chemical changes across aquatic ecosystem boundaries in a stream/lake complex. Spatial sensor data were verified in our examples by comparing with standard lab-based measurements of selected variables. Spatial fDOM data showed strong correlation with wet chemistry measurements of DOC, and optical NO3 concentrations were highly correlated with lab-based measurements. High-frequency spatial data similar to our examples could be used to further understand aquatic biogeochemical fluxes, ecological patterns, and ecosystem processes, and will both inform and benefit from fixed-site data.

High-speed limnology: Using advanced sensors to investigate spatial variability in biogeochemistry and hydrology

USGS Publications Warehouse

Crawford, John T.; Loken, Luke C.; Casson, Nora J.; Smith, Collin; Stone, Amanda G.; Winslow, Luke A.

2015-01-01

Advanced sensor technology is widely used in aquatic monitoring and research. Most applications focus on temporal variability, whereas spatial variability has been challenging to document. We assess the capability of water chemistry sensors embedded in a high-speed water intake system to document spatial variability. This new sensor platform continuously samples surface water at a range of speeds (0 to >45 km h–1) resulting in high-density, mesoscale spatial data. These novel observations reveal previously unknown variability in physical, chemical, and biological factors in streams, rivers, and lakes. By combining multiple sensors into one platform, we were able to detect terrestrial–aquatic hydrologic connections in a small dystrophic lake, to infer the role of main-channel vs backwater nutrient processing in a large river and to detect sharp chemical changes across aquatic ecosystem boundaries in a stream/lake complex. Spatial sensor data were verified in our examples by comparing with standard lab-based measurements of selected variables. Spatial fDOM data showed strong correlation with wet chemistry measurements of DOC, and optical NO3 concentrations were highly correlated with lab-based measurements. High-frequency spatial data similar to our examples could be used to further understand aquatic biogeochemical fluxes, ecological patterns, and ecosystem processes, and will both inform and benefit from fixed-site data.

mHealthMon: toward energy-efficient and distributed mobile health monitoring using parallel offloading.

PubMed

Ahnn, Jong Hoon; Potkonjak, Miodrag

2013-10-01

Although mobile health monitoring where mobile sensors continuously gather, process, and update sensor readings (e.g. vital signals) from patient's sensors is emerging, little effort has been investigated in an energy-efficient management of sensor information gathering and processing. Mobile health monitoring with the focus of energy consumption may instead be holistically analyzed and systematically designed as a global solution to optimization subproblems. This paper presents an attempt to decompose the very complex mobile health monitoring system whose layer in the system corresponds to decomposed subproblems, and interfaces between them are quantified as functions of the optimization variables in order to orchestrate the subproblems. We propose a distributed and energy-saving mobile health platform, called mHealthMon where mobile users publish/access sensor data via a cloud computing-based distributed P2P overlay network. The key objective is to satisfy the mobile health monitoring application's quality of service requirements by modeling each subsystem: mobile clients with medical sensors, wireless network medium, and distributed cloud services. By simulations based on experimental data, we present the proposed system can achieve up to 10.1 times more energy-efficient and 20.2 times faster compared to a standalone mobile health monitoring application, in various mobile health monitoring scenarios applying a realistic mobility model.

NASA/MSFC FY88 Global Scale Atmospheric Processes Research Program Review

NASA Technical Reports Server (NTRS)

Wilson, Greg S. (Editor); Leslie, Fred W. (Editor); Arnold, J. E. (Editor)

1989-01-01

Interest in environmental issues and the magnitude of the environmental changes continues. One way to gain more understanding of the atmosphere is to make measurements on a global scale from space. The Earth Observation System is a series of new sensors to measure globally atmospheric parameters. Analysis of satellite data by developing algorithms to interpret the radiance information improves the understanding and also defines requirements for these sensors. One measure of knowledge of the atmosphere lies in the ability to predict its behavior. Use of numerical and experimental models provides a better understanding of these processes. These efforts are described in the context of satellite data analysis and fundamental studies of atmospheric dynamics which examine selected processes important to the global circulation.

A collaborative computing framework of cloud network and WBSN applied to fall detection and 3-D motion reconstruction.

PubMed

Lai, Chin-Feng; Chen, Min; Pan, Jeng-Shyang; Youn, Chan-Hyun; Chao, Han-Chieh

2014-03-01

As cloud computing and wireless body sensor network technologies become gradually developed, ubiquitous healthcare services prevent accidents instantly and effectively, as well as provides relevant information to reduce related processing time and cost. This study proposes a co-processing intermediary framework integrated cloud and wireless body sensor networks, which is mainly applied to fall detection and 3-D motion reconstruction. In this study, the main focuses includes distributed computing and resource allocation of processing sensing data over the computing architecture, network conditions and performance evaluation. Through this framework, the transmissions and computing time of sensing data are reduced to enhance overall performance for the services of fall events detection and 3-D motion reconstruction.

Image-plane processing of visual information

NASA Technical Reports Server (NTRS)

Huck, F. O.; Fales, C. L.; Park, S. K.; Samms, R. W.

1984-01-01

Shannon's theory of information is used to optimize the optical design of sensor-array imaging systems which use neighborhood image-plane signal processing for enhancing edges and compressing dynamic range during image formation. The resultant edge-enhancement, or band-pass-filter, response is found to be very similar to that of human vision. Comparisons of traits in human vision with results from information theory suggest that: (1) Image-plane processing, like preprocessing in human vision, can improve visual information acquisition for pattern recognition when resolving power, sensitivity, and dynamic range are constrained. Improvements include reduced sensitivity to changes in lighter levels, reduced signal dynamic range, reduced data transmission and processing, and reduced aliasing and photosensor noise degradation. (2) Information content can be an appropriate figure of merit for optimizing the optical design of imaging systems when visual information is acquired for pattern recognition. The design trade-offs involve spatial response, sensitivity, and sampling interval.

GPS free navigation inspired by insects through monocular camera and inertial sensors

NASA Astrophysics Data System (ADS)

Liu, Yi; Liu, J. G.; Cao, H.; Huang, Y.

2015-12-01

Navigation without GPS and other knowledge of environment have been studied for many decades. Advance technology have made sensors more compact and subtle that can be easily integrated into micro and hand-hold device. Recently researchers found that bee and fruit fly have an effectively and efficiently navigation mechanism through optical flow information and process only with their miniature brain. We present a navigation system inspired by the study of insects through a calibrated camera and other inertial sensors. The system utilizes SLAM theory and can be worked in many GPS denied environment. Simulation and experimental results are presented for validation and quantification.

FPGA-based fused smart-sensor for tool-wear area quantitative estimation in CNC machine inserts.

PubMed

Trejo-Hernandez, Miguel; Osornio-Rios, Roque Alfredo; de Jesus Romero-Troncoso, Rene; Rodriguez-Donate, Carlos; Dominguez-Gonzalez, Aurelio; Herrera-Ruiz, Gilberto

2010-01-01

Manufacturing processes are of great relevance nowadays, when there is a constant claim for better productivity with high quality at low cost. The contribution of this work is the development of a fused smart-sensor, based on FPGA to improve the online quantitative estimation of flank-wear area in CNC machine inserts from the information provided by two primary sensors: the monitoring current output of a servoamplifier, and a 3-axis accelerometer. Results from experimentation show that the fusion of both parameters makes it possible to obtain three times better accuracy when compared with the accuracy obtained from current and vibration signals, individually used.