To develop and deploy a detection and tracking system based on wireless sensor networks. Real-Time detection and tracking is achieved using Wireless Sensor Networks Hardware. The system is envisioned to be able to effectively handle multiple arbitrarily moving targets

Mazomenos, Evangelos B.

English

Southampton (e-Prints Soton)

Real–Time Detection and Tracking using Wireless Sensor Networks Evangelos B. Mazomenos*,  Jeff S. Reeve,  Neil M. White*email: ebm07r@ecs.soton.ac.uk; web: http://www.ecs.soton.ac.uk/people/ebm07r; tel. +44 (0)23 8059 4996; fax. +44 (0)23 8059 2901Electronic Systems and Devices Group, School of Electronics and Computer Science, University of Southampton, SO17 1BJ, UKFor further information, please visit http://www.wise.ecs.soton.ac.uk or email ebm07r@ecs.soton.ac.ukLast updated 15 September 2008Project Aims Network Topology - StructureTracking in Wireless Sensor Networks To develop and deploy a detection and tracking system basedon wireless sensor networks. Real-Time detection and trackingis achieved using Wireless Sensor Networks Hardware. Thesystem is envisioned to be able to effectively handle multiplearbitrarily moving targets.A generic tracking scenario: A network comprised of low-power, resource constrained nodes,  detects an object of interest and initiates tracking based on sensor readings obtained be the nodes. A base station node is used to for report and display purposes.  A generic tracking scenario. Adapted from [1]In order to estimate an objects position, a certain sensingmodality which associates the distance of the object from thesensor node should be made available. Classification of targetscan be made possible by using more than one different sensorsto gather measurements. Some of the modalities consideredfor tracking are summarized below.1. Time of Flight2. Direction of Arrival3. Acoustic Sensors4. Passive Infrared Sensors5. Magnetic SensorsMost of these modalities have been investigated and sub-meteraccuracy can be achieved using range only measurements.A detection/tracking system requires the implementation of atracking algorithm which uses the measurements provided bysensors to estimate the object’s position. Other kinematicattributes that can be estimated through this procedure are,velocity and acceleration.The tracking algorithm is based on Particle Filters.P a r t i c l eFilters are sequential Monte Carlo algorithms based on sample(particle) representation of probabilities densities. These can beapplied to a state-space model and recursively estimate thestate vector of the system.This algorithm is scheduled to be implemented in WirelessSensor Network hardware, and experiments will be conductedto evaluate the system performance.References1. Feng Zhao, Jie Liu, Juan Liu, L. Guibas, and J. Reich. Collaborative signal and information processing: an information-directed approach. Proceedings of the IEEE, 91(8):1199–1209, Aug. 2003.A vehicle tracking scenarioApplication DomainsThe above system can be used in a number of differentdomains which require tracking of moving objects. Examplesinclude:1. Vehicle Navigation2. Wildlife Monitoring3. Military battlefield surveillance4. Industrial asset monitoring5. Security Systems

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