Estimation of Pollutant-Emitting Point-Sources Using Resource-Constrained Sensor Networks

Authors:
Michael Zoumboulakis;George Roussos
Affiliations:
School of Computer Science and Information Systems Birkbeck College, University of London, London, UK WC1E 7HX;School of Computer Science and Information Systems Birkbeck College, University of London, London, UK WC1E 7HX
Venue:
GSN '09 Proceedings of the 3rd International Conference on GeoSensor Networks
Year:
2009

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Abstract

We present an algorithm that makes an appropriate use of a Kalman filter combined with a geometric computation with respect to the localisation of a pollutant-emitting point source. Assuming resource-constrained inexpensive nodes and no specific placement distance to the source, our approach has been shown to perform well in estimating the coordinates and intensity of a source. Using local gossip to directionally propagate estimates, our algorithm initiates a real-time exchange of information that has as an ultimate goal to lead a packet from a node that initially sensed the event to a destination that is as close to the source as possible. The coordinates and intensity measurement of the destination comprise the final estimate. In this paper, we assert that this low-overhead coarse localisation method can rival more sophisticated and computationally-hungry solutions to the source estimation problem.