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

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 resourceconstrained 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. Key words: Source Localisation, Spatial Event Detection, Estimation, Kalman Filters....

• Type: Conference
• Year: 2009
• Where: GSN
• Authors: Michael Zoumboulakis, George Roussos
• Keywords: GSN 2009, Low-overhead Coarse Localisation, Pollutant-emitting Point Source, Resourceconstrained Inexpensive Nodes, Sensor Networks