Sensor networks are fast-emerging as a powerful technology for many distributed surveillance and monitoring applications. The crux of these applications lies in being able to compute various global characteristics, like contour, trajectory, direction, velocity etc., of mobile phenomena. In this paper, we present algorithms based on in-network aggregation to efficiently compute these global characteristics of phenomena by representing them as functions amenable to in-network processing, at a very low communication cost. We present two versions of these algorithms; one for post-event querying and the other for real-time warnings and include simulation results for all our algorithms.
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