Abstract
We propose a polynomial-based scheme that addresses the problem of event region detection (PERD) for wireless sensor networks (WSNs). Nodes of an aggregation tree perform function approximation of the event using multivariate polynomial regression. Only the coefficients of this polynomial are then transmitted up the tree instead of aggregated data. PERD includes two components: event recognition and event report with boundary detection. In addition, PERD is capable of detecting single event or multiple events simultaneously occurring in the WSN. Since PERD is implemented over a polynomial tree on a WSN in a distributed manner, it is easily scalable and computation overhead is very light. Results reveal that event(s) can be detected by PERD with error in detection remaining almost constant achieving a percentage error within a threshold of 10% with increase in communication range.
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