Towards Distributed Event Detection in Wireless Sensor Networks

Distributed event detection in wireless sensor networks (WSNs) is the process of observing and evaluating an event using multiple sensor nodes without the help of a base station or other means of central coordination and processing. Current approaches to event detection in WSNs transmit raw data to an external entity for evaluation or rely on simplistic pattern recognition schemes. This implies either high communication overhead or low event detection accuracy, especially for complex events. In this paper, we present our currently on-going work on a system for distributed event detection that particularly suits the specific characteristics of WSNs. Adapting traditional pattern recognition algorithms to highly embedded devices, it uses the distributed sampling of sensor nodes to optimize the accuracy of the event detection process. Four different algorithms for distributing, classifying and fusing “fingerprints” of the raw data sampled on each sensor are proposed and quantitatively evaluated in a small-scale experiment.