FED: Fuzzy Event Detection model for Wireless Sensor Networks

Abstract

Event detection is one of the required services in sensor network applications such as environmental monitoring and object tracking. Composite event detection faces several challenges.The first challenge is uncertainty caused by variety of factors, while the second one is heterogeneity of sensor nodes in sensing capabilities. Finally, distributed detection,which is vital to facilitate uncovering composite events in large scale sensor networks, is challenging.We devised a new fuzzy event detection model which is called FED that benefits from fuzzy variables to measure the intensity as well as the occurrenceof detected events. FED uses fuzzy rules to define composite eventsto enhance handling uncertainty. Moreover, FED provides a node level knowledge abstraction, which offers flexibility in applying heterogeneous sensors. The model is also applicable to a clustered network for distributed event detection. The simulation results show that FED is less sensitive to environmental noise and performs better in terms of percentage of detected eventscompare to a similar approach.