Abstract
Wireless Sensor Networks (WSN) can produce decisions that are unreliable due to the large inherent uncertainties in the areas which they are deployed. It is vital for the applications where WSN's are deployed that accurate decisions can be made from the data produced. Fault detection is a vital pursuit, however it is a challenging task. In this paper we present a fuzzy logic data fusion approach to fault detection within a Wireless Sensor Network using a Statistical Process Control and a clustered covariance method. Through the use of a fuzzy logic data fusion approach we have introduced a novel technique into this area to reduce uncertainty and false-positives within the fault detection process.
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