  Sensor networks aim at monitoring their surroundings for event detection and
object tracking. But, due to failure, or death of sensors, false signal can be
transmitted. In this paper, we consider the problems of distributed fault
detection in wireless sensor network (WSN). In particular, we consider how to
take decision regarding fault detection in a noisy environment as a result of
false detection or false response of event by some sensors, where the sensors
are placed at the center of regular hexagons and the event can occur at only
one hexagon. We propose fault detection schemes that explicitly introduce the
error probabilities into the optimal event detection process. We introduce two
types of detection probabilities, one for the center node, where the event
occurs and the other one for the adjacent nodes. This second type of detection
probability is new in sensor network literature. We develop schemes under the
model selection procedure, multiple model selection procedure and use the
concept of Bayesian model averaging to identify a set of likely fault sensors
and obtain an average predictive error.
