Reliable continuous objects detection algorithm in wireless sensor networks

In wireless sensor networks, reliable event detection is one of the most important research issues. For the reliable event detection, existing studies usually assume that events are individual objects such as tanks, people, and animals. The existing studies estimate detection reliability of an individual object by the ratio of the number of successfully received data packets at a sink to the number of data packets determined by applications for reliable detection. Recently, detection of the other one kind of events, called the continuous object, such as wild fire and bio-chemical material has been receiving increased attention. Unlike the individual objects, a continuous object might cover a wide area and it could dynamically alter its own shape according to physical environments, e.g. wind, geographical features, and so on. Hence, the continuous object detection reliability can not be estimated by the indicator for the individual objects. In this paper we newly define the reliability indicator for continuous object detection. Then, we propose error recovery and revision scheme based on the estimation result from the novel indicator. Simulation results prove that the proposed scheme provides high reliability with respect to continuous object detection.