Object Detection and Localization Using Wireless Sensor Networks Based On Probabilistic Model

Abstract

Wireless Sensor Network (WSN) has been widely used for monitoring where are deployed to operate sensors independently to sense abnormal phenomena. Most of the proposed objects monitoring systems are designed based on a predetermined sensing range which does not reflect the sensor reliability, object characteristics, and the environment conditions. Measuring of the capability of a sensor node to accurately detect a moving object within a sensing is of great important for surveillance applications. This paper presents an efficient mechanism for object detection and localization based on probabilistic sensing model. Different models have been presented theoretically in this paper to examine their adaptability and applicability to the real environment applications. The numerical results of the experimental evaluation have showed that the probabilistic sensing model provides accurate observation and delectability of objects, and it can be utilized for different environment scenarios.