Energy Efficient and Accurate Tracking and Detection of Continuous Objects in Wireless Sensor Networks

Abstract

Continuous objects such as mud flow, oil spill, forest fire and toxic gases detection and localization is a fundamental and significant subject in Wireless sensor networks (WSNs). A continuous object is usually blowout over a large area and therefore a large number of sensor nodes are required for tracking and detection. The nodes exchange control messages with each other and with sink node to report their detection status. For accurate tracking and detection nodes at the phenomenon boundary needs to be carefully selected. In this paper, we use four proximity graphs and different spatial interpolation methods for accurate boundary estimation and boundary nodes selection in a dense duty-cycled wireless sensor network. Accurate and reliable nodes are carefully chosen to be awakened when their sensual data is more applicable and consistent to be boundary node. To reduce overall network energy consumption and increase system lifetime, we propose sensor node scheduling scheme. Extensive simulation result shows that the proposed continuous objects detection and tracking technique is more energy efficient and the boundary area can be enhanced more accurately.