Face Tracking to Detect Dynamic Target in Wireless Sensor Networks

Abstract

Wireless sensor networks are collection of spatially distributed autonomous actuator devices called sensor nodes. Tracking target under surveillance is one of the main applications of wireless sensor networks. It enables remote monitoring of objects and its environments. In target tracking, sensor nodes are informed when the target under surveillance is discovered. Some nodes detect the target and send a detection message to the nodes on the targets expected moving path. So nodes can wake up earlier. Face tracking is a new tacking framework, in which divides the region into different polygons called Faces. Instead of predicting the target location separately in a face, here estimate the targets movement towards another face. It enables the wireless sensor network to be aware of a target entering the polygon a bit earlier. Face track method failed when target in dynamic motion, i.e. target in random motion or retracing the path again and again. If the target follows a dynamic motion, the polygons are reconstructed repeatedly and energy is wasted in sending messages to create new polygons. Here proposes a framework to track a mobile object in a sensor network dynamically. In this framework, Polygons are created initially in form of clusters to avoid repeated polygon reconstruction. The sensors are programmed in a way that at least one sensor stays active at any instant of time in the polygon to detect the target. Once the target is detected and it entered into the edge of polygon, the nodes of the neighboring polygon is activated. Then, activated polygon keep tracking the target. Thus energy of the sensor nodes are saved because of polygon is not created and deleted, instead activated.