Energy efficient multi-target tracking in heterogeneous wireless sensor networks

Abstract

Tracking multiple targets in an energy efficient way is an important challenge in wireless sensor networks (WSNs). While most of the prior work consider tracking multiple targets as execution of single target tracking algorithms multiple times and utilize only single parameters for efficient energy consumption, we identify multiple parameters that can influence the energy efficiency of sensors in the WSN. We observe that there are several impacting parameters that can affect the energy efficiency of the sensors in the WSN which are: the relative location of the sensor with respect to the target's motion, multiple targets tracked by the sensor, and the remaining energy in the sensor. These impacting parameters are used to decide the tracking state of the sensors and further, our observations reveal the implications of combining these parameters and we identify that the optimal energy consumption is governed by their usage in particular network conditions. Based on these observations we proceed to propose our Adaptive Multi-Target Tracking (AMTT) algorithm that can identify the local network conditions for individual sensors in distributed environment without any centralized co-ordination, and uses required combination of impacting parameters to achieve energy efficiency.