An Intelligent Energy Efficient Target Tracking Scheme for wireless sensor environment

Abstract

The continuous advancement of sensor technology facilitates its usage in many applications, such as surveillance, traffic and environmental monitoring applications. In these applications, the efficient usage of energy is very crucial issue since the sensors not only need to do monitoring and processing but also they need to communicate with each other in order to maintain long term monitoring of moving targets. The usage of sensors' energy can be improved by reducing the number of communication messages exchanged among them. Since it is assumed that, communication uses nearly twice more energy than other operations such as computation and data processing. This paper proposes an efficient strategy for monitoring and tracking of a single or multiple moving targets by reducing communication among the sensors for predicting the next location of moving targets. The experimental results show that our strategy performs well when the size of the network is large despite the underling structure of the sensors°.

Adaptive Dynamic Programming-Based Multi-Sensor Scheduling for Collaborative Target Tracking in Energy Harvesting Wireless Sensor Networks

“…For example, an adaptive sensor scheduling scheme was introduced by scheduling the next tasking sensor for the next time step according to the predicted tracking accuracy derived from the trace of the covariance matrix of the state estimation [21]. In [27], an energy-efficient target tracking method was proposed, where the KF is used to predict the target location for the next time step, then the sensor node and the cluster are selected to minimize the energy consumption. A multi-step sensor scheduling scheme is adopted based on the adaptive sampling interval approach to achieve fast tracking speed and superior energy efficiency without degrading the tracking accuracy [28].…”