A new adaptive power optimization scheme for target tracking Wireless Sensor Networks

Tracking moving objects with wireless sensor networks (WSNs) has received much concern because of its practical applications in nowadays world. Tracking accuracy is deeply dependant upon tracking time interval of the tracking network. This paper proposes a new adaptive power optimization scheme for target tracking sensor networks. This scheme includes a fast dynamic adaptive prediction-based tracking (FDAPT) algorithm to dynamically modify the tracking time interval such that it minimizes the power consumption while keeping the required accuracy. The simulation results show that using the proposed scheme the network has a good performance with the added advantage of reducing the power consumption significantly when compared to previous non-adaptive tracking schemes. Moreover, simulation results show that the performance of the proposed scheme is better than one of existing adaptive methods with respect to power consumption (up to 10%) and tracking accuracy (up to 4%).