On Localized Prediction for Power Efficient Object Tracking in Sensor Networks
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The accuracy of the object tracking is dependent on the tracking time interval. Smaller tracking time interval increases the accuracy of tracking a moving object. However, this increases the power consumption significantly. This paper proposes a new adaptive algorithm (AEC) to adapt tracking time interval such that it minimizes power consumption while keeping the required accuracy. Simulation results show that using the proposed algorithm, the tracking network has a good performance with the added advantage of reducing the power consumption significantly when compared with existing non-adaptive methods (like PATES). Moreover, simulation results show that the performance of the proposed algorithm is better than one of existing adaptive methods (PaM) with respect to power consumption (up to 12%) and tracking accuracy (up to 5%).