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HCTT&R: A complete scheme for object tracking and recovery of lost objects in cluster-based wireless sensor networks

This paper takes a look at the performance of an energy-efficient object tracking wireless sensor network. As you know object tracking is vulnerable to object losing due to reasons like predicting errors, sensor failures and abrupt changes in speed/course of the object. For a reliable object tracking method that could be used in critical situations, a foolproof mechanism is needed. This paper examines a novel object tracking method (HCTT&R) to track objects and recover lost objects in a clustered network. The simulation has been carried out using the Castalia simulation framework of OMNET++ to compare the proposed method with the base method to show the benefits and defeats of the proposed method. Finally with transferring the acquired data from Castalia into Matlab and interpolating them (LOWESS algorithm), we find a smooth course of object which let the user decide more easily about the future actions of the tracked object(s).