Abstract: Target tracking is one of the eye catching applications in wireless sensor network. The network employees the object tracking practices which track the affecting target when it moves through sensor network. Existing work mostly involves face tracking edge detection algorithm which tracks the movement of target in timely fashion. In this paper, we propose a new tracking framework, which involves prediction and detection of the target in a face. Here “Kalman filter” is introduces which is used to predicts the objects location individually in a face and “Face Tracking Framework” for target detection. Kalman Filter is capable of tracking a target with high resolution in the presence of compromised or colluding malicious beacon nodes. Face Tracking employs, the nodes of a spatial region surrounding a target, called a face. Edge detection algorithm is used to generate each face further in such a way that the nodes can arrange onward of the target’s moving, which helps tracking the target in a timely basis and recuperating from special cases, e.g., sensor fault, loss of tracking. Also, optimal selection algorithm is used which select the sensors of faces for enquiry and to acceleration of the tracking data. Simulation results, compared with existing work, show that new tracking methodology achieves better tracking accuracy and energy efficiency and effectiveness.

Keywords: WSN, target tracking, tracking techniques, Tracking methods, face tracking