Reliable Target Tracking Model Employing Wireless Sensor Networks

The wireless sensor networks (WSN) provides advancement of number of revolutionary applications such as localization, target tracking, etc. Most of these applications involve a numerous sensor device that are connected to the base station which behaves as a gateway to connect internally and cloud computing environments. The key operation of WSNs is data collection, data sensing and transmission. However, the sensor devices gather data and is communicated over the intermediate node in an episodic manner for smart decisions periodically. Enhancing the tracking prediction accuracy, reliability of network and lifetime performance for data gathered is the important objective of target tracking applications using WSNs. This work presents Reliable Target Tracking (RTT) model employing WSNs. First, in achieving higher prediction accuracy a Modified Kalman Filter (MKF) is introduced. Second, improved cluster head (CH) selection and multi-objective-based route optimization are presented. Experiment results shows the RTT model achieves major outcome when compared with present target tracking model employing WSNs for improving energy efficiency, tracking accuracy, latency reduction and communication overhead.