An Efficient Approach for Multi-Target Tracking in Sensor Networks using Ant Colony Optimization

Multi-Target Tracking for Sensor Networks using Ant Colony Optimization is proposed in this paper. The proposed approach uses ant colony optimization technique that composed of both dynamic and mobile nodes. While mobile nodes are used for optimizing the target tracking, dynamic nodes ensure the total coverage of the network. As a result, the performance of the Wireless Sensor Networks with multi-target tracking on mobility nodes will improve. While improving the performance of the wireless sensor networks, automatically minimum distance will be travelled by the nodes, thereby decreasing the energy consumption of the mobility nodes. This is achieved by selecting the optimal path by searching each path of the existing network. The software should check whether any chance of collision and if it is happening, then how to avoid it by providing a minimum delay for finding the optimal path. For finding the prediction of each node to reach the optimal path different methods should be applied, like k-means and random selection. The experimental results show that Object tracking with prediction mechanism is much better than without prediction mechanism.