Markovian model based indoor location tracking for Internet of Things (IoT) applications

The monitoring of personnel movements, package tracking and other constructional material based tracking is a top concern in pervasive smart environment. Wireless sensor network (WSN) has given its own individuality in tracking scenario. The challenges faced in this paper deals about an effective 2-dimensional movable system tracking and finding the possible prediction of its exact location of the object in the sensing area. An indoor based WSN with wireless sensor nodes has been created, in which RSSI based location sensing methodology is used. The sensing area is classified as shells and the movement of the node is judged with markov model. The proposed algorithm is tested with various speed conditions suitable for IoT applications. Real study shows the effectiveness of the proposed two dimensional algorithms. The obtained results show minimal location error and accurate location of the object. The proposed methodology serves as the better solution for IoT applications. The proposed algorithm outperforms the existing algorithm with reduced error rate and computing iterations or complexity. A cloud enabled IoT based application is developed to location the elderly and post-surgical people. The developed application serves as a better solution for monitoring the elderly people inside the smart home environment without disturbing their privacy.