Position Monitoring System Based on Hierarchical Clustering

Many scenarios require continuous positioning for mobile nodes, such as mobile wireless sensor networks (MWSN), the Internet of Things (IoT), and the Internet of Vehicles (IoV). However, because the position of a mobile node is constantly changing, a lag is caused in the position information during the process of collecting position-related information. Then, a huge challenge is brought to fast and continuous positioning. To address the issue, we propose a position monitoring system (PMS) based on hierarchical clustering. First, the cross location algorithm is used as the initial positioning method, and the possible positions of targets are recorded. Then, to overcome the problem of information lag, a hierarchical clustering based PMS is proposed to predict the positions through performing information fusion and redundancy removal on existing complete data including the possible positions. Finally, a comprehensive simulation of the proposed method is carried out. The simulation results prove that our method is effective.