A Novel Fleet Management System in Underground Coal Mines using Internet of Things

Currently, a variety of areas use fleet management systems to organize mobility and delivery services. One of the most important technologies for subterranean fleet management is optimal path planning. Due to the intricate nature of both the drift environment and the vehicle’s structure, some modifications are necessary to accommodate the unique requirements of underground mining. This study suggests leveraging the Internet of Things (IoT) to design a fleet management system for underground coal mines. Optimal path planning is one of the key technologies for underground fleet management. Thus, IoT gives the efficient solution for finding the optimal path in underground coal mines. Moreover, the Voronoi diagram approach and its associated scenarios are the basis of the optimal path planning method, which is based on an upgraded A* (A-Star) algorithm for path planning for underground vehicles. The results are analyzed in terms of length of the path and number of examined cells for various existing algorithms along with the proposed algorithms.