ABSTRACT
Due to the high frequency of subterranean accidents, real-time capture of underground workers’ location information is critical for the safe escape and rescue of miners. A better localization strategy is needed for this. As a result, studying the node positioning algorithm in wireless sensor networks is critical for the safe production of coal mines. We present an improved entropy-based received signal strength indicator (RSSI) localization technique for finding miners in this research. To acquire a more accurate distance, a novel RSSI value correcting model (entropy-weighted model) is proposed first, and then, genetic algorithm-based localization technique is presented to determine the location of the node of interest. MATLAB® is used to simulate the suggested technique. The simulation results confirm that the proposed algorithm can reduce the impact of bad environment factors like diffraction and multipath on the positioning process and can provide higher positioning accuracy than the conventional methods, meeting the requirements of personnel location precision in underground mining networks.
