IoT-based Seismic Hazard Detection in Coal Mines using Grey Systems Theory

Abstract

Internet of Things enabled applications are an amalgamation of many physical devices embedded with electronics, sensors etc. whose data can be successfully used for monitoring of nature induced hazards. One such special case of hazard is seismic hazard which is a common occurrence in underground mines. It is very hard to detect and predict and can thus be compared to an earthquake. Detection of a seismic hazard is therefore of utmost importance for a healthy mining activity. This work presents a Grey Systems theory based classification method for the detection of seismic hazard in underground mines. The proposed approach has been applied on a real life data set to verify its viability. The simulation results show that the proposed approach showcases better performance than some of the state-of-the-art machine learning techniques.