Application of IoT and Artificial Neural Networks (ANN) for Monitoring of Underground Coal Mines

Explosions in coal mines during the work time is a one of major cause of casualties in the coal mines. Thus possess a life threaten situation for coal miners. In this paper we propose a system in which sensors sense concentration of gases (Methane and carbon monoxide) in the air, measures the mine temperature and humidity and heartbeat of miner. In response it generate the alerts, and identifies the location of miners. We propose ZigBee based wireless sensor network (WSN) for communication between sensors and coal mine safety monitoring system. The iBeacons are proposed for identification of miners. A service oriented architecture (SOA) has used to develop the system. The main purpose of this research paper is to ensure miners safety, by predicting the methane has with artificial neural network (ANN). The application of ANN seems more viable than others, the calculated values shows that its prove a negligible relative error that is around 0.05.. than the actual measurements. The proposed work is then compared with the state-of-the-art methods that overcomes the limitations form the existing systems.