Energy efficient clustering protocol for early warning system for miner's safety in coal mines

Abstract

Early detection of spontaneous explosions in coal mines can be made possible by monitoring the concentration of toxic gases such as Carbon monoxide (CO), Methane (CH4) and Hydrogen sulfide (H2S). Methane gas detection is very important for outburst prediction. In order to protect people and to avoid destructive sequence, it is necessary to design a system that can predict methane outburst in coal mines. In order to improve the reliability of gas monitoring in coal mine, we design a wireless sensor network (WSN) with gas sensors. The wireless sensor network is suitable for toxic gas monitoring in the severe environment of underground coal mines. Semiconductor type methane sensor having low power consumption and high sensitivity is used in the proposed system. The chain type clustering of low power sensor nodes along with data aggregation is devised to optimize the power consumption by the WSN. Additional feature of minimum data transmission and state transitions between listening, sleeping and transmitting modes in sensor nodes also guarantee power optimization.