Management of methane emission in coal mines using artificial neural networks: A systematic review

Abstract

Underground mines are responsible for a large number of the released methane worldwide. Our study paper can contribute to mitigating methane emissions, hence reducing the concentration about greenhouse emissions within the environment and mitigating the associated hazardous risks. In this study, more than 45 recent journals on Methane emission in Coal Mines were gathered from Web of Science, IEEE Xplore, ScienceDirect, and ResearchGate. A systematic review is accomplished of the past four years of various parts of Methane gas emission such as anthropogenic emission sources, gas emissions detection, prediction of methane using different technology and the Artificial intelligence projection model for methane emission. The outcomes reveal that since the methane emission management has obtained increasing attention over the past four years. This study also shows that big countries are using technology to control and utilize the methane emission to reduce the energy crisis. To decrease the coal mine injuries, academic understanding of underground methane management has increased, different technologies are integrated and support from various IT departments has amplified for the forecasting. In the future, the most critical task for coal mines risk assessment is to restore the worker's trust in mine safety, and the primary solution is to give more awareness to the underground management and workers through utilizing Artificial Intelligence (AI) mainly Artificial Neural Networks (ANN).