Design of Coal Mine Gas Explosion Early Warning System Based on Big Data

Abstract

In the continuous updates of modern early warning technologies, traditional coal mine gas explosion early warning methods struggle to ensure data authenticity and periodicity, failing to provide real-time analysis and accurate predictions. In response to the diverse and heterogeneous characteristics of data sources in coal mine safety systems, this study combines big data technology to research and design a coal mine gas explosion early warning system. This system integrates data mining techniques, mathematical derivations, coal mine safety management, and big data analysis methods, featuring data collection, data processing, data storage, risk prediction, visual presentation, and email alerts. The system model and functional framework are provided, with detailed descriptions of the big data implementation processes for each functional module, effectively enhancing the risk prevention capabilities and decision-making efficiency of coal mine gas explosions.