A Monitoring and Warning System for Hazards in Coal Mines using CNN and Sensor Fusion

In the realm of coal mining, safety and risk management stand as paramount challenges, underscored by the inherent perils like structural failures and the presence of hazardous gases such as methane. Recognizing the urgent need for enhanced safety measures, this paper introduces a novel system seamlessly integrating structural integrity assessment with gas concentration analysis to ascertain the warning level in coal mines. The core objective revolves around fortifying safety protocols by implementing effective monitoring and early warning systems. This multifaceted approach encompasses addressing potential hazards, preventing accidents, reducing environmental impact, and, above all, safeguarding the well-being of mine workers. The system, intertwining structural monitoring and gas concentration measurement, dynamically generates real-time risk assessments and alerts based on the integrated data. Against the backdrop of these intricate challenges, the research strives to propel substantial advancements in mining safety practices. By harnessing the capabilities of camera imagery, machine learning, and gas sensors, it envisions a future marked by elevated safety standards and a noteworthy reduction in incidents within coal mines.