• Yokesh S M
• Paveen Karthik S
• Raja Pandi R
• Raj Nitheesh A P
• Prema C

This project introduces a smart helmet system tailored for miners, aiming to ensure both safety and health monitoring in hazardous work environments. The helmet integrates multiple sensors to measure temperature, humidity, heartbeat (BPM), helmet usage status, vibration, and the presence of poisonous gases. These parameters are transmitted in real-time using the IoT platform ThingSpeak, which serves as the central hub for data collection and visualization. The collected data is further displayed on a custom web-based monitoring dashboard, allowing supervisors to track each worker's condition continuously.An option to export the data in CSV format is also provided, enabling deeper offline analysis. In particular, the heartbeat data can be used as input for a machine learning model that predicts whether a miner is at risk of heart disease. This system not only enhances the safety protocols in mining operations but also introduces predictive health analytics. By combining real-time environmental monitoring with intelligent health predictions, the solution ensures proactive decision-making and emergency readiness. This comprehensive approach helps reduce accidents and improves overall occupational well-being. Future enhancements may include mobile app integration and automated alert systems to further streamline monitoring and response

Smart Helmet, IoT, ThingSpeak, Miners' Safety, Heartbeat Monitoring, Poisonous Gas Detection, Real-time Dashboard, Machine Learning, Health Prediction, Environmental Sensing

"SMART HELMET MONITORING AND HAZARDOUS EVENT DETECTION USING MACHINE LEARNING AND IOT FOR THE MINING INDUSTRY", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.12, Issue 5, page no.a908-a916, May-2025, Available :http://www.jetir.org/papers/JETIR2505099.pdf

"SMART HELMET MONITORING AND HAZARDOUS EVENT DETECTION USING MACHINE LEARNING AND IOT FOR THE MINING INDUSTRY", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.12, Issue 5, page no. ppa908-a916, May-2025, Available at : http://www.jetir.org/papers/JETIR2505099.pdf