IOT Based Coal Mine Safety Monitoring and Alerting Smart Helmet

Abstract

\"Coal mining remains one of the most hazardous occupations, with workers exposed to numerous safety threats such as toxic gases, high temperatures, low visibility, and potential structural collapses. This research presents the design and development of a smart helmet aimed at enhancing coal mine safety through real-time environmental monitoring and communication capabilities. The helmet integrates sensors for gas detection (e.g., methane, carbon monoxide), temperature and humidity monitoring, and an accelerometer for fall or impact detection. It also features wireless data transmission to alert supervisors in case of abnormal conditions or emergencies. The proposed system seeks to minimize risk and improve response times during incidents, contributing to a safer mining environment. Experimental validation in simulated mining conditions demonstrates the system\'s effectiveness and reliability.

Introduction

The project aims to improve coal mine worker safety by developing a smart helmet system that detects hazardous conditions such as flammable gases (LPG), high temperature, moisture, and pressure inside mine tunnels. Detectors mounted on the helmet communicate real-time data wirelessly via WiFi to a control room, enabling immediate alerts and emergency responses. Each helmet also features an emergency button for workers to request help instantly.

Background:
Coal mining is a highly dangerous occupation with risks from gas explosions, poor visibility, and physical hazards. Traditional helmets primarily protect against impacts, but modern safety helmets are evolving to include smart technologies like gas sensors, wireless communication, GPS tracking, and biometric monitoring to enhance safety.

Technological Components:

• ESP32 microcontroller: Core unit managing data collection and wireless communication.

• Gas Detector (MQ-3): Detects flammable and toxic gases.

• Temperature & Moisture Sensor (DHT11): Monitors environmental conditions.

• Pressure Sensor (BMP180): Measures atmospheric pressure and altitude.

• GSM/GPS Module (AI-Thinker A9): Enables communication and location tracking.

• Rechargeable Battery: Powers the system with efficient energy use.

System Architecture:
The helmet continuously monitors environmental parameters and sends alerts via WiFi to a remote control room when unsafe conditions arise. An alarm sounds within the mine for evacuation. The system is designed to be compact and wearable for mass production.

Results & Future Directions:
Testing confirmed effective real-time detection, reliable data transmission, and prompt alerts. Future improvements include integrating AI and machine learning for predictive hazard analysis, more sensitive compact sensors, longer-lasting power solutions such as energy harvesting, and enhanced ergonomic design for comfort and daily usability.

Conclusion

\"The development of a smart safety helmet for coal miners significantly improves workplace safety by integrating real- time monitoring, hazard discovery, and wireless communication. Equipped with detectors similar as gas sensors, temperature and moisture detectors, stir detectors, and pressure detectors, the helmet continuously monitors the mining terrain and provides instant cautions in case of peril. The objectification of IoT technology and data analytics enhances prophetic conservation and threat assessment, farther reducing the chances of accidents.\"

References

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Copyright

Copyright © 2025 Harshada R. Rokade, Priyanka G. Ghagre, Vaibhav M. Mandade. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.