Advanced IOT - Based Smart Mining Helmet with LoRa - Enabled Communication for Enhanced Safety

Abstract

This paper presents the advanced IoT-based smart mining helmet accompanying LoRa-enabled communication for enhancedsafetyancreativesafetyresolutioncreatedtopro- tect miners by mixing leading technology this Arduino-located headgear is outfitted with MQ vapor sensors a DHT11 hotness andhumiditysensoranquicksensorasignsoflifesensoran emergency fastener an LCD display and a siren alarm to steadilymonitorcriticalreferringtopracticesorpoliciesthat do not negatively affect the environment limits such as smoke aggregation temperature humidness and digger strength while detecting obstacles and falls the Lora-authorized ideas system guarantees general reliable dossier broadcast to a main moni- toring whole even in deep secret environments place common systems may be useless in dangers miners can use the panic button to transmit distress signals while certain-time voice ideas and a siren alarm allow quick alerts for next reaction the LCD display provides live rank amends and the buzzer advises of hazardstoadegreepoisonousgasuncoveringweirdpulseratesor dangerousenvironmentbyofferingevident-opportunitylistening proactive alerts and danger reaction capabilities this headgear considerably enhances laborer security and functional efficiency in perilous excavating environments.

Introduction

Mining is a highly hazardous industry due to risks like toxic gases, poor ventilation, cave-ins, and health issues. Many accidents can be prevented with better real-time monitoring and emergency response. This paper presents an IoT-based smart mining helmet designed to enhance miner safety by continuously monitoring both environmental and physiological conditions.

The helmet integrates multiple sensors: a pulse rate sensor to track heart health and detect physical stress, a gas sensor for hazardous gases like methane and carbon monoxide, and an ultrasonic sensor to detect nearby obstacles. It uses LoRa communication technology, which offers long-range, low-power data transmission suitable for underground environments where Wi-Fi and Bluetooth are unreliable.

Data collected by the helmet is sent to a central control system for real-time analysis. Alerts are triggered automatically if unsafe gas levels or abnormal heart rates are detected. Additionally, a manual emergency button allows miners to send immediate distress signals in case of sudden hazards. This comprehensive system addresses limitations of prior solutions that often lacked physiological monitoring, had limited communication range, or no manual alert mechanism.

The prototype was tested in simulated underground conditions, showing accurate detection of gas levels, heart rate abnormalities, and obstacles. LoRa communication maintained reliable data transmission up to 300 meters underground with low power consumption, enabling over 12 hours of continuous use. The smart helmet thus offers a cost-effective, scalable, and efficient solution to improve miner safety and enable rapid emergency response.

Conclusion

The Advanced IoT-Based Smart Mining Helmet provides a comprehensive solution for enhancing miner safety in under- ground environments. By integrating environmental sensors, physiological monitoring, and LoRa-enabled communication, the system ensures real-time data transmission and early detection of hazards. The inclusion of a manual emergency button further enhances the safety system, allowing miners to send distress signals in the event of an unforeseen emergency. The prototype has demonstrated high accuracy in detectinggas leaks, monitoring heart rate, and identifying proximity to obstacles, all while maintaining reliable communication over longdistances.Thissystemcanbescaledanddeployedacross mining operations to reduce accidents, improve response times, and ultimately save lives. Future work will focus on in- tegrating machine learning algorithms for predictive analysis, allowing the system to anticipate hazardous conditions based onhistorical data.Additionalsensors, suchas temperatureandvibrationsensors,couldalsobeincludedtoprovideevenmore comprehensive monitoring.

References

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Copyright

Copyright © 2025 Y. Mahesh, K. Nandhini, D. Mounisha, K. Muni Charan, M. Muni Sai. 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.