Smart Mines Helmet System

Authors

  • Aman Sahu, Ankit Kumar Singh, Atharva Singh Chouhan, Anish Singh,

Keywords:

Miner Tracking, ESP8266, DS18B20, DHT11, GPS, Flame Sensor, MQ-135, Coal Mine Safety, Smart Helmet, IoT

Abstract

Coal mines are considered one of the most dangerous working environments because miners are continuously exposed to toxic gases, poor ventilation, high temperature conditions, and unexpected fire hazards. Many accidents occur due to delayed detection of unsafe environmental conditions and the absence of real-time warning systems near workers. This paper presents an Internet of Things (IoT) based Smart Mines Helmet System that continuously monitors parameters such as temperature, humidity, toxic gas concentration, flame presence, and miner body temperature. A GPS module is integrated to provide real-time location tracking during rescue operations. Sensor readings are displayed on an LCD and uploaded to an IoT monitoring platform for remote supervision. Whenever hazardous conditions exceed safety limits, the system activates a buzzer and relay-based emergency alert mechanism and can also support ventilation through a fan system. The proposed helmet system is a low-cost, reliable, and efficient safety solution that improves worker protection and reduces accident risks in underground coal mines.

References

S. R. Rupanagudi, R. R. K. Babu, and V. G. Bhat, “IoT based smart mining safety system for underground applications,” International Journal of Advanced Research in Computer Science, vol. 8, no. 4, pp. 115–120, 2017.

Espressif Systems, “ESP8266EX Datasheet,” 2020.

Hanwei Electronics, “MQ-135 Gas Sensor Datasheet,” 2018.

Aosong Electronics, “DHT11 Temperature and Humidity Sensor Datasheet,” 2016.

u-blox, “NEO-6M GPS Module Datasheet,” 2019.

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How to Cite

Aman Sahu, Ankit Kumar Singh, Atharva Singh Chouhan, Anish Singh,. (2026). Smart Mines Helmet System. International Journal of Research & Technology, 14(2), 677–681. Retrieved from https://ijrt.org/j/article/view/1328

Issue

Section

Original Research Articles

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