Proceedings of the International Conference on Intelligent Systems and Digital Transformation (ICISD 2025)

Design and Implementation of a Smart Safety Helmet for Mining Workers

Authors
M. Anitha Mary1, *, C. Swetha1, S. Sanjana1
1Department of Electronics and Communication Engineering, Rajalakshmi Engineering College, Chennai, 6000, India
*Corresponding author. Email: anithamary.m@rajalakshmi.edu.in
Corresponding Author
M. Anitha Mary
Available Online 31 October 2025.
DOI
10.2991/978-94-6463-866-0_14How to use a DOI?
Keywords
Coal Mining Safety; IoT; Real-Time Monitoring; Smart Helmet; Hazard Detection; Emergency Response; Worker Protection
Abstract

Coal miners encounter significant dangers because of the challenging conditions they face underground, necessitating strong safety protocols. This endeavour introduces a Smart Safety Helmet powered by IoT, with Arduino serving as the primary controller, designed for instant monitoring and emergency notifications. The setup combines an infrared sensor for identifying the helmet’s presence, an inertial measurement unit sensor for detecting falls, a gas sensor for recognising dangerous gases, and a DHT11 sensor for assessing temperature and humidity levels. A GPS module provides accurate location tracking, facilitating swift rescue operations. The helmet features an alert system that includes a buzzer and an emergency button, which triggers a solenoid valve to dispense oxygen. For its communication capabilities, the system employs ESP8266-based IoT connectivity that interfaces with ThingSpeak for cloud data updates, Bluetooth for auditory notifications, and LoRa for long-distance communication back to a centralised control centre. The helmet underwent evaluations in a controlled setting to measure sensor efficiency, dependability of data transmission, and responsiveness in emergencies. The findings indicated that it effectively detected hazards, provided timely warnings, and maintained dependable communication. The emergency button reliably initiated oxygen release, proving to be beneficial in critical incidents. In summary, the Smart Safety Helmet considerably improves the safety of coal miners through ongoing surveillance, prompt notifications, and proactive measures. The combination of various sensors and communication methods guarantees real-time hazard management and quick reactions, diminishing the likelihood of workplace incidents in perilous situations.

Copyright
© 2025 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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Volume Title
Proceedings of the International Conference on Intelligent Systems and Digital Transformation (ICISD 2025)
Series
Atlantis Highlights in Intelligent Systems
Publication Date
31 October 2025
ISBN
978-94-6463-866-0
ISSN
2589-4919
DOI
10.2991/978-94-6463-866-0_14How to use a DOI?
Copyright
© 2025 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Cite this article

TY  - CONF
AU  - M. Anitha Mary
AU  - C. Swetha
AU  - S. Sanjana
PY  - 2025
DA  - 2025/10/31
TI  - Design and Implementation of a Smart Safety Helmet for Mining Workers
BT  - Proceedings of the International Conference on Intelligent Systems and Digital Transformation (ICISD 2025)
PB  - Atlantis Press
SP  - 137
EP  - 151
SN  - 2589-4919
UR  - https://doi.org/10.2991/978-94-6463-866-0_14
DO  - 10.2991/978-94-6463-866-0_14
ID  - Mary2025
ER  -