Design and Implementation of an Intelligent Safety Helmet for Miners

Abstract

Mining environments are among the most hazardous workspaces, where rapid response and continuous monitoring can spell the difference between safety and disaster. This paper presents the design, implementation, and testing of an intelligent safety helmet equipped with a suite of sensors—including an ultrasonic sensor to verify proper usage, a temperature sensor, gyroscopic motion detection, and atmospheric sensing—as well as an integrated SOS function for emergencies. The system leverages this sensor data to alert miners and supervisory systems of dangerous conditions. Future implementations propose integrating SIM card connectivity for direct emergency communication, thus reducing response times in critical situations.

Introduction

Overview:
Mining environments are inherently hazardous due to risks like fire, toxic gases, structural collapses, and falls. Traditional helmets offer only physical protection. The proposed intelligent helmet enhances miner safety by embedding sensors to monitor environmental conditions, detect improper helmet use, and track sudden movements or falls. An SOS button allows manual emergency alerts. The system is built on Arduino and integrates hardware and software to provide real-time monitoring and alerts.

Key Components & Functions:

1. Ultrasonic Sensor: Detects if the helmet is properly worn.

2. DHT22 (Temperature & Humidity Sensor): Identifies overheating or fire hazards.

3. MQ135 (Air Quality Sensor): Monitors harmful gases.

4. MPU6050 (Gyroscope): Detects falls or abnormal motion.

5. BMP180 (Pressure Sensor): Measures underground pressure.

6. SOS Button: Manually sends emergency alerts.

7. SIM800L Module (Optional): Sends SMS alerts with sensor data.

Software Implementation:

• Built using Arduino with libraries for sensor integration and LCD display.

• Helmet Detection: Alerts user if helmet is not worn.

• Real-Time Monitoring: LCD cycles through environmental and motion data.

• Safety Alerts: If danger thresholds are exceeded (e.g., temp > 40°C, poor air), buzzer and SMS alerts are triggered.

• Emergency SOS: Sends pre-configured SOS text to a designated number.

• Includes debounce handling, visual alerts via LEDs, and modular functions for sensor data display and emergency response.

Testing & Observations:

• Helmet Fit Detection: Accurate with ultrasonic sensor.

• Environmental Monitoring: Sensors responded appropriately to simulated hazards.

• Communication: SMS-based alerts functioned reliably, though dependent on network coverage.

• Modularity: System design allows future expansion or sensor replacement.

Comparison with Traditional Helmets:

Future Enhancements:

1. Integrated SIM Card: More stable and independent emergency communication, potentially with GPS.

2. Predictive Analytics: Use of machine learning to detect patterns and predict dangers.

3. Augmented Reality (AR): Integration of AR visors for in-field hazard visualization and navigation support.

Conclusion

The intelligent safety helmet presented in this paper goes beyond traditional protective gear by integrating a comprehensive sensor suite and communication mechanisms. Through continuous monitoring of environmental and physiological data, coupled with rapid emergency alerts, the helmet aims to reduce the response time and improve miner safety under hazardous conditions. The included Arduino implementation demonstrates a viable prototype that can be refined with further testing and enhanced features such as direct SIM communication and advanced analytics.

References

[1] Kamble, A. A., Deshmukh, A. R., Gawde, S. R., KulkarnI, G. S., & Biradar, N. S.Research & Development of Safety Helmet Using Composite Materials.International Advanced Research Journal in Science, Engineering and Technology (IARJSET), 2023. [2] Akshatha, Anitha, Anusha, Prema, & Anjum, R. Smart Helmet for Safety and Accident Detection using IoT. International Research Journal of Engineering and Technology (IRJET). (Details such as volume/issue/year may be added if available.) [3] Chandran, S., Chandrashekhar, S., & Elizabeth, N. Konnect: An Internet of Things (IoT) based Smart Helmet. Proceedings of the 2016 IEEE Annual INDICON Conference. [4] World Health Organization. Helmets: A Road Safety Manual for Decision-makers and Practitioners, Second Edition. Geneva: World Health Organization, 2023. [5] William, J., Padwal, K., Samuel, N., Bawkar, A., & Rukhande, S. Intelligent Helmet. International Journal of Scientific & Engineering Research. (If available, include further details on volume, issue, and year.)

Copyright

Copyright © 2025 Ravi Kumar, Leona Dutta, Sayandeep Das, Arghya Naskar, Saumyadip Pramanik, Partha Pratim Mondal, Koushik Pal, Palasri Dhar. 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.