The I-Helmet is an innovative, IoT-based safety helmet designed to enhance the safety of miners working in hazardous conditions. Developed as part of our final-year research project at the Sri Lanka Institute of Information Technology, this smart helmet leverages cutting-edge technologies to detect environmental hazards, monitor health parameters, and improve communication in mining sites.
This research aims to reduce the risks associated with mining accidents by providing real-time hazard detection, health monitoring, and proactive communication with control units and medical professionals.
- 🚨 Hazard Detection:
Detects falling objects, cracked walls, and wet mine areas using sensors and image processing (OpenCV). - 🌡️ Health Monitoring:
Tracks body oxygen levels, pulse rate, and temperature using advanced sensors. - 📷 Smart Camera Integration:
Uses image processing and machine learning to detect accidents and hazards. - 🌐 Telemedicine Support:
"Miner-Doc" app connects miners and doctors for real-time health monitoring. - 📡 IoT Connectivity:
Seamless communication with the central control unit using LoRa modules and Wi-Fi. - 🛑 Toxic Gas Detection:
Monitors harmful gases (CO, H2, Methane, LPG) and alerts the control unit. - 🍺 Alcohol Detection:
Identifies miners under the influence of alcohol and notifies supervisors. - 🔊 Real-Time Alerts:
Buzzers, vibrations, and LEDs alert miners to hazards immediately.
- Environmental Monitoring:
Visualize mining site conditions to prevent accidents. - Health Safety:
Detect miners' health parameters and provide hazard alerts. - Telemedicine Integration:
Enable communication between miners, doctors, and control units. - Structural Safety:
Identify cracks and wet areas in mine walls. - Hazard Alerts:
Notify miners of falling materials and other dangers in real time. - Air Quality Monitoring:
Detect and report toxic gases and employee alcohol levels.
- Hardware: LoRa Modules, NodeMCU, Raspberry Pi, Camera Module, Sensors (MQ-2, MQ-7, MQ-8, MQ-135).
- Software:
- Programming: Python, C++.
- Algorithms: OpenCV for image processing, Machine Learning for accident detection.
- Networking: IoT-based wireless networks with LoRa and Wi-Fi.
- Telemedicine: Miner-Doc web application for health communication.
- Data Visualization: Real-time dashboards for control units.
-
Hazard Detection:
- Sensors and cameras identify falling objects, structural issues, and toxic gases.
- Alerts are triggered via buzzers, vibrations, and LEDs.
-
Health Monitoring:
- Collect vital health data (oxygen levels, pulse rate, temperature).
- Share information with doctors via the Miner-Doc app.
-
Data Communication:
- LoRa modules transmit data to the control unit.
- Information is visualized on dashboards for quick decision-making.
- 👨💼 Team Leader: Gamlath G.R.G.K
- 👩💻 Team Members:
- Silva A.H.D.M
- Balasuriya D.A.M
- Rajapaksha R.P.S.C
- 🧑🏫 Supervisor: Mr. Supunya Swarnakantha
- 🧑🏫 Co-Supervisor: Dr. Anuradha Jayakody
If you use this research in your work, please cite:
@article{IHelmet2024,
author = {Gamlath G.R.G.K, Silva A.H.D.M, Balasuriya D.A.M, Rajapaksha R.P.S.C},
title = {I-Helmet: Enhancing Miner Safety with Smart Technology},
year = {2024},
institution = {Sri Lanka Institute of Information Technology},
}
This project is licensed under the MIT License. See the LICENSE file for more information.
- We extend our heartfelt thanks to our supervisors, Dr. Anuradha Jayakody and Mr. Supunya Swarnakantha, for their guidance throughout this research project.
