Coal Mine Safety Monitoring and Alerting System Based on Internet of Things
The increasing demand for coal in energy production and industrial applications necessitates enhanced safety measures in coal mining operations. Traditional monitoring systems in coal mines, often relying on wired communication, are susceptible to failures and inefficiencies. To address these challenges, we propose an advanced Internet of Things (IoT)-based coal mine safety monitoring and alerting system that offers real-time surveillance and proactive hazard detection. This system integrates multiple sensors, including gas detectors, temperature sensors, humidity sensors, flame sensors, and vibration sensors, interfaced with an Arduino microcontroller and an ESP01 Wi-Fi module for wireless data transmission. The data collected by these sensors are transmitted to a centralized server via the ThingSpeak platform, enabling continuous monitoring and data analysis. The proposed system is designed to detect hazardous conditions such as methane gas leaks, excessive temperatures, high humidity levels, the presence of flames, and abnormal vibrations, which are indicative of potential structural failures. When the detected parameters exceed predefined safety thresholds, the system triggers alarms and sends notifications to the miners and control room operators, ensuring timely intervention to prevent accidents. The real-time data visualization and storage on the ThingSpeak platform allow for historical data analysis and predictive maintenance, enhancing overall mine safety and operational efficiency. The system's architecture is modular and scalable, allowing for easy integration of additional sensors and expansion to cover larger mining areas. The use of wireless communication reduces the complexity and cost associated with traditional wired systems and ensures robust operation even in harsh underground environments.
Authors
- K. Uday Kumar (ORCID: https://orcid.org/0000-0003-1297-4104)
- B Bharathi
- Chitta Srikanth
- Najim Aubed Dawod
- Abrar Abdul-Hameed
- J Rakesh
Institutions
- Al-Nisour University College (IQ)
Publication Details
- Published
- 2024-12-20
- DOI
- https://doi.org/10.1109/ariia63345.2024.11051723
- Primary Topic
- Advanced Sensor and Control Systems
- Type
- article
- Field-Weighted Citation Impact
- 0.00