The IoT-Based Safety Helmet for Coal Mine Workers is an intelligent safety system designed to protect miners working in hazardous underground environments. The helmet is equipped with multiple sensors such as a gas sensor (MQ series) to detect harmful gases like methane and carbon monoxide, a temperature sensor to monitor heat levels, and a humidity sensor to assess environmental conditions. A vibration or fall detection sensor can also be integrated to identify accidents or worker inactivity. A microcontroller (such as ESP32) processes the sensor data and continuously monitors the worker’s surroundings. If any parameter exceeds safe limits, the system immediately alerts the worker through a buzzer or LED indicators. Simultaneously, the data is transmitted via IoT (Wi-Fi) to a remote monitoring system or web page, allowing supervisors to track workers' safety in real time. This system ensures early detection of dangerous conditions, enabling quick response and reducing the risk of accidents. It is cost-effective, energy-efficient, and highly reliable, making it suitable for improving safety standards in coal mines and other hazardous industrial environments.      

The Objectives of the project are:

• To design a smart safety helmet that continuously monitors environmental conditions in coal mines.
• To detect the presence of harmful gases such as methane and carbon monoxide using gas sensors.
• To monitor temperature and humidity levels to identify unsafe working conditions.
• To provide immediate alerts (buzzer/LED) to workers during hazardous situations.
• To implement real-time data transmission using IoT (Wi-Fi) for remote monitoring.
• To enable supervisors to track worker safety through a web-based monitoring system.
• To detect accidents or abnormal conditions (like falls or inactivity) using additional sensors.
• To reduce risks and improve safety standards in underground mining environments.
• To develop a cost-effective and energy-efficient safety solution.
• To ensure quick response and preventive action during emergencies.

      Components Used:

• Adapter Power Supply.
• ESP32 Microcontroller.
• MQ-6 sensor
• MQ-135 Sensor.
• DHT11sensor.
• Flame sensor.
• IR sensor.
• Buzzer.
• LCD display.

      Software’s used:  

1. Embedded C programming.
2. Arduino IDE for dumping code into Micro controller.
3. Express SCH for Circuit design.
4. WEB technology.

     

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