IoT-BASED COAL MINE WORKER SAFETY AND ENVIRONMENT MONITORING SYSTEM WITH CLOUD ANALYTICS

Abstract: Coal mining remains one of the most hazardous occupations globally, with workers constantly exposed to toxic gas accumulation, extreme temperatures, and oxygen-deficient underground environments. Conventional safety systems rely on manual inspections and threshold-only alarms that trigger regardless of worker presence, leading to delayed responses and frequent false alarms. This work presents an IoT-Based Coal Mine Worker Safety and Environment Monitoring System that integrates real-time environmental sensing with RFID-based personnel tracking and cloud-connected analytics. The system uses the LPC1768 ARM Cortex-M3 microcontroller interfaced with an MQ135 air quality sensor, DHT11 temperature and humidity sensor, and an RC522 RFID module for worker identification. A worker-aware alerting logic activates the emergency buzzer only when hazardous thresholds are breached and at least one worker is confirmed inside the mine, eliminating false alarms during unmanned shifts. An ESP32 Wi-Fi module receives structured data from the LPC1768 over UART and publishes JSON payloads to the Zoho IoT cloud platform via MQTT over a secure TLS connection, enabling remote real-time monitoring and historical analytics. Experimental results confirm accurate multi-parameter sensing, reliable RFID-based worker tracking, and stable cloud data delivery across all tested conditions.

Keywords: IoT, LPC1768, ARM Cortex-M3, ESP32, MQ135, RFID, Zoho IoT, MQTT, Real-Time Monitoring, Coal Mine Safety.