Abstract: Gas leakage incidents pose significant risks to human safety, property, and industrial environments due to the possibility of explosions, toxic exposure, and fire hazards. Traditional gas detection methods rely on manual monitoring and standalone alarms, which lack remote alerting capabilities and real-time environmental monitoring. With the advancement of Internet of Things (IoT) technologies, intelligent gas detection systems can be developed to provide continuous monitoring, automated alerts, and remote supervision.
This paper proposes a Gas Leakage Detection System using IoT, an intelligent embedded monitoring solution designed to detect hazardous gas concentrations and environmental variations while providing instant user notifications. The system integrates ESP32 as the core IoT controller, MQ-2 and MQ-135 gas sensors for detecting combustible and harmful gases, a DHT11 sensor for temperature and humidity monitoring, and SIM800L GSM module for SMS-based alert communication. Power management is handled using dual 3.7 V batteries and LM2596 voltage regulator to ensure stable system operation.
The proposed system continuously monitors gas concentration levels and environmental parameters. When abnormal conditions are detected, the ESP32 triggers local alerts and transmits SMS notifications to predefined users, enabling rapid response. Experimental implementation demonstrates improved safety monitoring, real-time alerting capability, energy-efficient operation, and cost-effective deployment. The proposed IoT-based Gas Leakage Detection System provides a reliable and scalable solution suitable for residential, industrial, and commercial safety applications.
Keywords: Gas Leakage Detection, IoT Safety System, ESP32, MQ-2 Sensor, MQ-135 Sensor, DHT11, SIM800L GSM, Embedded Monitoring, Hazard Detection, Smart Safety System.
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DOI:
10.17148/IARJSET.2026.13255
[1] Deepak M, Mr. R. Kalaichelvan, "GAS LEAKAGE DETECTION SYSTEM USING IoT," International Advanced Research Journal in Science, Engineering and Technology (IARJSET), DOI: 10.17148/IARJSET.2026.13255