Gas leakage is one of the major causes of accidents in both residential and industrial environments, posing serious risks to human life and property. To address this issue, this paper presents a gas leak detection and prevention that integrates Artificial Intelligence (AI) and the Internet of Things (IoT) for continuous monitoring and early warning. The system uses multiple sensors to detect hazardous gases such as methane, propane, and butane. The collected data is transferred to a cloud platform through IoT modules for real-time observation and analysis. An AI-based model processes this data to identify abnormal variations, predict potential leakages, and minimize false alarms. Whenever the gas concentration exceeds a safe threshold, the system alerts the user through a buzzer and automatically triggers safety mechanisms like shut-off the valves to stop the gas flow. The system enhances safety, reduces response time, and provides a cost-effective and scalable approach to preventing gas-related accidents.

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Gas Line Leakage Detection Using AI and IoT

  • H. K. Chethan,
  • N. Bhavya,
  • B. M. Divyashree,
  • N. S. Meghana,
  • V. R. Nandankumar

摘要

Gas leakage is one of the major causes of accidents in both residential and industrial environments, posing serious risks to human life and property. To address this issue, this paper presents a gas leak detection and prevention that integrates Artificial Intelligence (AI) and the Internet of Things (IoT) for continuous monitoring and early warning. The system uses multiple sensors to detect hazardous gases such as methane, propane, and butane. The collected data is transferred to a cloud platform through IoT modules for real-time observation and analysis. An AI-based model processes this data to identify abnormal variations, predict potential leakages, and minimize false alarms. Whenever the gas concentration exceeds a safe threshold, the system alerts the user through a buzzer and automatically triggers safety mechanisms like shut-off the valves to stop the gas flow. The system enhances safety, reduces response time, and provides a cost-effective and scalable approach to preventing gas-related accidents.