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@article{208361,
        author = {Sanskruti Mate and Rashmi Kumari and Yash Kalekar},
        title = {Intelligent LPG Leakage Detection and Automated Emergency Response},
        journal = {International Journal of Innovative Research in Technology},
        year = {2026},
        volume = {13},
        number = {no},
        pages = {26-36},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=208361},
        abstract = {Liquefied Petroleum Gas (LPG) leaks in residential kitchens pose serious risks, including fire accidents, explosions, property damage, and loss of life. Conventional gas leak detectors typically provide only local alarm notifications and lack automated hazard mitigation or remote emergency reporting capabilities. This paper proposes an AI-driven smart LPG leak detection and emergency response system that integrates edge computing with cloud-based monitoring. The system continuously monitors gas concentration using an MQ-2 sensor connected to a Raspberry Pi 4B and employs a rate-of-change analysis to distinguish actual gas leaks from normal environmental fluctuations. When a hazardous leak is detected, the system automatically shuts off the gas supply, activates ventilation, and transmits real-time alerts and sensor data to cloud platforms for remote monitoring. An adaptive communication strategy minimizes bandwidth consumption during normal operation while enabling high-frequency data transmission during emergencies. Experimental evaluation demonstrates rapid hazard detection, automatic physical response, and low-latency cloud notifications, highlighting the effectiveness of the proposed cyber-physical solution in improving residential kitchen safety.},
        keywords = {Internet of Things (IoT), LPG Leakage Prevention, Edge AI, Automated Regulator Valve, Raspberry Pi, Rate-of-Change Algorithm.},
        month = {September},
        }