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@article{176387,
        author = {B. Sravani},
        title = {Gas Leakage and Utilization Monitoring of LPG Cylinders Using Machine Learning and the Internet of Things (IOT)},
        journal = {International Journal of Innovative Research in Technology},
        year = {2025},
        volume = {11},
        number = {11},
        pages = {5568-5571},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=176387},
        abstract = {The use of LPG cylinders is progressively rising in India, with consumers including households and commercial establishments such as hotels, some of which also employ them for lighting purposes. Two issues may arise when utilising an LPG cylinder: leakages and monitoring gas use. A machine learning and IOT-based monitoring system has been designed to address the aforementioned issues. The consumer is unaware of the gas consumption rate for different applications and the depletion timeline of the cylinder's contents. This paper presents a machine learning and IOT-based system that monitors gas consumption past, present and future demand. To estimate the future demand by using PINN (Physics-Informed Neural Networks) algorithm based on the previous consumption history and present consumption for different gas consumption applications and notifies the consumer via SMS over a GSM-5G module. When the gas level falls below the threshold value, the system will send an alarm message to the user. A sensor known as a load cell determines the quantity of gas in the cylinder. Utilising this machine learning IOT-based monitoring system, we can mitigate gas leakage, prevent explosions, and monitor real-time gas usage, which facilitates efficient gas refills.},
        keywords = {PINN (Physics-Informed Neural Networks), LPG(Liquefied Petroleum Gas), SMS(Short Message Service), GSM (Global System for Mobile Communications)},
        month = {April},
        }