MUMBAI, India, Aug. 12 -- Intellectual Property India has published a patent application (202621061887 A) filed by Nutan Maharashtra Institute Of Engineering And Technology; Dr. Koteshwarrao Seelam; Veena Kiragi; Dr. Nagaratna B Chittaragi; Dr. Nandini V. Dhole; and Tushar Satish Waykole on May 15, 2026, for A Smart Iot-Enabled Machine Learning Framework For Domestic Lpg Level Estimation, Leakage Detection And Predictive Safety Alerting.
Inventors include Dr. Koteshwarrao Seelam; Veena Kiragi; Dr. Nagaratna B Chittaragi; Dr. Nandini V Dhole; and Tushar Satish Waykole.
The application for the patent was published on August 07, 2026, under issue no. 32/2026.
Abstract: The present invention relates to a smart, intelligent and integrated safety framework for domestic Liquefied Petroleum Gas (LPG) management, combining Internet of Things (IoT) technology with machine learning algorithms for real-time gas level estimation, leakage detection, risk prediction, and proactive safety alerting. The system comprises sensor modules including weight sensors, gas concentration sensors, temperature sensors, and environmental sensors interfaced with a microcontroller-based embedded unit and wireless communication modules. The collected sensor data is transmitted to a cloud-based analytics platform through IoT communication protocols for continuous monitoring and processing. The invention employs machine learning models trained on historical consumption patterns, leakage events, environmental parameters, and user behavior data to accurately estimate LPG cylinder levels, predict abnormal usage trends, identify potential leakage risks, and forecast hazardous conditions before critical thresholds are reached. The framework further integrates predictive analytics to generate early safety alerts, automatic emergency notifications, and intelligent decision support for users, gas agencies, and safety authorities through mobile applications, SMS, and web dashboards. The proposed system enables automated LPG refill prediction, preventive maintenance, real-time leakage detection, intelligent alert generation, and risk classification, thereby enhancing domestic safety, energy efficiency, and accident prevention. The invention is scalable, low-cost, energy-efficient, and adaptable to smart home environments, smart cities, and community safety infrastructures. This invention provides a novel, intelligent, and predictive safety solution for domestic LPG management by integrating IoT sensing, machine learning intelligence, and cloud-based decision systems into a unified safety framework.
Disclaimer: Curated by HT Syndication.
