MUMBAI, India, Nov. 2 -- Intellectual Property India has published a patent application (202641124809 A) filed by Dr. A. M. Arun Mohan; Sai Prabhu K B; Dr. S. Rathika; Priyam Goswami; Dr Uc Jha; Natesan Ezhilarasi; Dr. Pardeep Kumar; and A. Suganya on October 19, 2026, for Ai-Based Household Carbon Footprint Monitoring And Personalized Sustainability Recommendation System.
Inventors include Dr. A. M. Arun Mohan; Sai Prabhu K B; Dr. S. Rathika; Priyam Goswami; Dr Uc Jha; Natesan Ezhilarasi; Dr. Pardeep Kumar; and A. Suganya.
The application for the patent was published on October 30, 2026, under issue no. 44/2026.
Abstract: ABSTRACT AI-Based Household Carbon Footprint Monitoring and Personalized Sustainability Recommendation System The present invention relates to an artificial intelligence-based household carbon footprint monitoring and personalized sustainability recommendation system designed to estimate, analyze, and reduce greenhouse gas emissions associated with domestic activities. The system integrates household energy consumption, water usage, transportation patterns, waste generation, cooking fuel consumption, and purchasing behavior to develop a comprehensive representation of household environmental impact. Data are collected through smart meters, Internet of Things sensors, utility bills, connected devices, user inputs, and compatible digital platforms. An artificial intelligence engine processes the collected information using emission factor databases, machine learning algorithms, and predictive analytics to calculate carbon dioxide equivalent emissions across different household activities. The system identifies major emission sources, detects consumption trends, forecasts potential future emissions, and evaluates the effectiveness of existing sustainability practices. Based on household characteristics, geographical location, climatic conditions, available resources, consumption habits, and user- defined preferences, the system generates personalized recommendations for reducing carbon emissions. These recommendations may include optimizing electricity usage, improving appliance efficiency, conserving water, minimizing food waste, adopting lower-emission transportation, improving waste segregation, and increasing the use of renewable energy. A dynamic recommendation mechanism prioritizes suggested actions according to estimated emission reductions, implementation costs, practical feasibility, and user preferences. An interactive dashboard presents historical trends, category-wise emission distributions, progress indicators, and projected environmental benefits. Feedback collected from users enables the system to refine recommendations and improve personalization over time. The proposed invention further supports household goal setting, sustainability challenges, notifications, and comparative performance assessments while incorporating appropriate data privacy and security measures. By combining continuous carbon footprint assessment with adaptive decision support, the invention provides an accessible, data-driven framework for promoting environmentally responsible household behavior and supporting measurable reductions in domestic greenhouse gas emissions.
Disclaimer: Curated by HT Syndication.
