MUMBAI, India, Sept. 7 -- Intellectual Property India has published a patent application (202641104199 A) filed by Mlr Institute Of Technology; and Marri Laxman Reddy Institute Of Technology And Management on August 29, 2026, for Greenscore – A Real-Time Personal Carbon Footprint And Sustainability Scoring System.
Inventors include Dr. P. Subhashini; Mr. Gorli Mahesh; Mr. K. Sravan; and Mr. M. Sai Teja.
The application for the patent was published on September 04, 2026, under issue no. 36/2026.
Abstract: The present invention discloses GreenScore, a real-time personal carbon footprint estimation and sustainability scoring system that quantifies individual environmental impact through machine learning-based analysis of user lifestyle data and delivers actionable behavioral recommendations to support carbon emission reduction. The system ingests user-provided data spanning residential electricity consumption, motor vehicle fuel usage, air travel activity, dietary patterns, and consumer purchasing behaviour, and subjects these inputs to a structured preprocessing and feature engineering pipeline. A supervised ensemble regression model, trained on established emissions factor datasets and stratified lifestyle survey data, processes the extracted feature vectors to generate estimated carbon emission values expressed in kilograms of carbon dioxide equivalent. These emission estimates are subsequently normalized against population-level benchmarks to produce a Green Score—a standardized sustainability index ranging from zero to one hundred—that enables intuitive, relative interpretation of individual environmental performance. An integrated explainability module employing SHAP-based attribution analysis decomposes each user's Green Score into its constituent behavioral contributions, ensuring transparency and supporting informed user decision-making. A personalized recommendation engine maps high-impact behavioral features to a curated knowledge base of carbon-reduction strategies, generating ranked, context-sensitive suggestions tailored to each user's unique activity profile. The system is implemented using Python and associated scientific computing libraries, with relational database support for longitudinal data persistence, and is designed for scalability and modular extensibility. The invention advances individual environmental awareness, promotes evidence-based behavioral change, and contributes to the realization of United Nations Sustainable Development Goal 13 on Climate Action.
Disclaimer: Curated by HT Syndication.
