Abstract

This paper presents GreenBite, an AI Powered web application designed to encourage consumers to make environmentally conscious food choices by conducting a real time emissions analysis of their daily food recipes. The system integrates fuzzy string matching, emissions aggregation, and a trained Random Forest regression model to predict sustainability scores dynamically. GreenBite’s fully implemented core architecture includes ingredient parsing, emissions estimation, and dynamic scoring, validated through rigorous testing with real-world recipes.This study details both the realized implementation and proposed extensions, demonstrating the promise of data-driven decision tools for sustainable food systems.

Presenters

Anjali Dubey
Student, Computer Science and Engineering, SRM Institute of Science and Technology, Tamil Nadu, India

Details

Presentation Type

Innovation Showcase

Theme

Food, Nutrition, and Health

KEYWORDS

Sustainable Food, Emissions Analysis, LCA, ML, Recipe Matching

Digital Media

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