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A Machine Learning-Based Application for Assessing Packaged Food Healthiness and Suggesting Healthier Alternatives

Year: 2025

Type: article

Abstract: This project focuses on developing an AI-powered platform for assessing the healthiness of packaged food products and suggesting healthier alternatives. The system scans product barcodes, extracts ingredient details, and evaluates health impact using machine learning models. The application provides real-time feedback on food quality, detecting harmful additives, excess sugars, and unhealthy fats. The AI engine then recommends better alternatives based on the user’s dietary preferences. This solution aims to enhance consumer awareness and promote healthier eating habits through AI-driven insights.

Source: Zenodo (CERN European Organization for Nuclear Research)

DOI: 10.5281/zenodo.15618187

Authors: Nakhate, Sarthak, Murme, Guruprasad, Kulkarni, Sarthak, Patil, Vishal, Chaugule, Prof. Balaji

Institution: Zeal College of Engineering and Research, Pune

Language: English

Topic: Consumer Attitudes and Food Labeling

Subfield: Public Health, Environmental and Occupational Health

Field: Medicine

Domain: Health Sciences

SDG: Zero hunger

Open Access status: green

OpenAlex ID: W6912049437

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