FoodVisor: An AI-Powered Food Label Analysis System for Ingredient Interpretation and Personalized Dietary Recommendations

Authors

  • Padmapriya R Department of AI & ML, M S Ramaiah Institute of Technology, Bangalore, India. Author
  • Amoggha CH Department of AI & ML, M S Ramaiah Institute of Technology, Bangalore, India. Author
  • Ajina A Department of AI & ML, M S Ramaiah Institute of Technology, Bangalore, India. Author

DOI:

https://doi.org/10.47363/dw4wgk64

Keywords:

AI in Healthcare, Food Safety, Retrieval- Augmented Generation (RAG), LLaMA 2, Optical Character Recognition (OCR), Advanced Encryption Standard (AES-128)

Abstract

FoodVisor is an AI-powered food label analysis system that offers personalized ingredient interpretation and dietary recommendations. Users input health data securely (AES- 128 encryption), and scan product labels using OCR or barcodes. A hybrid AI model combining Retrieval-Augmented Generation (RAG) and a fine-tuned LLaMA 2 analyzes ingredients in context with user allergies and medical conditions. Integrated APIs support nutritional logging and product verification. FoodVisor also works via browser extension for online shopping, bridging ingredient transparency with personalized dietary safety through advanced NLP, OCR, and cloud deployment.

Author Biographies

  • Padmapriya R, Department of AI & ML, M S Ramaiah Institute of Technology, Bangalore, India.

    Padmapriya R,Department of AI & ML, M S Ramaiah Institute of Technology, Bangalore, India.

  • Amoggha CH, Department of AI & ML, M S Ramaiah Institute of Technology, Bangalore, India.

    Amoggha CH,Department of AI & ML, M S Ramaiah Institute of Technology, Bangalore, India.

  • Ajina A, Department of AI & ML, M S Ramaiah Institute of Technology, Bangalore, India.

    Ajina A,Department of AI & ML, M S Ramaiah Institute of Technology, Bangalore, India.

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Published

2026-01-25

Issue

Vol. 8 No. 1 (2026): Volume 8 Issue 1

Section

Articles