AI-Powered Personalized Recipe Recommendation System

  • Unique Paper ID: 206723
  • PageNo: 264-268
  • Abstract:
  • The development of an AI-powered personalized recipe recommendation system provides an intelligent and user-centric approach to simplifying everyday meal planning. This web-based platform enables users to generate customized recipes based on available ingredients, emotional mood, dietary preferences, allergies, and health goals through an interactive interface. Users can input ingredients using text or voice, while the system processes this data using artificial intelligence to generate practical, mood-aligned recipes. Secure authentication ensures personalized experiences, and user profiles maintain preferences and history for improved recommendations. The platform incorporates key modules such as ingredient processing, mood-based personalization, recipe history, favorites management, and analytics for tracking usage patterns. Implemented using React for the frontend, FastAPI for the backend, MongoDB for data storage, and Gemini AI for intelligent recipe generation, the system ensures scalability, usability, and real-time interaction. Experimental results demonstrate improved efficiency, reduced manual recipe search effort, and enhanced user satisfaction. This project contributes to smart lifestyle applications by offering a reliable, adaptive, and personalized solution for modern cooking needs.

Copyright & License

Copyright © 2026 Authors retain the copyright of this article. This article is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

BibTeX

@article{206723,
        author = {Ms. Deeksha Keshav Naik and Dr. Sandeep Bhat and Ms. Dhanya S and Ms. Disha Mahesh Shetty and Ms. Manisha Mahesh Naik},
        title = {AI-Powered Personalized Recipe Recommendation System},
        journal = {International Journal of Innovative Research in Technology},
        year = {2026},
        volume = {13},
        number = {no},
        pages = {264-268},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=206723},
        abstract = {The development of an AI-powered personalized recipe recommendation system provides an intelligent and user-centric approach to simplifying everyday meal planning. This web-based platform enables users to generate customized recipes based on available ingredients, emotional mood, dietary preferences, allergies, and health goals through an interactive interface. Users can input ingredients using text or voice, while the system processes this data using artificial intelligence to generate practical, mood-aligned recipes. Secure authentication ensures personalized experiences, and user profiles maintain preferences and history for improved recommendations. The platform incorporates key modules such as ingredient processing, mood-based personalization, recipe history, favorites management, and analytics for tracking usage patterns. Implemented using React for the frontend, FastAPI for the backend, MongoDB for data storage, and Gemini AI for intelligent recipe generation, the system ensures scalability, usability, and real-time interaction. Experimental results demonstrate improved efficiency, reduced manual recipe search effort, and enhanced user satisfaction. This project contributes to smart lifestyle applications by offering a reliable, adaptive, and personalized solution for modern cooking needs.},
        keywords = {AI-powered recipe recommendation, personalized cooking, mood-based food suggestions, ingredient-based recipes, artificial intelligence, web-based application, dietary preferences, smart meal planning.},
        month = {July},
        }

Cite This Article

Naik, M. D. K., & Bhat, D. S., & S, M. D., & Shetty, M. D. M., & Naik, M. M. M. (2026). AI-Powered Personalized Recipe Recommendation System. International Journal of Innovative Research in Technology (IJIRT), 264–268.

Related Articles

Join Our IPN

IJIRT Partner Network

Submit your research paper and those of your network (friends, colleagues, or peers) through your IPN account, and receive 800 INR for each paper that gets published.

Join Now arrowright18x

Recent Conferences

NCSEM 2024

National Conference on Sustainable Engineering and Management - 2024 Last Date: 15th March 2024

Submit inquiry arrowright18x