Proceedings of International Conference on Computer Science and Communication Engineering (ICCSCE 2025)

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AI-Powered Smart Recipe Generator: A Machine Learning Approach

Authors
S. Navaneeth1, *, V. R. Pragathi1, M. Deepak1, R. Arun Kumar1
1Department of CSE, Vardhaman College of Engineering, Hyderabad, TG, India
*Corresponding author. Email: navaneethsiliveri7288@gmail.com
Corresponding Author
S. Navaneeth
Available Online 4 November 2025.
DOI
10.2991/978-94-6463-858-5_79How to use a DOI?
Keywords
SmartRecipe Generator; Machine Learning (ML); Computer Vision; Natural Language Processing (NLP); Ingredient Recognition; Automatic Recipe Generation
Abstract

Home cooking supports a healthy lifestyle, but selecting what to cook using accessible ingredients is problematic. The AI-driven Smart Recipe Generator resolves this by leveraging Machine Learning (ML), Computer Vision, and Natural Language Processing (NLP) to offer tailored recipes. Users can either enter ingredients manually or upload an image, allowing real-time recognition of ingredients from a pretrained EfficientNetV2 model. With Google AI Studio’s Gemini API, recipe suggestions are dynamically generated based on user preferences, and recipe images are generated based on the Hugging Face API.

In addition to mere recommendations, the system offers step-by-step cooking directions to maximize user experience. In contrast to traditional static recipe databases, this method adjusts according to ingredients on hand, minimizing food waste and encouraging effective meal planning. The application is developed with Flask for the backend, incorporating AI-driven ingredient categorization and text-based recipe generation. A simple and user-friendly web interface guarantees ease of access, making the system feasible for daily use.

Copyright
© 2025 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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Volume Title
Proceedings of International Conference on Computer Science and Communication Engineering (ICCSCE 2025)
Series
Advances in Computer Science Research
Publication Date
4 November 2025
ISBN
978-94-6463-858-5
ISSN
2352-538X
DOI
10.2991/978-94-6463-858-5_79How to use a DOI?
Copyright
© 2025 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Cite this article

risenwbib
TY  - CONF
AU  - S. Navaneeth
AU  - V. R. Pragathi
AU  - M. Deepak
AU  - R. Arun Kumar
PY  - 2025
DA  - 2025/11/04
TI  - AI-Powered Smart Recipe Generator: A Machine Learning Approach
BT  - Proceedings of International Conference on Computer Science and Communication Engineering (ICCSCE 2025)
PB  - Atlantis Press
SP  - 937
EP  - 949
SN  - 2352-538X
UR  - https://doi.org/10.2991/978-94-6463-858-5_79
DO  - 10.2991/978-94-6463-858-5_79
ID  - Navaneeth2025
ER  -