AI based web application for diet planning and recipe generation

Introduces a web-based diet planning system based on machine learning, specifically Random Forests, deep learning and image processing capabilities to offer personalized nutritional input. Based on users' health data, their calorie needs, and food choices, the system is tailored to design diet plans specifically for each user. Finally, the system has functionalities of image processing capabilities: it identifies ingredients that feature in uploaded images of available food and thus comes out with recipes based on whatever is available. The goal of this integration is to make meal planning less painful, especially to individuals who have conditions like diabetes or hypertension, with respect to making healthier diets. Preliminary results demonstrate very good accuracy in recommending diets and identifying ingredients; these findings are positive toward the impact of the entire system in personalized nutrition management.

Authors

Publication Details

Journal
International Journal For Multidisciplinary Research
Published
2024-11-05
DOI
https://doi.org/10.36948/ijfmr.2024.v06i06.29919
Primary Topic
Food Industry and Aquatic Biology
Type
article
Field-Weighted Citation Impact
0.00
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article

AI based web application for diet planning and recipe generation

Pramod V. Mahajan, S. S. Waghmare, M.K. Malve, Sai Pagar - et al.
International Journal For Multidisciplinary Research
Food Industry and Aquatic Biology
article

AI based web application for diet planning and recipe generation

Pramod V. Mahajan, S. S. Waghmare, M.K. Malve, Sai Pagar -, Manisha Mali -
article en

Abstract

Introduces a web-based diet planning system based on machine learning, specifically Random Forests, deep learning and image processing capabilities to offer personalized nutritional input. Based on users' health data, their calorie needs, and food choices, the system is tailored to design diet plans specifically for each user. Finally, the system has functionalities of image processing capabilities: it identifies ingredients that feature in uploaded images of available food and thus comes out with recipes based on whatever is available. The goal of this integration is to make meal planning less painful, especially to individuals who have conditions like diabetes or hypertension, with respect to making healthier diets. Preliminary results demonstrate very good accuracy in recommending diets and identifying ingredients; these findings are positive toward the impact of the entire system in personalized nutrition management.

International Journal For Multidisciplinary ResearchVol. 6(6)
Zero hunger
Openalex Percentile: Top 76%
Food Industry and Aquatic Biology
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