AI-Powered Smart Diet and Workout Assistant

In the current digital health ecosystem, users often rely on multiple fragmented applications for food tracking, nutrition analysis, and fitness planning, leading to poor user experience, limited personalization, and reduced adherence. This project proposes an AI-Powered Smart Diet and Workout Assistant, a unified web-based platform that integrates diet planning, calorie tracking, recipe generation, and workout recommendations into a single, personalized system. Users securely register, set health goals, and receive tailored plans based on their profiles, with AI-driven food recognition from images or text inputs, nutritional estimation, and deep learning models for diverse cuisines. Built with HTML/CSS/JS frontend, Node.js backend, MongoDB, and TensorFlow, it features progress dashboards, quizzes, and motivational tools. The system enhances engagement, consistency, and long-term health outcomes by minimizing app fragmentation and delivering intelligent, interactive fitness support.

Authors

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2026-01-01
DOI
https://doi.org/10.5281/zenodo.19216770
Primary Topic
Nutritional Studies and Diet
Type
article
Field-Weighted Citation Impact
0.00
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article

AI-Powered Smart Diet and Workout Assistant

T.Manoj, S.Abilesh, K.Karthick, Mrs. P. Valarmathi
Zenodo (CERN European Organization for Nuclear Research)
Nutritional Studies and Diet
article

AI-Powered Smart Diet and Workout Assistant

T.Manoj, S.Abilesh, K.Karthick, Mrs. P. Valarmathi
article en

Abstract

In the current digital health ecosystem, users often rely on multiple fragmented applications for food tracking, nutrition analysis, and fitness planning, leading to poor user experience, limited personalization, and reduced adherence. This project proposes an AI-Powered Smart Diet and Workout Assistant, a unified web-based platform that integrates diet planning, calorie tracking, recipe generation, and workout recommendations into a single, personalized system. Users securely register, set health goals, and receive tailored plans based on their profiles, with AI-driven food recognition from images or text inputs, nutritional estimation, and deep learning models for diverse cuisines. Built with HTML/CSS/JS frontend, Node.js backend, MongoDB, and TensorFlow, it features progress dashboards, quizzes, and motivational tools. The system enhances engagement, consistency, and long-term health outcomes by minimizing app fragmentation and delivering intelligent, interactive fitness support.

Zenodo (CERN European Organization for Nuclear Research)
Zero hunger
Openalex Percentile: Top 11%
Nutritional Studies and Diet
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