DIET ADVISOR: A PERSONALIZED AIDRIVEN NUTRITION AND EXERCISE APP FOR BODYBUILDING ATHLETES

Bodybuilding athletes often face challenges in maintaining a diet that aligns with their training and performance goals. This project addresses that issue by developing the Diet Advisor app—a Flutter-based mobile application that offers personalized diet and exercise recommendations based on user profiles and daily activities. The system integrates three core components: user profiling, AI-driven recommendations, and data visualization. Key challenges included accurate data plotting, exercise tracking, and handling incomplete user profiles. These were addressed through adaptive UI design and fallback mechanisms [10]. Two experiments tested the AI's reliability in calculating BMR and generating diet plans. Results demonstrated strong accuracy and high practical value, with no significant discrepancies in BMR values and consistently high ratings for dietary recommendations. Compared to existing AI-based systems, this app provides superior precision and adaptability for bodybuilding needs [1]. Its user-friendly design and scientific basis make it a promising tool for promoting performance-oriented and sustainable nutritional practices.

Authors

Publication Details

Published
2025-07-19
DOI
https://doi.org/10.5121/csit.2025.151318
Primary Topic
Mobile Health and mHealth Applications
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

DIET ADVISOR: A PERSONALIZED AIDRIVEN NUTRITION AND EXERCISE APP FOR BODYBUILDING ATHLETES

Binh Nguyen, Hao Chen
Mobile Health and mHealth Applications
article

DIET ADVISOR: A PERSONALIZED AIDRIVEN NUTRITION AND EXERCISE APP FOR BODYBUILDING ATHLETES

Binh Nguyen, Hao Chen
article en

Abstract

Bodybuilding athletes often face challenges in maintaining a diet that aligns with their training and performance goals. This project addresses that issue by developing the Diet Advisor app—a Flutter-based mobile application that offers personalized diet and exercise recommendations based on user profiles and daily activities. The system integrates three core components: user profiling, AI-driven recommendations, and data visualization. Key challenges included accurate data plotting, exercise tracking, and handling incomplete user profiles. These were addressed through adaptive UI design and fallback mechanisms [10]. Two experiments tested the AI's reliability in calculating BMR and generating diet plans. Results demonstrated strong accuracy and high practical value, with no significant discrepancies in BMR values and consistently high ratings for dietary recommendations. Compared to existing AI-based systems, this app provides superior precision and adaptability for bodybuilding needs [1]. Its user-friendly design and scientific basis make it a promising tool for promoting performance-oriented and sustainable nutritional practices.

Openalex Percentile: Top 69%
Mobile Health and mHealth Applications
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.