
FitFeast – Smart Nutrition and Fitness Companion | IJCT Volume 13 – Issue 2 | IJCT-V13I2P50

International Journal of Computer Techniques
ISSN 2394-2231
Volume 13, Issue 2 | Published: March – April 2026
Table of Contents
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T. G. Ruby Angel, Shraddha
Abstract
This project introduces FitFeast, an intelligent health and nutrition application designed to provide personalized diet planning and wellness guidance using AI-driven insights. The system goes beyond traditional calorie tracking applications by integrating Body Mass Index (BMI) analysis, dietary preference customization, allergy-aware filtering, and adaptive meal recom- mendations into a unified platform. At its core, FitFeast evaluates user-specific parameters such as height, weight, age, and gender to determine optimal health metrics and caloric requirements. Based on these inputs, the system generates a balanced, nutrient- rich diet plan tailored to individual goals such as weight loss, maintenance, or weight gain. The application further enhances user experience through a dynamic food substitution mecha- nism, allowing users to replace meals with equivalent calorie alternatives while maintaining nutritional balance. A dedicated knowledge wall provides insights into food properties, calorie val- ues, and health precautions, ensuring informed dietary decisions. Additionally, FitFeast integrates a dietician consultation module, enabling users to book certified professionals for expert guidance. The inclusion of a physical activity section promotes holistic wellness by educating users on exercises such as walking, Zumba, gym workouts, and sports. Overall, the system aims to deliver a comprehensive, user-centric, and intelligent health management solution, promoting sustainable lifestyle improvements through personalized nutrition and fitness planning.
Keywords
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Conclusion
The proposed FitFeast — AI-Powered Personalized Diet and Wellness Application offers an intelligent and user- centric solution for modern health management by integrat- ing BMI analysis, calorie computation, and AI-driven diet recommendations. It delivers personalized and goal-oriented meal plans tailored to individual profiles while considering dietary preferences and allergies, ensuring both accuracy and long-term sustainability. The system also features a flexible food substitution mechanism, allowing users to modify their diets without affecting nutritional balance. To enhance user experience, FitFeast includes a knowledge wall for nutritional awareness and a dietician consultation module for expert guidance. Additionally, a physical activity module promotes a holistic approach by combining diet with fitness. Sys- tem evaluation shows that the application provides accurate, adaptable, and user-friendly recommendations with consistent performance. Future enhancements will focus on wearable device integration, advanced AI models, and expanded datasets to further improve personalization and scalability. Overall, Fit- Feast represents a promising step toward intelligent, flexible, and comprehensive digital health solutions.^
References
[1]Shraddha, “FitFeast: Smart Nutrition and Fitness Companion,” GitHub Repository, 2026. [Online] Available: https://github.com/shraddha241104/FitFeast
[2]National Library of Medicine : AI – Based Nutrition Recommendation System. [Online] Available: https://pmc.ncbi.nlm.nih.gov/articles/PMC12390980/
[3]National Library of Medicine : Optimal Diet Strategies for Weight Loss and Weight Loss Maintenance. [Online] Available: https://pmc.ncbi.nlm.nih.gov/articles/PMC8017325/
Wikipedia, “Body mass index,” [Online]. Available: https://en.wikipedia.org/wiki
How to Cite This Paper
T. G. Ruby Angel, Shraddha (2026). FitFeast – Smart Nutrition and Fitness Companion. International Journal of Computer Techniques, 13(2). ISSN: 2394-2231.
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