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FitTrack: An Intelligent Fitness Tracking and Gym Management System Using AI-Based Assistance


EOI: 10.11242/viva-tech.01.09.13

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Citation

Rudra Bandekar, Shubham Dhavane, Meet Thakur, " FitTrack: An Intelligent Fitness Tracking and Gym Management System Using AI-Based Assistance ", VIVA-IJRI Volume 1, Issue 9, Article 13, pp. 1-9, 2026. Published by Computer Engineering Department, VIVA Institute of Technology, Virar, India.

Abstract

Fitness tracking and gym member management are often handled using disconnected tools such as paper logs, spreadsheets, or basic mobile applications, leading to inconsistent records, reduced engagement, and limited personalization. This paper presents FitTrack, a full-stack web-based fitness management system that integrates membership management, workout logging, progress analytics, and chatbot-based assistance into a unified platform. The system supports role-based access for both users and administrators, enabling centralized plan management, subscription monitoring, and activity tracking. FitTrack follows a modular architecture with a React-based frontend and a Node.js/Express backend connected to a MongoDB database, ensuring scalability and maintainability. The chatbot module enhances user interaction by providing instant fitness guidance and query resolution. The system was implemented and evaluated through functional testing of core modules, including authentication, workout tracking, administrative controls, and dashboard analytics. The results demonstrate that FitTrack provides a structured and scalable solution for digital fitness management by reducing manual effort and improving accessibility to performance insights.

Keywords

- chatbot assistant, fitness tracking, gym management system, MERN stack, progress analytics, role-based access control, web application.

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