Fitmate
Year: 2025
Type: dissertation
Abstract: FitMate - Your Personal AI Fitness Companion The research paper presents FitMate, an AI-driven chatbot designed to provide personalized fitness and nutrition guidance. The paper discusses how artificial intelligence is transforming digital health by offering tailored workout and diet recommendations, previously accessible only through personal trainers and nutritionists. Key Highlights: Problem Statement: There is a lack of affordable and truly personalized fitness apps that consider user-specific needs like BMI, dietary preferences, and workout goals. Objective: FitMate is developed to bridge this gap by utilizing AI, web development, and NLP to create a chatbot capable of real-time fitness coaching. Methodology: The system integrates OpenAI’s GPT-4 model to generate intelligent workout and diet plans based on user inputs such as weight, height, age, and fitness goals. System Architecture: Frontend: Built using HTML and Tailwind CSS for a responsive design. Backend: Developed with Node.js and Express, handling user queries and API communication. AI Integration: Uses GPT-4 for generating personalized fitness advice. Error Handling & Scalability: Ensures smooth operation through input validation, API failure handling, and future database integration (MongoDB). Results & Findings: High User Engagement: Users actively interacted with FitMate for BMI calculations and fitness advice. Accurate BMI Calculation: Achieved 100% accuracy in BMI classification, helping users receive suitable recommendations. Diet Plan Effectiveness: 75% of users adhered to the personalized diet plans, with improvements in protein and vegetable consumption. Scalability Potential: The system can be expanded to integrate with wearable devices and store user history for enhanced personalization. Conclusion & Future Scope: FitMate demonstrates AI’s potential in revolutionizing fitness management by making personalized health guidance affordable and accessible. Future improvements include real-time health tracking, AI-powered progress monitoring, and expansion of fitness databases. This research contributes to the growing field of AI-powered fitness coaching, showcasing how AI-driven chatbots can enhance health, fitness adherence, and user engagement.
Author: tiwari, Jatin
Language: English
Subfield: Health Information Management
Field: Health Professions
Domain: Health Sciences
Open Access status: green
OpenAlex ID: W6949494231
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