FitSync - Comprehensive Fitness Synchronization Platform

FitSync is a holistic fitness ecosystem designed to bridge the gap between workout tracking, nutrition management, and AI-driven insights. It seamlessly integrates a cross-platform mobile application, a responsive web dashboard, a robust backend API, and advanced AI models to provide users with a personalized health experience.

🚀 Key Features

• Cross-Platform Mobile App: Built with Flutter, offering a native experience on both Android and iOS. Tracks workouts, diet, and integrates with health data.
• Web Dashboard: A React-based admin and user dashboard for detailed analytics, profile management, and visualization of fitness trends.
• AI-Powered Insights:
  • Food Clustering: Intelligent grouping of food items for better diet recommendations.
  • Workout Recommendations: AI models to suggest workouts based on user goals and history.
  • Heart Beat Analysis: Advanced analysis of heart rate data.
• Secure Authentication: Robust user management using JWT, OAuth (Google, Facebook), and Passport.js.
• Real-Time Tracking: Monitor progress with dynamic charts and logs.

🛠️ Technology Stack

FitSync utilizes a modern, full-stack architecture:

📱 Mobile (Flutter)

• Framework: Flutter SDK (Dart)
• State Management: Bloc
• Authentication: Firebase Auth, Google Sign-In
• Integrations: Health Connect, Local Notifications
• UI: Cupertino Icons, Google Fonts, Syncfusion Charts

💻 Front-End (Web)

• Framework: React.js
• Styling: Vanilla CSS, FontAwesome
• Charts: Chart.js, ApexCharts
• HTTP Client: Axios

🔙 Back-End (API)

• Runtime: Node.js
• Framework: Express.js
• Database: MongoDB (Mongoose ODM)
• Authentication: Passport.js, JWT, BCrypt
• Security: Helmet, XSS-Clean, Express-Rate-Limit

� AI & Data Science

• Language: Python
• API Framework: FastAPI
• Libraries: Pandas, Scikit-learn, NumPy, Diffusers, Transformers
• Notebooks: Jupyter for data collection and model training

📂 Project Structure

FitSync/
├── Ai/                 # AI Models, Notebooks, and FastAPI Service
│   ├── api/            # FastAPI application
│   ├── data/           # Datasets (CSV, etc.)
│   └── models/         # Trained model files
├── Back-End/           # Node.js/Express Server
│   ├── config/         # DB and App Configuration
│   ├── controllers/    # Route Logic
│   ├── models/         # Mongoose Schemas
│   └── routes/         # API Endpoints
├── Front-End/          # React Web Application
│   └── fitsync/        # React Source Code
└── Mobile/             # Flutter Mobile Application
    └── fitsync/        # Dart Source Code

🏁 Getting Started

Follow these instructions to set up the project locally.

Prerequisites

• Node.js (v16+) & npm
• Flutter SDK (v3.0+)
• Python (v3.8+)
• MongoDB (Local or Atlas URI)

1. Back-End Setup

Navigate to the backend directory and install dependencies:

cd Back-End
npm install

Create a .env file in Back-End/ and configure your variables (PORT, MONGO_URI, JWT_SECRET, etc.). Start the server:

npm start

2. Front-End Setup

Navigate to the frontend directory:

cd Front-End/fitsync
npm install

Start the React development server:

npm start

3. Mobile App Setup

Navigate to the mobile directory:

cd Mobile/fitsync
flutter pub get

Run the app on an emulator or physical device:

flutter run

4. AI Service Setup

Navigate to the AI API directory:

cd Ai/api
pip install -r requirements.txt

Start the FastAPI server:

uvicorn main:app --reload

📄 License

This project is licensed under the ISC License.