Facial Recognition Employee Tracking System

A comprehensive employee attendance and behavior monitoring system powered by facial recognition technology. This full-stack application uses AI-powered face detection to track employee attendance, monitor work hours, and generate detailed reports.

🌟 Features

• Facial Recognition Authentication: Secure login and attendance tracking using face-api.js
• Real-time Attendance Monitoring: Track employee check-ins and check-outs in real-time
• Employee Management: Complete CRUD operations for employee records
• Behavior Tracking: Monitor and analyze employee behavior patterns
• Alert System: Automated alerts for anomalies and important events
• Reports & Analytics: Generate detailed reports with charts and export to PDF
• Admin Dashboard: Comprehensive dashboard for administrators with analytics
• Real-time Updates: Socket.io integration for live updates across the system

🚀 Technology Stack

Frontend

• React 18 - Modern UI library
• Vite - Fast build tool and dev server
• React Router - Client-side routing
• Tailwind CSS - Utility-first CSS framework
• face-api.js - Face detection and recognition
• Recharts - Data visualization
• Framer Motion - Animations
• Axios - HTTP client

Backend

• Node.js - JavaScript runtime
• Express 5 - Web application framework
• MongoDB - NoSQL database
• Mongoose - MongoDB ODM
• Socket.io - Real-time bidirectional communication
• TensorFlow.js - Machine learning
• JWT - Authentication
• bcrypt - Password hashing

📋 Prerequisites

Before you begin, ensure you have the following installed:

• Node.js (v18 or higher recommended)
• npm or yarn
• MongoDB (local installation or MongoDB Atlas account)

🔧 Installation

1. Clone the repository

   git clone https://github.com/Mereyem02/reconnaissance_Faciale_Project.git
   cd reconnaissance_Faciale_Project

2. Install root dependencies

   npm install

3. Install client dependencies

   cd client
   npm install
   cd ..

4. Install server dependencies

   cd server
   npm install
   cd ..

⚙️ Configuration

1. Create environment variables file

   Create a .env file in the root directory with the following variables:

   PORT=5000
   MONGO_URI=your_mongodb_connection_string
   JWT_SECRET=your_jwt_secret_key

2. MongoDB Setup

   • For local MongoDB: Ensure MongoDB service is running
   • For MongoDB Atlas: Create a cluster and get your connection string

3. Configure Client API URL

   The client is configured to connect to http://localhost:5000/api by default. Update this in client/src/App.jsx if needed.

🚀 Running the Application

Development Mode

1. Start the server

   cd server
   npm run dev

   The server will run on http://localhost:5000

2. Start the client (in a new terminal)

   cd client
   npm run dev

   The client will run on http://localhost:5173

3. Access the application

   Open your browser and navigate to http://localhost:5173

Production Build

1. Build the client

   cd client
   npm run build

2. Preview the production build

   npm run preview

📁 Project Structure

reconnaissance_Faciale_Project/
├── client/                 # React frontend application
│   ├── public/            # Static assets
│   ├── src/
│   │   ├── components/    # Reusable React components
│   │   ├── pages/         # Page components
│   │   ├── App.jsx        # Main application component
│   │   └── main.jsx       # Application entry point
│   ├── package.json
│   └── vite.config.js
├── server/                # Express backend application
│   ├── controllers/       # Route controllers
│   ├── models/           # Mongoose models
│   ├── routes/           # API routes
│   ├── public/           # Static files (images, etc.)
│   ├── server.js         # Server entry point
│   └── package.json
├── database/             # Database related files
├── .env                  # Environment variables
├── package.json          # Root package.json
└── README.md            # This file

💡 Usage

For Administrators

1. Log in with admin credentials
2. Access the dashboard to view real-time statistics
3. Manage employees (add, edit, delete)
4. View attendance records
5. Generate and export reports
6. Configure alerts and notifications

For Employees

1. Use facial recognition to log in
2. Check in/out using the face recognition system
3. View personal attendance history
4. Track work hours

🔒 Security Features

• JWT-based authentication
• Password hashing with bcrypt
• Protected API routes
• Secure facial recognition data storage
• Environment variable configuration

🤝 Contributing

Contributions are welcome! Please feel free to submit a Pull Request.

1. Fork the repository
2. Create your feature branch (git checkout -b feature/AmazingFeature)
3. Commit your changes (git commit -m 'Add some AmazingFeature')
4. Push to the branch (git push origin feature/AmazingFeature)
5. Open a Pull Request

📄 License

This project is part of an academic/research project. Please contact the repository owner for licensing information.

👥 Authors

• Mereyem02 - GitHub Profile

🙏 Acknowledgments

• face-api.js for facial recognition capabilities
• TensorFlow.js for machine learning models
• The open-source community for various libraries and tools

📞 Support

For support, please open an issue in the GitHub repository or contact the project maintainers.

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Note: This is a facial recognition system. Ensure you comply with local privacy laws and regulations when deploying this application in a production environment.