This project is a smart building management system that combines a ReactJS frontend, Flask backend, YOLOv11-powered camera integration, and ESP32-based smart outlets. The system allows administrators to manage buildings, rooms, and IoT devices, automate device control based on room occupancy, and monitor live camera feeds.

• Features
• Project Structure
• Setup Instructions
  • Backend Setup
  • Frontend Setup
  • ESP32 Device Setup
• Usage
• Troubleshooting

• Admin authentication (login/logout)
• Manage buildings, rooms, and devices
• Live camera feed and person detection (YOLOv11)
• Automated device control based on occupancy
• Real-time device status and communication

AI-hackathon/
├── backend/        # Flask API server
├── frontend/       # ReactJS client
├── embedded/       # ESP32/IoT code (optional)
├── requirements.txt
└── README.md

1. Navigate to the backend directory:

   cd backend

2. Create and activate a Python virtual environment (optional but recommended):

   python3 -m venv venv
   source venv/bin/activate

3. Install dependencies:

   pip install -r ../requirements.txt

4. Run the backend server:

   python app.py

   The backend will start on http://127.0.0.1:5000/ by default.

1. Navigate to the frontend directory:

   cd ../frontend

2. Install dependencies:

   npm install

3. Start the frontend development server:

   npm start

   The frontend will start on http://localhost:3000/ by default.

• Upload the provided code in the embedded/ directory to your ESP32 smart outlet.
• Make sure the ESP32 can reach the backend server's API endpoints over the network.

• Access the frontend at http://localhost:3000/
• Log in with the default admin credentials (admin/admin).
• Add buildings, rooms, and devices via the web interface.
• View live camera feeds and monitor device status.
• Devices will be automatically controlled based on person detection if configured.

• Ensure both backend and frontend servers are running.
• Check network/firewall settings for device communication.
• For camera/YOLO issues, verify dependencies (ultralytics, opencv-python-headless, torch, etc.) are installed.
• Use browser dev tools or backend logs for debugging errors.

For further questions, please refer to the code comments or contact the project maintainer.