Fire Guard AI / Yapay Zeka Yangın Tespit Sistemi

Fire Guard AI is an advanced fire and smoke detection system designed to provide 24/7 protection using real-time computer vision and artificial intelligence.

Fire Guard AI, gerçek zamanlı görüntü işleme ve yapay zeka kullanarak 7/24 koruma sağlayan ileri seviye bir yangın ve duman tespit sistemidir.

Features / Özellikler

Dashboard / Kontrol Paneli

Real-time multi-camera monitoring and event notification panel.

• Real-Time Detection: Instant fire and smoke detection using the YOLOv8 AI model.
• Multi-Camera Support: Monitor unlimited cameras (Webcam, RTSP, IP Camera) simultaneously in a grid view.
• Background Service: Continuous protection running in the background, even when the web interface is closed.

Notification Settings / Bildirim Ayarları

E-posta Ayarları	Telegram Ayarları

Event History / Geçmiş Kayıtları

Detailed list of past events and snapshots.

• Instant Notifications:
  • Telegram: Receive real-time photos of the detected event directly to your phone.
  • Email: Detailed incident reports sent to your inbox.
• Stats & History: Daily/Weekly charts and a searchable archive of past events with snapshots.
• Easy Management: User-friendly interface to manage cameras and configure notification settings.

Tech Stack / Teknolojiler

• Backend: Python, FastAPI, OpenCV, Ultralytics (YOLOv8), SQLite
• Frontend: Next.js, React, Tailwind CSS, Recharts
• AI Model: Custom trained YOLOv8 for Fire & Smoke

Installation / Kurulum

Follow these steps to run the project locally. / Projeyi yerel makinenizde çalıştırmak için aşağıdaki adımları izleyin.

Prerequisites / Ön Gereksinimler

• Python 3.9+
• Node.js 18+
• Git

1. Clone the Repository / Projeyi Klonlayın

git clone https://github.com/vahapogut/AI-fire-detection.git
cd AI-fire-detection

2. Backend Setup / Backend Kurulumu

The backend handles video processing and AI inference.

cd backend
# Create virtual environment (Recommended)
python -m venv venv
# Activate on Windows:
venv\Scripts\activate
# Activate on Mac/Linux:
# source venv/bin/activate

# Install dependencies
pip install -r requirements.txt

# Start the server
python main.py

Backend runs at http://localhost:8000 by default.

cd frontend
# Install packages
npm install

# Start the application
npm run dev

Frontend runs at http://localhost:3000 by default.

Usage / Kullanım

1. Open http://localhost:3000 in your browser.
2. Click Add Camera to add a source:
   • For Webcam: 0 or 1
   • For IP Cam: rtsp://user:password@ip_address:554/stream
3. Go to Settings to configure Telegram and Email credentials.
4. The system is now active! It will alert you upon detecting fire or smoke.

Contributing / Katkıda Bulunma

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

License / Lisans

Distributed under the MIT License. See LICENSE for more information.

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Developer: Abdulvahap Öğüt