An AI-powered national security and surveillance platform designed to support intelligent defence operations. PakShield Defence AI integrates multiple computer vision and deep learning modules for real-time monitoring, threat detection, anomaly identification, and strategic situational awareness.
PakShield Defence AI is a comprehensive defence intelligence system built to assist in monitoring and securing critical environments. The platform leverages artificial intelligence, computer vision, and machine learning to analyze visual data from multiple sources and detect potential threats automatically.
- Real-time surveillance and monitoring
- Border anomaly detection
- Drone detection and tracking
- Weapon detection
- Intrusion and suspicious activity identification
- AI-assisted threat analysis
- Centralized security dashboard
- Automated alert generation
Detects unusual movement and suspicious activities near restricted border zones.
Identifies unauthorized drones in restricted airspace using deep learning models.
Recognizes firearms and dangerous objects in surveillance footage.
Provides a unified interface for monitoring multiple AI modules in real time.
Instantly generates alerts when suspicious or high-risk events are detected.
- Frontend: Python CustomTkinter
- Backend: Python
- Computer Vision: OpenCV
- Deep Learning Framework: PyTorch / YOLO
- Machine Learning: NumPy, Pandas
- Visualization: Matplotlib
- Database (optional): SQLite / Supabase
PakShield_Defence_AI/
├── Backend/
│ ├── BorderAnomly/
│ │ └── drones/
│ │ └── best.pt # Download separately
│ ├── WeaponDetection/
│ └── ...
├── Frontend/
├── Assets/
├── README.md
└── requirements.txt
git clone https://github.com/fewgets/PakShield_Defence_AI.git
cd PakShield_Defence_AIpython -m venv venvWindows
venv\Scripts\activatemacOS / Linux
source venv/bin/activatepip install -r requirements.txtDue to GitHub's file size limitations, the trained drone detection model is not included in this repository.
Download the best.pt file from the following Google Drive folder:
Google Drive Link: https://drive.google.com/drive/folders/1ij55ZdL8atJGVm1cakVKcxjZ3jSrcuab?usp=sharing
After downloading, place the best.pt file in the following directory:
Backend/BorderAnomly/drones/best.pt
If the drones folder does not exist, create it manually.
python main.pyOr run the appropriate launcher file for your application.
- Border surveillance and intrusion detection
- Military base perimeter security
- Restricted airspace drone monitoring
- Weapon threat detection in sensitive zones
- Smart city security and public safety
- Critical infrastructure protection
- Multi-camera distributed monitoring
- Thermal imaging integration
- Facial recognition for watchlist detection
- Predictive threat analytics
- Cloud-based deployment
- Mobile monitoring application
- Real-time incident reporting
Contributions are welcome. To contribute:
- Fork the repository
- Create a feature branch
- Commit your changes
- Push to your branch
- Open a Pull Request
This project is intended for educational, research, and innovation purposes.
Please contact the author for commercial or defense-related deployment permissions.
Usama Shahid
- GitHub: https://github.com/fewgets
- Email: shaikhusama541@gmail.com
This repository does not include large trained model files (.pt, .pth, etc.) due to GitHub storage restrictions.
Please download the required model files from the provided Google Drive link and place them in their designated directories before running the project.
Special thanks to the open-source community and the developers of:
- PyTorch
- OpenCV
- YOLO
- CustomTkinter
Their tools and frameworks make projects like this possible.