An intelligent drone detection system developed using Python, OpenCV, and YOLOv5 for real-time aerial object detection and monitoring. The system identifies drones from live video feeds, tracks their positions, and generates alerts when drones enter a predefined security zone.
The Advanced Drone Detection System is designed to enhance surveillance and security by automatically detecting drones in real time. The project combines computer vision and deep learning techniques to identify drone activity and provide instant visual alerts.
This system can be applied in:
- Airport and aviation security
- Military and defense monitoring
- Border surveillance
- Industrial and restricted-area protection
- Smart city security systems
- Real-time drone detection using YOLOv5
- Live video stream processing with OpenCV
- Detection confidence display
- Interactive security boundary creation
- Automatic warning alerts for intrusions
- Adjustable detection area without modifying code
- Lightweight and easy-to-use implementation
- Python
- OpenCV
- YOLOv5
- NumPy
- Pandas
- Computer Vision
- Machine Learning
- Capture live video feed from the camera.
- Process frames using OpenCV.
- Detect drones using the trained YOLOv5 model.
- Draw bounding boxes around detected drones.
- Calculate object position relative to the defined security zone.
- Trigger alerts when drones enter or approach the protected area.
git clone https://github.com/shaikayan13/advanced-drone-detection.git
cd advanced-drone-detectionpython -m venv venvWindows:
venv\Scripts\activatepip install -r requirements.txtpython Advanced_Drone_Detection.py- Launch the application.
- The webcam feed will open automatically.
- Draw a security boundary using the mouse.
- Monitor detected drones in real time.
- Receive warning notifications when drones enter the protected region.
- Press Q to exit the application.
Provides continuous drone monitoring for sensitive locations.
Reduces dependency on manual monitoring.
Instant notification when suspicious aerial activity is detected.
Users can dynamically define surveillance boundaries.
Can be extended for larger surveillance networks and smart security systems.
Uses open-source technologies to minimize deployment costs.
- Multi-drone tracking support
- Cloud-based monitoring dashboard
- Mobile application integration
- Drone classification and identification
- GPS-based alert system
- Advanced threat assessment module
advanced-drone-detection/
│
├── images/
├── models/
├── screenshots/
├── Advanced_Drone_Detection.py
├── requirements.txt
├── README.md
└── LICENSE
Shaik Ayan
GitHub: https://github.com/shaikayan13
Computer Science Engineering Student
This project is intended for educational and research purposes.