I will build yolo ai camera detection system with real time alerts

A Virtual Fence system uses computer vision and AI to define invisible zones in a physical environment. It detects when a person enters or stays within a restricted area and tracks their movement in real-time.

I use advanced computer vision technologies such as Python, YOLO (object detection models), OpenCV, and deep learning frameworks to build accurate and real-time detection systems.

Yes. The system is designed to detect human presence in predefined zones and track the time spent near specific machines or restricted areas in real-time.

You will need a camera system (CCTV or IP cameras) to capture video input. The AI system processes this feed in real-time. I can also help you with hardware recommendations if needed.

Yes. The solution can be integrated with existing surveillance systems or factory monitoring systems depending on your infrastructure.

Yes. The system is fully scalable and can monitor multiple zones, machines, or factory areas simultaneously with optimized performance.

Yes. The system can be configured to generate logs, alerts, and reports based on time spent in zones, entry/exit events, or custom rules.

Yes. You will receive the full Python source code along with setup instructions and documentation.

Yes. The system is optimized for real-time processing depending on your hardware capabilities (CPU/GPU).

Yes. Please contact me first so we can discuss your factory layout, camera setup, and specific monitoring requirements to ensure the best solution.