Real-Time Multi-Camera Crowd Density Detection and Overcrowding Alert System Using YOLO

A real-time multi-camera crowd density detection and overcrowding alert system that uses YOLO.

A real-time multi-camera crowd density detection and overcrowding alert system that uses YOLO. It is offered as a reference project: a complete, worked example of how a system like this is designed, built and evaluated, so that a developer can study it, run it and learn from it.

It suits learners who want to work with images or video: building a dataset, training or fine-tuning a vision model, measuring its performance and wrapping it in a usable tool.

The main parts are real-time processing of incoming data, alerts when a threshold or risk is reached, dataset preparation and annotation, model training or fine-tuning, and evaluation with standard metrics, plus visual examples. The reference build uses YOLO, Apache Kafka, Python, OpenCV, and PyTorch, with a clear project structure, setup instructions and sample data so that it can be run and extended.