Abstract
In order to prevent safety accidents while walking in schools, a monitoring system using object recognition technology was developed for corridors and stairs. Using a fixed webcam and computer, the function of detecting and tracking the human body in real time and calculating the movement speed of the student was implemented. The object detection model was trained using COCO dataset and YOLOv7 network training architecture. Using the object tracking model and Python, it created an object speed estimation system through real-time video analysis. A custom model for human body detection was developed, and the accuracy of the model was mAP_0.5: 0.7387, mAP_0.5_0.95: 0.4314.
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