1(1).mp4 | 999 Part

: The study noted that moving machine parts (like an excavator's arm) can sometimes obstruct the view or cause perspective distortion, leading to slight distance errors.

Because real-world collision data is dangerous and expensive to collect, researchers used a approach: 999 Part 1(1).mp4

: Adjusts risk based on where the camera is mounted on the machine (e.g., blind spots). How the Video Was Created : The study noted that moving machine parts

: Recognizes if a worker is facing away or kneeling, which increases risk. The full research and technical details can be

The full research and technical details can be found in the article Dynamic Collision Alert System for Collaboration of Construction Equipment and Workers published in Buildings (MDPI).

: To save time, researchers used the virtual environment to automatically generate bounding boxes around objects, ensuring high precision for the AI training. Key Findings from the Research

: The video frames were used to train YOLOv7 (You Only Look Once) and Mask-RCNN models to detect objects and estimate distances accurately in real-time.