Part 1(1).mp4 | 999

: Recognizes if a worker is facing away or kneeling, which increases risk.

: 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. 999 Part 1(1).mp4

Because real-world collision data is dangerous and expensive to collect, researchers used a approach: : Recognizes if a worker is facing away

The video is part of a study that addresses the high rate of accidents in the construction industry. Unlike traditional sensors that fire an alarm whenever any object is near, DCAS uses a to evaluate risk dynamically based on: Unlike traditional sensors that fire an alarm whenever

: 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

: Distinguishes between workers, excavators, and forklifts.