: Scenarios were built in Unity 3D to mimic real-world construction tasks, such as collaborative excavation.
: By using the known size of objects and camera focal lengths, the system can estimate the distance of a worker or machine within a small margin of error.
: Recognizes if a worker is facing away or kneeling, which increases risk.
: 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.
: 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 system significantly decreased the number of "nuisance" alarms compared to static sensors, as it understands when a worker or another machine is approaching safely for collaboration.
: Adjusts risk based on where the camera is mounted on the machine (e.g., blind spots). How the Video Was Created
: Distinguishes between workers, excavators, and forklifts.
: Scenarios were built in Unity 3D to mimic real-world construction tasks, such as collaborative excavation.
: By using the known size of objects and camera focal lengths, the system can estimate the distance of a worker or machine within a small margin of error.
: Recognizes if a worker is facing away or kneeling, which increases risk.
: 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.
: 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 system significantly decreased the number of "nuisance" alarms compared to static sensors, as it understands when a worker or another machine is approaching safely for collaboration.
: Adjusts risk based on where the camera is mounted on the machine (e.g., blind spots). How the Video Was Created
: Distinguishes between workers, excavators, and forklifts.
