A Vision-Based Collision Monitoring System for Proximity of Construction Workers to Trucks Enhanced by Posture-Dependent Perception and Truck Bodies’ Occupied Space

Abstract

In the study, an automated visualization of the proximity between workers and equipmeis developed to manage workers’ safety at construction sites using the convolutional-neural-networbased image processing of a closed-circuit television video. The images are analyzed to automaticaltransform a hazard index visualized in the form of a plane map. The graphical representation personalized proximity in the plane map is proposed and termed as safety ellipse in the study. Tsafety ellipse depending on the posture of workers and the area occupied by the hazardous objec(trucks) enable to represent precise proximity. Collision monitoring is automated with computvision techniques of artificial-intelligence-based object detection, occupied space calculation, poestimation, and homography.