The Detection System for a Danger State of a Collision between Construction Equipment and Workers Using Fixed CCTV on Construction Sites

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According to data from the Ministry of Employment and Labor in Korea, a significant portion of fatal accidents on construction sites occur due to collisions between construction workers and equipment, with many of these collisions being attributed to worker negligence. This study introduces a method for accurately localizing construction equipment and workers on-site, delineating areas prone to collisions as 'a danger area of a collision', and defining collision risk states. Utilizing advanced deep learning models which specialize in object detection, video footage obtained from strategically placed closed-circuit television (CCTV) cameras across the construction site is analyzed. The positions of each detected object are determined using transformation or homography matrices representing the conversion relationship between a sufficiently flat reference plane and image coordinates. Additionally, 'a danger area of a collision' is proposed for evaluating equipment collision risk based on the moving equipment's speed, and the validity of this area is verified. Through this, the paper presents a system designed to preemptively identify potential collision risks, particularly when workers are located within the 'danger area of a collision', thereby mitigating accident risks on construction sites.
Publisher
MDPI
Issue Date
2023-10
Language
English
Article Type
Article
Citation

SENSORS, v.23, no.20

ISSN
1424-8220
DOI
10.3390/s23208371
URI
http://hdl.handle.net/10203/315243
Appears in Collection
CE-Journal Papers(저널논문)
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