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http://dx.doi.org/10.5762/KAIS.2019.20.7.622

Development on Identification Algorithm of Risk Situation around Construction Vehicle using YOLO-v3  

Shim, Seungbo (Future Infrastruture Research Center, KICT)
Choi, Sang-Il (Future Infrastruture Research Center, KICT)
Publication Information
Journal of the Korea Academia-Industrial cooperation Society / v.20, no.7, 2019 , pp. 622-629 More about this Journal
Abstract
Recently, the government is taking new approaches to change the fact that the accident rate and accident death rate of the construction industry account for a high percentage of the whole industry. Especially, it is investing heavily in the development of construction technology that is fused with ICT technology in line with the current trend of the 4th Industrial Revolution. In order to cope with this situation, this paper proposed a concept to recognize and share the work situation information between the construction machine driver and the surrounding worker to enhance the safety in the place where construction machines are operated. In order to realize the part of the concept, we applied image processing technology using camera based on artificial intelligence to earth-moving work. Especially, we implemented an algorithm that can recognize the surrounding worker's circumstance and identify the risk situation through the experiment using the compaction equipment. and image processing algorithm based on YOLO-v3. This algorithm processes 15.06 frames per second in video and can recognize danger situation around construction machine with accuracy of 90.48%. We will contribute to the prevention of safety accidents at the construction site by utilizing this technology in the future.
Keywords
Deep Learning; Image Processing; Construction Safety; Sensor; Construction Equipment;
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Times Cited By KSCI : 3  (Citation Analysis)
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