Research on Artificial Intelligence Based Shipping Container Loading Safety Management System


KIPS Transactions on Computer and Communication Systems, Vol. 12, No. 9, pp. 273-282, Sep. 2023
https://doi.org/10.3745/KTCCS.2023.12.9.273,   PDF Download:
Keywords: Intelligent Port Safety Technology, Shipping Container, Object Detection, Deep Learning, YOLO
Abstract

Recently, various technologies such as logistics automation and port operations automation with ICT technology are being developed to build smart ports. However, there is a lack of technology development for port safety and safety accident prevention. This paper proposes an AI-based shipping container loading safety management system for the prevention of safety accidents at container loading fields in ports. The system consists of an AI-based shipping container safety accident risk classification and storage function and a real-time safety accident monitoring function. The system monitors the accident risk at the site in real-time and can prevent container collapse accidents. The proposed system is developed as a prototype, and the system is ecaluated by direct application in a port.


Statistics
Show / Hide Statistics

Statistics (Cumulative Counts from September 1st, 2017)
Multiple requests among the same browser session are counted as one view.
If you mouse over a chart, the values of data points will be shown.


Cite this article
[IEEE Style]
K. S. Woo, O. S. Yeong, S. Y. Uk, Y. J. Hum, C. H. Jeong, Y. Joosang, "Research on Artificial Intelligence Based Shipping Container Loading Safety Management System," KIPS Transactions on Computer and Communication Systems, vol. 12, no. 9, pp. 273-282, 2023. DOI: https://doi.org/10.3745/KTCCS.2023.12.9.273.

[ACM Style]
Kim Sang Woo, Oh Se Yeong, Seo Yong Uk, Yeon Jeong Hum, Cho Hee Jeong, and Youn Joosang. 2023. Research on Artificial Intelligence Based Shipping Container Loading Safety Management System. KIPS Transactions on Computer and Communication Systems, 12, 9, (2023), 273-282. DOI: https://doi.org/10.3745/KTCCS.2023.12.9.273.