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The Problem and Optimization of Container Cargo Loading Based on Intelligent System Under the Background of Information Technology

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2021 International Conference on Big Data Analytics for Cyber-Physical System in Smart City (BDCPS 2021)

Part of the book series: Lecture Notes on Data Engineering and Communications Technologies ((LNDECT,volume 102))

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Abstract

Under the background of the Internet, Internet of Things, cloud platform, big data and other advanced information technology means, this paper studies the cargo loading problems of the aircraft container in-depth by large air cargo transportation companies, and proposes to optimize the fixed “three principles” board operation by using the principle of “combination of light and weight, and stacking and placing” to solve the problem of waste of the container and the imbalance of aircraft load; The problem of super high edge of the board and box is solved by CAD computer aided design 3D modeling; The tracking and positioning of cargo plate is realized by RFID and GPS, which solves the problem of missing and wrong position of the container. It is expected that through the optimization design of all links of cargo loading, air cargo transportation will be safer and lower cost, and the timeliness and loading capacity of air transportation will be improved.

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Acknowledgements

Huihui Sang, Hong cai Chen, Qi xian Wu, Li min Wang and Xin yao li, five students of School of logistics management and engineering, Zhuhai University of Science and Technology, also contributed to this paper. Thank you.

Research platform and project of Guangdong Universities in 2021—Characteristic Innovation Project (Humanities and Social Sciences)—Research on cold chain logistics system of fresh products in Zhuhai-Macao cross border industrial zone.

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Correspondence to Lijin Liu .

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Liu, L. (2022). The Problem and Optimization of Container Cargo Loading Based on Intelligent System Under the Background of Information Technology. In: Atiquzzaman, M., Yen, N., Xu, Z. (eds) 2021 International Conference on Big Data Analytics for Cyber-Physical System in Smart City. BDCPS 2021. Lecture Notes on Data Engineering and Communications Technologies, vol 102. Springer, Singapore. https://doi.org/10.1007/978-981-16-7466-2_137

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