Proceedings of the 9th International Conference on Engineering Management and the 2nd Forum on Modern Logistics and Supply Chain Management (ICEM-MLSCM 2024)

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Research on the Use of UVA and Pix4D RTK Technology for Logistics Park Planning and Warehouse Management

Authors
Xiaoming Zhang1, Meng Wang2, *, Heping Liu3
1Guangzhou College of Commerce, Huangpu District, Guangzhou, Guangdong, China
2Wuhan Technology and Business University, Hongshan District, Wuhan, Hubei, China
3Jinhua Technician College, Wucheng District, Jinhua, Zhejiang, China
*Corresponding author.
Corresponding Author
Meng Wang
Available Online 1 October 2024.
DOI
10.2991/978-94-6463-531-7_27How to use a DOI?
Keywords
UVA; Pix4D RTK; Warehouse Layout; 3D Modeling
Abstract

The integration of UVA and Pix4D RTK technology with high-precision GPS positioning in logistics park planning and warehouse management has significantly propelled the process of layout optimization. By utilizing drones equipped with RTK devices, this technology enables centimeter-level precise data collection, followed by 3D reconstruction on the Pix4D software platform to generate detailed digital models of warehouses. These models serve as the foundation for analyzing existing layouts and designing improvements. Through the simulation of different shelf configurations, aisle layouts, and other strategies, managers can estimate the impact of various scenarios on inventory capacity and picking efficiency without making physical changes. The integration of AI and big data analysis into this process further guides decision-making, such as dynamically adjusting storage areas based on commodity flow data or optimizing picking routes using intelligent algorithms. After implementing optimizations, continuous RTK monitoring ensures the effective execution of the layout and timely adjustments to adapt to operational changes. In summary, Pix4D RTK technology provides a comprehensive optimization solution for warehouses, from current status assessment to implementation and post-maintenance, making it an essential tool for achieving intelligent and efficient warehouse management.

Copyright
© 2024 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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Volume Title
Proceedings of the 9th International Conference on Engineering Management and the 2nd Forum on Modern Logistics and Supply Chain Management (ICEM-MLSCM 2024)
Series
Advances in Engineering Research
Publication Date
1 October 2024
ISBN
978-94-6463-531-7
ISSN
2352-5401
DOI
10.2991/978-94-6463-531-7_27How to use a DOI?
Copyright
© 2024 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Cite this article

risenwbib
TY  - CONF
AU  - Xiaoming Zhang
AU  - Meng Wang
AU  - Heping Liu
PY  - 2024
DA  - 2024/10/01
TI  - Research on the Use of UVA and Pix4D RTK Technology for Logistics Park Planning and Warehouse Management
BT  - Proceedings of the 9th International Conference on Engineering Management and the 2nd Forum on Modern Logistics and Supply Chain Management (ICEM-MLSCM 2024)
PB  - Atlantis Press
SP  - 241
EP  - 248
SN  - 2352-5401
UR  - https://doi.org/10.2991/978-94-6463-531-7_27
DO  - 10.2991/978-94-6463-531-7_27
ID  - Zhang2024
ER  -