Proceedings of the 2024 3rd International Conference on Engineering Management and Information Science (EMIS 2024)

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The Application of Big Data in Intelligent Management of Engineering Materials under the New Situation

Authors
Xiaowei Chang1, *, Xuan Wei2
1State Grid HeBei Material Branch Corporation, No.56 Donggang Road, Yuhua District, Shijiazhuang, China
2Shijiazhuang Xibaipo Expressway Operation Center, No.160 Botanical Garden Street, Luquan District, Shijiazhuang City, China
*Corresponding author. Email: 174250931@qq.com
Corresponding Author
Xiaowei Chang
Available Online 14 July 2024.
DOI
10.2991/978-94-6463-447-1_50How to use a DOI?
Keywords
big data; Engineering materials; Intelligent management system
Abstract

With the deepening development of globalization and informatization, the scale and complexity of engineering projects are increasing day by day, and the requirements for engineering material management are also increasing. The traditional material management methods are no longer able to meet the needs of modern engineering projects, especially in the procurement, storage, transportation, and distribution of materials, facing problems such as low efficiency, high costs, and difficult to control risks.This article adopts the method of association feature mining for big data mining and optimization scheduling of engineering materials. Design an intelligent material management system in ARM and wireless networking environments. The main functional modules of the system include a database module, a program loading module, an information scheduling module, and a human-machine interaction module. Integrated development of logistics inventory intelligent management system using PCI bus technology. The system test results show that the designed intelligent management system for logistics inventory materials has good big data mining and classification recognition capabilities, and the intelligence of information management is good.

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 2024 3rd International Conference on Engineering Management and Information Science (EMIS 2024)
Series
Advances in Computer Science Research
Publication Date
14 July 2024
ISBN
10.2991/978-94-6463-447-1_50
ISSN
2352-538X
DOI
10.2991/978-94-6463-447-1_50How 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  - Xiaowei Chang
AU  - Xuan Wei
PY  - 2024
DA  - 2024/07/14
TI  - The Application of Big Data in Intelligent Management of Engineering Materials under the New Situation
BT  - Proceedings of the 2024 3rd International Conference on Engineering Management and Information Science (EMIS 2024)
PB  - Atlantis Press
SP  - 479
EP  - 488
SN  - 2352-538X
UR  - https://doi.org/10.2991/978-94-6463-447-1_50
DO  - 10.2991/978-94-6463-447-1_50
ID  - Chang2024
ER  -