Construction and Application Analysis of Information Model for Automotive Industry Test Equipment
- DOI
- 10.2991/978-94-6463-264-4_90How to use a DOI?
- Keywords
- Test equipment data; Information model; Edge collection
- Abstract
Experimental data is an important resource for detecting and evaluating the performance and safety of automobiles. The current experimental equipment has a wide variety of data types and a large amount of data, which can be effectively managed and used through information models. Therefore, this article focuses on the field of automotive testing, dividing test equipment data into equipment, projects, results, and controls, and abstracting the categories, attributes, and association relationships of the data to construct an automotive test equipment information model. Based on this model, XML language is used to define semantic standards, which are applied to edge gateways to achieve semantic conversion and format encapsulation of collected data, ensuring the standardization and uniformity of test equipment data, Lay the foundation for the application of experimental data.
- 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
TY - CONF AU - Jun Zhu AU - Jia Zhao AU - Yang Liu AU - Ran Bo PY - 2023 DA - 2023/09/28 TI - Construction and Application Analysis of Information Model for Automotive Industry Test Equipment BT - Proceedings of the 2023 3rd International Conference on Education, Information Management and Service Science (EIMSS 2023) PB - Atlantis Press SP - 780 EP - 787 SN - 2589-4900 UR - https://doi.org/10.2991/978-94-6463-264-4_90 DO - 10.2991/978-94-6463-264-4_90 ID - Zhu2023 ER -