Application and Prospect of Computer Vision Technology in Engineering Management

DOI

10.2991/978-94-6239-652-4_3How to use a DOI?

Keywords

Computer Vision; Civil Engineering Management; Structural Health Monitoring; Smart Construction Site; Application Challenges

Abstract

As a key technology to simulate human visual perception, computer vision technology is playing an increasingly important role in civil engineering management. In this study, the application of computer vision technology in engineering management is systematically reviewed with typical cases. On the basis of a brief description of the eight core tasks of computer vision technology, the application effects of this technology in typical engineering projects such as buildings, bridges, roads, tunnels and dams are emphasized, and the important role of this technology in intelligent construction and smart construction sites is elaborated. Although computer vision technology shows good application effects, it still faces a series of problems such as technical bottlenecks, economic challenges and social risks in its large-scale application and promotion. With the continuous development of artificial intelligence technology, computer vision technology will provide greater drive to improve the quality and efficiency of engineering management.

Copyright

© 2026 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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TY  - CONF
AU  - Kangchao Shu
PY  - 2026
DA  - 2026/04/19
TI  - Application and Prospect of Computer Vision Technology in Engineering Management
BT  - Proceedings of the  2026 5th International Conference on Engineering Management and Information Science (EMIS 2026)
PB  - Atlantis Press
SP  - 17
EP  - 26
SN  - 2352-538X
UR  - https://doi.org/10.2991/978-94-6239-652-4_3
DO  - 10.2991/978-94-6239-652-4_3
ID  - Shu2026
ER  -