| Issue |
E3S Web Conf.
Volume 347, 2022
2nd International Conference on Civil and Environmental Engineering (ICCEE 2022)
|
|
|---|---|---|
| Article Number | 01011 | |
| Number of page(s) | 10 | |
| Section | Infrastructure and Building Construction | |
| DOI | https://doi.org/10.1051/e3sconf/202234701011 | |
| Published online | 14 April 2022 | |
Application of building information modeling and damage detection technology in disaster recovery and reconstruction
1 Department of Civil Engineering, Construction Engineering and Management Division, National Taiwan University, Taipei, Taiwan
2 Department of Building, Civil & Environmental Engineering, Concordia University, Montreal, Canada
* Corresponding author: d09521030@ntu.edu.tw
In the post-disaster recovery and reconstruction phase, building assessment is a very important first step in the process of repairing damaged buildings. In practices, the building assessment still needs building visual inspection and manual analysis which requires a lot of energy and time. Various emerging technologies in the construction sector that can be used to solve problems, for example: Building Information Modeling (BIM), image processing, artificial intelligence. The study aims to review the application of BIM and damage detection technology in postdisaster buildings assessment process. Furthermore, the study focuses more specifically on review of the technology application related to BIM and artificial intelligence for damage detection on crack or concrete spalling in post-disaster recovery and reconstruction. The framework of the automatic integration of damage detection technology and BIM was developed as a way to generate retrofitting designs automatically based on field inspection and building information in post-disaster recovery and reconstruction.
© The Authors, published by EDP Sciences, 2022
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.