Intelligent post-earthquake building recovery system: A framework combining BIM and deep learning
Journal
Journal of Building Engineering
Journal Volume
98
Start Page
111366
ISSN
2352-7102
Date Issued
2024-12-01
Author(s)
Abstract
Post-earthquake building recovery is always a crucial task after the strike of an earthquake. Conventionally, such building recovery is time-consuming. The availability of building information modeling (BIM) and deep learning enables the possibility of a more efficient building assessment and rehabilitation planning process. In this paper, an intelligent post-earthquake building recovery system that integrates BIM and deep learning is proposed. Deep learning is used for damage classification and recognition, while BIM provides data on all building elements to support the analyses of the building recovery process. The proposed system is expected to assist engineers in building inspection, structural element assessment, and rehabilitation planning. More specifically, the system combines the visual indicators for structural element assessment and semantic segmentation for damage area estimation to achieve damage classification, with a BIM software plug-in for building recovery plan application. Finally, a case study is presented to validate the implementation of the system framework.
Subjects
Building information modeling (BIM)
Building recovery
Deep learning
Earthquake
Recovery plan application
Publisher
Elsevier BV
Type
journal article