
Computer Vision and AI in Structural Health Monitoring and Structural Engineering
Woodhead Publishing
Will be published approx. on 1. May 2026
Book
Paperback/Softback
250 pages
978-0-443-45022-8 (ISBN)
Description
In an era of aging infrastructure and an increasing demand for safety, structural health monitoring (SHM) has become critical for ensuring the longevity and reliability of buildings, bridges, and other essential structures. Computer Vision and AI in Structural Health Monitoring and Structural Engineering explores cutting-edge approaches to SHM, integrating advancements in computer vision, artificial intelligence (AI), and multimodal technologies to revolutionize how infrastructure is monitored, maintained, and managed. Starting with the fundamentals of SHM and structural engineering, the book examines the transformative power of computer vision applications, such as crack detection, corrosion assessment, and real-time deformation analysis. It also introduces vision-language models (VLMs), enabling automated defect reporting, multimodal analysis, and natural language interfaces for SHM systems.
More details
Series
Language
English
Place of publication
United States
Publishing group
Elsevier - Health Sciences Division
Target group
Professional and scholarly
Product notice
Paperback (trade)
Unsewn / adhesive bound
Dimensions
Height: 275 mm
Width: 219 mm
Thickness: 8 mm
Weight
544 gr
ISBN-13
978-0-443-45022-8 (9780443450228)
Copyright in bibliographic data and cover images is held by Nielsen Book Services Limited or by the publishers or by their respective licensors: all rights reserved.
Schweitzer Classification
Other editions
Additional editions

Cheng Liu | Yingchao Zhang Msc | Xuebing Xu Msc
Computer Vision and AI in Structural Health Monitoring and Structural Engineering
E-Book
04/2026
Elsevier
€178.99
Available for download
Persons
Dr. Liu received his PhD from the Department of Mechanical Engineering at Stanford University and an M.Sc. in Aeronautics and Astronautics, also from Stanford University. Cheng Liu's research is focused on physics-guided machine learning for structural health monitoring (SHM), smart structures, cyber-physical systems/digital twin, robotic tactile sensing and the mechanics of composite structures. His recent research includes the fusion of data-driven and physics-based methods for SHM to improve its robustness and explainability, so that SHM can really be widely applied in real-world scenarios Yingchao Zhang is currently pursuing a PhD degree in Systems Engineering at the City University of Hong Kong. He received his bachelor's and master's degrees in civil engineering from Shandong University. His main research interest is in intelligent detection of transport infrastructure Xuebing Xu is currently pursuing a PhD degree in Systems Engineering at the City University of Hong Kong. He received his bachelor's and master's degrees from Huazhong University of Science and Technology. His main research includes the development and application of vision language models and large language models Yan Chen is currently pursuing a PhD degree in Systems Engineering at the City University of Hong Kong. He received his bachelor's from the National University of Defense Technology, China, and a masters degree from the City University of Hong Kong. His main research includes the development and application of deep learning and large language models
Author
City University of Hong Kong, Hong Kong
City University of Hong Kong, Hong Kong
City University of Hong Kong, Hong Kong
City University of Hong Kong, Hong Kong
Content
Part I: Fundamentals
1. Introduction
2. Basic Concepts
Part II: Computer Vision in SHM
3. Computer Vision Fundamentals
4. CV Applications in Construction
Part III: Vision-Language Models
5. Foundation of Vision-Language Models
6. VLM Applications
Part IV: Implementation and Evaluation
7. Evaluation Metrics
8. Data Collection and Management
Part V: Advanced Topics
9. Automation Systems
10. AI and Machine Learning
Part VI: Practical Considerations
11. Implementation Guidelines
12. Case Studies
Part VII: Future Directions
13. Emerging Technologies
14. Research Opportunities
1. Introduction
2. Basic Concepts
Part II: Computer Vision in SHM
3. Computer Vision Fundamentals
4. CV Applications in Construction
Part III: Vision-Language Models
5. Foundation of Vision-Language Models
6. VLM Applications
Part IV: Implementation and Evaluation
7. Evaluation Metrics
8. Data Collection and Management
Part V: Advanced Topics
9. Automation Systems
10. AI and Machine Learning
Part VI: Practical Considerations
11. Implementation Guidelines
12. Case Studies
Part VII: Future Directions
13. Emerging Technologies
14. Research Opportunities