Artificial Intelligence for Structural Health Monitoring, Inspection, Maintenance, and Rehabilitation of Civil Infrastructure
A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Civil Engineering".
Deadline for manuscript submissions: 20 April 2025 | Viewed by 78
Special Issue Editors
Interests: structural health monitoring; computer vision; deep learning
Special Issues, Collections and Topics in MDPI journals
Interests: reinforced concrete; vibration-based structural system; machine learning; AI
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
Recently, artificial intelligence, especially machine learning, deep learning, computer vision, and large-scale models, has inspired novel progress and revolutional advances in structural health monitoring, inspection, maintenance, and rehabilitation. Advancements of full-field high-resolution sensing, multi-scale contextual modeling and digital twin, cascade inference in cyber space, accurate and robust recognition of multi-type damage and change, reasonable evaluation and credible assessment of structural condition, autonomous decision-making of maintenance strategies, swarm intelligence and human–machine–thing synergetic interaction, as well as various multi-modal large-scale models and high-effectiveness learning algorithms, greatly enhance the domain knowledge discovery, embedding, and intelligent applications for structural health diagnosis and performance improvement in a data–model–knowledge fusion-driven manner. This Special Issue aims to provide a platform to share current scientific original research and engineering technical applications of the related topics.
Dr. Yang Xu
Dr. Yasutaka Narazaki
Dr. Vedhus Hoskere
Guest Editors
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Keywords
- data, feature, and decision fusion of multi-source sensing data
- universal time-series analysis for singal generation, reconstruction, and assessment
- generalized vision-based damage recognition and change measurement
- intelligent structural 3D modeling, rendering, mapping, and updating
- learning-based feature extraction and pattern recognition for damage diagnosis
- data, model, and knowledge fusion-driven intelligent computing and inference
- multi-modal large-scale model-based navigation, inspection, and interaction agent
- autonomous decision making for intelligent maintenance and rehabilitation
- intelligent Internet-of-Thing and system intergration for industry applications
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