Guest Editors
Dr. Jinghao Yang
Email: jinghao.yang@utrgv.edu
Affiliation: Department of Electrical and Computer Engineering, The University of Texas Rio Grande Valley, 78539, Edinburg, United States
Homepage:
Research Interests: AI, computer vision, smart sensing
Dr. Linfeng Wu
Email: linfeng.wu@utrgv.edu
Affiliation: Department of Electrical and Computer Engineering, The University of Texas Rio Grande Valley, Edinburg, TX 78539, USA
Homepage:
Research Interests: human factor, VR, MR
Dr. Hongkai Yu
Email: h.yu19@csuohio.edu
Affiliation: Department of Electrical and Computer Engineering, Cleveland State University, Cleveland, OH 44115, USA
Homepage:
Research Interests: computer vision, image processing, machine learning, deep learning, intelligent transportation, intelligent vehicles
Summary
Artificial intelligence (AI) and computer vision (CV) are transforming the way we monitor, assess, and predict the durability of structures and systems. Real-time, non-contact, and non-destructive sensing technologies are opening new opportunities for intelligent diagnostics, early fault detection, and predictive maintenance across civil infrastructure, aerospace, automotive, manufacturing, and energy applications.
This special issue seeks original research articles, reviews, and case studies that highlight recent advances in AI- and CV-based sensing for structural durability and health monitoring. Topics of interest include (but are not limited to):
· AI-driven sensing methods for non-destructive evaluation (NDE)
· Computer-vision-based damage detection and anomaly recognition
· Multi-modal data fusion and intelligent feature extraction
· Real-time monitoring frameworks and digital twins
· Machine learning and deep learning for predictive maintenance
· Scalable, interpretable, and robust AI models for complex environments
Keywords
AI, computer vision, smart sensing
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