Advances in Computer Vision-Based Civil Infrastructure Inspection and Monitoring

A review of non-contact assessment of civil infrastructure using cameras and UAVs, drawing on computer vision, machine learning and structural engineering. It splits the field into inspection (component recognition, local and global damage, change detection against a reference) and monitoring (static strain and displacement, dynamic displacement for modal analysis). It frames the goal as turning raw imagery into actionable information automatically and lists what still blocks full automation.

Key findings

• Inspection methods grouped into component recognition, damage characterization, and change detection
• Monitoring methods grouped into static strain/displacement and dynamic displacement for modal analysis
• Concludes that fully automated vision-based inspection still faces several open challenges

Limitations

• Only the abstract was read here; the publisher page could not be fetched
• Review of vision methods; flight operations and regulation are not its focus