Methodologies for Remote Bridge Inspection-Review

Area of Science:

• Civil Engineering
• Computer Vision
• Artificial Intelligence

Background:

• Traditional bridge inspection methods are labor-intensive and may not capture all critical data.
• The need for advanced, automated, and intelligent solutions for bridge management is growing.
• IABSE Task Group 5.9 focuses on remote inspection techniques for bridges.

Purpose of the Study:

• To present the state-of-the-art methodologies for remote bridge inspection.
• To explore the potential integration of these methods into Bridge Management Systems (BMS).
• To highlight advancements in computer vision, AI, and data handling for bridge assessment.

Main Methods:

• 3D geometric reconstruction using photogrammetry, LiDAR, and hybrid fusion.
• Damage and component identification via heuristics and Artificial Intelligence (AI).
• Non-contact measurement of displacements, strains, and modal parameters.

Main Results:

• Computer vision and AI enable detailed damage and component identification.
• Non-contact methods provide precise structural parameter measurements.
• Big Data techniques and Digital Twins are crucial for managing inspection data and asset maintenance.

Conclusions:

• These advanced methodologies enhance the safety, automation, and intelligence of bridge assessment.
• The integration of these technologies can improve the resilience and lifespan of transportation infrastructure.
• Augmented Reality (AR) offers immersive environments for effective bridge inspection.