Condition assessment of reinforced and prestressed concrete bridges using visual inspection and 3D modeling

This study explores UAV-based 3D modeling for bridge damage assessment. UAVs with high-resolution cameras captured images of two bridges at different life cycle stages and locations. These images were processed into detailed 3D models, offering more accurate evaluations than traditional visual inspections (VI). The models provided precise damage localization, geometric data information, and identified areas requiring urgent maintenance, reducing repair costs and time. Despite the advantages, challenges such as model accuracy and flight planning precision were noted. The results showed that larger and more complex bridges require significantly greater resources for 3D modeling, including longer flight and processing times, higher data volumes, and increased detail in the models, as reflected in the differences between the two case studies. Future research should focus on optimizing data acquisition, enhancing algorithms, and integrating augmented reality (AR) to improve collaboration and decision-making in bridge inspections.