ABSTRACT
This paper offers an in-depth review of a European-funded R&D project involving Minho University, the Center for Graphical Computation, and Betar, a Portuguese company specializing in asset management and bridge inspection. The project’s goal was to digitally transform Betar’s existing BMS system by integrating BIM standards, AI, and 3D technologies. Key developments included a computer vision AI for defect detection in bridges, a BIM-to-3D model conversion tool, a mobile app for efficient inspection using 3D models, a user-friendly tool for generating 3D models in the absence of BIM models, and frameworks for degradation prediction and maintenance optimization. The paper details the project’s objectives, developed tools, and main outcomes, providing a practical assessment of these tools, their operational details, and real-world applicability based on pilot tests. It also discusses the challenges faced, key learnings, and future research directions to enhance civil engineering and infrastructure maintenance.
