Keywords: bridge inspections, drones, photogrammetric 3D modelling, GIS based platforms, bridge management systems, AI driven computer vision.

Rete Ferroviaria Italiana, part of the Ferrovie dello Stato Group and the Italian railway infrastructure manager, has developed an integrated digital framework for the structural inspection of bridges, combining Unmanned Aircraft Systems, high resolution photogrammetric surveying, and advanced data processing workflows. Central to this framework is the I.O.D.A. platform, a GIS based environment designed for storing, managing, and visualizing inspection datasets, including georeferenced and metrically accurate 3D photogrammetric models generated from UAS acquisitions. The platform is continuously synchronized with InRete.2000—RFI SAP based enterprise system for managing technical, operational, and asset information—and with DOMUS, RFI Bridge Management System, ensuring standardization of defect taxonomies and full interoperability across asset management processes. Drone based surveys provide extensive high-resolution imagery that supports inspectors in detecting and documenting structural anomalies, though manual interpretation becomes increasingly demanding for complex structures. To address this challenge, RFI is developing AI enabled Computer Vision pipelines capable of automatically identifying and classifying defects according to the DOMUS catalogue, while maintaining human in the loop validation to ensure engineering accountability and diagnostic reliability. By integrating UAS derived digital twins, standardized defect ontologies, and AI driven diagnostic tools within a unified ecosystem, the framework supports a shift from condition-based assessment toward predictive, risk informed maintenance strategies, advancing the digitalization of railway infrastructure inspection.

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