NDT-Driven Digitalization for the Optimization of Inspection and Monitoring Processes of Linear Civil Infrastructures

The management of transport infrastructure is currently undergoing a profound paradigm shift, driven by evolving regulatory frameworks that mandate a transition from reactive maintenance to proactive, predictive, and data-driven strategies. In response to these industry demands, this doctoral research proposes and implements an integrated, multi-scale workflow for the optimization of inspection and monitoring processes of linear civil infrastructures. Digitalization strategies driven by Non-Destructive Testing (NDT) are critically analyzed, focusing on the synergistic use of high-performance reality capture technologies, specifically Terrestrial Laser Scanning (TLS) and Unmanned Aerial Systems (UAS) equipped with multi-sensor payloads. The core of the proposed methodology lies in the development of a rigorous data fusion framework that merges high-fidelity geometric precision with radiometric information, significantly enhancing defect detection and material characterization. To manage the resulting massive point clouds, the workflow integrates semi-automated segmentation algorithms, implemented via the OPALS (Orientation and Processing of Airborne Laser Scanning data) modular library, which efficiently structure raw spatial data into meaningful semantic components. Subsequently, a deterministic, parametric Scan-to-BIM (Building Information Modeling) pipeline is executed. By utilizing adaptive families, the process converts unstructured survey data into intelligent, object-oriented digital models designed to serve as dynamic repositories throughout the infrastructure's lifecycle. The robustness and versatility of this methodology are validated through two distinct, real-world case studies representing diverse morphological and operational challenges. In the first application, the historic Ponte Sisto in Rome, the research extends beyond standard BIM environments by transposing the high-resolution structural model into an immersive Virtual Reality (VR) ecosystem. Leveraging a real-time rendering engine (Unity), this implementation enables a safe, remote digital inspection workflow, effectively decoupling the assessment process from physical site constraints. Conversely, the application to the Bridge of Cave addresses the critical need for standardized data interoperability. This case study demonstrates the seamless integration of open-standard models (Industry Foundation Classes - IFC) into cloud-based management platforms, functioning as a georeferenced single source of truth for continuous monitoring. Overall, the implementation of these optimized processes designed to leverage BIM and Digital Twins (DT) ensures greater objectivity in safety assessments, improves the allocation of maintenance resources, and enhances operational efficiency. Conducted during a historical period of significant digital transformation within the civil engineering sector, this research provides a scalable, rigorous foundation for advancing the industry toward the realization of fully functional Digital Twins for the national transportation network.