A Digital-Based Approach for Efficient and Reliable Bridge Inspections Using Non-Destructive Technologies

Ensuring the safety and durability of bridge infrastructure has become a critical issue in Italy, where a significant portion of the network was constructed between the 1950s and 1970s. Many of these bridges were designed based on standards and load assumptions that are now outdated. Today, they are subject to increased traffic volumes, environmental stressors, and aging-related deterioration. Despite this, traditional inspection methods—primarily based on visual assessments—are still the standard practices. While relatively simple to conduct, these inspections are often subjective, time-consuming, and dependent on the availability of specialized personnel. Moreover, they typically require partial or full road closures, leading to traffic disruptions and logistical challenges. To address these limitations, this research explores the use of digital and non-destructive surveying technologies to support and potentially enhance bridge inspection workflows. The study focuses on the integration of laser scanning, UAV-based photogrammetry, and thermographic imaging for the generation of high-resolution 3D models of bridge structures. These technologies enable the acquisition of accurate geometric data, which can be used to build accurate and updatable digital representations of physical assets. The methodology relies on a multi-sensor data acquisition strategy, followed by advanced processing techniques that include point cloud segmentation and surface extraction algorithms to identify structural elements and detect potential anomalies, such as moisture infiltration or material loss. The processed data are incorporated into a Building Information Modeling (BIM) environment and interoperable with a digital platform developed within the framework of the PIASTRE Project. This platform supports multiple data formats, allowing for the integration of semantic information and enabling long-term monitoring paving the way for the development of a Digital Twin. A historic masonry bridge was selected as a case study to demonstrate the effectiveness of the proposed approach. The results highlight the method’s potential to increase the efficiency, accuracy, and objectivity of infrastructure inspections while minimizing disruption to traffic. Ultimately, this integrated workflow represents a step forward in creating resilient, data-driven management systems for transport infrastructure.