Teaching & training

Doctoral course · 2 CFU (8 hours)

Data-Driven Technologies & Artificial Intelligence for Infrastructure Management

Docente: Prof. Giuseppe Santarsiero

This doctoral course offers an in-depth exploration of innovative, data-driven methods for infrastructure management with a specific focus on bridges. Participants analyse inspection reports through traditional engineering workflows and machine learning techniques to spot structural deficiencies and prioritise maintenance actions.

The syllabus presents cutting-edge solutions for automatically detecting degradation via deep learning applied to inspection imagery and public datasets. A core component is the use of open-source data—such as OpenStreetMap and Google Street View—to build infrastructure inventories and extract actionable features for decision support.

Real-world case studies illustrate how these methodologies assist public authorities and infrastructure managers in planning and executing resilient maintenance programmes.