UAS AI-driven INSPECTion and Maintenance System for Bridge Infrastructure
The general aim of the U-AInSPECT project is to develop a UAS AI-based inspection service for bridge infrastructure in order to optimize the damage assessment for both routine surveys and/or disaster response.
This will be achieved through the following main steps:
- Definition of an operative UAS-based guideline for the inspection and mapping of bridge infrastructure in order to optimize the dataset collection and forward the monitoring survey repeatability, analysing the operative implications within the national and European UAS regulations;
- Use of innovative procedures based on artificial intelligence algorithms for semi-automated detection of selected damage classes;
- Provide a service value chain beginning with the infrastructure inspection and concluding with the fast assessment of the bridge attention class (according to the Italian Technical Guideline), serving as a basis to support proper priority planning for interventions.
Challenges and how they will be addressed
Challenge 1: Ensuring safety and efficiency in rural bridge inspections. Traditional bridge inspection methods are often time-consuming, hazardous and may be inefficient in remote rural areas where accessibility is limited. As a result, some bridges may lack proper systematic inspections, increasing the risk of undetected damage. These issues become even more critical in post-disaster response scenarios, where timely interventions are essential.
U-AInSPECT system uses UAS and AI algorithms to enable safer and faster inspections. It reduces human risks, provides reliable results in challenging environments and supports proper priority planning for interventions.
Challenge 2: Strengthening rural connectivity to enhance economic and social resilience. In rural areas, bridges are critical for local economies and daily mobility of persons and cargo; their limited redundancy makes them vulnerable to damage or disruptions.
U-AInSPECT helps keep bridges and the transportation system in good condition by supporting timely inspections and assessments. This improves mobility for people and goods, boosts the local economy, and enhances the quality of life for rural communities.
Challenge 3: Fostering consistent and reliable data collection. Varying environmental conditions related to bridge inspection often lead to difficulty in collecting consistent and proper data information.
U-AInSPECT provides guidelines for UAS-based data collection, ensuring accuracy, efficiency and repeatability in inspection results.
Tech components and data
The U-AInSPECT project involves the use of:
(i) low-cost commercial drones equipped with RGB HR cameras for capturing bridge imagery datasets
(ii) AI advanced deep learning and computer vision algorithms to analyse the collected data
(iii) web-based GIS application that allows filling the assessment form for the fast evaluation of the bridge class of attention
Expected outcomes
- Comprehensive Service Value Chain: U-AInSPECT provides a service solution for bridge infrastructure, from UAS-based inspection to fast assessment and prioritization, based on AI-powered damage detection procedures. By increasing efficiency, it strengthens rural connectivity and ensures safer transportation networks. This approach also reduces emissions, fuel consumption and costs, supporting sustainable infrastructure management in rural areas.
- Knowledge Transfer: Deliverables such as guidelines, datasets and market reports, will promote knowledge sharing, offering stakeholders valuable insights to support the enhancement of rural infrastructure.
- Demonstration: Pilot use case application, whether real or simulated, will demonstrate the system’s capabilities.
About EUCENTRE
| Full name | EUCENTRE |
| Country | Italy |
| Website | https://www.eucentre.it |
| Contact Persons | Martina Mandirola, Chiara Casarotti |
| Contact’s email | , |
Eucentre is a non-profit foundation specializing in earthquake and risk engineering. It has an important asset of experimental labs capable of reproducing seismic events for testing both structural and non-structural elements, as well as training programs in collaboration with Pavia’s universities.
As a Centre of Competence of the National Department of Civil Protection, Eucentre provides emergency support, risk scenarios, and vulnerability assessments. Additionally, Eucentre has developed an internal Drone Unit supporting structural and infrastructural assessment and post-emergency rapid mapping.
The foundation actively engages with stakeholders and partners to advance safety engineering, promote a culture of prevention, and develop tools for risk assessment, aiming to improve living conditions by enhancing safety and resilience.
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Views and opinions expressed are however those of the author(s) only and do not necessarily reflect those of the European Union or Research Executive Agency. Neither the European Union nor the granting authority can be held responsible for them.