Federal data management: the country needs new bridges

With many bridges in Germany, the question arises: how much longer will they remain safe for traffic? Fortunately, the condition of bridges is monitored regularly and reliably. However, with around 16,000 affected bridge structures, the need for renovation is alarmingly high.

The immense backlog of renovation work that has built up over the past 30–40 years cannot be cleared so easily. Furthermore, the plans for this work are out of date and need to be adapted to new traffic conditions. The bridges can only be renovated gradually, but where to start?

In addition to the regular major inspections of bridge structures, it is essential to assess not only their current condition but also their future development, in order to avoid unforeseen restrictions, closures or demolitions. A recent example of such unannounced incidents is the A45 Rahmede viaduct in Lüdenscheid. It had to be closed immediately to all traffic at the end of 2021 because damage to the supporting structure had been detected. Four years earlier, the bridge – which had already been classified as requiring refurbishment – had been moved down the priority list.

This example illustrates just how vitally important it is to ensure accurate and up-to-date monitoring of bridge conditions. However, suitable experts are in short supply and there is a huge backlog of assessments to be cleared.

Federated data rooms help clear the refurbishment backlog

Federal data rooms can, quite literally, bridge current bottlenecks in condition monitoring and renovation planning. Materna has developed a prototype for a federal data room that can serve as a planning aid for infrastructure operators – such as motorway or rail operators – who manage bridges. It provides a valid basis for reliably determining the current condition using data and, with the aid of artificial intelligence (AI), predicting and visualising the future condition of bridges.

Materna follows a three-stage approach: in the first stage, historical structural plans and traffic flow data are combined via the data room with infrastructure-specific wear-and-tear algorithms, thereby generating a service life forecast for the bridges under consideration. The analysis of motorway bridges incorporates, in particular, data on lorry traffic – the main cause of accelerated wear and tear – as well as the load-bearing capacity index and other master data relating to the bridges. The resulting forecast provides an initial ranking of the bridges in terms of their vulnerability. In the second step, the structures at greatest risk are surveyed using camera-equipped drones, and the image data obtained is analysed using AI. The results of this analysis update the service life forecast and identify which bridges require immediate attention. Finally, in the third step, a detailed assessment is carried out by experts, or structural sensors are installed, and live monitoring is initiated to generate situational overviews and record the condition of the structures.

We can apply this approach to all built infrastructure, such as transport corridors, roads, depots or buildings. A prerequisite for this is the provision of suitable historical and current transport and infrastructure data via a federated data space.

In this blog series, we present a wide range of use cases in the field of the data economy.

Further Data Economy projects from Materna:
FreiburgRESIST – Federated data for resilient local authorities