Practical example and current challenges
- The infrastructure is a central part of our daily life: on the way to work, shopping or on holiday. How long a bridge or railway line lasts, for example, when it has to be renewed and what effects this has on the flow of traffic leads to discussions and displeasure, especially, in the summer months. It often depends on the type of communication and increasingly on the reliability of the data collected to prove the necessity and timing of the repair.
- Building and infrastructure owners, such as federal, district and city administrations, Deutsche Bahn AG or Autobahn GmbH, invest in collecting data on the current and future condition of their facilities.
- Currently, building reports and photo data are mostly stored in different IT systems and data-bases without interfaces to each other. They are not subject to any further evaluation with regard to type, scope or costs. Service and maintenance recommendations are derived from the reports, but weather and environmental data are only considered rudimentarily.
- The latest innovations, such as drone flights or sensor measurements, provide additional and more detailed information on the condition of the infrastructure. They are currently being carried out in pilot projects based on individual orders. However, these data are also stored in various IT systems, usually without interfaces to the building inspection data.
- The evaluation of the condition progression and operating time of the structure remains manual, time-consuming and associated with high costs, which leads to inefficiency and long planning, tendering and maintenance periods.
- It is estimated that more than 20% of the buildings/ constructions represent risks and major challenges for the responsible administrations due to their condition and age. Various innovative technologies (drones, sensors, lasers) do not offer a consolidated database or predictive maintenance strategies in isolation. A cloud-based digital platform for predictive maintenance of the transport infrastructure, such as InfraX, could be a remedy here. It could also be an important component of the German government's traffic turnaround and digitisation strategy.
- InfraX creates digital twins (as virtual replicas of physical assets) of infrastructure structures. InfraX does not collect its own data, but systematically consolidates data from different sources and thus helps the responsible authorities and administrations in their daily work.
- All input data (such as building inspection reports, photos, sensor or laser data) are assigned to the digital and predictive twin of each building. As a result, users can perform their own simulations and receive precise recommendations based on automated prediction and evaluation of the structures and their remaining lifetimes.
What added value does the "GAIA-X project" offer?
- GAIA-X provides a high level of data security, from which the InfraX user groups benefit.
- GAIA-X's embedded compliance and privacy features are inherent features of InfraX.
- GAIA-X can break lock-in effects; this will have a positive effect on the acceptance and attractiveness of InfraX and its user groups.
- The data migration and interaction of AI frameworks between different clouds will lead to healthy competition.
- Different software modules are available within GAIA-X, which can be used in compatible releases for different developments of AI frameworks.
Use Case Team
- Armida Hemeling – Goduni International GmbH
- Prof. Dr. Michael Gertz, University Heidelberg
- Stefan Weingaertner, LandesCloud GmbH