PREMIUM Project 2026-2027: Atos

Design a forward-looking Digital Twin concept that combines AI, geospatial, environmental and maintenance data to help Rijkswaterstaat predict infrastructure deterioration, prioritise interventions and manage critical Dutch infrastructure more proactively, safely and sustainably.
  • atos

    The Project:

    Can artificial intelligence predict infrastructure issues before they become visible? Can weather conditions, water levels, oxidation and corrosion, maintenance history, geographic data, and satellite observations be combined to make infrastructure safer and more resilient?

    Rijkswaterstaat, one of Atos’ accounts, manages thousands of critical infrastructure assets, including bridges, tunnels, locks, roads, and waterways. A wealth of information is available through maintenance systems, GIS platforms, inspection reports, environmental data, and operational monitoring. However, these data sources are often fragmented and primarily used retrospectively. 

    Reliable infrastructure is essential for mobility, public safety, economic activity, and climate resilience. Unexpected asset failure can lead to major societal disruptions and significant financial consequences. Due to aging infrastructure and increasing climate-related pressures, asset managers require better methods to detect degradation early, assess risks, and prioritize interventions. A smarter, predictive maintenance approach can improve availability, extend asset lifespans, support sound investment decisions, and ensure the more effective use of public resources. 

    We challenge students to design a forward-looking Digital Twin concept that integrates data from enterprise asset management systems (such as Ultimo), Esri GIS platforms, inspection records, environmental sources, satellite observations, and AI models into an intelligent decision-support environment. Together with Atos, you will explore how such a new generation of Digital Twins can support predictive maintenance for the critical Dutch infrastructure managed by Rijkswaterstaat.

    The project explores how AI, geo-intelligence, weather data, water levels, oxidation and corrosion, satellite observations, and other factors can support predictive maintenance and earlier, better-informed interventions.

    The project results will serve as strategic input for future initiatives regarding digital twins and predictive maintenance within Rijkswaterstaat and similar infrastructure-intensive organizations. We intend to use the students' recommendations to identify opportunities for innovation, define conceptual architectural principles, and assess how operational, environmental, geospatial, and maintenance data can be combined within a future asset management ecosystem. The results should provide Rijkswaterstaat with a concrete basis for evaluating potential use cases, identifying gaps in data and skills, and selecting promising applications for further validation. The findings can subsequently serve as a foundation for proofs of concept or pilot projects.

    You will work on a socially relevant issue at the intersection of artificial intelligence, geo-technology, sustainability, infrastructure, and public administration. Through bi-weekly sessions with experienced professionals, you will develop a concept that offers Rijkswaterstaat new perspectives on the future of predictive asset management.

    The intended final product of this project is a coherent and visually compelling conceptual blueprint for a 360-degree Digital Twin. It encompasses a vision for the future, an overview of the relevant data ecosystem, priority use cases for predictive maintenance, conceptual architectural principles, and a pragmatic roadmap for experimentation or validation. The final product must be sufficiently concrete to generate genuine value for Rijkswaterstaat, while allowing students the freedom to propose unexpected technologies, analytical methods, and forms of presentation.

    Apply your creativity, challenge existing assumptions, and help shape the future of how critical infrastructure is monitored and maintained.
     

  • The Client:

    Atos is a European technology company that supports governments and operators of critical infrastructure in their digital transformation. We help organizations leverage data, artificial intelligence, cloud technology, and digital twins to enhance their resilience, sustainability, and operational performance. In the Netherlands, Atos collaborates with public and regulated organizations to address complex challenges in the areas of infrastructure, mobility, energy, and digital sovereignty. Our focus extends beyond technology alone; we translate innovation into practical solutions that create societal value, strengthen decision-making, and contribute to the reliable, secure, and sustainable long-term management of critical national infrastructure.

    We are looking for students who feel comfortable dealing with complex and open-ended issues, and are interested in the intersection of technology, public infrastructure, and societal impact. Curiosity, creativity, critical thinking skills, and the ability to translate diverse disciplinary perspectives into a single, coherent concept are more important than prior technical experience. 
    The PREMIUM students will receive active guidance during bi-weekly working sessions with Atos professionals. We challenge the students to link technological possibilities with concrete needs in the areas of infrastructure and asset management. The students retain considerable freedom to determine the direction of the approach, methodology, and the final form of the solution.
  • design oriented

    In this project, the focus is on “creating something new”


     
    Co-Creator Client

    This client might join the team for brainstorm sessions, meetings, and preparatory sessions. The co-creator is more actively involved in/during the project execution.