The Smart City & Infrastructure group is dedicated to researching the important role of water in cities and how it interacts with other infrastructure and urban services. We explore the benefits and challenges of data sharing in the water sector, and how digitalisation can improve the management of urban water systems.
Our main focus is on asset management of water and wastewater infrastructure. As most infrastructure networks are over a century old, utilities currently face the task of preserving their value while also meeting sustainability requirements. In addition to technological advancements, our team also addresses overlooked areas of digitalization, such as data governance, interoperability, and cybersecurity. We explore how public decisions based on artificial intelligence can be relevant, and how the quality of data used in these decisions can be ensured. Through our research, we aim to promote the safe adoption of digital solutions by public utilities and municipalities.
Overview of Core Competencies:
Researching the role of water in cities and its interaction with urban infrastructure and services
Studying the benefits and challenges of data sharing in the water sector
Exploring the potential of digitalisation for urban water management
Investigating the use of artificial intelligence in public decision-making
Asset management for ageing water and wastewater infrastructure
Addressing the blind spots of digitalization in terms of data governance, interoperability and cybersecurity
Promoting the safe adoption of digital solutions by public utilities and municipalities
Research themes
Projects
Services
Selected Publications
- Digitalisation in the Water Sector: Recommendations for Policy Developments at EU Level
- On the implementation of reliable early warning systems at European bathing waters using multivariate Bayesian regression modelling
- Digital Water City: digitale Lösungen zur Sicherstellung der urbanen Wasserversorgung in Europa
- Von Daten zu Prognosen: Neue Ansätze für die strategische Kanalsanierungsplanung
- Practical benchmarking of statistical and machine learning models for predicting the condition of sewer pipes in Berlin, Germany