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Project | DZW

Duration:

Digital twin in water resource management

Being able to guarantee unrestricted access to fresh drinking water is generally taken for granted. However, the appearance of clean water is deceptive - climate change and urbanization in particular are putting enormous strain on natural resources. Demographic and societal changes, political targets regarding wastewater treatment or energy-related CO2 emissions from water supply are also among the many new challenges facing the water industry. Water utilities face similar issues. Variables such as size, population density, types of uses, topology of the service area, and different water and wastewater network structures all influence the issues.

The object of this research project is the development of pilot projects in which, with the help of experience-based methods and suitable forecasting and simulation models, the complex processes in the water sector can be made more resource-efficient and resilient to storms in the future. Based on this, digital twins are being developed that can be used to address the various problems in the field of water management.

Partners

Hochschule Trier (Umweltcampus Birkenfeld) – Trier University of Applied Sciences (Environmental Campus Birkenfeld)

Publications about the project

  1. Towards Machine Learning-based Digital Twins in Cyber-Physical Systems

    Felix Theusch; Lukas Seemann; Achim Guldner; Stefan Naumann; Ralph Bergmann

    In: Gianfranco Lombardo; Marco Picone; Diego Reforgiato Recupero; Giuseppe Vizzari (Hrsg.). Proceedings of The First Workshop on AI for Digital Twins and Cyber-Physical Applications (AI4DT&CP). IJCAI Workshop on AI for Digital Twins and Cyber-Physical Applications (AI4DT&CP-2023), located at IJCAI International Joint Conference on Artificial Intelligence 2023, August 19, Macao, Macao, CEUR, 2023.

Sponsors

Ministerium für Klimaschutz, Umwelt, Energie und Mobilität Rheinland-Pfalz