Digitalization

We are working on the development of novel validation methodologies for decentralized water treatment systems using innovative monitoring and control concepts. The required water quality is ensured through mobile sampling and measurement stations, advanced sensor technologies, and digital cloud-based applications.

The interdisciplinary integration of process engineering and computer science opens new opportunities for efficiency improvements and process optimization in industrial applications. By combining data-driven methods with engineering expertise, complex processes can be better understood, controlled, and further developed.

The collaboration between process engineering and computer science focuses on two main areas: first, the optimization and (further) development of process-engineering operations through the identification of relevant influencing factors and the exploration of alternatives, for example in flocculation processes; second, real-time monitoring using AI, which allows, for instance, conclusions about dosing quantities based on optical floc properties.

By leveraging neural networks, additional relevant process-engineering characteristics can be identified that would not be detectable through human analysis alone (Black Box). This approach enables not only the optimization of existing processes but also the development of new products. 

The development and implementation of advanced sensor technologies and control concepts is transforming the operation of sewer networks. High-precision sensors provide real-time data on flow rates, pollutant loads, and system conditions. Based on these data, model-based control strategies can be developed and further optimized through dynamic simulations and AI-based predictions.

These approaches enable volume- and load-based regulation that prevents system overloads, improves the efficient use of treatment plants, and reduces emissions. Through pilot projects and practical partnerships, we implement the developed models in fully operational systems—delivering cost-efficient, sustainable, and climate-resilient urban drainage solutions.

In the modeling domain, the team focuses on hydrological, hydrodynamic, and hydrochemical modeling to investigate various flooding and drought scenarios as well as developments in water quality, and to derive appropriate management measures. In current R&D projects, a range of surface water, water balance, water quality, and damage potential models are applied.

Furthermore, models for sewer networks and wastewater treatment plants are developed and utilized to better capture and assess material flows, pollution peaks, and optimization potentials within the urban water cycle.

For science communication and targeted knowledge transfer, we employ media such as virtual and augmented reality, 3D printing, and WebGIS.

The IT Security Act, the KritisV ordinance, and the NIS-2 Directive legally mandate the protection of critical infrastructure across various sectors, including water supply and wastewater treatment. Since cybersecurity and resilience against outages are essential even for small- and medium-sized operators and their customers, FiW collaborates with partners to conduct a comprehensive assessment of the current state of IT security for these operators and supports the identification of necessary actions to establish a secure IT infrastructure.