Intelligent control for wastewater treatment Demo Case #3 Amsterdam Netherlands Alex van der Helm Waternet Demo case 3 leader lane, for prediction of the influent flow and for determining the airflow per lane. The soft sensors are virtual sensor, whose output is based on (AI) calculation of multiple observed measurements. Next to the soft sensors an AI smart application for (near) real-time data validation is deployed. The implemented AI control model has a control objective to minimize nitrous oxide emissions and energy consumption whilst meeting effluent water quality targets. From the Amsterdam demo case it can be concluded that F4W architecture can be integrated in a water utility legacy system with AI smart applications running in (near) real-time. Furthermore it is possible to use real-time AI control for optimizing nitrous oxide emissions and energy for wastewater treatment plants in practice. The methodologies, approaches, and developed technologies in the Amsterdam West WWTP demo case present a successful baseline to guide other water utilities for future digitalization processes. The demo case has also boosted the knowledge and research about the formation and reduction of nitrous oxide emissions from WWTPs. It is therefore directly contributing to the acceleration of the twin –green and digital –transition, which is seen as a necessity in order to reach the climate goals by 2030. Back to content Back to the list scientific focus
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