Climate change, emerging pollutants and growing operational complexity are reshaping wastewater treatment. We developed a set of AI tools to support operators through better data, smarter decisions and adaptive process control.

As DARROW enters its final year, Janelcy Alferes shares insights into the data challenges in wastewater treatment and how they can be addressed in practice. From improving data availability and quality to enabling reliable AI applications, she reflects on what it takes to turn imperfect data into actionable solutions.

As DARROW enters its final year, Ruud Kassing from Haskoning reflects on what it takes to achieve secure AI integration in wastewater treatment. From connecting advanced models to real plant control systems to meeting strict cybersecurity requirements, he shares lessons on turning research pilots into deployable operational solutions.

As DARROW enters its final year, Omid Sobhani shares insights into the development of reinforcement learning for wastewater treatment control. From designing adaptive AI controllers to translating industrial constraints into learnable objectives, he reflects on what it takes to move advanced algorithms into real operational environments.

As DARROW enters its final year, Elena Torfs reflects on the shift toward holistic optimisation in wastewater treatment. From full-plant modelling and automated calibration to multi-objective decision support, she explains how reliable models enable system-wide optimisation of water quality, energy use, and emissions.

As DARROW enters its final year, Ruud Peeters from the Dommel Water Authority reflects on what it takes to implement AI in real wastewater operations. From hybrid model training with synthetic data to ambitions for plant-wide control, he shares lessons from bridging operational needs and advanced modelling.