Waste water treatment operations will be optimised with the aim of reducing greenhouse gas emissions and energy use, and optimising treatment plant performance. (Demo Case #3). An application will be developed that validates, fuses and analyses the data from current on-line water quality sensors (e.g. phosphate, nitrate, ammonium), off-gas sensors (e.g. oxygen, nitrous oxide) and flow sensors, combined with actuators in the treatment process (e.g. valves, recirculation pumps). The analyses consist of intelligent algorithms to determine important process parameters e.g. soft sensors for oxygen uptake, respiration and nitrification rate. During the project sensors will be selected and added to the treatment plant, for that the application needs to be able to adapt to an increasing number of sensors and additional data sources to improve the performance of the algorithms. The application will need to learn the relations between process conditions, nitrous oxide emissions and energy use to propose more optimal control settings for the treatment plant based on the predicted future states, sensor and softsensor data. The display to the end-users will be developed using advanced visualisation techniques (EUT).