Aquasuite PURE

How it works?

Aquasuite PURE uses existing sensors and instruments to gain a complete understanding of the wastewater treatment process.  It uses machine learning and external factors such as weather, public holidays, etc., to make a very accurate prediction of influent flow and load.  Aquasuite PURE additionally learns the relationships between key treatment stages such as aeration, influent flow & load and required effluent quality.

The system uses this clear oversight of the processes to become a virtual operator for the wastewater treatment plant. It uses the learnt relationships between each of the processes and the required effluent quality to provide predictive control set points for each process, based on the predicted influent flow and load.  This drives the most efficient combination of processes, whilst still achieving the required effluent quality.  Aquasuite further uses a self-learning algorithm to iteratively improve its set-point determination which, together with the AI predictions, results in very stable and energy efficient wastewater treatment.

Aquasuite collects data from numerous data sources and automatically provides control set points to assets via existing SCADA or PLC control methods.  Its aim is to be hardware agnostic and work with existing sensors, data collection and control systems.