Optimising drinking water treatment with data and modelling: An Australian perspective and future directions Dr. Edoardo Bertone (Griffith University)

It has been argued that future provision of safe drinking water supply cannot occur without significant innovation and modernisation of water quality monitoring and treatment approaches, and embracing digital solutions fit for the increasingly challenging extremes and demands. With conventional water monitoring more often supported by high-frequency in-situ sensors, there is a need to extract the highest value from these expensive, often underutilised novel monitoring tools. With machine learning and other data-driven modelling techniques finding widespread application in multiple fields, there is potential to use such high-frequency data, as well as more conventional data and other alternative sources of information, to gain a better understanding and prediction of changes in water quality and treatment processes. In this seminar, Dr. Bertone will outline a number of his relevant, recent modelling projects adding value to monitoring and treatment operations, outlining how water utilities of the future could harness the value of big data and machine learning.