Achieving Circular Wastewater Management with Machine Learning

Effective wastewater treatment is essential to the health of the environment. When operating wastewater treatment plants, utilities must ensure that the treated water meets environmental regulations, while balancing competing needs to minimize the cost of running the plant against the maximizing resource recovery. Additionally, most wastewater treatment plants include a combination of physical, chemical, and biological processes, all of which are complex and which can change rapidly in response to changing conditions. Operators need reliable tools to predict the future state of the plant so that they can effectively operate the plant proactively – ensuring that environmental regulations are met without incurring massive costs, all while recovering resources from the wastewater. In this project we will use machine learning tools help generate insights from routinely monitored data in a wastewater treatment plant operated by the Ontario Clean Water Agency to support the operation and control of the plant.

Michael De Santi
Faculty Supervisor: 
Stephanie Gora;Usman Khan;Satinder Brar
Partner University: