Digital Platform, Artificial Intelligence and Machine Learning in Potable Reuse Projects (Webcast)
Learn how digital platforms that include artificial intelligence and machine learning can be used to improve asset management strategies and operational efficiencies.
11:00 am – 12:00 pm PT | 2:00 pm – 3:00 pm ET
WateReuse Members: Free
In this webcast, our presenters will introduce how digital platforms that include artificial intelligence (AI) and machine learning (ML) can be used to improve asset management strategies and operational efficiencies, as well as enhance source control, validate unit process performance, predict product water quality and make sound decisions for assessing suitability of product water for human consumption.
The data collected from pilot and full-scale potable reuse treatment trains have been used to develop artificial neuron networks as part of an ML platform. The platform clearly demonstrates that ML can be used to predict, for example, the product water total organic carbon (TOC) concentration of a pilot advanced treatment facility and the specific fluxes on the third stage of a full-scale advanced treatment facility as the feed quality and operating conditions are changed.
The methodology used and model outputs will be discussed during the webcast. The presenters will also examine how we can couple AI/ML concepts with the Internet of Things (IoT) and next generation of the SCADA systems to operate and maintain assets efficiently while significantly enhancing public and regulatory confidence in potable reuse projects.
- Ufuk Erdal, Arcadis
- Jim Cooper, Arcadis
- Raluca Constantinescu, Arcadis
- Ozan Erdal, University of Washington