AI tech could help protect water supplies, study says

Ground Water Canada
July 19, 2018
By Ground Water Canada
Waterloo, Ont. – Progress on new artificial intelligence technology could make monitoring at water treatment plants cheaper and easier and help safeguard public health, suggest researchers at the University of Waterloo.

Researchers at the University of Waterloo have developed AI software capable of identifying and quantifying different kinds of cyanobacteria, or blue-green algae, a threat to shut down water systems when it suddenly proliferates.

“We need to protect our water supplies,” said Monica Emelko, a professor of civil and environmental engineering and member of the Water Institute at Waterloo in a news release. “This tool will arm us with a sentinel system, a more rapid indication when they are threatened.

“The exciting piece is that we’ve shown testing utilizing AI can be done quickly and well. Now it’s time to work through all the possible scenarios and optimize the technology.”

The operational AI system uses software in combination with a microscope to inexpensively and automatically analyze water samples for algae cells in about one to two hours, including confirmation of results by a human analyst.

Current testing methods, which typically involve sending samples to labs for manual analysis by technicians, take one to two days. Some automated systems already exist as well, but they require extremely expensive equipment and supplies.

According to Emelko and collaborator Alexander Wong, a systems design engineering professor at Waterloo, the AI system would provide an early warning of problems since testing could be done much more quickly and frequently.

Moving forward, the goal is an AI system to continuously monitor water flowing through a microscope  for a wide range of contaminants and microorganisms.

“This brings our research into a high-impact area,” said Wong. “Helping to ensure safe water through widespread deployment of this technology would be one of the great ways to really make AI count.”

The researchers estimate it may take two to three years to refine a fully commercial sample testing system for use in labs or in-house at treatment plants. The technology to provide continuous monitoring could be three to four years away.

“It’s critical to have running water, even if we have to boil it, for basic hygiene,” said Monica Emelko, a professor of civil and environmental engineering at Waterloo. “If you don’t have running water, people start to get sick.”

Adjunct engineering professor Chao Jin, doctoral student Jason Deglint and research associate Maria Mesquita are also collaborators.

A study on the research, "Quantification of cyanobacterial cells via a novel imaging-driven technique with an integrated fluorescence signature," was recently published in the journal Scientific Reports.

Add comment


Security code
Refresh

Subscription Centre

 
New Subscription
 
Already a Subscriber
 
Customer Service
 
View Digital Magazine Renew

We are using cookies to give you the best experience on our website. By continuing to use the site, you agree to the use of cookies. To find out more, read our Privacy Policy.