Progress on new artificial intelligence (AI) technology could make monitoring at water treatment plants cheaper and easier and help safeguard public health. According to the German news agency (dpa), researchers at the University of Waterloo have developed AI software capable of identifying and quantifying different kinds of cyanobacteria, or blue-green algae, which poses a threat to water systems when it suddenly proliferates. The Phys.org website cited Monica Emelko, a professor of civil and environmental engineering, as saying: “We need to protect our water supplies. This tool will arm us with a sentinel system, a more rapid indication when they are threatened.” 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. 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. 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.