It’s easy to take water for granted. Turn on the tap, and you’ll receive clean, life-giving water (with some very notable exceptions). But for a myriad of reasons, ranging from our changing climate to aging infrastructure to growing demands for water, all aspects of the water cycle — how it is collected, cleaned, distributed (and repeat) — are overdue for a technological makeover.
For one thing, the workforce behind our waterworks is aging, at least within the public water utility sector, which is composed of an astounding 50,000 individual systems. “Lots of senior engineers are 30 years into their job and are reaching retirement,” says Will Maize, a water industry analyst with market research firm Bluefield Research. When they go, so will a good deal of institutional knowledge.
But as recent and prolonged droughts in the West reminded farmers, municipalities, and manufacturers, water scarcity calls for better water measurement and management. That’s why there’s an emerging shift toward what Will Sarni, CEO of the consultancy firm Water Foundry, calls “digital water.”
“When supply vastly exceeds demand, you can do stupid things, and we have a few hundred years of doing that,” says Sarni, referring to how utilities and the private sector have traditionally managed water.
Digital water is water that is managed using software-based tools such as data analytics, visualization, and predictive analytics. It goes by other monikers as well — Maize calls it “smart water.” Hardware, such as sensors to track water quality, pressure, and flow, is at the base of this new tech pyramid.
But to advance the digital analytics tools, a healthy dose of data science is needed. Sarni considers artificial intelligence to be “the holy grail” when it comes to digital water. With the right development, AI could unlock an incredible amount of value in terms of cutting waste, improving wastewater treatment systems, and keeping water infrastructure healthy.
Though most in the water industry agree that it’s still early days for AI tools that manage water. (Much earlier than for the energy sector.)
However, once water utilities, distributors, and companies catch on, AI and machine learning could transform water consumption and…