Increasing visibility into municipal water systemsThe 50,000 or so public water systems in the United States represent a distributed network as ...Increasing visibility into municipal water systems
The 50,000 or so public water systems in the United States represent a distributed network as complex as the internet. The difference is that we still don’t know where all the water goes after it leaves the treatment plants.
A Water Quality and Health Council report estimated that U.S. water utilities lose 16% of their water each year. Some aging and economically constrained systems—including several in and around Chicago—lose more than 30%. The report said that leaking pipes led to the loss of 25 billion gallons of water drawn from Lake Michigan in 2016.
It’s not an easy fix. Water systems are often completely independent and must stand up to rugged conditions: hot, humid and full of water. In many areas, they don’t have the luxury of a connection to any sort of private network that would help them improve performance or identify problems.
That’s now changing. The technology available in the industry—low-power edge computing chipsets, solar panels and battery technology—is finally maturing to the point where it can be deployed at scale. And the advent of artificial intelligence and machine learning has pushed the boundaries of what’s possible.
Today’s most advanced solutions put sensors right down into the commercial water meter pit. A visual sensor (a camera) reads the meter’s dial, a vibration sensor feels the water flow in the meter and pipe and a rotational sensor tracks the meter’s spin. Together, they collect performance data, much like sensors in modern cars.