When Meena Sankaran was a child growing up in Mumbai, India, her family didn’t have consistent access to water in their home, and what they did have wasn’t always safe to drink. She was often sick—with typhoid, malaria, jaundice, mumps, and pneumonia, all before she was 17. If these illnesses weren’t directly water-related, the lack of clean water didn’t help her recovery.
“My immune system just got used to it,” Sankaran says.
Sankaran is one of the lucky ones. The World Bank estimates that almost a quarter of all communicable diseases in India are due to unsafe water and the lack of safe hygiene practices, with more than 500 children under the age of five dying each day from diarrhea.
Sankaran spent 20 years getting an engineering degree in the U.S. and working in the tech industry before using her personal experiences to launch a startup in 2016 called KETOS, a water management company that uses AI to monitor and test quality.
The company has two products: KETOS Wave, a device that sits in a water pipe and can detect more than 20 parameters like flow, pressure, usage, and volume that feed into a machine learning algorithm that can identify possible leaks and track use. So if water volume goes down in a way that the algorithm parsing the data doesn’t expect, Wave can notify the user of the likely leak with a mobile app, which also has the ability to remotely shut the water off.
The company’s other product is KETOS Shield, which can measure and detect 20 different dangerous contaminants like lead, copper, nitrates, arsenic, and chlorine. Measuring these toxins doesn’t utilize AI, but Shield combines routine chemical testing with factors that can contribute to fluctuations—such as the time of year, or the temperature—in a machine learning algorithm that predicts chemical spikes before they happen.
While the 140 deployments to date are mainly with municipal and agricultural clients in the U.S. and Mexico, Sankaran also wants to do something for her homeland. That led KETOS to offer water solutions across India as part of the government’s Smart Village Initiative. In 2017, the company deployed its technology in 25 villages. None of the villages had a way to monitor quality, and several could go days without getting water at all. Sankaran said they were able to improve that supply by up to two hours a day in most cases.
Not that there haven’t been hiccups. Saravana Sarru is a resident of Kuppam, the first village in the State of Andhra Pradesh that KETOS worked in, and ended up working as a liaison on the ground for many of the other villages. In some of them, the rainy season interfered with the devices sending information back to those monitoring the water, a problem that was solved by relying on a mesh network, a type of network that made internet connectivity more reliable. Even with the initial issues, Sarru said that all the communities have been excited by the potential to have more control over their water source.
“It’s very new to India,” Sarru says.
KETOS is planning a project in Majuli, the world’s largest river island, which has major problems with arsenic contamination. They are actively partnering with an Indian NGO to recruit local women as field support personnel, giving them jobs that are also empowering villagers to take care of their own water. Thousands of other villages have expressed interest, but the recent elections have halted the project.
“We are slowly but surely pressing forward,” Sankaran says. “India takes time.”
But the country has no time to spare in finding new ways to better monitor and improve water management. More than 163 million Indians don’t have access to clean water, the highest number of any country in the world, and more than 600 million face acute water shortages. Nearly two dozen cities could run out of groundwater by next year, including megacities like Bangalore and New Delhi.
A Global Problem
Across the rest of the world, over 2 billion people are living in areas of water scarcity, according to the United Nations, and that number could grow to 5 billion by 2050. Nearly a million people die each year from water, sanitation, and hygiene-related diseases that would be reduced with access to clean water.
The U.S. has one of the safest overall systems but still has serious issues to contend with in the coming decades. America’s drinking water is delivered through more than a million miles of pipes, most of which were laid in the early to the mid-20th century with a lifespan of 75 to 100 years. This past-retirement age system contributes to an estimated 240,000 water main breaks each year—and some two trillion gallons of water lost annually. The government will need to spend a trillion dollars maintaining and expanding services for a growing population over the next 25 years, according to the American Water Works Association.
These old pipes also create water quality problems. While the bigger public drinking water systems have the ability to test water frequently, smaller municipal systems that still serve millions of Americans in more rural areas don’t necessarily have the budget or expertise to do the same amount of testing. AI-powered tools like KETOS could help bridge the gap, and identify problems that otherwise might remain invisible for years.
“We are desperately in need of better monitoring,” says Peter Gleick, a climate and water scientist who co-founded the Pacific Institute. “It’s a problem, even here in the U.S.”
By far the most public water crisis has been unfolding in Flint, Michigan, where over 100,000 citizens have been exposed to dangerous levels of lead leaching from their pipes due to insufficient treatment. The state has struggled for five years to make it right. AI might be part of the solution to finally helping Flint: Volunteer researchers developed a machine learning algorithm to predict which homes are most likely to have lead pipes that need to be changed out.
Implementing this inspection system has proven difficult, however. Some residents whose pipes were not prioritized by the algorithm have complained, feeding into the general atmosphere of distrust in politicians and policymakers that still simmers in Flint five years after the crisis started. Roughly one-quarter of the water pipes in the city have yet to be inspected, and even when that’s done and any remaining lead pipes have been replaced, an unknown number of damaged pipes within homes will remain, ensuring that Flint’s struggle for safe drinking water will drag on for years to come.
The problem isn’t unique to Flint, however. There are an estimated 6.1 million lead pipes across the country. Flint is the only city that has so far been able to prove a causal link between its water and elevated lead levels, but a Reuters’ investigation found 3,000 areas in the U.S. with lead poisoning rates that were at least double those that were seen in Flint during the height of that crisis. Most spots have what the report calls a “lead legacy” made up of old pipes, abandoned industrial waste, and peeling paint that could all be contributing to elevated lead levels.
“We’ve known for a long time that there are certain water problems that require a lot of data and observations to get a hand on,” Gleick says. “If AI can help sort through that data, it would be enormous step forward in better management of our limited water resources."
Sankaran’s work in India got KETOS more business but she said that’s not the point. She wants to see a focus on using new tools, like the ones she’s developed, to make the world a better place.
“You have to question yourself about what’s the benefit of all these advancements in technology if you can’t improve the quality life at a basic level,” Sankaran says.