Explain in which way artificial intelligence can help us to conserve water and light?
Answers
Explanation:
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 Blue Field 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 Sarno, CEO of the consultancy firm Water Foundry, calls “digital water.”
“When supply vastly exceeds demand, you can do bad things, and we have a few hundred years of doing that,” says Sari, 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. Sarnoff 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 delivery systems. It’s an important problem to solve, as the world’s population grows to 9 billion by 2050 and water scarcity becomes of increasing concern.
Leaky Pipes and Mains
Rome is known for its aqueducts, which played an important role in expanding the Roman Empire. It’s ironic, then, that the city had to ration water during this drought-stricken summer, partly due to Rome’s notoriously leaky municipal water infrastructure that loses up to 44 percent of the water moving through the system.
According to industry group American Water Works Association, between 2011 and 2050, U.S. utilities will spend $1.7 trillion on repair and expansion of drinking water infrastructure, and more than half of that bill will go toward replacing distribution pipes as they reach their end of life.
But when does that time come? Replace them too soon, and you’ve squandered energy and resources. Wait too long, and pipes fail, wasting a great deal of clean water.
Fractions, a startup based in Redwood City, California, has developed a system that aims to help water utilities save money and resources by prioritizing cities’ replacement of water mains and distribution pipes, from which smaller pipes branch out into buildings.
Lars Stansted The, COO of Fractals, says utilities are already looking to analyze as many of the variables that go into a given pipe’s life cycle as possible, but “as the number of relative variables go up, the only way to approach this is through machine learning.”
Fractions analyses data related to the type of soil in which pipes rest, the topography, and weather records, and then applies machine learning to find patterns, across an entire city or region, that offer clues as to which pipes are at the greatest risk of leaks or failure. The company is currently working with two water utilities in the Bay Area to prove that its approach works.
Predictive analytics firm Pluto is applying artificial intelligence to the legacy water equipment and data management systems used by utilities and industrial water users, such as beverage manufacturers. The year-old company says it can help water managers conserve energy, lower operating costs, and squeeze more life from water plant assets. It does this by running data from disparate sources, such as pumps and filtration systems, through its algorithms to come up with optimal management and control protects