“Water is the New Fire”: Artificial Intelligence, Machine Learning, and Water Conservation

By Luke Carothers

Yaron Dycian describes himself as a serial entrepreneur.  Over the last 30 years, Dycian has worked in fields ranging from cyber security to digital agriculture; he has been at the forefront of a lot of cutting-edge technology, and he believes that his purpose is to help solve the world’s big problems.  Dycian’s latest endeavor is no different.

Dycian is the Chief Product and Strategy Officer for WINT, which is a leading water conservation and leak detection tool that makes constructing green buildings easier.  In other words, WINT seeks to solve water problems in buildings and facilities, moving from the construction phase into the actual occupation of the building.  This means that when construction is completed, WINT continues working and transitions to the operational phase.

The staff at WINT have created a core technology that seeks to understand the flow of water within pipes.  The end-goal is twofold: to prevent damage to the project and save money from wasted water.  On average, WINT helps their customers save 20-25 percent on water during the course of a project.  However, when it comes to more serious issues, WINT has the potential to save millions of dollars on catastrophic water damage.

WINT’s core technology operates under the assumption that there are many different types of water-use in a given building—sinks, toilets, washing machines, irrigation, etc.  Tracking the variations in the flow of water, WINT uses artificial intelligence to record patterns that could indicate leaks and/or other forms of waste.  It can also learn through multiple functions, using pre-established databases to create flexible action policies, which are useful in projects that have varying usage patterns.  Furthermore, when WINT detects a leak or waste, it applies the same artificial intelligence to offer solutions and take action.  A problem such as a broken water pipe in the wall that happens during off hours can be switched off by the technology, saving money and time for the crew.

This exact situation occurred when renovations were being made to the historic Howard de Walden Estate in London.  During this project, the upper floors of the building were under construction while the high-end retail shops on the ground level were still open for business.  At around 4 a.m. during construction, an upstairs pipe ruptured, creating a high flow leak at a time when the building wasn’t being occupied.  WINT was able to identify the leak and shut off the flow of water before any significant damage could be done to either the historical building or the merchandise at the high end retail stores.

Dycian believes this is the start of a paradigm shift in the construction industry, stating “water is the new fire” in reference to water damage.  He believes that the industry has focused on fire for such a long time, and rightfully so, that many problems associated with fire have been all but solved.  Now, according to Dycian, the biggest cause for the rise in premium rates amongst construction projects is the potential for water damage.  Thus, it is not unreasonable to assume that more projects will turn to artificial intelligence and machine-learning to solve the problems of unused water and water damage.

Luke Carothers is the Editor for Civil + Structural Engineer Media. If you want us to cover your project or want to feature your own article, he can be reached at lcarothers@zweiggroup.com.