7 Industrial IoT Startups Using AI to Monitor Machines
If you follow technology news and trends long enough, a few statistics pop up again and again. One oft-quoted stat goes something like this: About 90 percent of the data in the world has been created in the last two years. Now, we’ve been hearing this factoid foryears, so it’s possibly time for some underemployed MBA to redo the math. However, the bottom line: There is a isht-ton of data out there today, and more and more companies are developing ways to corral and coax that information into valuable insights for a price. Combining these big data sets withartificial intelligence, specifically machine learning, has given birth to an entireindustry of predictive analytics. Add the Internet of Things (IoT)—devices from coffeemakers to cars connected together with sensors and beacons—and you can start to detect patterns and make predictions about each network. Like your smart toaster is about to burn the house down.
In the world of the Industrial IoT, there are potentiallybillions of dollarsthat could be saved if companies could anticipate machine breakdowns or failures before they happen. As we’ve noted before, General Electric (NYSE:GE) has made some big investments to position itself asthe IIoT company. Of course, there are more than a few startups hoping they are agile enough to compete against the likes of GE. We introduced you to one such company,C3 IoT, last year after it took in a $70 million Series D. This year’s IIoT mega-round winner appears to be Uptake Technologies, which closed on a $117 million Series D at the end of last month. That brings total disclosed funding for the Chicago-based startup to about $263 million, for a post-money valuation of$2.3 billion. Not bad considering it was only founded back in 2014.
Uptake’s “insight platform” crunches millions of data points from its clients to provide actionable information to improve efficiency, safety and asset performance. In real-world language, that means Uptake analyzes data coming in from machines, from oil rigs and wind turbines to locomotives and tractors, to identify possible maintenance problems or performance issues. The system gets better—learns—over time as it compares its analyses against findings from technicians in the field.
For example, in the first week that Uptake deployed its insight platform at a wind farm operated by MidAmerican Energy Company, a subsidiary of Berkshire Hathaway Energy, it identified signatures that a gearbox main bearing might fail on one of the turbine towers. A few hours of downtime to address the issue cost the company about $5,000 versus up to $250,000 if the turbine had completely crashed. Uptake estimates it can save a large wind farm about $3.3 million per year. Similarly, its algorithms have helped save one rail company $80,000 per year per locomotive in maintenance costs. Other high-profile customers include Caterpillar (NYSE:CAT) and its three million oversized Tonka Toys.
The brains behind the operation are Brad Keywell and Eric Lefkofsky, two co-founders of Groupon (NASDAQ:GRPN). Despite the fears of such luminaries as Elon Musk and Stephen Hawking, who believe AI will destroy us all, Uptake is upbeat about the power of machines to do good. It has even established aphilanthropic armof the company that provides predictive analytics to nonprofits at no cost. It has launched a tool,Student Union, for first-generation college applicants to apply to schools where they would have the best chance to succeed. Another platform calledReRoutetackles human trafficking, which calls to mind our recent piece on howAI will help fight crime.
Uptake is certainly one of the heavyweights in IIoT predictive analytics, but it’s not alone. The bright minds at CB Insights put together this impressive market map.
