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A predictive analytics startup armed with a patented learning algorithm aimed at security applications along with Internet of Things devices said it has attracted seed funding for a platform that could spot the precursors of impending fires and floods before they start.
OneEvent Technologies said this week it has so far raised $4.3 million to commercialize its predictive learning and analytics engine for building monitoring and security. The cloud-based platform—the IoT version of a smoke alarm—uses wireless sensors to measure factors such as temperature, air quality and humidity. The engine eventually learns what is “normal” for a given structure and issues alerts when it detects an abnormal reading that might indicate fire or flood.
Company founders Dan Parent and Kurt Wedig said a TV segment showing hotel occupants crawling down a smoke-filled hallway, searching for an exit, inspired them. Their idea was spurred by the realization that smoke detectors and fire alarms did little to prevent the fire.
Founded in 2014, the startup based in Mount Horeb, Wis., holds eight U.S. patents on its software platform. The startup is currently testing the predictive alarm system with local fire departments and other agencies using controlled burns to determine how far in advance the OnePrevent system can predict trouble.
During testing at the safety certifier UL (formerly Underwriters Laboratories), OneEvent said signs of a fire were detected by its system up to 20 minutes before smoke alarms sounded.
The predictive learning and analytics engine can, for example, be trained to detect rising temperatures in a kitchen or increasing moisture from a leaking pipe. Each data point collected by wireless sensors can be processed via the OneEvent algorithm, alerting a building manager or homeowner via a smart app on a mobile phone or tablet. “As opportunity in IoT and building monitoring grows, there’s a potential to create solutions that can do more than just alert people to danger as it happens or after the fact,” OneEvent CEO Wedig asserted.
The startup notes that its predictive-alert system is neither a fire nor burglar alarm. Rather, it is positioning the platform as “supplementary protection that empowers users with data and anticipated warnings via a cloud based platform and app.”
Along with first responders and homeowners, the analytics engine also is being pitched to property and casualty insurers, allowing them to “look back in time” to determine whether an insured property was protected by working sensors.
Along with predictive capabilities, embedded sensors also could be used by first responders track the progress of a fire, generating data for investigators and claims adjusters on the cause of a fire.
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