Industrial controls — particularly “Condition Monitoring” systems — are increasingly supported by sophisticated sensors and data analysis tools. Using artificial intelligence (AI) for data classification and analysis, these tools do not simply add intelligence to IoT sensors.
Over the last few years, as sensor and MCU prices plummeted and shipped volumes have gone thru the roof, more and more companies have tried to take advantage by adding sensor-driven embedded AI to their products.
Machine learning on high-sample-rate sensor data is different. For a lot of reasons. The outcomes can be very powerful – just look at the proliferation of “smart” devices and the things they can do. But the process that creates the “smarts” is fundamentally different than the way most engineers are used to working.
Reality AI stole the show and won the Gold Medal Best of Sensors Midwest 2017 award in Rosemont last week. We would like to thank all the attendees of the show and our customers for their trust and loyalty.
IoT World sponsors a startup pitch competition in conjunction with Project Kairos, looking for the most innovative startups active in the Internet of Things.
TechCrunch interviews CEO Stuart Feffer and profiles Reality AI on the floor of Disrupt NYC 2017.
Design News names Reality AI one of “Ten Artificial Intelligence Companies You Should Know”.
IoT Evolution Expo Awards the “Most Innovative and Creative Companies” in the Industry.
We all know what a sensor is, right?
A sensor makes “sense” of physical property — it turns something about the physical world into data upon which a system can act. Traditionally, sensors have filled well defined, single-purpose roles: A thermostat, a pressure switch, a motion detector, an oxygen sensor, a knock detector, a smoke detector, a voltage arrestor.