“I was on a train about three years ago, going back to my hotel after a business meeting,” 3DSignals CEO Amnon Shenfeld told Digital Trends. “The train suddenly started making strange noises. These weren’t the usual sounds that trains make, but something out of the ordinary. It was the same week that a train had overturned in Spain, injuring a lot of people. Everyone stopped talking and was getting very worried. I had the thought that maybe if there was a train mechanic or engineer sitting on the train, they could tell us if the noise was normal and, if not, where it was coming from and whether it could be safely ignored.”
From that slightly scary scenario (from which he emerged unscathed), Shenfeld came up with the idea behind the company called 3DSignals. The company’s goal? To harness the latest AI machine learning technology to understand the noise patterns made by machines running into trouble and relating them back to users via their smartphone or tablet.
Properly trained, Shenfeld said that the company’s deep-learning algorithms are able to identify and predict specific problems with an accuracy rate of 98 percent.
To do this, machinery for monitoring has to be kitted out with the company’s proprietary hardware: Consisting of a connected processing unit and an ultrasonic microphone five times more sensitive than the human ear. While the human range is between 20Hz and 20kHz, 3DSignals’ custom mic can detect sounds ranging up to 100kHz.
Shenfeld said his company never set out to create its own hardware, but had to in order to carry out its mission statement. After all, as pioneering technologist Alan Kay once said, people serious about software need to build their own hardware. “We went on Google and searched for ultrasonic, cloud-connected, ruggedized microphones, but we couldn’t find what we wanted,” Shenfeld said. “So right now we’re manufacturing the only device of its type that can be used for remote monitoring via acoustics.”
At present, 3DSignals is busy speaking with leading European carmakers about using the technology both in cars as well as to monitor auto factory machinery. It is also being used to monitor other non-auto industrial machinery like circular cutting blades in mills and hydroelectric turbines in power plants. The tech will be shown off on January 23 as part of the IoT Tech Expo in London.
“You know that saying about whether or not a tree that falls in the forest makes any sound?” Shenfeld said. “Well, we want to update the question to what happens to a machine that fails with no engineer standing next to it? We think we have the answer.”
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