Your smartphone is utterly packed to the brim with sensor of all kinds. Some of those are out in the open, like the cameras our phones use to image their surroundings, while others are hidden within, like the accelerometers that tell our phones what direction we’re holding them. Collectively, these sensors can be used by clever software to deliver all sorts of useful features, like how Pixel phones are able to detect when we’re in a car crash and summon emergency assistance. But now we’re hearing about how those same sensors are keeping some much larger vehicles safe, with New York City’s Metropolitan Transportation Authority (MTA) tapping Pixel phones for some help with subway maintenance.
AndroidAuthority.com
The MTA’s got a big job, responsible for keeping the population of the country’s biggest city moving around without clogging the streets with an impossible number of cars. But running a subway system this expansive means there’s a lot of track that you’ve got to keep safe and operational — some 665 miles of it.
Normally, looking for track issues in need of repair either requires manually walking those miles and miles of tracks, or scanning them with “train geometry cars,” packed with sensors able to identify problem areas. But recently, Wired reports, the MTA partnered up with Google to see if Pixel phones could maybe replace some of those expensive scanner cars. Rather than using dedicated equipment to only scan subway lines a few times a year, more affordable hardware could allow the MTA to deploy it more broadly, gathering data with higher frequency and potentially spotting problems even earlier. And as smartphones are basically commodity devices now, strapping a Pixel phone to a subway car makes for a cheap and easy way to augment it with sensors.
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On the same topic, from Trains.com
The Metropolitan Transportation Authority has begun a pilot program with a division of Google that uses smartphones to help detect potential subway track defects. The program announced Thursday, Feb. 27, builds on TrackInspect, a prototype developed with the Rapid Innovation Team at Google Public Sector. Tested on the subway A line of New York City transit, that effort fitted Google Pixel phones in off-the-shelf plastic cases onto R46 subway cars to capture vibrations and sound patterns through sensors with an attached microphone to find locations in need of preventative maintenance.
The sound and vibration data is sent to cloud-based systems using artificial intelligence and machine learning to develop predictions. New York City Transit track inspectors then inspect the locations to determine if there is an issue, providing feedback to help develop the modeling. The AI involved also allows inspectors to ask questions about maintenance history and other details, receiving answers in conversational language.
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