The Metropolitan Transportation Authority (MTA) in New York City has partnered with Google Public Sector on a pilot program designed to detect track defects before they cause significant disruptions. Using Google Pixel smartphones retrofitted onto subway cars, the system captured millions of sensor readings, GPS locations, and hours of audio to identify potential problems. The project aimed to improve the efficiency of the MTA's response to track issues, potentially saving time and money while reducing delays for passengers.

The AI-powered program, called TrackInspect, analyses the sounds and vibrations from the subway to pinpoint areas that could signal defects, such as loose rails or worn joints. Data collected during the pilot, which ran from September 2024 to January 2025, showed that the AI system successfully identified 92% of defect locations found by human inspectors. The system was trained using feedback from MTA inspectors, helping refine its ability to predict track issues.

While the pilot was considered a success, the future of the program remains uncertain due to financial concerns at the MTA. Despite this, the success of the project has sparked interest from other transit systems looking to adopt similar AI-driven technologies to improve infrastructure maintenance and reduce delays. The MTA is now exploring other technological partnerships to enhance its track monitoring and maintenance efforts.