TrackInspect — the MTA and Google Public Sector's AI Pilot for Predictive Subway Track Maintenance

The MTA (Metropolitan Transportation Authority), which runs the largest subway system in North America, faces a constant backlog of manual track inspection. In September 2024, New York City Transit and Google Public Sector launched TrackInspect, retrofitting six R46 subway cars on the A line with off-the-shelf Google Pixel smartphones mounted to capture vibration and audio signals as trains ran their normal routes.
Over the pilot's five months (September 2024–January 2025), the phones collected 335 million sensor readings, 1 million GPS points and 1,200 hours of audio, which cloud-based machine-learning models analyzed to flag likely track defects such as loose fasteners or rail irregularities. Human track inspectors then verified each flagged location and fed their findings back into the model. TrackInspect's flagged locations matched 92% of the defects independently found by MTA's human inspectors.
Track inspectors remain "in the loop": the system flags candidate locations for human confirmation rather than acting autonomously, and its performance figures come from MTA and Google's own reporting rather than an independent third-party audit. The pilot covered only six cars on a single line; MTA has stated an intention to expand AI-assisted inspection system-wide, but as of the pilot's public reporting no confirmed system-wide rollout, budget commitment, or post-pilot funding arrangement with Google Public Sector (which developed the tool at no cost during the pilot) had been disclosed.

Read the full analysis: https://www.cnn.com/2025/03/09/tech/mta-google-pixel-smartphones-new-york-subways