The Metropolitan Transportation Authority (MTA) in New York City has partnered with Google for a groundbreaking pilot program focused on enhancing the reliability of its old subway network. Utilizing Google’s mobile technology, the effort aims to detect and resolve rail problems before they cause service interruptions. Named “TrackInspect,” the project signifies a considerable advancement in applying artificial intelligence and contemporary technology to public transportation.
La iniciativa piloto, que inició en septiembre de 2024 y finalizó en enero de 2025, consistió en equipar algunos vagones del metro con teléfonos Google Pixel. Estos dispositivos se encargaron de recolectar datos de audio y vibración para identificar posibles fallas en las vías. Luego, la información fue evaluada a través de los sistemas de inteligencia artificial en la nube de Google, los cuales señalaban las zonas que necesitaban una revisión más detallada por parte del personal de la MTA.
The pilot project, which began in September 2024 and concluded in January 2025, involved installing Google Pixel smartphones on select subway cars. These devices were tasked with collecting audio and vibration data to detect potential track defects. The data was then analyzed using Google’s cloud-based AI systems, which flagged areas requiring closer inspection by MTA personnel.
The collaboration between the MTA and Google forms a component of a larger initiative to update New York City’s 120-year-old subway system, which still confronts issues due to its outdated infrastructure and regular delays. Although the pilot program yielded encouraging outcomes, doubts persist about the potential expansion of TrackInspect, considering the financial limitations the MTA is experiencing.
The MTA’s partnership with Google is part of a broader effort to modernize New York’s 120-year-old subway system, which continues to face challenges related to aging infrastructure and frequent delays. While the pilot program demonstrated promising results, questions remain about whether TrackInspect will be expanded given the financial constraints facing the MTA.
Tackling delays with AI and smartphones
The TrackInspect initiative focuses on tackling a crucial element of the problem: pinpointing and correcting mechanical issues before they worsen. Throughout the pilot phase, six Google Pixel smartphones were placed in four R46 subway cars, recognizable by their unique orange and yellow seats. These devices captured 335 million sensor readings, more than one million GPS points, and 1,200 hours of audio data.
The TrackInspect program aims to address one critical aspect of the issue: identifying and resolving mechanical problems before they escalate. During the pilot, six Google Pixel smartphones were installed on four R46 subway cars, which are known for their distinctive orange and yellow seats. The devices recorded 335 million sensor readings, over one million GPS data points, and 1,200 hours of audio.
The smartphones were strategically placed both inside and underneath the subway cars. While the external devices were equipped with microphones to capture audio and vibrations, the internal phones had their microphones disabled to ensure passenger conversations were not recorded. Instead, these devices focused solely on vibrations to detect irregularities in the tracks.
The A train line was selected for the pilot, providing a varied testing environment with both subterranean and elevated tracks. It also featured segments of newly built infrastructure, which served as a benchmark for analysis. Although not every delay on the A line is due to mechanical issues, the data gathered during the pilot could assist in resolving persistent problems and enhancing overall service.
Encouraging outcomes, yet challenges persist
Promising results but hurdles remain
El programa también incorporó una herramienta impulsada por inteligencia artificial basada en el modelo Gemini de Google, que permitía a los inspectores hacer preguntas sobre protocolos de mantenimiento e historial de reparaciones. Esta inteligencia artificial conversacional ofrecía a los inspectores información clara y útil, lo que facilitaba aún más el proceso de mantenimiento.
The program also included an AI-powered tool based on Google’s Gemini model, which allowed inspectors to ask questions about maintenance protocols and repair history. This conversational AI provided inspectors with clear, actionable insights, further streamlining the maintenance process.
Google participated in the pilot as part of a proof-of-concept initiative that was provided at no expense to the MTA. However, broadening the program would probably demand substantial investment, making financing a key factor for those making decisions.
An increasing trend in transit advancement
A growing trend in transit innovation
New York’s partnership with Google is part of a broader trend in which cities worldwide are adopting artificial intelligence and smart technologies to improve public transit systems. For example, New Jersey Transit has used AI to analyze passenger flow and crowd management, while the Chicago Transit Authority has implemented AI-driven security measures to detect weapons. In Beijing, facial recognition technology has been introduced as an alternative to traditional transit tickets, reducing wait times during peak hours.
Google itself has collaborated with other transportation agencies in the past. The tech giant has developed tools to enhance Amtrak’s scheduling and partnered with parking technology providers to integrate street parking data into Google Maps. However, the scale and complexity of New York’s subway system make this project particularly ambitious.
The MTA’s subway network is the largest in the United States, with 24-hour service on many lines. This round-the-clock operation adds another layer of complexity to maintenance efforts, as repairs and upgrades often need to be conducted alongside active service. By using AI and smartphone technology, the TrackInspect program could help the MTA address these challenges more efficiently.
Although the TrackInspect pilot has concluded, the MTA is investigating collaborations with additional technology providers to further improve its maintenance procedures. The agency is also evaluating data from the pilot to assess its effects on minimizing delays and enhancing service. Initial signs indicate that specific types of delays, including those from braking problems and track defects, declined on the A line during the pilot. However, the MTA warns that more analysis is required to verify a direct connection to the program.
While the TrackInspect pilot has ended, the MTA is exploring partnerships with other technology providers to further enhance its maintenance processes. The agency is also analyzing data from the pilot to determine its impact on reducing delays and improving service. Early indications suggest that certain types of delays, such as those caused by braking issues and track defects, decreased on the A line during the pilot period. However, the MTA cautions that further analysis is needed to confirm a direct link to the program.
Mientras Sarno reflexiona sobre el proyecto, destaca el potencial de las soluciones impulsadas por inteligencia artificial para transformar el transporte público. “Esta tecnología nos permite identificar problemas con anticipación, reaccionar más rápido y, en última instancia, ofrecer un mejor servicio a nuestros clientes,” afirmó.
As Sarno reflects on the project, he emphasizes the potential of AI-driven solutions to transform public transportation. “This technology allows us to detect problems earlier, respond faster, and ultimately provide better service to our customers,” he said.
The MTA’s collaboration with Google underscores the potential of public-private partnerships to drive innovation in critical infrastructure. Whether TrackInspect becomes a permanent fixture in New York’s subway system remains to be seen, but its success highlights the possibilities of integrating cutting-edge technology into the daily lives of commuters.
