Keeping Transit Networks Moving: How AI-Powered Predictive Maintenance Transforms Public Transport

Millions of commuters rely on fare gates daily, with London alone seeing over 3.5 billion journeys in the past 2 years. These machines, though designed for seamless operation, sometimes experience breakdowns due to wear and vandalism, causing delays and frustration.

Traditional maintenance is reactive, requiring engineers to respond after failures —often without the right parts—leading to extended downtime and higher costs.

Can we proactively anticipate issues and prepare engineers with the correct parts before breakdowns occur?

The answer is yes, with AI-powered Predictive maintenance.

In our collaboration with Cubic Transportation Systems, we used large language models to analyse fare gate logs and error reports, identifying the solution to improve public transport reliability and efficiency. Get the insights from Steffen Reymann, Engineering Fellow at Cubic 👇

Check out the leadership piece here!