AI-driven sensors in bullet trains
06/05/2026
An artificial intelligence (AI)-driven monitoring system using sensors mounted on trains running at up to 350 km/h to detect track defects early, before cracks develop, and to automatically slow trains will be installed on India’s first bullet train corridor, between Mumbai and Ahmedabad.
Part of a condition-based monitoring (CBM) system, the technology also tracks the health of train components such as bearings, gearboxes, traction motors and doors in real time, predicting failures weeks in advance and enabling maintenance based on actual wear rather than fixed replacement schedules.
Developed by South Korea-based company Globiz, the system was showcased at the International Rail Coach Expo 2026, organised by Integral Coach Factory (ICF) and the Confederation of Indian Industry (CII). The system uses sensors installed on key parts of the train, including wheels, bogies, doors and electrical systems. As the train runs, the sensors continuously record vibrations and mechanical behaviour.
The data is processed through an on-board edge server, where algorithms analyse patterns to detect anomalies.
One of the key capabilities of the system is identifying potential track defects. Wheel-mounted sensors measure vibration changes as the train moves. If multiple coaches detect the same abnormal vibration at a location, the system flags that stretch of track for inspection. In critical situations, the system can automatically reduce the speed of the train to about
20 km/h using the braking system, while at the same time alerting the driver through the display unit and notifying maintenance teams.
The technology can predict failures in components such as bearings weeks before breakdowns occur, allowing railway
operators to intervene when early signs of wear are detected. “That helps prevent accidents and save lives while also reducing maintenance costs,” said Woo Seong Seo, Director of Globiz.
For India, the technology has been adapted to withstand harsher operating conditions, including higher vibration levels and integration with multiple telecommunications networks and cloud-based monitoring systems.
