Intelligent Predictive Maintenance for Metro Elevators and Escalators

Metro stations' elevators and escalators are essential for passenger safety, accessibility, and service continuity. Unexpected failures not only disrupt operations but can also compromise passenger experience. Current maintenance practices are largely reactive, which leads to high costs and downtime.

This project, proposed in collaboration with Fizix, aims to develop an intelligent predictive maintenance solution using IoT-enabled sensors, LTE/5G communications, and AI-driven analytics. By continuously monitoring critical components such as motors, gears, brakes, and belts, the system can predict failures before they occur, allowing maintenance teams to act proactively.

Key benefits for metro operator companies:

• Reduced maintenance costs and asset lifecycle optimization.

• Improved reliability and safety of elevators and escalators.

• Real-time monitoring and early fault detection through a scalable IoT platform.

• Demonstration of a smart asset management approach that can be extended to other rail infrastructure and rolling stock.

The project envisions creating a collaborative platform for technology partners and end-users to explore innovative predictive maintenance strategies, share data insights, and accelerate the adoption of intelligent asset management across urban rail systems.