Railway Smart Passenger Information System (PIS)

The Railway Smart Passenger Information System (PIS) represents the next generation of traveler-facing technology. By integrating AI-driven passenger loading metrics with dynamic information delivery, we transformed static displays into intelligent, real-time communication hubs.

“The journey is just as important as the destination. Intelligence should be the silent companion of every traveler.”

The Challenge

Traditional railway PIS systems are often static, providing only schedule-based information that doesn’t reflect the real-time state of the train (e.g., carriage occupancy or platform crowding). The challenge was to build an affordable, scalable, and AI-empowered system that delivers personalized information to travelers and actionable insights to operators.

The Solution

In collaboration with TrainFX and Loughborough University as part of a Postdoctoral Research Associate (KTP) initiative, we developed a system that uses Big Data analytics and Computer Vision to redefine the passenger experience.

• Real-Time Occupancy Tracking: Integrated live passenger loading metrics into the TrainFX Smart-PIS, allowing travelers to find quieter carriages.
• Predictive Analytics: Applied short- and mid-term forecasting models to predict demand and operational anomalies.
• Personalized Delivery: Built a framework for delivering hyper-local alerts and transit information directly to passenger devices and station displays.
• Scalable Architecture: Engineered a low-cost, high-impact architecture designed for practical deployment across diverse railway fleets.

Technical Stewardship

This project was guided by leading experts in Computer Vision and Machine Learning:

• Professor Baihua Li (Knowledge Base Lead)
• Professor Qinggang
• Dr. Mohamad Saada & Dr. Haibin Cai

Field Implementation

Impact and Outcomes

The Smart-PIS solution is a first-of-its-kind in the rail industry, offering bespoke customization aligned with modern operational objectives. It has significantly improved service efficiency and passenger satisfaction by turning data into a real-time utility.