This project focuses on the design and implementation of a real-time Passenger Information System (PIS) that leverages live data from onboard passenger counting sensors. The goal is to improve the quality and responsiveness of railway information systems by directly integrating accurate, real-time load data into the Smart-PIS environment.
My primary role in this project was to lead the system design and integration process, ensuring that sensor data feeds are processed, analyzed, and translated into meaningful information for both passengers and railway operators.
Key objectives of the project included:
- Designing a scalable system architecture for sensor-driven passenger information
- Ensuring real-time communication between data sources and display systems
- Supporting dynamic passenger updates (e.g. carriage load, crowd levels)
- Enabling future extensions with predictive models and reporting features
This work contributes to more efficient railway operations and better-informed travel experiences, aligning with modern goals in intelligent transport systems and smart mobility.
My Role
As the lead system designer, I was responsible for:
- Integrating passenger counter sensor data into the Smart-PIS framework
- Defining the data flow and communication architecture
- Developing and testing real-time data processing pipelines
- Collaborating with engineers and domain experts to ensure system reliability
Knowledge Base Team
Lead Researcher:
Professor Baihua Li
Professor of Computer Vision and Machine Learning, Department of Computer Science
Supervisors:
- Professor Qinggang
- Dr. Mohamad Saada
- Dr. Haibin Cai
