Analysis and Visualization of MTR Passenger Behavior During COVID-19

Principal Investigator: Professor Reynold C.K. CHENG (Professor from Department of Computer Science, Associate Director of Musketers Foundation Institute of Data Science and Data Science & Engineering Programme Director)

This project is showcased in the third exhibition – Technology for Future.

About the scholar

Professor Reynold C.K. CHENG

Research interests:
• Big Graph
• Uncertain data management
• Data science for social goods

Email: ckcheng@cs.hku.hk
Website: https://reynold.hku.hk 

Project information
This project aims to study the behaviour of MTR passengers during COVID-19 based on a large set (>325GB) of MTR trip records collected in 2019-2020. An efficient and secure online platform has been built to enable researchers to perform analyses and generate visualizations.
The home screen of the platform appears after logging in and provides the Query and Visualization tools
Project video
Project images
The Query tool allows retrieval of data (grouping and filtering on selected parameters) from the MTR dataset and COVID cases data
Line graph visualization, e.g. Passenger Volume showing number of total trips per day by all MTR passengers
Geospatial visualization using ArcGIS, e.g. Travel Pattern showing the top 10 station pairs with the most trips and COVID cases
Advanced data analysis, e.g. Resilience i.e. rate of recovery from Referenced period (2019) to Selected period (2020)
Other projects
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