research project - public

Powering Urban Smart Mobility with Data Analytics

The rapid urbanisation and wide adoption of motor vehicles in Guangdong, China has increased traffic and resulted in congestion, loss of productivity, and negative effects on the environment. The project aims to respond to these challenges by using big data analytics to characterise and predict the spatial-temporal (ST) traveller mobility and traffic patterns, to develop data analytics platforms and applications to enhance smart mobility (SM), e.g., public transportation schedules, and seamless connection between public transportation and shared bikes.

Traffic Management
Busy city traffic
Screen showing coding in progress
Our objective
air quality monitoring station

Transport Scheduling

The improved efficiency/ optimised scheduling of public transport, using SM solutions, will benefit the working class who rely on such transports by reducing their cost of travel and trip time. This project will also provide environmental benefits such as reducing congestion and therefore CO2 emission, resulting in better air quality and improving the health of the residents in large cities.


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