Traders, hotel and catering owners, entrepreneurs, investors, etc. are interested in information on how many shopping visitors pass through a shopping street. They want to have information on where it makes sense to invest.
These actors are strongly interested in evolution and want to be able to compare time intervals. And that's where the EFRO project VLOED comes in.
The project starts with a user survey to be able to respond to the needs and expectations of entrepreneurs.
Through analysis and combination of the already available data sources, not only the current traffic image is displayed but this also leads to useful traffic predictions. Using AI and data science, algorithms are trained that will predict how busy it will be.
This data will be further expanded for both internal and external use and the knowledge and insights gained will be shared with the existing data community and other interested governments and knowledge institutions.
The following figures show real-time data that CrowdScan captures in the city of Bruges. The figure shows the relative crowd density in a timeframe of 10 days.
Here we get real-time information (capacity and measured people counts) about the moment at which the people density was captured.