Crowd Insights


Mobile devices constantly generate movement data in our network.
We divide our network into geographical areas large enough to ensure that individuals cannot be identified. We then irreversibly anonymize this data before aggregating and then extracting it as crowd data.

We analyze the crowd movement between different parts of the city: for example where people commute to and from each day. We also analyze the crowd density in different parts of the city at different times of the day

This provides insights into the way crowds move. For example, it helps city planners and public transport operators to optimize the services they offer and create new services to fulfill unidentified needs.

Journey Analysis

Understanding where and how people travel to and from each day lets transport operators and urban planners make better-informed decisions.

• Identify new public transportation routes to fulfill unmet needs

• Reduce commute and connection times

• Reduce operating costs by matching services and staffing to real needs.

Footfall Analysis

Understanding how many people pass by a given location at a given time helps urban planners to better understand and meet peoples’ needs:

• Understand where to situate public facilities such as car parking, food kiosks, cycle stands
• Identify commuter congestions at transit points and take steps to alleviate and improve the commuting experience
• Understand crowd flow at large-scale events and where to position food stalls, security and toilets

Activity Analysis

When you combine Origin-Destination and Footfall analysis, Interesting patterns begin to emerge. Where people congregate during work hours. During weekends. During sleeping hours.

This is a snapshot of Stockolm divided into sections. The size of the circle in each represents how many people were in each section at the time of measurement.

If we zoom in on the area around Telia head offce in Stockholm, we can see more detailed patterns:

This cell includes our office. Business hours stand out clearly with not much happening over the weekends.

This cell has fewer offices in it and a mall; so the daily peaks are less pronounced. But it also has a stadium – and the football crowds are easy to see. 

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