Smart City Use Case – Seoullo 7017

Seoullo 7017

Project Goal

Seoullo 7017 Bridge, Seoul, April 12, 2018: analysis of visitors’ footfall, duration of stay and population density versus holidays and outside temperature correlation, in 4 different parts of the Seoullo 7017 Bridge in Seoul, Korea.

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Key findings

Four LBASense Crowd Analytics sensors were deployed onsite, detecting passively and anonymously mobile phone signals, allowing to count in real-time the number of persons located in four areas of the bridge.

Screenshot from the LBASense Dashboard showing real-time (minute resolution) Crowd Analytics from 4 sensors (numbered from 1 to 4) along the popular touristic Seoullo 7017 bridge in Seoul, Korea.
Screenshot from the LBASense Dashboard showing real-time (minute resolution) Crowd Analytics from 4 sensors (numbered from 1 to 4) along the popular touristic Seoullo 7017 bridge in Seoul, Korea, in April 2018.

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Over the entire winter, the data analysis, from January to March 2018, showed that the temperature had an impact on the decision to have a walk on the touristic bridge.

Results show that people’s behaviour is different from weekends and weekdays, considering additional factors like work and free time as drivers in the decision-making process.

On top of that, warmer temperatures seem to invite people on Seoullo Bridge, increasing the crowd of 50% on average (55% over weekends, 45% over weekdays).

Crowd analytics and Weather data
Crowd analytics and Weather data, Seoullo 7017 Bridge.

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Based on these results, predictions could be built in order to provide tourism businesses such as festival organisers with detailed weather/crowd predictions.

 

Credits: Cover image By 한국어: 분당선M [CC BY-SA 3.0], from Wikimedia Commons; LBASense images © by DFRC, April 2018.


Interested in deploying a similar system to analyse the crowd in your city? Contact us for more information, we will be happy to help.

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