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.
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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).
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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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