People Flow Visualization based on Proximity Networks

Abstract

With the worldwide spread of novel coronavirus (COVID-19), Japanese politicians require people to avoid the“ Three Cs. ” Here, three Cs stands for Crowded places, Close-contact settings and Confined and enclosed spaces. Against this background, there have been a lot of studies that analyze the flow of people and visualize it. It is important to reduce congestion during events, and reducing the proximity of people is particularly effective, in order to prevent the spread of infections. On the other hand, there are a small number of methods to visualize the human flow based on the proximity of people. This paper presents a method to visualize walking patterns with high infection risk based on the network formed by connecting conjunct pedestrians. The effectiveness of theproposed method is confirmed by using data measured at the event site.