Mobile sensing has played a key role in providing digital solutions to aid with COVID-19 containment policies. These solutions include, among other efforts, enforcing social distancing and monitoring crowd movements in indoor spaces. However, such solutions may not be effective without mass adoption. As more and more countries reopen from lockdowns, there remains a pressing need to minimize crowd movements and interactions, particularly in enclosed spaces. This paper conjectures that analyzing user occupancy and mobility via deployed WiFi infrastructure can help institutions monitor and maintain safety compliance according to the public health guidelines. Using smartphones as a proxy for user location, our analysis demonstrates how coarse-grained WiFi data can sufficiently reflect indoor occupancy spectrum when different COVID-19 policies were enacted. Our work analyzes staff and students' mobility data from three different university campuses. Two of these campuses are in Singapore, and the third is in the Northeastern United States. Our results show that online learning, split-team, and other space management policies effectively lower occupancy. However, they do not change the mobility for individuals transitioning between spaces. We demonstrate how this data source can be put to practical application for institutional crowd control and discuss the implications of our findings for policy-making.
翻译:移动遥感在提供数字解决方案以帮助实施COVID-19遏制政策方面发挥了关键作用,这些解决方案包括,除其他努力外,在室内空间加强社会疏远和监测人群流动;然而,如果不大规模采用,这些解决方案可能不会有效。随着越来越多的国家重新关闭,仍然迫切需要最大限度地减少人群流动和互动,特别是在封闭空间。通过已部署的WiFi基础设施分析用户占用和流动情况的文件推测有助于各机构根据公共卫生准则监测和保持安全合规性。使用智能手机作为用户位置的代用工具,我们的分析表明,在颁布不同的COVID-19政策时,粗糙的WiFi数据如何能充分反映室内占用频谱。我们的工作分析了三个不同大学校园的工作人员和学生的流动数据。其中两个校园位于新加坡,第三个校园位于美国东北部。我们的结果显示,在线学习、分队和其他空间管理政策可以有效地降低占用率。但是,它们并没有改变个人在空间之间过渡的流动性。我们展示了如何将这一数据源用于实际应用,以便进行机构人群控制,并讨论我们发现的影响。