论文标题
基于WiFi的人群监控和工作空间计划COVID-19恢复
WiFi-based Crowd Monitoring and Workspace Planning for COVID-19 Recovery
论文作者
论文摘要
COVID-19大流行的恢复阶段需要仔细的计划和监测，而人们逐渐恢复工作。 Things Internet（IoT）被广泛认为是在许多领域和社会中帮助与Covid-19的大流行作斗争的关键工具。特别是，IoT解决方案捕获的异质数据可以为政策制定和对社区活动的快速响应提供信息。本文介绍了一种新型的IoT人群监视解决方案，该解决方案使用软件定义的网络（SDN）辅助WiFi接入点作为24/7传感器来监视和分析物理空间的使用。原型和人群行为模型是使用在大学校园中捕获的5亿张唱片开发的。除了支持机构一级的知情决定外，各个访问者还可以使用这些结果来计划或安排他们对设施的访问。
The recovery phase of the COVID-19 pandemic requires careful planning and monitoring while people gradually return to work. Internet-of-Things (IoT) is widely regarded as a crucial tool to help combating COVID-19 pandemic in many areas and societies. In particular, the heterogeneous data captured by IoT solutions can inform policy making and quick responses to community events. This article introduces a novel IoT crowd monitoring solution which uses software defined networks (SDN) assisted WiFi access points as 24/7 sensors to monitor and analyze the use of physical space. Prototypes and crowd behavior models are developed using over 500 million records captured on a university campus. Besides supporting informed decision at institution level, the results can be used by individual visitors to plan or schedule their access to facilities.
