WiFi-based Crowd Monitoring and Workspace Planning for COVID-19 Recovery
This addresses the need for real-time crowd monitoring and workspace planning during the pandemic, offering a practical tool for institutions and individuals, though it is incremental in applying existing IoT and WiFi technologies to a new context.
The paper tackled the problem of monitoring crowd behavior for COVID-19 recovery by developing an IoT solution using WiFi access points as sensors, analyzing over 500 million records from a university campus to inform decision-making and visitor planning.
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.