Publication Type
Journal Article
Version
acceptedVersion
Publication Date
9-2022
Abstract
Mobile sensing has played a key role in providing digital solutions to aid with COVID-19 containment policies, primarily to automate contact tracing and social distancing measures. As more and more countries reopen from lockdowns, there remains a pressing need to minimize crowd movements and interactions, particularly in enclosed spaces. Many COVID-19 technology solutions leverage positioning systems, generally using Bluetooth and GPS, and can theoretically be adapted to monitor safety compliance within dedicated environments. However, they may not be the ideal modalities for indoor positioning. This article 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 the indoor occupancy spectrum when different COVID-19 policies were enacted. Our work analyzes staff and students’ mobility data from three 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 a practical application for institutional crowd control and discuss the implications of our findings for policymaking.
Keywords
COVID-19, occupancy, mobility, campus, WiFi, analysis, large-scale
Discipline
Databases and Information Systems | Health Information Technology
Research Areas
Information Systems and Management
Publication
ACM Transactions on Spatial Algorithms and Systems
Volume
8
Issue
3
First Page
1
Last Page
26
ISSN
2374-0353
Identifier
10.1145/3516524
Publisher
Association for Computing Machinery (ACM)
Citation
ZAKARIA, Camellia; TRIVEDI, Amee; CECCHET, Emmanuel; CHEE, Michael; SHENOY, Prashant; and BALAN, Rajesh Krishna.
Analyzing the Impact of COVID-19 control policies on campus occupancy and mobility via WiFi sensing. (2022). ACM Transactions on Spatial Algorithms and Systems. 8, (3), 1-26.
Available at: https://ink.library.smu.edu.sg/sis_research/7789
Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-No Derivative Works 4.0 International License.
Additional URL
https://doi.org/10.1145/3516524