Social distancing is a critical tool for mitigating disease transmission, particularly in crowded indoor spaces. In this paper, we contribute by assessing the feasibility of re-purposing existing infrastructure of occupancy monitoring sensors and environmental sensors for the dual purpose of monitoring social distancing and supporting disease transmission risk estimation. We consider 410 continuous days of measurements from CO2 and PIR (passive infrared) motion detectors collected from a collaborative smart space, prior to the start of the pandemic in 2017-2018. We demonstrate how these sensors can be used to estimate occupancy levels, as well as analyze occupancy patterns within the space. We also consider disease transmission risk estimation based on the overall air quality within the space. Based on our analysis, we derive insights into how infrastructure-based sensors can be used to detect problematic areas in the space and offer insights into how to modify these areas to be more social distancing aware.
Original languageEnglish
Title of host publicationIEEE 7th World Forum on Internet of Things (WF-IoT 2021)
Number of pages6
Publication date9 Nov 2021
ISBN (Print)978-1-6654-4432-3
ISBN (Electronic)978-1-6654-4431-6
Publication statusPublished - 9 Nov 2021
MoE publication typeA4 Article in conference proceedings
EventIEEE World Forum on Internet of Things - New Orleans, United States
Duration: 14 Jun 202131 Jul 2021
Conference number: 7

Fields of Science

  • 113 Computer and information sciences

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