Monitoring Social Distancing in Smart Spaces using Infrastructure-Based Sensors

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http://hdl.handle.net/10138/336412

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Hossein Motlagh , N , Toivonen , P , Zaidan , M A , Lagerspetz , E , Peltonen , E , Gilman , E , Nurmi , P & Tarkoma , S 2021 , Monitoring Social Distancing in Smart Spaces using Infrastructure-Based Sensors . in IEEE 7th World Forum on Internet of Things (WF-IoT 2021) . IEEE , pp. 124-129 , IEEE World Forum on Internet of Things , New Orleans , United States , 14/06/2021 . https://doi.org/10.1109/WF-IoT51360.2021.9595897

Title: Monitoring Social Distancing in Smart Spaces using Infrastructure-Based Sensors
Author: Hossein Motlagh, Naser; Toivonen, Pupu; Zaidan, Martha Arbayani; Lagerspetz, Eemil; Peltonen, Ella; Gilman, Ekaterina; Nurmi, Petteri; Tarkoma, Sasu
Other contributor: University of Helsinki, Department of Computer Science
University of Helsinki, Department of Computer Science
University of Helsinki, Institute for Atmospheric and Earth System Research (INAR)
University of Helsinki, Department of Computer Science
University of Helsinki, Department of Computer Science
University of Helsinki, Content-Centric Structures and Networking research group / Sasu Tarkoma





Publisher: IEEE
Date: 2021-11-09
Language: eng
Number of pages: 6
Belongs to series: IEEE 7th World Forum on Internet of Things (WF-IoT 2021)
ISBN: 978-1-6654-4432-3
978-1-6654-4431-6
DOI: https://doi.org/10.1109/WF-IoT51360.2021.9595897
URI: http://hdl.handle.net/10138/336412
Abstract: 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.
Subject: 113 Computer and information sciences
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