Building Occupancy Simulation and Analysis under Virus Scenarios
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Published:2022-01-28
Issue:3
Volume:8
Page:1-20
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ISSN:2374-0353
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Container-title:ACM Transactions on Spatial Algorithms and Systems
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language:en
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Short-container-title:ACM Trans. Spatial Algorithms Syst.
Author:
Sydora Christoph1ORCID,
Nawaz Faiza1,
Bindra Leepakshi1ORCID,
Stroulia Eleni1
Affiliation:
1. University of Alberta, Canada
Abstract
During the COVID-19 pandemic, regulations on building usage and occupancy density were brought to the forefront, as research indicated that transmission was most likely to occur in indoor environments. Public health officials and building managers had to decide how to best use their buildings while curtailing the infection risk for their occupants.
In this article, we present a systematic simulation-based methodology for estimating the infection risk for a building’s occupants under different scenarios of building usage. We have evaluated our simulations against some real-world building usage data from a university campus building; our experiments demonstrate the realism of our simulations. Based on this finding, we have developed a virus transmission model that estimates the potential infection transmission risk given the behaviors of a building’s occupants. Our methodology enables building managers to simulate alternative building usage scenarios and estimate their relative infection transmission risk. We argue that such risk estimate comparisons can be useful in making decision about alternative building usage options.
Funder
Natural Science and Engineering Research Council
“Dependable Internet of Things Applications” (DITA) CREATE Program
Publisher
Association for Computing Machinery (ACM)
Subject
Discrete Mathematics and Combinatorics,Geometry and Topology,Computer Science Applications,Modeling and Simulation,Information Systems,Signal Processing
Reference30 articles.
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