Location via proxy:   [ UP ]  
[Report a bug]   [Manage cookies]                
skip to main content
research-article

Building Occupancy Simulation and Analysis under Virus Scenarios

Published: 28 January 2022 Publication History

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.

References

[1]
Government of Alberta. 2021. Alberta, Canada COVID-19 Safety Guidelines. Retrieved January 17, 20201, from https://www.alberta.ca/prevent-the-spread.aspx.
[2]
buildingSMART International, Ltd. 2021. buildingSMART IFC. Retrieved January 17, 20201, from https://technical.buildingsmart.org/standards/ifc.
[3]
Unity Technologies. 2021. Unity Game Engine. Retrieved January 17, 20201, from https://unity.com/.
[4]
Felipe Aros-Vera, Azadeh Sadeghi, Roohollah Younes Sinaki, and Dusan Sormaz. 2020. A simulation-based framework for checkpoint design in large-scale crowd management: Case study of the papal mass in philadelphia. Safety Science 127 (2020), 104701.
[5]
Eric Bonabeau. 2002. Agent-based modeling: Methods and techniques for simulating human systems. Proceedings of the National Academy of Sciences 99, suppl 3 (2002), 7280–7287.
[6]
Wen-kuei Chang and Tianzhen Hong. 2013. Statistical analysis and modeling of occupancy patterns in open-plan offices using measured lighting-switch data. In Building Simulation, Vol. 6. Springer, 23–32.
[7]
Yixing Chen, Tianzhen Hong, and Xuan Luo. 2018. An agent-based stochastic occupancy simulator. In Building Simulation, Vol. 11. Springer, 37–49.
[8]
Simona D’Oca, H. Burak Gunay, Sara Gilani, and William O’Brien. 2019. Critical review and illustrative examples of office occupant modelling formalisms. Building Services Engineering Research and Technology 40, 6 (2019), 732–757.
[9]
Jakub Wladyslaw Dziedzic, Da Yan, Hongsan Sun, and Vojislav Novakovic. 2020. Building occupant transient agent-based model–Movement module. Applied Energy 261 (2020), 114417.
[10]
Xiaohang Feng, Da Yan, and Tianzhen Hong. 2015. Simulation of occupancy in buildings. Energy and Buildings 87 (2015), 348–359.
[11]
Isabella Gaetani, Pieter-Jan Hoes, and Jan L. M. Hensen. 2016. Occupant behavior in building energy simulation: Towards a fit-for-purpose modeling strategy. Energy and Buildings 121 (2016), 188–204.
[12]
Rhys Goldstein, Alex Tessier, and Azam Khan. 2010. Customizing the behavior of interacting occupants using personas. Proceedings of SimBuild 4, 1 (2010), 252–259.
[13]
H. Burak Gunay, William O’Brien, and Ian Beausoleil-Morrison. 2013. A critical review of observation studies, modeling, and simulation of adaptive occupant behaviors in offices. Building and Environment 70 (2013), 31–47.
[14]
Tianzhen Hong, Yixing Chen, Zsofia Belafi, and Simona D’Oca. 2018. Occupant behavior models: A critical review of implementation and representation approaches in building performance simulation programs. In Building Simulation, Vol. 11. Springer, 1–14.
[15]
Xuan Luo, Khee Poh Lam, Yixing Chen, and Tianzhen Hong. 2017. Performance evaluation of an agent-based occupancy simulation model. Building and Environment 115 (2017), 42–53.
[16]
Ardeshir Mahdavi and Farhang Tahmasebi. 2015. Predicting people’s presence in buildings: An empirically based model performance analysis. Energy and Buildings 86 (2015), 349–355.
[17]
David O’Sullivan and Mordechai Haklay. 2000. Agent-based models and individualism: Is the world agent-based? Environment and Planning A 32, 8 (2000), 1409–1425.
[18]
William O’Brien, Aly Abdelalim, Tareq Abuimara, Ian Beausoleil-Morrison, J. S. Carrizo, R. Danks, and M. Ouf. 2018. Roadmap for occupant modelling in building codes and standards. In Building Performance Simulation Conference. 9–10.
[19]
Jessen Page, Darren Robinson, Nicolas Morel, and J.-L. Scartezzini. 2008. A generalised stochastic model for the simulation of occupant presence. Energy and Buildings 40, 2 (2008), 83–98.
[20]
Nuria Pelechano and Ali Malkawi. 2008. Evacuation simulation models: Challenges in modeling high rise building evacuation with cellular automata approaches. Automation in Construction 17, 4 (2008), 377–385.
[21]
Shide Salimi, Zheng Liu, and Amin Hammad. 2019. Occupancy prediction model for open-plan offices using real-time location system and inhomogeneous Markov chain. Building and Environment 152 (2019), 1–16.
[22]
Davide Schaumann, Simon Breslav, Rhys Goldstein, Azam Khan, and Yehuda E. Kalay. 2017. Simulating use scenarios in hospitals using multi-agent narratives. Journal of Building Performance Simulation 10, 5–6 (2017), 636–652.
[23]
Davide Schaumann, Nirit Putievsky Pilosof, Hadas Sopher, Jacob Yahav, and Yehuda E. Kalay. 2019. Simulating multi-agent narratives for pre-occupancy evaluation of architectural designs. Automation in Construction 106 (2019), 102896.
[24]
Tzu-Sheng Shen. 2005. ESM: A building evacuation simulation model. Building and Environment 40, 5 (2005), 671–680.
[25]
Christoph Sydora and Eleni Stroulia. 2020. Rule-based compliance checking and generative design for building interiors using BIM. Automation in Construction 120 (2020), 103368.
[26]
Christoph Sydora and Eleni Stroulia. 2021. BIM-kit: An extendible toolkit for reasoning about building information models. In 2021 European Conference on Computing in Construction (EC3’21).
[27]
João Virote and Rui Neves-Silva. 2012. Stochastic models for building energy prediction based on occupant behavior assessment. Energy and Buildings 53 (2012), 183–193.
[28]
Chuang Wang, Da Yan, and Yi Jiang. 2011. A novel approach for building occupancy simulation. In Building Simulation, Vol. 4. Springer, 149–167.
[29]
Sebastian Wolf, Davide Calì, Maria Justo Alonso, Rongling Li, Rune Korsholm Andersen, John Krogstie, and Henrik Madsen. 2019. Room-level occupancy simulation model for private households. In Journal of Physics: Conference Series, Vol. 1343. IOP Publishing, 012126.
[30]
Da Yan, William O’Brien, Tianzhen Hong, Xiaohang Feng, H. Burak Gunay, Farhang Tahmasebi, and Ardeshir Mahdavi. 2015. Occupant behavior modeling for building performance simulation: Current state and future challenges. Energy and Buildings 107 (2015), 264–278.

Cited By

View all
  • (2024)Let's Speak Trajectories: A Vision to Use NLP Models for Trajectory Analysis TasksACM Transactions on Spatial Algorithms and Systems10.1145/365647010:2(1-25)Online publication date: 1-Jul-2024

Index Terms

  1. Building Occupancy Simulation and Analysis under Virus Scenarios

      Recommendations

      Comments

      Information & Contributors

      Information

      Published In

      cover image ACM Transactions on Spatial Algorithms and Systems
      ACM Transactions on Spatial Algorithms and Systems  Volume 8, Issue 3
      September 2022
      185 pages
      ISSN:2374-0353
      EISSN:2374-0361
      DOI:10.1145/3512350
      Issue’s Table of Contents

      Publisher

      Association for Computing Machinery

      New York, NY, United States

      Publication History

      Published: 28 January 2022
      Accepted: 01 September 2021
      Revised: 01 September 2021
      Received: 01 April 2021
      Published in TSAS Volume 8, Issue 3

      Permissions

      Request permissions for this article.

      Check for updates

      Author Tags

      1. Occupancy simulation
      2. COVID-19
      3. BIM

      Qualifiers

      • Research-article
      • Refereed

      Funding Sources

      • Natural Science and Engineering Research Council (NSERC)
      • “Dependable Internet of Things Applications” (DITA) CREATE Program

      Contributors

      Other Metrics

      Bibliometrics & Citations

      Bibliometrics

      Article Metrics

      • Downloads (Last 12 months)27
      • Downloads (Last 6 weeks)1
      Reflects downloads up to 30 Aug 2024

      Other Metrics

      Citations

      Cited By

      View all
      • (2024)Let's Speak Trajectories: A Vision to Use NLP Models for Trajectory Analysis TasksACM Transactions on Spatial Algorithms and Systems10.1145/365647010:2(1-25)Online publication date: 1-Jul-2024

      View Options

      Get Access

      Login options

      Full Access

      View options

      PDF

      View or Download as a PDF file.

      PDF

      eReader

      View online with eReader.

      eReader

      Full Text

      View this article in Full Text.

      Full Text

      HTML Format

      View this article in HTML Format.

      HTML Format

      Media

      Figures

      Other

      Tables

      Share

      Share

      Share this Publication link

      Share on social media