mlsanityData to 13 Oct 2026

ArchABM: an agent-based simulator of human interaction with the built environment. CO2 and viral load analysis for indoor air quality

arXiv 2111.01484 ↗First posted 2 Nov 2021cs.MA cs.AI cs.CYcited by 0

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Abstract (arXiv)

Recent evidence suggests that SARS-CoV-2, which is the virus causing a global pandemic in 2020, is predominantly transmitted via airborne aerosols in indoor environments. This calls for novel strategies when assessing and controlling a building's indoor air quality (IAQ). IAQ can generally be controlled by ventilation and/or policies to regulate human-building-interaction. However, in a building, occupants use rooms in different ways, and it may not be obvious which measure or combination of measures leads to a cost- and energy-effective solution ensuring good IAQ across the entire building. Therefore, in this article, we introduce a novel agent-based simulator, ArchABM, designed to assist in creating new or adapt existing buildings by estimating adequate room sizes, ventilation parameters and testing the effect of policies while taking into account IAQ as a result of complex human-building interaction patterns. A recently published aerosol model was adapted to calculate time-dependent carbon dioxide (CO2) and virus quanta concentrations in each room and inhaled CO2 and virus quanta for each occupant over a day as a measure of physiological response. ArchABM is flexible regarding the aerosol model and the building layout due to its modular architecture, which allows implementing further models, any number and size of rooms, agents, and actions reflecting human-building interaction patterns. We present a use case based on a real floor plan and working schedules adopted in our research center. This study demonstrates how advanced simulation tools can contribute to improving IAQ across a building, thereby ensuring a healthy indoor environment.

Key facts. No citing papers in the map yet (data through 13 Oct 2026). Builds on 7 of its 67 references that are in the map. First posted on arXiv 2 Nov 2021.

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7 of 67 references.

References · 7

  1. 2020COVID-ABS: An Agent-Based Model of COVID-19 Epidemic to Simulate Health and Economic Effects of Social Distancing Interventionscited by 18
  2. 2020Modelling transmission and control of the COVID-19 pandemic in Australiacited by 10
  3. 2020How to restart? An agent-based simulation model towards the definition of strategies for COVID-19 "second phase" in public buildingscited by 3
  4. 2020Indoor Air Quality Improvementcited by 3
  5. 2020Modelling COVID-19 transmission in supermarkets using an agent-based modelcited by 2
  6. 2016Dynamic Bayesian Networks to simulate occupant behaviours in office buildings related to indoor air qualitycited by 1
  7. 2020EXPOSED: An occupant exposure model for confined spaces to retrofit crowd models during a pandemiccited by 1

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