Data-driven control of COVID-19 in buildings: a reinforcement-learning approach

In addition to its public health crisis, COVID-19 pandemic has led to the shutdown and closure of workplaces with an estimated total cost of more than $16 trillion. Given the long hours an average person spends in buildings and indoor environments, this research article proposes data-driven control...

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Bibliographic Details
Published inarXiv.org
Main Authors Ashkan Haji Hosseinloo, Nabi, Saleh, Hosoi, Anette, Dahleh, Munther A
Format Paper
LanguageEnglish
Published Ithaca Cornell University Library, arXiv.org 27.12.2022
Subjects
Air flow
Algorithms
Antiseptics
Buildings
Coronaviruses
COVID-19
Indoor environments
Machine learning
Optimization
Pathogens
Public health
Shutdowns
Urban environments
Velocity distribution
Viral diseases
Workplaces
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Summary:In addition to its public health crisis, COVID-19 pandemic has led to the shutdown and closure of workplaces with an estimated total cost of more than $16 trillion. Given the long hours an average person spends in buildings and indoor environments, this research article proposes data-driven control strategies to design optimal indoor airflow to minimize the exposure of occupants to viral pathogens in built environments. A general control framework is put forward for designing an optimal velocity field and proximal policy optimization, a reinforcement learning algorithm is employed to solve the control problem in a data-driven fashion. The same framework is used for optimal placement of disinfectants to neutralize the viral pathogens as an alternative to the airflow design when the latter is practically infeasible or hard to implement. We show, via simulation experiments, that the control agent learns the optimal policy in both scenarios within a reasonable time. The proposed data-driven control framework in this study will have significant societal and economic benefits by setting the foundation for an improved methodology in designing case-specific infection control guidelines that can be realized by affordable ventilation devices and disinfectants.
ISSN:2331-8422