Viral Aerosol Concentration Characterization and Detection in Bounded Environments
Al-Naffouri, Tareq Y.
KAUST DepartmentComputer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
Electrical Engineering Program
Computer Science Program
Preprint Posting Date2020-08-10
Permanent link to this recordhttp://hdl.handle.net/10754/664670
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AbstractViral spread has been intermittently threatening human life over time. Characterizing the viral concentration and modelling the viral transmission are, therefore, considered major milestones for enhancing viral detection capabilities. This paper addresses the problem of viral aerosol detection from the exhaled breath in a bounded environment, e.g., a bounded room. The paper models the exhaled breath as a cloud which is emitted through the room, and analyzes the temporal-spatial virus-laden aerosol concentration by accounting for partial absorption and reflection at each side of the room. The paper first derives a closed form expression of the temporal-spatial virus-laden aerosol concentration. It then considers the deployment of a receiver composed of an air sampler and a bio-sensor to detect the viral existence of a specific virus. We, therefore, assess the detection capabilities of the proposed system via evaluating the viral miss-detection probability as a function of the sampling volume and the detection time-instance at the receiver side. Our numerical simulations verify the validity of the analytical results, and illustrate the ability of the proposed system to detect viruses in indoor environments. The results further characterize the impacts of several system parameters on the miss-detection probability.
CitationAmin, O., Dahrouj, H., Almayouf, N., Al-Naffouri, T. Y., Shihada, B., & Alouini, M.-S. (2021). Viral Aerosol Concentration Characterization and Detection in Bounded Environments. IEEE Transactions on Molecular, Biological and Multi-Scale Communications, 1–1. doi:10.1109/tmbmc.2021.3083718
SponsorsThis work was supported by the King Abdullah University of Science and Technology (KAUST). The work of H. Dahrouj was supported by the Center of Excellence for NEOM Research at KAUST.