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Real-Time Risk Assessment of Airborne Diseases
dc.contributor.authorKeener, Jacob
dc.contributor.authorFaktor, Robert
dc.contributor.authorHoelscher, Andrew
dc.contributor.authorScilken, Michael
dc.contributor.advisorKaviany, Massoud
dc.date.accessioned2022-05-19T17:38:25Z
dc.date.available2022-05-19T17:38:25Z
dc.date.issued2022-05
dc.identifier.urihttps://hdl.handle.net/2027.42/172472en
dc.descriptionME450 Capstone Design and Manufacturing Experience: Fall 2021en_US
dc.description.abstractCurrent models of the risk of COVID-19 and other airborne infections often are inaccessible to those without a scientific background, rely on assumptions that are not always accurate, and do not provide confidence intervals. This project created a smartphone app design that is able to provide users with a means to determine their risk of infection of airborne diseases with confidence intervals for any room. This was accomplished by using a Dose-Response along with simple and qualitative user inputs (e.g., room geometry, ventilation, number of occupants) to output a probability of infection with confidence intervals.en_US
dc.description.sponsorshipProfessor Jesse Capecelatro: Mechanical Engineering at University of Michiganen_US
dc.language.isoen_USen_US
dc.subjectME450en_US
dc.subjectCOVID-19en_US
dc.subjectphone appen_US
dc.subjectfluid mechanicsen_US
dc.subjectmodellingen_US
dc.titleReal-Time Risk Assessment of Airborne Diseasesen_US
dc.typeProjecten_US
dc.subject.hlbsecondlevelMechanical Engineering
dc.subject.hlbtoplevelEngineering
dc.contributor.affiliationumMechanical Engineering, Department ofen_US
dc.contributor.affiliationumcampusAnn Arbor
dc.description.bitstreamurlhttp://deepblue.lib.umich.edu/bitstream/2027.42/172472/1/Team11-RealTimeRiskAssesmentofAirborneDiseases.pdf
dc.identifier.doihttps://dx.doi.org/10.7302/4501
dc.working.doi10.7302/4501en_US
dc.owningcollnameMechanical Engineering, Department of


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