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Classification of Mold-Infested Buildings Using Gas Sensors Readouts and Support Vector Machine

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21110%2F20%3A00342887" target="_blank" >RIV/68407700:21110/20:00342887 - isvavai.cz</a>

  • Result on the web

    <a href="https://doi.org/10.1063/5.0025889" target="_blank" >https://doi.org/10.1063/5.0025889</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.1063/5.0025889" target="_blank" >10.1063/5.0025889</a>

Alternative languages

  • Result language

    angličtina

  • Original language name

    Classification of Mold-Infested Buildings Using Gas Sensors Readouts and Support Vector Machine

  • Original language description

    Increased humidity of building envelopes frequently leads to the appearance and growth of mold, which is one of the most important factors concerning Sick Building Syndrome evaluation. Detection of Volatile Organic Compounds (VOCs) emitted by the fungi can be performed using gas sensor arrays. Array output in a form of multidimensional electric signals has to be analyzed by means of appropriate statistical methods. The idea presented within this paper is to use Support Vector Machine (SVM) in the classification of the mold-infested buildings because of different admixture of fungal VOCs within their indoor atmosphere. The mappings used by SVM schemes are designed to ensure that dot products of pairs of input data vectors are computed in terms of the variables in the original space, by defining them in terms of a kernel function k(x,y) selected to suit the problem. Using different types of kernel function actual levels of contamination could be assessed based on readouts from a Metal Oxide Semiconductor (MOS) sensors array. SVM method is appropriated for situations where the functional form of the relationship between signals from sensor array and the classes of contamination is unknown or relationship is complex. The ultidimensional sensor readouts pertaining to the air sampled near the building envelopes in varying degree of mold-contamination, compared with clean and synthetic air, are interpreted and presented.

  • Czech name

  • Czech description

Classification

  • Type

    D - Article in proceedings

  • CEP classification

  • OECD FORD branch

    20501 - Materials engineering

Result continuities

  • Project

    <a href="/en/project/GA19-01558S" target="_blank" >GA19-01558S: Effect of Biofilms on Hygrothermal Performance of Building Facades Materials</a><br>

  • Continuities

    P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Others

  • Publication year

    2020

  • Confidentiality

    S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Data specific for result type

  • Article name in the collection

    AIP Conference Proceedings 2275

  • ISBN

    978-0-7354-4005-0

  • ISSN

  • e-ISSN

    1551-7616

  • Number of pages

    5

  • Pages from-to

  • Publisher name

    AIP Publishing, APL, the American Institute of Physics

  • Place of publication

    Melville, NY

  • Event location

    Eger

  • Event date

    Sep 2, 2020

  • Type of event by nationality

    WRD - Celosvětová akce

  • UT code for WoS article