The application of the statistical classifying models for signal evaluation of the gas sensors analyzing mold contamination of the building materials

Mold that develops on moistened building barriers is a major cause of the Sick Building Syndrome (SBS). Fungal contamination is normally evaluated using standard biological methods which are time-consuming and require a lot of manual labor. Fungi emit Volatile Organic Compounds (VOC) that can be det...

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Bibliographic Details
Main Authors: Majerek, Dariusz, Guz, Łukasz, Suchorab, Zbigniew, Łagód, Grzegorz, Sobczuk, Henryk
Format: Conference Proceeding
Language:English
Subjects:
Building materials
Construction materials
Contamination
Gas sensors
Physical work
Reference materials
Sensor arrays
Sensors
Sick building syndrome
Signal classification
Statistical methods
VOCs
Volatile organic compounds
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Summary:Mold that develops on moistened building barriers is a major cause of the Sick Building Syndrome (SBS). Fungal contamination is normally evaluated using standard biological methods which are time-consuming and require a lot of manual labor. Fungi emit Volatile Organic Compounds (VOC) that can be detected in the indoor air using several techniques of detection e.g. chromatography. VOCs can be also detected using gas sensors arrays. All array sensors generate particular voltage signals that ought to be analyzed using properly selected statistical methods of interpretation. This work is focused on the attempt to apply statistical classifying models in evaluation of signals from gas sensors matrix to analyze the air sampled from the headspace of various types of the building materials at different level of contamination but also clean reference materials.
ISSN:0094-243X
1551-7616
DOI:10.1063/1.4994504