Detection of Airborne Biological Particles in Indoor Air Using a Real-Time Advanced Morphological Parameter UV-LIF Spectrometer and Gradient Boosting Ensemble Decision Tree Classifiers

Detection of Airborne Biological Particles in Indoor Air Using a Real-Time Advanced Morphological Parameter UV-LIF Spectrometer and Gradient Boosting Ensemble Decision Tree Classifiers

We present results from a study evaluating the utility of supervised machine learning to classify single particle ultraviolet laser-induced fluorescence (UV-LIF) signatures to investigate airborne primary biological aerosol particle (PBAP) concentrations in a busy, multifunctional building using a M...

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Bibliographic Details
Main Authors: Ian Crawford, David Topping, Martin Gallagher, Elizabeth Forde, Jonathan R. Lloyd, Virginia Foot, Chris Stopford, Paul Kaye
Format: Article
Language:English
Published: MDPI AG 2020-09-01
Series:Atmosphere
Subjects:
PBAP
biological aerosol
bioaerosol
UV-LIF
supervised machine learning
real-time bioaerosol detection
Online Access:https://www.mdpi.com/2073-4433/11/10/1039

Internet

https://www.mdpi.com/2073-4433/11/10/1039

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