Using A Low-Cost Sensor Array and Machine Learning Techniques to Detect Complex Pollutant Mixtures and Identify Likely Sources

An array of low-cost sensors was assembled and tested in a chamber environment wherein several pollutant mixtures were generated. The four classes of sources that were simulated were mobile emissions, biomass burning, natural gas emissions, and gasoline vapors. A two-step regression and classificati...

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Detalles Bibliográficos
Autores principales: Thorson, Jacob, Collier-Oxandale, Ashley, Hannigan, Michael
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2019
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6749282/
https://www.ncbi.nlm.nih.gov/pubmed/31466288
http://dx.doi.org/10.3390/s19173723

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6749282/
https://www.ncbi.nlm.nih.gov/pubmed/31466288
http://dx.doi.org/10.3390/s19173723

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