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Developing Relative Humidity and Temperature Corrections for Low-Cost Sensors Using Machine Learning
Existing government air quality monitoring networks consist of static measurement stations, which are highly reliable and accurately measure a wide range of air pollutants, but they are very large, expensive and require significant amounts of maintenance. As a promising solution, low-cost sensors ar...
| Autores principales: | , , , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
MDPI
2021
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8151330/ https://www.ncbi.nlm.nih.gov/pubmed/34065017 http://dx.doi.org/10.3390/s21103338 |