Calibration of low-cost air pollutant sensors using machine learning techniques
Nowadays concern about air pollution has risen due to the effects of the climate change.The application of machine learning methods for the calibration of low-cost sensors is studied. The short-term, long-term, sensor fusion and training set size needed are analyzed. Thus,considering real scenarios.
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| Tipo de recurso: | tesis de maestría |
| Fecha de publicación: | 2019 |
| País: | España |
| Institución: | Universitat Politècnica de Catalunya (UPC) |
| Repositorio: | UPCommons. Portal del coneixement obert de la UPC |
| Idioma: | inglés |
| OAI Identifier: | oai:upcommons.upc.edu:2117/168918 |
| Acceso en línea: | https://hdl.handle.net/2117/168918 |
| Access Level: | acceso abierto |
| Palabra clave: | Machine learning Detectors Calibration Sensors baix cost contaminació fusió de sensors Low-cost sensors pollution sensor fusion Aprenentatge automàtic Calibratge Àrees temàtiques de la UPC::Informàtica |
| Sumario: | Nowadays concern about air pollution has risen due to the effects of the climate change.The application of machine learning methods for the calibration of low-cost sensors is studied. The short-term, long-term, sensor fusion and training set size needed are analyzed. Thus,considering real scenarios. |
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