Calibration of low-cost air pollutant sensors using machine learning techniques

Ferrer Cid, Pau

View/Open

143249.pdf (6,022Mb)

View Usage Statistics

Cita com:

Show full item record

Ferrer Cid, Pau

Tutor / directorBarceló Ordinas, José María

; García Vidal, Jorge

Document typeMaster thesis

Date2019-06

Rights accessOpen Access

All rights reserved. This work is protected by the corresponding intellectual and industrial property rights. Without prejudice to any existing legal exemptions, reproduction, distribution, public communication or transformation of this work are prohibited without permission of the copyright holder

Abstract

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.

SubjectsMachine learning, Detectors, Calibration, Aprenentatge automàtic, Detectors, Calibratge

DegreeMÀSTER UNIVERSITARI EN INNOVACIÓ I RECERCA EN INFORMÀTICA (Pla 2012)

URIhttp://hdl.handle.net/2117/168918

Collections

Màsters oficials - Master in Innovation and Research in Informatics - MIRI [371]

View Usage Statistics

Show full item record

Files	Description	Size	Format	View
143249.pdf		6,022Mb	PDF	View/Open

UPCommons. Global access to UPC knowledge

Calibration of low-cost air pollutant sensors using machine learning techniques

View/Open

Browse