Inferring Exhaust Gases Levels using Taxi Service and Meteorological Data: An Experiment in the City of Porto, Portugal

Inferring Exhaust Gases Levels using Taxi Service and Meteorological Data: An Experiment in the City of Porto, Portugal

© 2016 IEEE. In this work, we study exhaust gas concentration patterns in Porto, Portugal, and explore techniques to estimate the level of NO2 concentrations using taxi service and meteorological data as sensors. The exploratory analysis revealed daily and seasonal patterns of exhaust gases, with hi...

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Main Authors: Marco Veloso, Pedro M. D'Orey, Santi Phithakkitnukoon, Carlos Bento, Michel Ferreira
Format: Conference Proceeding
Published: 2018
Subjects:
Computer Science
Engineering
Online Access:https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85010047787&origin=inward
http://cmuir.cmu.ac.th/jspui/handle/6653943832/55489
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Institution: Chiang Mai University
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spelling th-cmuir.6653943832-554892018-09-05T02:59:59Z Inferring Exhaust Gases Levels using Taxi Service and Meteorological Data: An Experiment in the City of Porto, Portugal Marco Veloso Pedro M. D'Orey Santi Phithakkitnukoon Carlos Bento Michel Ferreira Computer Science Engineering © 2016 IEEE. In this work, we study exhaust gas concentration patterns in Porto, Portugal, and explore techniques to estimate the level of NO2 concentrations using taxi service and meteorological data as sensors. The exploratory analysis revealed daily and seasonal patterns of exhaust gases, with higher concentrations in the morning and on colder months. Based on nine months of data, we are able to estimate the concentration of NO2 using a multilayer perceptron (r = 0.7358) and linear regression (r = 0.5407). The analysis was extended to estimate NO and NOx, showing a lower performance. 2018-09-05T02:57:09Z 2018-09-05T02:57:09Z 2016-12-22 Conference Proceeding 2-s2.0-85010047787 10.1109/ITSC.2016.7795874 https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85010047787&origin=inward http://cmuir.cmu.ac.th/jspui/handle/6653943832/55489
institution Chiang Mai University
building Chiang Mai University Library
country Thailand
collection CMU Intellectual Repository
topic Computer Science
Engineering
spellingShingle Computer Science
Engineering
Marco Veloso
Pedro M. D'Orey
Santi Phithakkitnukoon
Carlos Bento
Michel Ferreira
Inferring Exhaust Gases Levels using Taxi Service and Meteorological Data: An Experiment in the City of Porto, Portugal
description © 2016 IEEE. In this work, we study exhaust gas concentration patterns in Porto, Portugal, and explore techniques to estimate the level of NO2 concentrations using taxi service and meteorological data as sensors. The exploratory analysis revealed daily and seasonal patterns of exhaust gases, with higher concentrations in the morning and on colder months. Based on nine months of data, we are able to estimate the concentration of NO2 using a multilayer perceptron (r = 0.7358) and linear regression (r = 0.5407). The analysis was extended to estimate NO and NOx, showing a lower performance.
format Conference Proceeding
author Marco Veloso
Pedro M. D'Orey
Santi Phithakkitnukoon
Carlos Bento
Michel Ferreira
author_facet Marco Veloso
Pedro M. D'Orey
Santi Phithakkitnukoon
Carlos Bento
Michel Ferreira
author_sort Marco Veloso
title Inferring Exhaust Gases Levels using Taxi Service and Meteorological Data: An Experiment in the City of Porto, Portugal
title_short Inferring Exhaust Gases Levels using Taxi Service and Meteorological Data: An Experiment in the City of Porto, Portugal
title_full Inferring Exhaust Gases Levels using Taxi Service and Meteorological Data: An Experiment in the City of Porto, Portugal
title_fullStr Inferring Exhaust Gases Levels using Taxi Service and Meteorological Data: An Experiment in the City of Porto, Portugal
title_full_unstemmed Inferring Exhaust Gases Levels using Taxi Service and Meteorological Data: An Experiment in the City of Porto, Portugal
title_sort inferring exhaust gases levels using taxi service and meteorological data: an experiment in the city of porto, portugal
publishDate 2018
url https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85010047787&origin=inward
http://cmuir.cmu.ac.th/jspui/handle/6653943832/55489
_version_ 1681424515274375168

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