An analysis of Bicing mobility patterns using big data

Nowadays, technology advances really fast and so does the generation of data. Almost all electronic devices are constantly generating and sharing a huge amount of data through the World Wide Web. Moreover, recent policies of open governments and data, are helping to make available this information f...

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Detalles Bibliográficos
Autor: Manchón Contreras, Oriol
Tipo de recurso: tesis de maestría
Fecha de publicación:2016
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:2117/103163
Acceso en línea:https://hdl.handle.net/2117/103163
Access Level:acceso abierto
Palabra clave:Big data
Bicycle commuting
big
data
bicing
mobility
patterns
Macrodades
Desplaçaments en bicicleta
Àrees temàtiques de la UPC::Enginyeria civil
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spelling An analysis of Bicing mobility patterns using big dataManchón Contreras, OriolBig dataBicycle commutingbigdatabicingmobilitypatternsMacrodadesDesplaçaments en bicicletaÀrees temàtiques de la UPC::Enginyeria civilNowadays, technology advances really fast and so does the generation of data. Almost all electronic devices are constantly generating and sharing a huge amount of data through the World Wide Web. Moreover, recent policies of open governments and data, are helping to make available this information for everybody that wants to take it and use it. The aim of using Big Data is to discover knowledge that is hidden behind thousands of rows of information. However, to find out the value of the data, it is necessary to use non-traditional methods able to deal with such amount of information. Furthermore, big cities have traffic problems and complex mobility patterns which need to be studied in depth to improve life conditions of citizens, reduce pollution and to create eco-friendly cities. This work is focused on the city of Barcelona and its bike-sharing system Bicing. The aim is to understand the mobility patterns of Bicing subscribers using Big Data. Treating Big Data requires of more resources than conventional problems. So that, setting a methodology to acquire, pre-process and treat the data has been necessary before proceeding with the analysis. In order to gain visibility out of the data, two different approaches have been followed. First of all, an exploratory analysis of the behaviour of the users of Bicing. On the other hand, a Principal Component Analysis has also been carried out to understand the data but also to reduce the dimensionality, hence the volume of the data necessary to provide acceptable results. To sum up, the present work is a particular example of the possibilities that Big Data offers in terms of gaining knowledge out of massive amounts of data. Moreover, it studies the patterns of Bicing subscribers during different periods of the day, week and year based on real data.Universitat Politècnica de CatalunyaArroyo Balaguer, Marino20162016-06-2320172017-03-31master thesishttp://purl.org/coar/resource_type/c_bdccNAhttp://purl.org/coar/version/c_be7fb7dd8ff6fe43info:eu-repo/semantics/masterThesisapplication/pdfhttps://hdl.handle.net/2117/103163reponame:UPCommons. Portal del coneixement obert de la UPCinstname:Universitat Politècnica de Catalunya (UPC)Inglésengopen accesshttp://purl.org/coar/access_right/c_abf2Attribution 3.0 Spainhttp://creativecommons.org/licenses/by/3.0/es/info:eu-repo/semantics/openAccessoai:upcommons.upc.edu:2117/1031632026-05-27T15:37:01Z
dc.title.none.fl_str_mv An analysis of Bicing mobility patterns using big data
title An analysis of Bicing mobility patterns using big data
spellingShingle An analysis of Bicing mobility patterns using big data
Manchón Contreras, Oriol
Big data
Bicycle commuting
big
data
bicing
mobility
patterns
Macrodades
Desplaçaments en bicicleta
Àrees temàtiques de la UPC::Enginyeria civil
title_short An analysis of Bicing mobility patterns using big data
title_full An analysis of Bicing mobility patterns using big data
title_fullStr An analysis of Bicing mobility patterns using big data
title_full_unstemmed An analysis of Bicing mobility patterns using big data
title_sort An analysis of Bicing mobility patterns using big data
dc.creator.none.fl_str_mv Manchón Contreras, Oriol
author Manchón Contreras, Oriol
author_facet Manchón Contreras, Oriol
author_role author
dc.contributor.none.fl_str_mv Arroyo Balaguer, Marino
dc.subject.none.fl_str_mv Big data
Bicycle commuting
big
data
bicing
mobility
patterns
Macrodades
Desplaçaments en bicicleta
Àrees temàtiques de la UPC::Enginyeria civil
topic Big data
Bicycle commuting
big
data
bicing
mobility
patterns
Macrodades
Desplaçaments en bicicleta
Àrees temàtiques de la UPC::Enginyeria civil
description Nowadays, technology advances really fast and so does the generation of data. Almost all electronic devices are constantly generating and sharing a huge amount of data through the World Wide Web. Moreover, recent policies of open governments and data, are helping to make available this information for everybody that wants to take it and use it. The aim of using Big Data is to discover knowledge that is hidden behind thousands of rows of information. However, to find out the value of the data, it is necessary to use non-traditional methods able to deal with such amount of information. Furthermore, big cities have traffic problems and complex mobility patterns which need to be studied in depth to improve life conditions of citizens, reduce pollution and to create eco-friendly cities. This work is focused on the city of Barcelona and its bike-sharing system Bicing. The aim is to understand the mobility patterns of Bicing subscribers using Big Data. Treating Big Data requires of more resources than conventional problems. So that, setting a methodology to acquire, pre-process and treat the data has been necessary before proceeding with the analysis. In order to gain visibility out of the data, two different approaches have been followed. First of all, an exploratory analysis of the behaviour of the users of Bicing. On the other hand, a Principal Component Analysis has also been carried out to understand the data but also to reduce the dimensionality, hence the volume of the data necessary to provide acceptable results. To sum up, the present work is a particular example of the possibilities that Big Data offers in terms of gaining knowledge out of massive amounts of data. Moreover, it studies the patterns of Bicing subscribers during different periods of the day, week and year based on real data.
publishDate 2016
dc.date.none.fl_str_mv 2016
2016-06-23
2017
2017-03-31
dc.type.none.fl_str_mv master thesis
http://purl.org/coar/resource_type/c_bdcc
NA
http://purl.org/coar/version/c_be7fb7dd8ff6fe43
dc.type.openaire.fl_str_mv info:eu-repo/semantics/masterThesis
format masterThesis
dc.identifier.none.fl_str_mv https://hdl.handle.net/2117/103163
url https://hdl.handle.net/2117/103163
dc.language.none.fl_str_mv Inglés
eng
language_invalid_str_mv Inglés
language eng
dc.rights.none.fl_str_mv open access
http://purl.org/coar/access_right/c_abf2
Attribution 3.0 Spain
http://creativecommons.org/licenses/by/3.0/es/
dc.rights.openaire.fl_str_mv info:eu-repo/semantics/openAccess
rights_invalid_str_mv open access
http://purl.org/coar/access_right/c_abf2
Attribution 3.0 Spain
http://creativecommons.org/licenses/by/3.0/es/
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Universitat Politècnica de Catalunya
publisher.none.fl_str_mv Universitat Politècnica de Catalunya
dc.source.none.fl_str_mv reponame:UPCommons. Portal del coneixement obert de la UPC
instname:Universitat Politècnica de Catalunya (UPC)
instname_str Universitat Politècnica de Catalunya (UPC)
reponame_str UPCommons. Portal del coneixement obert de la UPC
collection UPCommons. Portal del coneixement obert de la UPC
repository.name.fl_str_mv
repository.mail.fl_str_mv
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