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Visualization of Urban Mobility Data from Intelligent Transportation Systems

Intelligent Transportation Systems are an important enabler for the smart cities paradigm. Currently, such systems generate massive amounts of granular data that can be analyzed to better understand people’s dynamics. To address the multivariate nature of spatiotemporal urban mobility data, research...

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Detalles Bibliográficos
Autores principales: Sobral, Thiago, Galvão, Teresa, Borges, José
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6359619/
https://www.ncbi.nlm.nih.gov/pubmed/30650641
http://dx.doi.org/10.3390/s19020332
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author Sobral, Thiago
Galvão, Teresa
Borges, José
author_facet Sobral, Thiago
Galvão, Teresa
Borges, José
author_sort Sobral, Thiago
collection PubMed
description Intelligent Transportation Systems are an important enabler for the smart cities paradigm. Currently, such systems generate massive amounts of granular data that can be analyzed to better understand people’s dynamics. To address the multivariate nature of spatiotemporal urban mobility data, researchers and practitioners have developed an extensive body of research and interactive visualization tools. Data visualization provides multiple perspectives on data and supports the analytical tasks of domain experts. This article surveys related studies to analyze which topics of urban mobility were addressed and their related phenomena, and to identify the adopted visualization techniques and sensors data types. We highlight research opportunities based on our findings.
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spelling pubmed-63596192019-02-06 Visualization of Urban Mobility Data from Intelligent Transportation Systems Sobral, Thiago Galvão, Teresa Borges, José Sensors (Basel) Review Intelligent Transportation Systems are an important enabler for the smart cities paradigm. Currently, such systems generate massive amounts of granular data that can be analyzed to better understand people’s dynamics. To address the multivariate nature of spatiotemporal urban mobility data, researchers and practitioners have developed an extensive body of research and interactive visualization tools. Data visualization provides multiple perspectives on data and supports the analytical tasks of domain experts. This article surveys related studies to analyze which topics of urban mobility were addressed and their related phenomena, and to identify the adopted visualization techniques and sensors data types. We highlight research opportunities based on our findings. MDPI 2019-01-15 /pmc/articles/PMC6359619/ /pubmed/30650641 http://dx.doi.org/10.3390/s19020332 Text en © 2019 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Review
Sobral, Thiago
Galvão, Teresa
Borges, José
Visualization of Urban Mobility Data from Intelligent Transportation Systems
title Visualization of Urban Mobility Data from Intelligent Transportation Systems
title_full Visualization of Urban Mobility Data from Intelligent Transportation Systems
title_fullStr Visualization of Urban Mobility Data from Intelligent Transportation Systems
title_full_unstemmed Visualization of Urban Mobility Data from Intelligent Transportation Systems
title_short Visualization of Urban Mobility Data from Intelligent Transportation Systems
title_sort visualization of urban mobility data from intelligent transportation systems
topic Review
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6359619/
https://www.ncbi.nlm.nih.gov/pubmed/30650641
http://dx.doi.org/10.3390/s19020332
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