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An Integrated Big and Fast Data Analytics Platform for Smart Urban Transportation Management

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An Integrated Big and Fast Data Analytics Platform for Smart Urban Transportation Management

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Fiore, S.; Elia, D.; Pires, CE.; Mestre, DG.; Cappiello, C.; Vitali, M.; Andrade, N.... (2019). An Integrated Big and Fast Data Analytics Platform for Smart Urban Transportation Management. IEEE Access. 7:117652-117677. https://doi.org/10.1109/ACCESS.2019.2936941

Por favor, use este identificador para citar o enlazar este ítem: http://hdl.handle.net/10251/139363

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Título: An Integrated Big and Fast Data Analytics Platform for Smart Urban Transportation Management
Autor: Fiore, Sandro Elia, Donatello Pires, Carlos E. Mestre, Demetrio Gomes Cappiello, Cinzia Vitali, Monica Andrade, Nazareno Braz, Tarciso Lezzi, Daniele Moraes, Regina Basso, Tania Kozievitch, Nadia P. Ono Fonseca, Keiko Veronica Antunes, Nuno Vieira, Marco Palazzo, Cosimo Blanquer Espert, Ignacio
Entidad UPV: Universitat Politècnica de València. Departamento de Sistemas Informáticos y Computación - Departament de Sistemes Informàtics i Computació
Fecha difusión:
Resumen:
[EN] Smart urban transportation management can be considered as a multifaceted big data challenge. It strongly relies on the information collected into multiple, widespread, and heterogeneous data sources as well as on the ...[+]
Palabras clave: Big data , Cloud computing , Data analytics , Data privacy , Data quality , Distributed environment , Public transport management , Smart city
Derechos de uso: Reconocimiento (by)
Fuente:
IEEE Access. (eissn: 2169-3536 )
DOI: 10.1109/ACCESS.2019.2936941
Editorial:
Institute of Electrical and Electronics Engineers
Versión del editor: https://doi.org/10.1109/ACCESS.2019.2936941
Código del Proyecto:
info:eu-repo/grantAgreement/EC/H2020/690116/EU/EUrope-BRAzil Collaboration on BIG Data Scientific REsearch through Cloud-Centric Applications/
Descripción: (c) 20xx IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/ republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works.
Agradecimientos:
This work was supported by the European Commission through the Cooperation Programme under EUBra-BIGSEA Horizon 2020 Grant [Este projeto e resultante da 3a Chamada Coordenada BR-UE em Tecnologias da Informacao e Comunicacao ...[+]
Tipo: Artículo

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