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

• Main Author: Fiore, Sandro
• Publication Date: 2019
• Other Authors: Elia, Donatello, Pires, Carlos Eduardo, Mestre, Demetrio Gomes, Cappiello, Cinzia, Vitali, Monica, Andrade, Nazareno, Braz, Tarciso, Lezzi, Daniele, Moraes, Regina, Basso, Tania, Kozievitch, Nadia P., Fonseca, Keiko Veronica Ono, Antunes, Nuno, Vieira, Marco, Palazzo, Cosimo, Blanquer, Ignacio, Meira, Wagner, Aloisio, Giovanni
• Format: Article
• Language: eng
• Source: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
• Download full: http://hdl.handle.net/10316/107013; https://doi.org/10.1109/ACCESS.2019.2936941
• topic: Big data; cloud computing; data analytics; data privacy; data quality; distributed environment; public transport management; smart city

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 ability to extract actionable insights from them. Besides data, full stack (from platform to services and applications) Information and Communications Technology (ICT) solutions need to be speci cally adopted to address smart cities challenges. Smart urban transportation management is one of the key use cases addressed in the context of the EUBra-BIGSEA (Europe-Brazil Collaboration of Big Data Scienti c Research through Cloud-Centric Applications) project. This paper speci cally focuses on the City Administration Dashboard, a public transport analytics application that has been developed on top of the EUBra-BIGSEA platform and used by the Municipality stakeholders of Curitiba, Brazil, to tackle urban traf c data analysis and planning challenges. The solution proposed in this paper joins together a scalable big and fast data analytics platform, a exible and dynamic cloud infrastructure, data quality and entity matching algorithms as well as security and privacy techniques. By exploiting an interoperable programming framework based on Python Application Programming Interface (API), it allows an easy, rapid and transparent development of smart cities applications.