Title: An infrastructure model for smart cities based on big data

Authors: Eliza H.A. Gomes; Mario A.R. Dantas; Douglas D.J. De Macedo; Carlos R. De Rolt; Julio Dias; Luca Foschini

Addresses: Department of Informatics and Statistics (INE), Federal University of Santa Catarina (UFSC), Florianópolis, SC, Brazil ' Department of Computer Science (DCC), Federal University of Juiz de Fora (UFJF), Juiz de Fora, MG, Brazil ' Department of Information Science (CIN), Federal University of Santa Catarina (UFSC), Florianópolis, SC, Brazil ' Centre of Management and Socioeconomic Science (ESAG), State University of Santa Catarina (UDESC), Florianópolis, SC, Brazil ' Centre of Management and Socioeconomic Science (ESAG), State University of Santa Catarina (UDESC), Florianópolis, SC, Brazil ' Department of Computer Science Engineering (DISI), University of Bologna (UNIBO), Bologna, Italy

Abstract: The massive amount of data generated in projects focused on smart cities creates a degree of complexity in how to manage all this information. In attention to solve this problem, several approaches have been developed in recent years. In this paper we propose an infrastructure model for big data for a smart city project. The goal of this model is to present the stages for the processing of data in the steps of extraction, storage, processing and visualisation, as well as the types of tools needed for each phase. To implement our proposed model, we used the ParticipACT Brazil, which is a project based in smart cities. This project uses different databases to compose its big data and uses this data to solve urban problems. We observe that our model provides a structured vision of the software to be used in big data server of ParticipACT Brazil.

Keywords: big data; smart city; big data tools.

DOI: 10.1504/IJGUC.2018.095435

International Journal of Grid and Utility Computing, 2018 Vol.9 No.4, pp.322 - 332

Available online: 17 Sep 2018 *

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