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Transportation Big Data Simulation Platform for the Greater Toronto Area (GTA)

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Smart City 360° (SmartCity 360 2016, SmartCity 360 2015)

Abstract

This paper presents how big data could be utilized in preparing for smart cities. Within this context, smart cities require intelligent decisions in real time, while processing large amount of data. One big component that relates to smart cities in ITS applications is using artificial intelligent techniques that rely heavily on simulation environments for the evaluation and testing of ITS strategies. In this paper, we present a model for the GTA transportation network. While the model enables big data transportation applications to run in real time, its building process implied intensive work with big data. Within this paper, we show the structure, the calibration, and the outputs of the model. Moreover, some applications, which use the proposed model, are presented. These big data applications are a step towards the smart city of Toronto. Finally, we conclude with some thoughts of future work and the next generation of big data models.

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Correspondence to Islam R. Kamel .

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© 2016 ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering

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Kamel, I.R., Abdelgawad, H., Abdulhai, B. (2016). Transportation Big Data Simulation Platform for the Greater Toronto Area (GTA). In: Leon-Garcia, A., et al. Smart City 360°. SmartCity 360 SmartCity 360 2016 2015. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 166. Springer, Cham. https://doi.org/10.1007/978-3-319-33681-7_37

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  • DOI: https://doi.org/10.1007/978-3-319-33681-7_37

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-33680-0

  • Online ISBN: 978-3-319-33681-7

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