Sipresk: A Big Data Analytic Platform for Smart Transportation

Hamzeh Khazaei; Saeed Zareian; Rodrigo Veleda; Marin Litoiu

Smart City 360°. First EAI International Summit, Smart City 360°, Bratislava, Slovakia and Toronto, Canada, October 13-16, 2015. Revised Selected Papers

Research Article

Sipresk: A Big Data Analytic Platform for Smart Transportation

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@INPROCEEDINGS{10.1007/978-3-319-33681-7_35,
    author={Hamzeh Khazaei and Saeed Zareian and Rodrigo Veleda and Marin Litoiu},
    title={Sipresk: A Big Data Analytic Platform for Smart Transportation},
    proceedings={Smart City 360°. First EAI International Summit, Smart City 360°, Bratislava, Slovakia and Toronto, Canada, October 13-16, 2015. Revised Selected Papers},
    proceedings_a={SMARTCITY360},
    year={2016},
    month={6},
    keywords={Smart transportation Data analytics platform Traffic data Adaptive systems},
    doi={10.1007/978-3-319-33681-7_35}
}

Hamzeh Khazaei
Saeed Zareian
Rodrigo Veleda
Marin Litoiu
Year: 2016
Sipresk: A Big Data Analytic Platform for Smart Transportation
SMARTCITY360
Springer
DOI: 10.1007/978-3-319-33681-7_35

Hamzeh Khazaei¹^,*, Saeed Zareian¹^,*, Rodrigo Veleda¹^,*, Marin Litoiu¹^,*

1: York University

*Contact email: hkh@yorku.ca, zareian@yorku.ca, rveleda@yorku.ca, litoiu@yorku.ca

Abstract

In this paper, we propose a platform for performing analytics on urban transportation data to gain insights into traffic patterns. The platform consists of data, analytics and management layers and it can be leveraged by overlay traffic-related applications or directly by researchers, traffic engineers and planners. The platform is cluster-based and leverages the cloud to achieve reliability, scalability and adaptivity to the changing operating conditions. It can be leveraged for both on-line and retrospective analysis. We validated several use cases such as finding average speed and congested segments in the major highways in Greater Toronto Area (GTA).

Keywords: Smart transportation Data analytics platform Traffic data Adaptive systems

Published: 2016-06-29
Appears in: SpringerLink

: http://dx.doi.org/10.1007/978-3-319-33681-7_35