Title |
An Intelligent Predictive Analytics System for Transportation Analytics on Open Data Towards the Development of a Smart City |
ID_Doc |
39479 |
Authors |
Audu, ARA; Cuzzocrea, A; Leung, CK; MacLeod, KA; Ohin, NI; Pulgar-Vidal, NC |
Title |
An Intelligent Predictive Analytics System for Transportation Analytics on Open Data Towards the Development of a Smart City |
Year |
2020 |
Published |
|
DOI |
10.1007/978-3-030-22354-0_21 |
Abstract |
As time is a precious asset, bus riders would desire to get accurate information about bus arrival time. Although different research approaches have been developed to correctly predict bus arrival time, very few of them produce highly precise and accurate results based on open data. In this paper, we present an intelligent system designed for transportation analytics on open data such as bus delay data. Specifically, the system accesses open data to analyze public transport data-such as historical bus arrival time-for urban analytics; it then conducts data analytics and mining to discover frequent patterns. Based on the discovered patterns, the system makes predictions on whether the bus arrives on time or is being late. Evaluation on real-life open data provided by a Canadian city show the effectiveness and prediction accuracy of our intelligent system in transportation analytics on open data. The results are encouraging towards the goal of developing smart cities. |
Author Keywords |
Intelligent system; Transportation analytics; Open data; Public transportation; Bus; Bus delay; Data analytics; Frequent pattern mining; Predictive analytics; Smart city |
Index Keywords |
Index Keywords |
Document Type |
Other |
Open Access |
Open Access |
Source |
Conference Proceedings Citation Index - Science (CPCI-S) |
EID |
WOS:000619500800021 |
WoS Category |
Computer Science, Artificial Intelligence; Computer Science, Information Systems; Computer Science, Software Engineering; Computer Science, Theory & Methods |
Research Area |
Computer Science |
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