The Public Transportation BigData Clustering

Authors

  • Tomislav Galba J.J. Strossmayer University of Osijek Faculty of Electrical Engineering Cara Hadriana 10b, 31000 Osijek, Croatia
  • Zoran Balkić J.J. Strossmayer University of Osijek Faculty of Electrical Engineering Cara Hadriana 10b, 31000 Osijek, Croatia
  • Goran Martinović J.J. Strossmayer University of Osijek Faculty of Electrical Engineering Department of Electromechanical Engineering Cara Hadriana 10b, 31000 Osijek, Croatia

Keywords:

analysis, big data, clustering, GPS, public transportation

Abstract

An increase in the use of GPS modules and cell phones with location services has created a need for new ways of collecting and storing data. Considering a fairly large number of devices, data collected in such way in most cases take up a vast amount of space on servers while on the other hand, they represent a source of very useful information. A large number of companies use this method of data collection in order to create prediction models, reports and data analysis. As an object of observation, we use the database of a modern public transportation system which contains information about vehicle telemetry. In this paper, we will describe the application and result analysis of some well-known clustering algorithms in order to solve public transportation problems like traffic congestion, passenger transport, etc.

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Published

2013-04-01

How to Cite

[1]
T. Galba, Z. Balkić, and G. Martinović, “The Public Transportation BigData Clustering”, IJECES, vol. 4, no. 1, pp. 21-26, Apr. 2013.

Issue

Section

Preliminary Communications