Clustering of public transport operation using K-means

Abdul Kadir Rabiah, Yasuki Shima, Riza Sulaiman, Fathelalem Ali

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

This paper describes a methodology for analysing the operation of transport buses, using a simplified generic approach. In recent years, location systems that utilize GPS data have become widespread, including their use for monitoring the operation of buses. In this paper, we simplify the bus routes, monitoring process, present new insights using K-means, and enhance their effectiveness. The primary focus of this work is data collection, subsequent data analysis and reporting, for use in schedule adjustments and resource allocation. The experimental data for this study is obtained from the operation of public transport buses at the main campus of Universiti Kebangsaan Malaysia (UKM), where several buses operate on a 30-minute interval over three different concurrent routes. The proposed approach to data analysis is based on three attributes of the data being collected, namely time, volume and quality. The effectiveness of the proposed approach described and discussed.

Original languageEnglish
Title of host publication2018 IEEE 3rd International Conference on Big Data Analysis, ICBDA 2018
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages427-432
Number of pages6
ISBN (Electronic)9781538647936
DOIs
Publication statusPublished - 25 May 2018
Event3rd IEEE International Conference on Big Data Analysis, ICBDA 2018 - Shanghai, China
Duration: 9 Mar 201812 Mar 2018

Other

Other3rd IEEE International Conference on Big Data Analysis, ICBDA 2018
CountryChina
CityShanghai
Period9/3/1812/3/18

Fingerprint

Process monitoring
Resource allocation
Global positioning system
Bus
K-means
Clustering
Public transport
Monitoring
Malaysia
Schedule
Data collection
Methodology

Keywords

  • Big Data Analysis
  • GPS
  • Internet of Things
  • K-means
  • Visualisation

ASJC Scopus subject areas

  • Information Systems
  • Information Systems and Management

Cite this

Rabiah, A. K., Shima, Y., Sulaiman, R., & Ali, F. (2018). Clustering of public transport operation using K-means. In 2018 IEEE 3rd International Conference on Big Data Analysis, ICBDA 2018 (pp. 427-432). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICBDA.2018.8367721

Clustering of public transport operation using K-means. / Rabiah, Abdul Kadir; Shima, Yasuki; Sulaiman, Riza; Ali, Fathelalem.

2018 IEEE 3rd International Conference on Big Data Analysis, ICBDA 2018. Institute of Electrical and Electronics Engineers Inc., 2018. p. 427-432.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Rabiah, AK, Shima, Y, Sulaiman, R & Ali, F 2018, Clustering of public transport operation using K-means. in 2018 IEEE 3rd International Conference on Big Data Analysis, ICBDA 2018. Institute of Electrical and Electronics Engineers Inc., pp. 427-432, 3rd IEEE International Conference on Big Data Analysis, ICBDA 2018, Shanghai, China, 9/3/18. https://doi.org/10.1109/ICBDA.2018.8367721
Rabiah AK, Shima Y, Sulaiman R, Ali F. Clustering of public transport operation using K-means. In 2018 IEEE 3rd International Conference on Big Data Analysis, ICBDA 2018. Institute of Electrical and Electronics Engineers Inc. 2018. p. 427-432 https://doi.org/10.1109/ICBDA.2018.8367721
Rabiah, Abdul Kadir ; Shima, Yasuki ; Sulaiman, Riza ; Ali, Fathelalem. / Clustering of public transport operation using K-means. 2018 IEEE 3rd International Conference on Big Data Analysis, ICBDA 2018. Institute of Electrical and Electronics Engineers Inc., 2018. pp. 427-432
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