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TrafficWatch: Real-Time Traffic Incident Detection and Monitoring Using Social Media

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Advances in Knowledge Discovery and Data Mining (PAKDD 2016)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 9651))

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Abstract

Social media has become a valuable source of real-time information. Transport Management Centre (TMC) in Australian state government of New South Wales has been collaborating with us to develop TrafficWatch, a system that leverages Twitter as a channel for transport network monitoring, incident and event managements. This system utilises advanced web technologies and state-of-the-art machine learning algorithms. The crawled tweets are first filtered to show incidents in Australia, and then divided into different groups by online clustering and classification algorithms. Findings from the use of TrafficWatch at TMC demonstrated that it has strong potential to report incidents earlier than other data sources, as well as identifying unreported incidents. TrafficWatch also shows its advantages in improving TMC’s network monitoring capabilities to assess network impacts of incidents and events.

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Notes

  1. 1.

    http://www.transport.nsw.gov.au/tmc.

  2. 2.

    https://about.twitter.com/company.

  3. 3.

    http://nlp.stanford.edu/software/corenlp.shtml.

  4. 4.

    http://nlp.stanford.edu/software/tagger.shtml.

  5. 5.

    http://brat.nlplab.org/.

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Author information

Authors and Affiliations

  1. National ICT Australia, Eveleigh, NSW, 2015, Australia

    Hoang Nguyen, Paul Rivera & Fang Chen

  2. Advanced Analytics Institute, University of Technology Sydney, Sydney, Australia

    Wei Liu

Authors
  1. Hoang Nguyen
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  2. Wei Liu
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  3. Paul Rivera
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  4. Fang Chen
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Corresponding author

Correspondence to Hoang Nguyen .

Editor information

Editors and Affiliations

  1. The University of Melbourne, Melbourne, Victoria, Australia

    James Bailey

  2. The University of Texas at Dallas, Richardson, Texas, USA

    Latifur Khan

  3. Osaka University, Osaka, Japan

    Takashi Washio

  4. University of Auckland, Auckland, New Zealand

    Gill Dobbie

  5. Shenzhen University, Shenzhen, China

    Joshua Zhexue Huang

  6. Massey University, Auckland, New Zealand

    Ruili Wang

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© 2016 Springer International Publishing Switzerland

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Nguyen, H., Liu, W., Rivera, P., Chen, F. (2016). TrafficWatch: Real-Time Traffic Incident Detection and Monitoring Using Social Media. In: Bailey, J., Khan, L., Washio, T., Dobbie, G., Huang, J., Wang, R. (eds) Advances in Knowledge Discovery and Data Mining. PAKDD 2016. Lecture Notes in Computer Science(), vol 9651. Springer, Cham. https://doi.org/10.1007/978-3-319-31753-3_43

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  • DOI: https://doi.org/10.1007/978-3-319-31753-3_43

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-31752-6

  • Online ISBN: 978-3-319-31753-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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