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Anomalous Taxi Route Detection System Based on Cloud Services

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Cloud Computing, Smart Grid and Innovative Frontiers in Telecommunications (CloudComp 2019, SmartGift 2019)

Abstract

Machine learning is very popular right now. We can apply the knowledge of machine learning to deal with some problems in our daily life. Taxi service provides a convenient way of transportation, especially for those who travel to an unfamiliar place. But there can be a risk that the passenger gets overcharged on the unnecessary mileages. To help the passenger to determine whether the taxi driver has made a detour, we propose a solution which is a cloud-based system and applies machine learning algorithms to detect anomaly taxi trajectory for the passenger. This paper briefly describes the research on several state-of-art detection methods. It also demonstrates the system architecture design in detail and gives the reader a big picture on what parts of the application have been implemented.

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References

  1. Build amazing native apps and progressive web apps with ionic

    Google Scholar 

  2. Welcome to apache hadoop. https://hadoop.apache.org/old/

  3. Chen, C., et al.: iBOAT: isolation-based online anomalous trajectory detection. IEEE Trans. Intell. Transp. Syst. 14(2), 806–818 (2013)

    Article  Google Scholar 

  4. Ge, Y., Xiong, H., Liu, C., Zhou, Z.H.: A taxi driving fraud detection system. In: IEEE 11th International Conference on Data Mining, pp. 181–190 (2011)

    Google Scholar 

  5. Google: [9] google maps APIs - google developers. https://developers.google.com/maps/documentation/

  6. MySQL: Why MySQL? https://www.mysql.com/why-mysql/

  7. Oracle: The Java EE 6 tutorial. https://docs.oracle.com/javaee/6/tutorial/doc/

  8. Oracle: Java EE at a glance. https://www.oracle.com/technetwork/java/javaee/overview/javaee-135128.html

  9. Sillito, R.R., Fisher, R.B.: Semi-supervised learning for anomalous trajectory detection. In: BMVC, vol. 1, pp. 035–1 (2008)

    Google Scholar 

  10. Zhang, D., Li, N., Zhou, Z.H., Chen, C., Sun, L., Li, S.: iBAT: detecting anomalous taxi trajectories from GPS traces. In: ACM 13th International Conference on Ubiquitous Computing, pp. 99–108 (2011)

    Google Scholar 

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Acknowledgement

This work was supported in part by the New Zealand Marsden Fund under Grant No. 17-UOA-248, and the UoA FRDF fund under Grant No. 3714668.

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Correspondence to Yun Luo .

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© 2020 ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering

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Zi, Y., Luo, Y., Guang, Z., Qi, L., Wu, T., Zhang, X. (2020). Anomalous Taxi Route Detection System Based on Cloud Services. In: Zhang, X., Liu, G., Qiu, M., Xiang, W., Huang, T. (eds) Cloud Computing, Smart Grid and Innovative Frontiers in Telecommunications. CloudComp SmartGift 2019 2019. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 322. Springer, Cham. https://doi.org/10.1007/978-3-030-48513-9_20

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  • DOI: https://doi.org/10.1007/978-3-030-48513-9_20

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-48512-2

  • Online ISBN: 978-3-030-48513-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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