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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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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© 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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