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A Quality Analysis Method for the Fuel-level Data of IOV

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Internet of Vehicles - Safe and Intelligent Mobility (IOV 2015)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 9502))

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Abstract

With the development of Internet of Vehicles (IOV), data mining on vehicle running status data has been a hot field of research, and the data quality has an important effect to the result of data mining. In this paper, we have investigated the problem of multidimensional analysis of vehicle running state data, especially the abnormal fuel-level data. In order to screen out the vehicles with abnormal sensors or equipments and evaluate the credibility of the data, we propose a bayesian classification algorithm to efficiently assess the data quality and screen out the abnormal vehicles in our database, with coefficient of variance (COV) and dispensation (COD) as feature attributes. Moreover, the accuracy indicators F-score and PPV of the classifier are used to determine the optimal threshold of the classifier. Our experiments on large real datasets show the feasibility and practical utility of proposed methods.

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Acknowledgments

This research is supported by the National Natural Science Foundation of China under Grant No. 91118008, and the Foundation of Key Laboratory of Road and Traffic Engineering of the Ministry of Education in Tongji University.

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Authors and Affiliations

  1. Beijing Key Laboratory for Cooperative Vehicle Infrastructure Systems and Safety Control, School of Transportation Science and Engineering, Beihang University, Beijing, 100191, China

    Daxin Tian, Yukai Zhu & Jian Wang

  2. Research Institute of Highway Ministry Transport, Beijing, 100088, China

    Haiying Xia

  3. The Quartermaster Equipment Institute of the General Logistics Department of CPLA, Beijing, 100010, China

    He Liu

  4. Key Laboratory of Urban ITS Technology Optimization and Integration, The Ministry of Public Security of China, Hefei, China

    Daxin Tian

  5. Jiangsu Province Collaborative Innovation Center of Modern Urban Traffic Technologies, Beijing, 100191, China

    Daxin Tian

Authors
  1. Daxin Tian
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  2. Yukai Zhu
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  3. Haiying Xia
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  4. Jian Wang
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  5. He Liu
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Corresponding author

Correspondence to Haiying Xia .

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Editors and Affiliations

  1. Department of Computer Science, Chung Hua University, Hsinchu, Taiwan, Taiwan

    Ching-Hsien Hsu

  2. School of Software, Dalian University of Technology, Dalian, China

    Feng Xia

  3. School of Electronic Engineering, University of Electronic Science and Tec, Chengdu, Sichuan, China

    Xingang Liu

  4. Network Technology Institute, Beijing University of Posts & Telec, Beijing, China

    Shangguang Wang

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Tian, D., Zhu, Y., Xia, H., Wang, J., Liu, H. (2015). A Quality Analysis Method for the Fuel-level Data of IOV. In: Hsu, CH., Xia, F., Liu, X., Wang, S. (eds) Internet of Vehicles - Safe and Intelligent Mobility. IOV 2015. Lecture Notes in Computer Science(), vol 9502. Springer, Cham. https://doi.org/10.1007/978-3-319-27293-1_16

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  • DOI: https://doi.org/10.1007/978-3-319-27293-1_16

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-27292-4

  • Online ISBN: 978-3-319-27293-1

  • eBook Packages: Computer ScienceComputer Science (R0)

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