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A Data Cleaning Method and Its Application for Earthen Site Data Monitored by WSN

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Pattern Recognition (CCPR 2016)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 662))

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Abstract

This paper focuses on a data cleaning method to denoise and detect outliers of earthen site monitoring data with wireless sensor network (WSN). A data cleaning method, named DC_ESVS is proposed, which is based on the temporal and spatial characteristics of monitoring data with WSN. Using the cubic exponential smoothing algorithm and voting strategy, it can denoise and detect outliers of earthen site monitoring data based on the decision rule. We conduct various experiments on the dataset of the monitoring data of Xi’an Tang Hanguangmen city wall site with WSN to show detection accuracy of the presented method. Experimental results on anther dataset of the monitoring data of the Ming Great Wall in Shaanxi also show good performance of the proposed method.

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Acknowledgements

This work was partially supported by International cooperation and exchange program of Shaanxi Province (No. 2016KW-034), Industrial Science and technology project of Shaanxi Province (No. 2015GY013), the Education Department of Shaanxi Province Natural Science Foundation, China (Grant No. 12JK0937, 15JK1742).

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Authors and Affiliations

  1. School of Information Science and Technology, Northwest University, Xi’an, China

    Yun Xiao, Xin Wang, Pengfei Xu, Xiaojiang Chen & Dingyi Fang

  2. Department of Communication, Xi’an University of Posts and Telecommunications, Xi’an, China

    Xuanhong Wang

  3. Department of Geomatics Engineering, University of Calgary, Calgary, Canada

    Xin Wang

  4. Cultural Heritage Department, University of Salento, Lecce, Italy

    Baoying Liu

Authors
  1. Yun Xiao
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  2. Xuanhong Wang
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  3. Xin Wang
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  4. Pengfei Xu
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  5. Xiaojiang Chen
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  6. Dingyi Fang
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  7. Baoying Liu
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Corresponding author

Correspondence to Yun Xiao .

Editor information

Editors and Affiliations

  1. Institute of Automation, Chinese Academy of Sciences, Beijing, China

    Tieniu Tan

  2. Xi’an Institute of Optics and Precision Mechanics, Chinese Academy of Sciences, Xi'an, China

    Xuelong Li

  3. Chinese Academy of Sciences, Institute of Computing Technology, Beijing, China

    Xilin Chen

  4. Tsinghua University , Beijing, China

    Jie Zhou

  5. Nanjing University of Science and Technology, Nanjing, China

    Jian Yang

  6. University of Electronic Science and Technology, Chengdu, Sichuan, China

    Hong Cheng

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© 2016 Springer Nature Singapore Pte Ltd.

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Xiao, Y. et al. (2016). A Data Cleaning Method and Its Application for Earthen Site Data Monitored by WSN. In: Tan, T., Li, X., Chen, X., Zhou, J., Yang, J., Cheng, H. (eds) Pattern Recognition. CCPR 2016. Communications in Computer and Information Science, vol 662. Springer, Singapore. https://doi.org/10.1007/978-981-10-3002-4_52

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  • DOI: https://doi.org/10.1007/978-981-10-3002-4_52

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-10-3001-7

  • Online ISBN: 978-981-10-3002-4

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