• DocumentCode
    1765635
  • Title

    Automatic Data Quality Control of Observations in Wireless Sensor Network

  • Author

    Jianwen Guo ; Feng Liu

  • Author_Institution
    Cold & Arid Regions Environ. & Eng. Res. Inst., Lanzhou, China
  • Volume
    12
  • Issue
    4
  • fYear
    2015
  • fDate
    42095
  • Firstpage
    716
  • Lastpage
    720
  • Abstract
    Emerging multisource earth observation technologies represented by wireless sensor network (WSN) technology are widely used in land surface observation and simulation studies. Consequently, data quality control of massive observation data has brought challenges to researchers. This letter describes a comprehensive approach applied to automatic data quality control of WSN data. First, summarize the quality element of WSN observation data which can be achieved through automated methods by analyzing the characteristics of WSN observation data, and develop a decision algorithm for each quality element. Then, associate the data type and algorithm through data quality control rules. Finally, establish an automatic data quality control system based on data quality control rules. As a matter of fact, this system has run for one and a half years and processed more than 500 million observation data records without human intervention. Application results show that this method system can effectively control the data quality of WSN data automatically.
  • Keywords
    data analysis; wireless sensor networks; WSN data; automated methods; automatic data quality control; data type; decision algorithm; land surface observation; multisource earth observation technologies; wireless sensor network technology; Biological system modeling; Data models; Instruments; Null value; Process control; Quality control; Wireless sensor networks; Data preprocessing; data quality control; geographic information systems; information systems;
  • fLanguage
    English
  • Journal_Title
    Geoscience and Remote Sensing Letters, IEEE
  • Publisher
    ieee
  • ISSN
    1545-598X
  • Type

    jour

  • DOI
    10.1109/LGRS.2014.2359685
  • Filename
    6919248