• DocumentCode
    2916965
  • Title

    SROS: Sensor-Based Real-Time Observing System for Ecological Research

  • Author

    Cheng, Jie ; Zhou, Yuanchun ; Wang, Binglin ; Wang, Xuezhi ; Li, Jianhui

  • Author_Institution
    Comput. Network Inf. Center, Chinese Acad. of Sci., Beijing, China
  • fYear
    2009
  • fDate
    7-8 Nov. 2009
  • Firstpage
    396
  • Lastpage
    400
  • Abstract
    The environmental science communities are actively engaged in developing the next generation of large-scale sensor based field observing systems. The challenges that these systems face are listed as below: complexity of sensor data stream processing and effects of Web-based real-time data display. In this paper, we utilized the RBNB DataTurbine, an open-source streaming data middleware to improve the reliability of streaming data transportation. By using server push technology, we ensure the stability and effectiveness of Web-based streaming data visualization. The results indicate that the system has enhanced the efficiency and performance of field ecological data transportation and visualization. The system is currently used for observation by ecological research scientists at the Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences.
  • Keywords
    Internet; data visualisation; distributed sensors; ecology; middleware; public domain software; RBNB DataTurbine; SROS; Web-based real-time data display; Web-based streaming data visualization; ecological research; open-source streaming data middleware; sensor data stream processing; sensor-based real-time observing system; server push technology; Data visualization; Displays; Face; Large-scale systems; Middleware; Open source software; Real time systems; Sensor systems; Stability; Transportation; rbnb; real-time data transportation; sensor networks; server push;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Web Information Systems and Mining, 2009. WISM 2009. International Conference on
  • Conference_Location
    Shanghai
  • Print_ISBN
    978-0-7695-3817-4
  • Type

    conf

  • DOI
    10.1109/WISM.2009.87
  • Filename
    5369412