• DocumentCode
    3373675
  • Title

    Using Google Fusion Tables for Cloud-based sensor observation services

  • Author

    Peng Yue ; Chongxin Guo ; Liangcun Jiang

  • Author_Institution
    State Key Lab. of Inf. Eng. in Surveying, Wuhan Univ., Wuhan, China
  • fYear
    2013
  • fDate
    12-16 Aug. 2013
  • Firstpage
    388
  • Lastpage
    392
  • Abstract
    Google Fusion Tables (GFT) is a Cloud Computing database that provides a service on the Web for data management and integration. By using GFT for managing sensor observations, it is possible to take advantages of benefits of Cloud Computing database, and provide a scalable sensor observation service. A Sensor Observation Service (SOS) can provide real-time or near-real-time observations. This paper presents the design and implementation of a Cloud-based sensor observation service using Cloud Computing database in SOS services. GFT allows time-critical access and visualization of these sensor observations. By storing sensor observations in GFT, the SOS service is scalable and observations can be visualized easily. Challenges of developing applications and approaches on the integration of GFT and SOS are discussed. A prototype service is developed to demonstrate the applicability of the approach.
  • Keywords
    cloud computing; data integration; data visualisation; database management systems; sensor fusion; GFT; Google Fusion Tables; SOS services; cloud computing database; cloud-based sensor observation services; data integration; data management; scalable sensor observation service; sensor observation visualization; time-critical sensor observation access; Abstracts; Cloud computing; Google; Indexes; Information management; Real-time systems; XML; Cloud Computing; Geospatial Service; Google Fusion Tables; Sensor Observation Service;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Agro-Geoinformatics (Agro-Geoinformatics), 2013 Second International Conference on
  • Conference_Location
    Fairfax, VA
  • Type

    conf

  • DOI
    10.1109/Argo-Geoinformatics.2013.6621949
  • Filename
    6621949