• DocumentCode
    245767
  • Title

    Modeling Geospatial Sensor Knowledge under a Semantic Sensor Web Environment

  • Author

    Xiaoliang Meng ; Yuwei Wang ; Yunhao Wu

  • Author_Institution
    Int. Sch. of Software, Wuhan Univ., Wuhan, China
  • fYear
    2014
  • fDate
    19-21 Dec. 2014
  • Firstpage
    1090
  • Lastpage
    1095
  • Abstract
    In recent years, developments in Internet of things and ubiquitous computing have created new opportunities to promote sensors participation in environmental, military and personalized monitoring. Up to now, sensor networks have been proposed for various applications, which are however characterized by a lack of interoperability. In this context, the paper gives a survey on semantic sensor web, and proposes a general method for modeling geospatial sensor knowledge by adding semantic annotations and rule reasoning to the Sensor ML (Sensor Model Language) described sensor information within OGC (Open Geospatial Consortium) SWE (Sensor Web Enablement) framework. We describe the air quality monitoring instance which gives a solution for automatically reporting the health implications and cautionary statements to the nearby people. This work constitutes an essential step towards the geospatial knowledge modeling of interoperable and intelligent sensor networks.
  • Keywords
    Internet of Things; open systems; semantic Web; sensors; Internet of Things; OGC; Open Geospatial Consortium; SWE framework; geospatial knowledge modeling; geospatial sensor knowledge; intelligent sensor networks; interoperability; personalized monitoring; rule reasoning; semantic annotations; semantic sensor Web environment; sensor ML; sensor Web enablement framework; sensor information; sensor model language; ubiquitous computing; Atmospheric modeling; Cognition; Geospatial analysis; Monitoring; Ontologies; Semantics; Sensor ML; geospatial sensor knowledge; ontology; semantic; sensor web;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computational Science and Engineering (CSE), 2014 IEEE 17th International Conference on
  • Conference_Location
    Chengdu
  • Print_ISBN
    978-1-4799-7980-6
  • Type

    conf

  • DOI
    10.1109/CSE.2014.215
  • Filename
    7023725