• DocumentCode
    708802
  • Title

    Using sensors to bridge the gap between real places and their web-based representations

  • Author

    Leggieri, Myriam ; von der Weth, Christian ; Breslin, John G.

  • Author_Institution
    Insight Centre for Data Analytics, Nat. Univ. of Ireland Galway, Galway, Ireland
  • fYear
    2015
  • fDate
    7-9 April 2015
  • Firstpage
    1
  • Lastpage
    6
  • Abstract
    With the proliferation of Smart Cities, more and more live data sources such as web cam feeds and physical sensor information are publicly accessible over the Web. However, these sources are typically decoupled from normal web sites, and are therefore not within the scope of traditional online search using Web search engines. In this paper, we focus on websites that refer to physical locations (e.g., restaurants, hotel, shops) for which live sensor data and information might be available. We propose G-Sensing, our platform for the seamless integration of live data into the normal browsing experience of online users. In a nutshell, we provide a browser add-on that injects sensor information into Google result pages for each result that refers to a physical place. Our backend infrastructure consists of a data repository connecting web sites to physical locations, as well as a data source for sensor information based on Linked Data principles. In our evaluation, we first show that websites referring to places are a very common phenomenon, thus motivating the potential benefits of G-Sensing. Furthermore, we show that our system only adds a small overhead to normal bandwidth requirements when browsing the Web.
  • Keywords
    Internet; search engines; Linked Data principles; Smart Cities; Web cam feeds; Web sites; Web-based representations; backend infrastructure; data repository; physical sensor information; Browsers; Cities and towns; Google; Joining processes; Ontologies; Resource description framework; Semantics;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Intelligent Sensors, Sensor Networks and Information Processing (ISSNIP), 2015 IEEE Tenth International Conference on
  • Conference_Location
    Singapore
  • Print_ISBN
    978-1-4799-8054-3
  • Type

    conf

  • DOI
    10.1109/ISSNIP.2015.7106949
  • Filename
    7106949