Semantic Models for Scalable Search in the Internet of Things

Richard Mietz, Sven Groppe, Kay Römer, Dennis Pfisterer


The Internet of Things is anticipated to connect billions of embedded devices equipped with sensors to perceive their surroundings. Thereby, the state of the real world will be available online and in real-time and can be combined with other data and services in the Internet to realize novel applications such as Smart Cities, Smart Grids, or Smart Healthcare. This requires an open representation of sensor data and scalable search over data from diverse sources including sensors. In this paper we show how the Semantic Web technologies RDF (an open semantic data format) and SPARQL (a query language for RDF-encoded data) can be used to address those challenges. In particular, we describe how prediction models can be employed for scalable sensor search, how these prediction models can be encoded as RDF, and how the models can be queried by means of SPARQL.
Original languageEnglish
JournalJournal of Sensor and Actuator Networks
Pages (from-to)172-195
Number of pages24
Publication statusPublished - 27.03.2013

Research Areas and Centers

  • Research Area: Intelligent Systems
  • Centers: Center for Artificial Intelligence Luebeck (ZKIL)

DFG Research Classification Scheme

  • 409-06 Information Systems, Process and Knowledge Management
  • 409-04 Operating, Communication, Database and Distributed Systems


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