Semantic Models for Scalable Search in the Internet of Things

Journal of Sensor and Actuator Networks

Richard Mietz¹  Sven Groppe²  Kay Römer¹ 

[1] Institute of Computer Engineering, University of Lübeck, 23562 Lübeck, Germany; E-Mails:;Institute of Information Systems, University of Lübeck, 23562 Lübeck, Germany; E-Mail:

关键词: Internet of Things;    searching;    sensors;    probability models;   

DOI  :  10.3390/jsan2020172

来源: mdpi

【 摘 要 】

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.

【 授权许可】

CC BY   
© 2013 by the authors; licensee MDPI, Basel, Switzerland.