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  • Semantic Sensor Networks

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    Nadine Cranenburgh


    A very important technology in the sensor discovery area, introduced in 2013, is semantic sensor networks (SSN). Describing sensors and their data in a consistent and common framework makes it easier to discover them. This particular semantic system network description was developed by a consortium of organisations around the world called the W3C. The W3C is also working with the Open Geospatial Consortium (OGC) to develop clarify and formalise the standards landscape for spatial information on the web.

    SSN is an ontology that describes aspects of the sensors and the systems using them. It describes the deployment, the data, the system, the operating restrictions, the devices, the measuring capability, and the constraints of the sensors. The SSN can be focussed on:

    • a sensor perspective: what is sensed, how it is sensed
    • a data or observation perspective: observations and related metadata
    • a system perspective: systems of sensors
    • a feature and property perspective: features, properties of features and what can sense them.

    The SSN ontology can be downloaded from the W3C website. It has been used to annotate semantic web open-link data technologies, and can be queried using tools such as SPARQL. SSN is used extensively around the world, especially in Europe, and is the de-facto standard in this area today.

    Paradigm shift

    SSN represents a paradigm shift from the hard-coded vertical approach of referencing sensors by name or number to discovering sensors based on a description of the sensor, the sensor platform or the information it can provide, as shown in the diagram below.


    Diagram courtesy of Prem Prakash Jayaraman, Swinburne University of Technology

    Ontology modules

    The SSN consists of several ontology modules as shown in the diagram below.


    Diagram courtesy of Prem Prakash Jayaraman, Swinburne University of Technology

    These modules provide the ability to describe sensing platforms, sensors, and capabilities at a minute level.

    The sensor is described using an HTTP URI. For example, a sensor could be an air temperature sensor which was made by a particular manufacturer. It could observe air temperature and humidity. The unit of measurement of this observation could be Celsius or Fahrenheit. Any machine can look at this URI, get a description of the sensor, and be able to understand exactly what the sensor produces, how it produces this information, and from where the data is coming from. Other entries in the sensor description could include accuracy, location, owner and frequency of measurement. An example is shown in the diagram below. System developers can develop queries using properties and features that are relevant to their solution.


    Diagram courtesy of Prem Prakash Jayaraman, Swinburne University of Technology


    The information on this page has been sourced primarily from the following:


    Edited by Nadine Cranenburgh


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