From Sensor Data to Triples: Information Flow in Semantic Sensor Networks
Semantic Sensor Service Networks
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Transcript of Semantic Sensor Service Networks
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Semantic Sensor Service Networks
Wei Wang, Payam Barnaghi, Gilbert Cassar, Frieder Ganz, Pirabakaran Navaratnam
Centre for Communication Systems Research
University of Surrey
Guildford, Surrey
United Kingdom
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Sensors, Sensor Networks and Internet of “Things”
Physical world objects e.g. A room, a car, A person;
Feature of Interest e.g. Temperature of the room, Location of
the car, heart-rate of the person; Sensors
e.g. Temperature sensor, GPS, pulse sensor Embedded devices
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Semantics and Sensor Networks
Image credits: [1] Protocols and Architectures for Wireless Sensor Networks, Holger Karl, Andreas Willig, Wiley, 2005[2] Cisco - Interne of Things
Image credits: [1] Protocols and Architectures for Wireless Sensor Networks, Holger Karl, Andreas Willig, Wiley, 2005[2] Cisco - Interne of Things
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Distributed WSN
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The Internet of Things
A primary goal of interconnecting devices and collecting/processing data from them is to create situation awareness and enable applications, machines, and human users to better understand their surrounding environments.
The understanding of a situation, or context, potentially enables services and applications to make intelligent decisions and to respond to the dynamics of their environments.
A key enabler is providing Services that represent sensors/resources and integrating them into the cyber-space.
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Semantics, sensors and services
Semantics are machine-interpretable metadata (for mark-up), logical inference mechanisms, query mechanism, linked data solutions
For semantic sensor services this means: ontologies for: devices (e.g. sensors), observation and
measurement data (e.g. sensor readings), domain concepts (e.g. unit of measurement, location), service descriptions (e.g. IoT services) and other data sources (e.g. those available on linked open data)
Semantic annotation should also supports data represented using existing forms
Reasoning /processing to infer relationships or hierarchies between different resources, data
Semantics (/ontologies) as meta-data (to describe the services/resources) / knowledge bases (domain knowledge).
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A layered model
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Existing models for resources and data W3C Semantic Sensor Network Incubator
Group’s SSN ontology (mainly for sensors and sensor networks, observation and measurement, and platforms and systems)
Quantity Kinds and Units Used together with the SSN ontology based on QUDV model OMG SysML(TM) Working group of the SysML 1.2 Revision
Task Force (RTF) and W3C Semantic Sensor Network Incubator Group
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SSN Ontology Modules
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Existing models for services
OWL-S and WSMO are heavy weight models: practical use?
Minimal service model Deprecated Procedure-Oriented Service Model (POSM) and Resource-
Oriented Service Model (ROSM): two different models for different service technologies
Defines Operations and Messages No profile, no grounding
SAWSDL: mixture of XML, XML schema, RDF and OWL hRESTS and SA-REST: mixture of HTML and reference
to a semantic model; sensor services are not anticipated to have HTML
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Semantic modelling
Lightweight: experiences show that a lightweight ontology model that well balances expressiveness and inference complexity is more likely to be widely adopted and reused; also large number of IoT resources and huge amount of data need efficient processing
Compatibility: an ontology needs to be consistent with those well designed, existing ontologies to ensure compatibility wherever possible.
Modularity: modular approach to facilitate ontology evolution, extension and integration with external ontologies.
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IoT.est service profile highlight
ServiceType class represents the service technologies: RESTful and SOAP/WSDL services.
serviceQos and serviceQoI are defined as subproperty of serviceParameter; they link to concepts in the QoS/QoI ontology.
serviceArea: the area where the service is provided; different from the sensor observation area
Links to the IoT resources through “exposedBy” property
Future extension: serviceNetwork, servicePlatform and
serviceDeployment Service lifecycle, SLA…
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A snapshot of the model
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Service Search and Discovery
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Linked data principles
using URI’s as names for things: Everything is addressed using unique URI’s.
using HTTP URI’s to enable people to look up those names: All the URI’s are accessible via HTTP interfaces.
provide useful RDF information related to URI’s that are looked up by machine or people;
including RDF statements that link to other URI’s to enable discovery of other related concepts of the Web of Data: The URI’s are linked to other URI’s.
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Linked data layer for not only IoT…
Diagram from Stefan Decker, http://fi-ghent.fi-week.eu/files/2010/10/Linked-Data-scheme1.png; linked data diagram: http://richard.cyganiak.de/2007/10/lod/
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A Sample demonstrator
http://ccsriottb3.ee.surrey.ac.uk:8080/IOTA/
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Sensor discovery using linked sensor data
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Conclusions Sensor service connectivity, discovery and
composition are some of the most key issues in semantic sensor service networks.
SOA based design can support seamless integration to existing applications on cyber-space.
While the direct access method uses the standard HTTP protocols for service communications, the intermediate access method is designed on the top of the Constrained Application Protocol (CoAp) and 6LowPan for devices operating in constrained environments.
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Questions?
Thank you.