IoT Learning Model Based on Virtual Object Cognition

Intelligent service provisioning in the Internet of Things infrastructure can be achieved by discovering and composing most relevant virtual objects and autonomic modification of context information that require learning the system behavior through steady association between the virtual object and the real world object. To meet these challenges, Web of-Objects enables the objects to be deployed, maintained and operated in the Internet of Things through virtualizing the real world objects with the use of semantic ontology. Learning model can be represented in terms of composite virtual object that is formed by combining multiple functionalities of virtual objects. Different functionalities at the virtual object level and their iteration enable the cognition in virtual object. The creation and functional architecture of virtual object in Web-of-Objects have been discussed. For the efficient discovery- and composition of virtual object, a Web-of-Objects based learning model has been proposed in this paper. Finally, to realize the service composition, a use-case scenario has been studied.