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Experience-Oriented Intelligence for Internet of Things

Abstract

The Internet of Things (IoT) has gained significant attention from industry as well as academia during the past decade. The main reason behind this interest is the capabilities of the IoT for seamlessly integrating classical networks and networked objects, and hence allows people to create an intelligent environment based on this powerful integration. However, how to extract useful information from data produced by IoT and facilitate standard knowledge sharing amongst different IoT systems, are still open issues to be addressed. In this paper, we propose a novel approach, the Experience-Oriented Smart Things (EOST), that utilizes deep learning and knowledge representation concept called Decisional DNA to help IoT systems acquire, represent, and store knowledge, as well as share it amid various domains where it can be required to support decisions. We demonstrate our approach in a set of experiments, in which the IoT systems use knowledge gained from past experience to make decisions and predictions. The presented initial results show that the EOST is a very promising approach for knowledge capture, representation, sharing, and reusing in IoT systems.

Citations

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Authors (5)

Keywords

Details

Category:
Articles
Type:
artykuł w czasopiśmie wyróżnionym w JCR
Published in:
CYBERNETICS AND SYSTEMS no. 48, edition 3, pages 162 - 181,
ISSN: 0196-9722
Language:
English
Publication year:
2017
Bibliographic description:
Zhang H., Li F., Wang J., Sanín C., Szczerbicki E.: Experience-Oriented Intelligence for Internet of Things// CYBERNETICS AND SYSTEMS. -Vol. 48, iss. 3 (2017), s.162-181
DOI:
Digital Object Identifier (open in new tab) 10.1080/01969722.2016.1276771
Verified by:
Gdańsk University of Technology

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