Please use this identifier to cite or link to this item: https://hdl.handle.net/1959.11/61884
Title: Applying Decisional DNA to Internet of Things: The Concept and Initial Case Study
Contributor(s): Zhang, Haoxi (author); Sanin, Cesar  (author)orcid ; Szczerbicki, Edward (author)
Publication Date: 2015
Early Online Version: 2015-03-24
DOI: 10.1080/01969722.2015.1007738
Handle Link: https://hdl.handle.net/1959.11/61884
Abstract: 

In this article, we present a novel approach utilizing Decisional DNA to help the Internet of Things capture decisional events and reuse them for decision making in future operations. The Decisional DNA is a domain-independent, standard and flexible knowledge representation structure that allows its domains to acquire, store, and share experiential knowledge and formal decision events in an explicit way. We apply this approach to our current work—SmartBike, a sensor-equipped bicycle built under the concept of Internet of Things. By using Decisional DNA and machine learning algorithms, the SmartBike is able to distinguish its user's patterns based on past riding data. The presented conceptual approach demonstrates how Decisional DNA can be applied to the Internet of Things and bring to them intelligence required by forthcoming semantic networks.

Publication Type: Journal Article
Source of Publication: Cybernetics and Systems, v.46, p. 84-93
Publisher: Taylor & Francis Inc
Place of Publication: United States of America
ISSN: 1087-6553
0196-9722
Fields of Research (FoR) 2020: 4602 Artificial intelligence
Peer Reviewed: Yes
HERDC Category Description: C1 Refereed Article in a Scholarly Journal
Appears in Collections:Journal Article
School of Science and Technology

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