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https://hdl.handle.net/1959.11/61858
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DC Field | Value | Language |
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dc.contributor.author | Zhang, Haoxi | en |
dc.contributor.author | Li, Fei | en |
dc.contributor.author | Wang, Juan | en |
dc.contributor.author | Wang, Zuli | en |
dc.contributor.author | Sanin, Cesar | en |
dc.contributor.author | Szczerbicki, Edward | en |
dc.date.accessioned | 2024-07-29T21:33:49Z | - |
dc.date.available | 2024-07-29T21:33:49Z | - |
dc.date.issued | 2017 | - |
dc.identifier.citation | Cybernetics and Systems, 48(3), p. 162-181 | en |
dc.identifier.issn | 1087-6553 | en |
dc.identifier.issn | 0196-9722 | en |
dc.identifier.uri | https://hdl.handle.net/1959.11/61858 | - |
dc.description.abstract | <p>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 allowing 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 among 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. Decisional DNA motivation stems from the role of deoxyribonucleic acid (DNA) in storing and sharing information and knowledge. 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.</p> | en |
dc.language | en | en |
dc.publisher | Taylor & Francis Inc | en |
dc.relation.ispartof | Cybernetics and Systems | en |
dc.title | Experience-Oriented Intelligence for Internet of Things | en |
dc.type | Journal Article | en |
dc.identifier.doi | 10.1080/01969722.2016.1276771 | en |
local.contributor.firstname | Haoxi | en |
local.contributor.firstname | Fei | en |
local.contributor.firstname | Juan | en |
local.contributor.firstname | Zuli | en |
local.contributor.firstname | Cesar | en |
local.contributor.firstname | Edward | en |
local.profile.school | School of Science and Technology | en |
local.profile.email | cmaldon3@une.edu.au | en |
local.output.category | C1 | en |
local.record.place | au | en |
local.record.institution | University of New England | en |
local.publisher.place | United States of America | en |
local.format.startpage | 162 | en |
local.format.endpage | 181 | en |
local.peerreviewed | Yes | en |
local.identifier.volume | 48 | en |
local.identifier.issue | 3 | en |
local.contributor.lastname | Zhang | en |
local.contributor.lastname | Li | en |
local.contributor.lastname | Wang | en |
local.contributor.lastname | Wang | en |
local.contributor.lastname | Sanin | en |
local.contributor.lastname | Szczerbicki | en |
dc.identifier.staff | une-id:cmaldon3 | en |
local.profile.orcid | 0000-0001-8515-417X | en |
local.profile.role | author | en |
local.profile.role | author | en |
local.profile.role | author | en |
local.profile.role | author | en |
local.profile.role | author | en |
local.profile.role | author | en |
local.identifier.unepublicationid | une:1959.11/61858 | en |
local.date.onlineversion | 2017-03-02 | - |
dc.identifier.academiclevel | Academic | en |
dc.identifier.academiclevel | Academic | en |
dc.identifier.academiclevel | Academic | en |
dc.identifier.academiclevel | Academic | en |
dc.identifier.academiclevel | Academic | en |
dc.identifier.academiclevel | Academic | en |
local.title.maintitle | Experience-Oriented Intelligence for Internet of Things | en |
local.relation.fundingsourcenote | This work is supported by the Project KYTZ201422 by the Scientific Research Foundation of CUIT, the Application Basic Research Project of Sichuan Province (No. 2014JY0071), and the Open Project of Network and Data Security Key Laboratory of Sichuan province (NDS2015-01). | en |
local.output.categorydescription | C1 Refereed Article in a Scholarly Journal | en |
local.search.author | Zhang, Haoxi | en |
local.search.author | Li, Fei | en |
local.search.author | Wang, Juan | en |
local.search.author | Wang, Zuli | en |
local.search.author | Sanin, Cesar | en |
local.search.author | Szczerbicki, Edward | en |
local.uneassociation | No | en |
local.atsiresearch | No | en |
local.sensitive.cultural | No | en |
local.year.available | 2017 | en |
local.year.published | 2017 | en |
local.fileurl.closedpublished | https://rune.une.edu.au/web/retrieve/a6564b86-2944-403a-b95c-02fe59836021 | en |
local.subject.for2020 | 4602 Artificial intelligence | en |
local.profile.affiliationtype | External Affiliation | en |
local.profile.affiliationtype | External Affiliation | en |
local.profile.affiliationtype | External Affiliation | en |
local.profile.affiliationtype | External Affiliation | en |
local.profile.affiliationtype | External Affiliation | en |
local.profile.affiliationtype | External Affiliation | en |
local.date.moved | 2024-08-01 | en |
Appears in Collections: | Journal Article School of Science and Technology |
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