Please use this identifier to cite or link to this item: https://hdl.handle.net/1959.11/61898
Full metadata record
DC FieldValueLanguage
dc.contributor.authorde Oliveira, Caterine Silvaen
dc.contributor.authorSanin, Cesaren
dc.contributor.authorSzczerbicki, Edwarden
local.source.editorEditor(s): Zofia Wilimowska, Leszek Borzemski and Jerzy Świąteken
dc.date.accessioned2024-08-02T05:16:07Z-
dc.date.available2024-08-02T05:16:07Z-
dc.date.issued2017-09-01-
dc.identifier.citationInformation Systems Architecture and Technology, p. 243-252en
dc.identifier.isbn9783319672236en
dc.identifier.isbn9783319672229en
dc.identifier.urihttps://hdl.handle.net/1959.11/61898-
dc.description.abstract<p>This paper proposes the integration of image processing techniques (such as image segmentation, feature extraction and selection) and a knowledge representation approach in a framework for the development of an automatic system able to identify, in real time, unsafe activities in industrial environments. In this framework, the visual information (feature extraction) acquired from video-camera images and other context based gathered data are represented as Set of Experience Knowledge Structure (SOEKS), a formal decision event for reasoning and risk evaluation. Then, grouped sets of decisions from the same category are stored as decisional experience Decisional DNA (DDNA) to support future decision making events in similar input images. Unlike the existing sensor and vision-based approaches, that required rewriting most of the code when a condition, situation or requirement changes, our platform is an adaptable system capable of working in a variety of video analysis scenarios. Depending on the safety requirements of each industrial environment, users can feed the system with flexible rules and in the end, the platform provides decision makers with hazard evaluations that reuse experience for event identification and correction.</p>en
dc.languageenen
dc.publisherSpringeren
dc.relation.ispartofInformation Systems Architecture and Technologyen
dc.relation.ispartofseriesAdvances in Intelligent Systems and Computingen
dc.titleHazard Control in Industrial Environments: A Knowledge-Vision-Based Approachen
dc.typeConference Publicationen
dc.relation.conferenceISAT 2017: 38th International Conference on Information Systems Architecture and Technologyen
dc.identifier.doi10.1007/978-3-319-67223-6_23en
local.contributor.firstnameCaterine Silvaen
local.contributor.firstnameCesaren
local.contributor.firstnameEdwarden
local.profile.schoolSchool of Science and Technologyen
local.profile.emailcmaldon3@une.edu.auen
local.output.categoryE1en
local.record.placeauen
local.record.institutionUniversity of New Englanden
local.date.conference17th- 19th September, 2017en
local.conference.placeSzklarska Poręba, Polanden
local.publisher.placeGermanyen
local.format.startpage243en
local.format.endpage252en
local.series.issn2194-5365-
local.series.issn2194-5357-
local.series.number657en
local.peerreviewedYesen
local.title.subtitleA Knowledge-Vision-Based Approachen
local.contributor.lastnamede Oliveiraen
local.contributor.lastnameSaninen
local.contributor.lastnameSzczerbickien
dc.identifier.staffune-id:cmaldon3en
local.profile.orcid0000-0001-8515-417Xen
local.profile.roleauthoren
local.profile.roleauthoren
local.profile.roleauthoren
local.identifier.unepublicationidune:1959.11/61898en
dc.identifier.academiclevelAcademicen
dc.identifier.academiclevelAcademicen
dc.identifier.academiclevelAcademicen
local.title.maintitleHazard Control in Industrial Environmentsen
local.output.categorydescriptionE1 Refereed Scholarly Conference Publicationen
local.conference.detailsISAT 2017: 38th International Conference on Information Systems Architecture and Technology, Szklarska Poręba, Poland, 17th- 19th September, 2017en
local.search.authorde Oliveira, Caterine Silvaen
local.search.authorSanin, Cesaren
local.search.authorSzczerbicki, Edwarden
local.open.fileurlhttps://rune.une.edu.au/web/retrieve/c497cfa9-ee1d-4359-b571-14f3414aca0aen
local.uneassociationNoen
local.atsiresearchNoen
local.sensitive.culturalNoen
local.year.published2017en
local.fileurl.openhttps://rune.une.edu.au/web/retrieve/c497cfa9-ee1d-4359-b571-14f3414aca0aen
local.subject.for20204602 Artificial intelligenceen
local.date.start2017-09-17-
local.date.end2017-09-19-
local.profile.affiliationtypeExternal Affiliationen
local.profile.affiliationtypeExternal Affiliationen
local.profile.affiliationtypeExternal Affiliationen
local.date.moved2024-08-02en
Appears in Collections:Conference Publication
School of Science and Technology
Files in This Item:
1 files
File SizeFormat 
Show simple item record

SCOPUSTM   
Citations

5
checked on Nov 2, 2024
Google Media

Google ScholarTM

Check

Altmetric


Items in Research UNE are protected by copyright, with all rights reserved, unless otherwise indicated.