Publication:
Edge intelligence for empowering IoT-based healthcare systems

dc.contributor.coauthorAloqaily, Moayad
dc.contributor.coauthorGuizani, Mohsen
dc.contributor.departmentDepartment of Computer Engineering
dc.contributor.departmentGraduate School of Sciences and Engineering
dc.contributor.kuauthorHayyolalam, Vahideh
dc.contributor.kuauthorÖzkasap, Öznur
dc.contributor.schoolcollegeinstituteCollege of Engineering
dc.contributor.schoolcollegeinstituteGRADUATE SCHOOL OF SCIENCES AND ENGINEERING
dc.date.accessioned2024-11-09T13:13:47Z
dc.date.issued2021
dc.description.abstractThe demand for real-time, affordable, and efficient smart healthcare services is increasing exponentially due to the technological revolution and burst of population. To meet the increasing demands on this critical infrastructure, there is a need for intelligent methods to cope with the existing related challenges. In this regard, edge computing technology can reduce latency and energy consumption by moving processes closer to the data sources in comparison to the traditional centralized cloud and IoT-based healthcare systems. In addition, by bringing automated insights into the smart healthcare systems, artificial intelligence (AI) provides the possibility of detecting and predicting high-risk diseases in advance, decreasing medical costs for patients, and offering efficient treatments. The objective of this article is to highlight the benefits of the adoption of the edge intelligent technology, along with the use of AI in smart healthcare systems. Moreover, a novel smart healthcare model is proposed to boost the utilization of AI and edge technology in smart healthcare systems. Additionally, we discuss potential challenges and future research directions arising when integrating these different technologies.
dc.description.fulltextYES
dc.description.indexedbyWOS
dc.description.indexedbyScopus
dc.description.issue3
dc.description.openaccessYES
dc.description.publisherscopeInternational
dc.description.sponsoredbyTubitakEuN/A
dc.description.sponsorshipN/A
dc.description.versionAuthor's final manuscript
dc.description.volume28
dc.identifier.doi10.1109/MWC.001.2000345
dc.identifier.eissn1558-0687
dc.identifier.embargoNO
dc.identifier.filenameinventorynoIR03084
dc.identifier.issn1536-1284
dc.identifier.quartileQ1
dc.identifier.scopus2-s2.0-85111098131
dc.identifier.urihttps://hdl.handle.net/20.500.14288/2952
dc.identifier.wos675202200003
dc.keywordsSociology
dc.keywordsMedical services
dc.keywordsReal-time systems
dc.keywordsData models
dc.keywordsServers
dc.keywordsComputer security
dc.keywordsArtificial intelligence
dc.keywordsInternet of Things
dc.language.isoeng
dc.publisherInstitute of Electrical and Electronics Engineers (IEEE)
dc.relation.grantnoNA
dc.relation.ispartofIEEE Wireless Communications
dc.relation.urihttp://cdm21054.contentdm.oclc.org/cdm/ref/collection/IR/id/9742
dc.subjectComputer science
dc.subjectHardware and architecture
dc.subjectInformation systems
dc.subjectElectrical and electronic engineering
dc.subjectTelecommunications
dc.titleEdge intelligence for empowering IoT-based healthcare systems
dc.typeJournal Article
dspace.entity.typePublication
local.contributor.kuauthorÖzkasap, Öznur
local.contributor.kuauthorHayyolalam, Vahideh
local.publication.orgunit1College of Engineering
local.publication.orgunit1GRADUATE SCHOOL OF SCIENCES AND ENGINEERING
local.publication.orgunit2Department of Computer Engineering
local.publication.orgunit2Graduate School of Sciences and Engineering
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