DC FieldValueLanguage
dc.contributor.authorTsotsolas, Nikos-
dc.contributor.authorAnagnostopoulos, Theodoros-
dc.contributor.authorSalmon, Ioannis-
dc.contributor.authorKantzavelou, Ioanna-
dc.contributor.authorKostakos, Panos-
dc.contributor.authorHarle, Robert-
dc.contributor.authorZaslavsky, Arkady-
dc.contributor.authorMorley, Jeremy-
dc.date.accessioned2024-03-22T12:50:16Z-
dc.date.available2024-03-22T12:50:16Z-
dc.date.issued2021-09-22-
dc.identifierscopus-85115703249-
dc.identifier.issn2169-3536-
dc.identifier.other85115703249-
dc.identifier.urihttps://uniwacris.uniwa.gr/handle/3000/1553-
dc.description.abstractA Smart Campus is a miniature of a Smart City with a more demanding framework that enables learning, social interaction and creativity. To ensure a Smart Campus uninterruptible secure operation, a key requirement is that daily routines and activities are performed protected in an environment monitored unobtrusively by a robust surveillance system. The various components that compose such an environment, buildings, labs, public spaces, smart lighting, smart parking, or even smart traffic lights, require us to focus on surveillance systems, and recognize which detection activities to establish. In this paper, we perform a comparative assessment in the area of surveillance systems for Smart Campuses. A proposed taxonomy for IoT-enabled Smart Campus unfold five research dimensions: (1) physical infrastructure; (2) enabling technologies; (3) software analytics; (4) system security; and (5) research methodology. By applying this taxonomy and by adopting a weighted scoring model on the surveyed systems, we first present the state-of-the-art, and then we make a comparative assessment and classify the systems. We extract valuable conclusions and inferences from this classification, providing insights and directions towards required services offered by surveillance systems for Smart Campus.en_US
dc.language.isoenen_US
dc.publisherIEEEen_US
dc.relation.ispartofAccessen_US
dc.subjectIoTen_US
dc.subjectResearch methodologyen_US
dc.subjectSecurityen_US
dc.subjectSmart campusen_US
dc.subjectSoftware analyticsen_US
dc.subjectSurveillance systemsen_US
dc.subjectWeighted scoring modelen_US
dc.titleChallenges and Solutions of Surveillance Systems in IoT-Enabled Smart Campus: A Surveyen_US
dc.typeArticleen_US
dc.identifier.doi10.1109/ACCESS.2021.3114447en_US
dc.identifier.scopus2-s2.0-85115703249-
dcterms.accessRights1en_US
dc.relation.deptDepartment of Business Administrationen_US
dc.relation.facultySchool of Administrative, Economics and Social Sciencesen_US
dc.relation.volume9en_US
dc.identifier.spage131926en_US
dc.identifier.epage131954en_US
dc.collaborationUniversity of West Attica (UNIWA)en_US
dc.subject.fieldEngineering and Technologyen_US
dc.journalsOpen Accessen_US
dc.publicationPeer Revieweden_US
dc.countryGreeceen_US
local.metadatastatusverifieden_US
item.grantfulltextnone-
item.cerifentitytypePublications-
item.openairetypeArticle-
item.openairecristypehttp://purl.org/coar/resource_type/c_18cf-
item.fulltextNo Fulltext-
item.languageiso639-1en-
crisitem.author.deptDepartment of Business Administration-
crisitem.author.deptDepartment of Business Administration-
crisitem.author.deptDepartment of Business Administration-
crisitem.author.facultySchool of Administrative, Economics and Social Sciences-
crisitem.author.facultySchool of Administrative, Economics and Social Sciences-
crisitem.author.facultySchool of Administrative, Economics and Social Sciences-
crisitem.author.orcid0000-0003-4173-3780-
crisitem.author.orcid0000-0002-5587-2848-
crisitem.author.orcid0009-0006-9089-8898-
crisitem.author.parentorgSchool of Administrative, Economics and Social Sciences-
crisitem.author.parentorgSchool of Administrative, Economics and Social Sciences-
crisitem.author.parentorgSchool of Administrative, Economics and Social Sciences-
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