Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.14279/12968
DC FieldValueLanguage
dc.contributor.authorKyriacou, Alexis-
dc.contributor.authorMichaelides, Michalis P.-
dc.contributor.authorReppa, Vasso-
dc.contributor.authorTimotheou, Stelios-
dc.contributor.authorPanayiotou, Christos G.-
dc.contributor.authorPolycarpou, Marios M.-
dc.date.accessioned2018-12-07T07:33:57Z-
dc.date.available2018-12-07T07:33:57Z-
dc.date.issued2018-11-
dc.identifier.citationIEEE Transactions on Control Systems Technology, 2018, Vol. 26, No. 6, pp. 1925-1941en_US
dc.identifier.issn15580865-
dc.description.abstractThe automatic preservation of the indoor air quality (IAQ) is an important task of the intelligent building design in order to ensure the health and safety of the occupants. The IAQ, however, is often compromised by various airborne contaminants that penetrate the indoor environment as a result of accidents or planned attacks. In this paper, we provide the detailed analysis, implementation, and evaluation of a distributed methodology for detecting and isolating multiple contaminant events in large-scale buildings. Specifically, we consider the building as a collection of interconnected subsystems, and we design a contaminant event monitoring software agent for each subsystem. Each monitoring agent aims to detect the contaminant and isolate the zone where the contaminant source is located, while it is allowed to exchange information with its neighboring agents. For configuring the subsystems, we implement both exact and heuristic partitioning solutions. A main contribution of this paper is the investigation of the impact of the partitioning solution on the performance of the distributed contaminant detection and isolation (CDI) scheme with respect to the detectability and isolability of the contaminant sources. The performance of the proposed distributed CDI methodology is demonstrated using the models of real building case studies created on CONTAM.1 1CONTAM is a multizone simulation program developed by the U.S. National Institute of Standards and Technology.en_US
dc.formatpdfen_US
dc.language.isoenen_US
dc.relation.ispartofIEEE Transactions on Control Systems Technologyen_US
dc.rights© IEEEen_US
dc.subjectContaminant detectionen_US
dc.subjectDistributed algorithmsen_US
dc.subjectFault diagnosisen_US
dc.subjectIndoor air quality (IAQ) monitoringen_US
dc.subjectIntelligent buildingsen_US
dc.titleDistributed contaminant detection and isolation for intelligent buildingsen_US
dc.typeArticleen_US
dc.collaborationUniversity of Cyprusen_US
dc.collaborationCyprus University of Technologyen_US
dc.subject.categoryComputer and Information Sciencesen_US
dc.subject.categoryElectrical Engineering - Electronic Engineering - Information Engineeringen_US
dc.journalsSubscriptionen_US
dc.countryCyprusen_US
dc.subject.fieldNatural Sciencesen_US
dc.subject.fieldEngineering and Technologyen_US
dc.publicationPeer Revieweden_US
dc.identifier.doi10.1109/TCST.2017.2754986en_US
dc.relation.issue6en_US
dc.relation.volume26en_US
cut.common.academicyear2017-2018en_US
dc.identifier.spage2925en_US
dc.identifier.epage1941en_US
item.fulltextNo Fulltext-
item.cerifentitytypePublications-
item.grantfulltextnone-
item.openairecristypehttp://purl.org/coar/resource_type/c_6501-
item.openairetypearticle-
item.languageiso639-1en-
crisitem.journal.journalissn1063-6536-
crisitem.journal.publisherIEEE-
crisitem.author.deptDepartment of Electrical Engineering, Computer Engineering and Informatics-
crisitem.author.facultyFaculty of Engineering and Technology-
crisitem.author.orcid0000-0002-0549-704X-
crisitem.author.parentorgFaculty of Engineering and Technology-
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