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dc.contributor.authorEkwevugbe, Toboreen
dc.contributor.authorBrown, Neilen
dc.contributor.authorPakka, V. H.en
dc.contributor.authorFan, Denisen
dc.date.accessioned2017-02-23T14:25:28Z
dc.date.available2017-02-23T14:25:28Z
dc.date.issued2017-01-29
dc.identifier.citationEkwevugbe, T. Brown, N., Pakka, V.H. and Fan, D. (2017) Improved occupancy monitoring in non-domestic buildings. Sustainable Cities and Society, 30, pp. 97-107en
dc.identifier.urihttp://hdl.handle.net/2086/13316
dc.descriptionThe file attached to this record is the author's final peer reviewed version. The Publisher's final version can be found by following the DOI link.en
dc.description.abstractMeasuring occupancy can facilitate energy efficiency in non-domestic buildings, when control systems are able to adjust heating and cooling based on demand rather than fixed schedules. The variable “occupancy profile” itself is rarely considered as a control system parameter in building energy management systems (BEMS), and this is largely because reliably measuring occupancy in the past has been too difficult, expensive, or a mixture of both. Occupancy detection is possible using e.g. CO2 sensors, passive infra-red (PIR) detectors, which can provide a basic trigger for services, but the actual occupancy count, and therefore the expected load on building services, requires a step change in instrumentation. Advanced occupancy sensors developed from a heterogeneous multisensory fusion strategy offer this, improving control system performance, e.g. turning off services out of hours, and not over-ventilating, saving energy, while not under-ventilating during occupancy, benefitting comfort and health. While this is the case, there is a shortage of any systematic methodology for developing robust and reliable occupancy monitoring systems from heterogeneous multi-sensory sources. In this paper we describe an innovative sensor fusion approach utilising symmetrical uncertainty (SU) analysis and a genetic based feature selection for building occupancy estimation.en
dc.language.isoenen
dc.publisherElsevieren
dc.subjectEnergyen
dc.subjectSensor fusionen
dc.subjectEfficiencyen
dc.subjectBuildingen
dc.subjectControlsen
dc.subjectOccupancyen
dc.titleImproved occupancy monitoring in non-domestic buildingsen
dc.typeArticleen
dc.identifier.doihttp://dx.doi.org/10.1016/j.scs.2017.01.003
dc.researchgroupInstitute of Energy and Sustainable Developmenten
dc.peerreviewedYesen
dc.fundern/aen
dc.projectidn/aen
dc.cclicenceCC-BY-NCen
dc.date.acceptance2017-01-06en
dc.researchinstituteInstitute of Energy and Sustainable Development (IESD)en


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