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Description
  • The article addresses the problem of intelligent analysis and evaluation of facility management data gathered from heterogeneous sources, including environmental data collected from building automation sensors, temporal weather characteristics and scheduling. We suggest the framework of analytical model, based on deriving descriptors which could sentinel the level of thermal comfort of working environments. The model aims to facilitateprocess of extracting essential characteristics of facility management for detecting dependencies and observing anomalies. The framework aims to discover hidden relations between performance of building conditioning and environmental and spatial factors that cannot be observed from the building automation system itself. The performance of the model was tested by experimental analysis of facility management of the university cam- pus, designed for exploring how various environment variables affect temperature in the lecture rooms, equipped by the air conditioning devices.
  • The article addresses the problem of intelligent analysis and evaluation of facility management data gathered from heterogeneous sources, including environmental data collected from building automation sensors, temporal weather characteristics and scheduling. We suggest the framework of analytical model, based on deriving descriptors which could sentinel the level of thermal comfort of working environments. The model aims to facilitateprocess of extracting essential characteristics of facility management for detecting dependencies and observing anomalies. The framework aims to discover hidden relations between performance of building conditioning and environmental and spatial factors that cannot be observed from the building automation system itself. The performance of the model was tested by experimental analysis of facility management of the university cam- pus, designed for exploring how various environment variables affect temperature in the lecture rooms, equipped by the air conditioning devices. (en)
Title
  • Data Analysis in the Intelligent Building Environment
  • Data Analysis in the Intelligent Building Environment (en)
skos:prefLabel
  • Data Analysis in the Intelligent Building Environment
  • Data Analysis in the Intelligent Building Environment (en)
skos:notation
  • RIV/00216224:14330/14:00076194!RIV15-MSM-14330___
http://linked.open...avai/riv/aktivita
http://linked.open...avai/riv/aktivity
  • S
http://linked.open...iv/cisloPeriodika
  • Issue 1
http://linked.open...vai/riv/dodaniDat
http://linked.open...aciTvurceVysledku
http://linked.open.../riv/druhVysledku
http://linked.open...iv/duvernostUdaju
http://linked.open...titaPredkladatele
http://linked.open...dnocenehoVysledku
  • 9791
http://linked.open...ai/riv/idVysledku
  • RIV/00216224:14330/14:00076194
http://linked.open...riv/jazykVysledku
http://linked.open.../riv/klicovaSlova
  • Facility management; computational intelligence; machine learning; sensor networks; system integration; environmental conditions (en)
http://linked.open.../riv/klicoveSlovo
http://linked.open...odStatuVydavatele
  • IN - Indická republika
http://linked.open...ontrolniKodProRIV
  • [8011596DBB9F]
http://linked.open...i/riv/nazevZdroje
  • International Journal of Computer Science & Applications
http://linked.open...in/vavai/riv/obor
http://linked.open...ichTvurcuVysledku
http://linked.open...cetTvurcuVysledku
http://linked.open...UplatneniVysledku
http://linked.open...v/svazekPeriodika
  • Volume 11
http://linked.open...iv/tvurceVysledku
  • Pitner, Tomáš
  • Kriksciuniene, Dalia
  • Sakalauskas, Virgilijus
  • Kučera, Adam
issn
  • 0972-9038
number of pages
http://localhost/t...ganizacniJednotka
  • 14330
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