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@article{1195469,
author = {Kriksciuniene, Dalia and Pitner, Tomáš and Kučera, Adam and Sakalauskas, Virgilijus},
article_location = {Kolhapur, India},
article_number = {Issue 1},
keywords = {Facility management; computational intelligence; machine learning; sensor networks; system integration; environmental conditions},
language = {eng},
issn = {0972-9038},
journal = {International Journal of Computer Science & Applications},
title = {Data Analysis in the Intelligent Building Environment},
url = {http://www.tmrfindia.org/ijcsa/v111.html},
volume = {Volume 11},
year = {2014}
}
TY - JOUR
ID - 1195469
AU - Kriksciuniene, Dalia - Pitner, Tomáš - Kučera, Adam - Sakalauskas, Virgilijus
PY - 2014
TI - Data Analysis in the Intelligent Building Environment
JF - International Journal of Computer Science & Applications
VL - Volume 11
IS - Issue 1
SP - 1-17
EP - 1-17
PB - Technomathematics Research Foundation
SN - 09729038
KW - Facility management
KW - computational intelligence
KW - machine learning
KW - sensor networks
KW - system integration
KW - environmental conditions
UR - http://www.tmrfindia.org/ijcsa/v111.html
L2 - http://www.tmrfindia.org/ijcsa/v111.html
N2 - 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. Based on the obtained results, we elaborate on further steps needed for beneficial, efficient and flexible data analysis system for the field of facility management.
ER -
KRIKSCIUNIENE, Dalia, Tomáš PITNER, Adam KUČERA a Virgilijus SAKALAUSKAS. Data Analysis in the Intelligent Building Environment. \textit{International Journal of Computer Science \&{} Applications}. Kolhapur, India: Technomathematics Research Foundation, 2014, Volume 11, Issue 1, s.~1-17. ISSN~0972-9038.
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