Sensor Network Analytics for Intelligent Facility Management

D 2013

Sensor Network Analytics for Intelligent Facility Management

KRIKSCIUNIENE, Dalia, Tomáš PITNER, Adam KUČERA a Virgilijus SAKALAUSKAS

Základní údaje

Originální název

Sensor Network Analytics for Intelligent Facility Management

Autoři

KRIKSCIUNIENE, Dalia (440 Litva, domácí), Tomáš PITNER (203 Česká republika, garant, domácí), Adam KUČERA (203 Česká republika, domácí) a Virgilijus SAKALAUSKAS (440 Litva)

Vydání

Amsterdam, Proceedings of the 6th International Conference on Intelligent Interactive Multimedia Systems and Services (IIMSS2013), od s. 212-221, 10 s. 2013

Nakladatel

IOS Press

Další údaje

Jazyk

angličtina

Typ výsledku

Stať ve sborníku

Obor

10201 Computer sciences, information science, bioinformatics

Stát vydavatele

Česká republika

Utajení

není předmětem státního či obchodního tajemství

Forma vydání

tištěná verze "print"

Kód RIV

RIV/00216224:14330/13:00068804

Organizační jednotka

Fakulta informatiky

ISBN

978-1-61499-261-5

ISSN

DOI

http://dx.doi.org/10.3233/978-1-61499-262-2-212

UT WoS

000339340900023

Klíčová slova anglicky

Facility management system;computational intelligence;machine learning;thermal comfort;sensor networks

Příznaky

Mezinárodní význam, Recenzováno

Změněno: 28. 4. 2014 00:12, RNDr. Pavel Šmerk, Ph.D.

Anotace

V originále

The article addresses the problem of intelligent monitoring of facility management data flows collected from heterogeneous sources, including low-level data of sensors and probes, geographical indicators, scheduling and personal identification systems. 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 facilitate process of extracting essential characteristics of facility management for detecting dependencies and observing anomalies. The performance of the model was tested by experimental analysis of facility management of the university campus, designed for exploring how various environment variables affect temperature in the lecture rooms, equipped by the air conditioning devices.

Návaznosti

LG13010, projekt VaV

Název: Zastoupení ČR v European Research Consortium for Informatics and Mathematics (Akronym: ERCIM-CZ)

Investor: Ministerstvo školství, mládeže a tělovýchovy ČR, Zastoupení ČR v European Research Consortium for Informatics and Mathematics

Citovat

KRIKSCIUNIENE, Dalia, Tomáš PITNER, Adam KUČERA a Virgilijus SAKALAUSKAS. Sensor Network Analytics for Intelligent Facility Management. In George A. Tsihrintzis, Maria Virvou, Toyohide Watanabe, Lakhmi C. Jain, Robert J. Howlett. Proceedings of the 6th International Conference on Intelligent Interactive Multimedia Systems and Services (IIMSS2013). Amsterdam: IOS Press, 2013, s. 212-221. ISBN 978-1-61499-261-5. Dostupné z: https://dx.doi.org/10.3233/978-1-61499-262-2-212.

@inproceedings{1115236,
   author = {Kriksciuniene, Dalia and Pitner, Tomáš and Kučera, Adam and Sakalauskas, Virgilijus},
   address = {Amsterdam},
   booktitle = {Proceedings of the 6th International Conference on Intelligent Interactive Multimedia Systems and Services (IIMSS2013)},
   doi = {http://dx.doi.org/10.3233/978-1-61499-262-2-212},
   editor = {George A. Tsihrintzis, Maria Virvou, Toyohide Watanabe, Lakhmi C. Jain, Robert J. Howlett},
   keywords = {Facility management system;computational intelligence;machine learning;thermal comfort;sensor networks},
   howpublished = {tištěná verze "print"},
   language = {eng},
   location = {Amsterdam},
   isbn = {978-1-61499-261-5},
   pages = {212-221},
   publisher = {IOS Press},
   title = {Sensor Network Analytics for Intelligent Facility Management},
   year = {2013}
}

TY  - JOUR
ID  - 1115236
AU  - Kriksciuniene, Dalia - Pitner, Tomáš - Kučera, Adam - Sakalauskas, Virgilijus
PY  - 2013
TI  - Sensor Network Analytics for Intelligent Facility Management
PB  - IOS Press
CY  - Amsterdam
SN  - 9781614992615
KW  - Facility management system;computational intelligence;machine learning;thermal comfort;sensor networks
N2  - The article addresses the problem of intelligent monitoring of facility management data flows collected from heterogeneous sources, including low-level data of sensors and probes, geographical indicators, scheduling and personal identification systems. 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 facilitate process of extracting essential characteristics of facility management for detecting dependencies and observing anomalies. The performance of the model was tested by experimental analysis of facility management of the university campus, designed for exploring how various environment variables affect temperature in the lecture rooms, equipped by the air conditioning devices.
ER  -

KRIKSCIUNIENE, Dalia, Tomáš PITNER, Adam KUČERA a Virgilijus SAKALAUSKAS. Sensor Network Analytics for Intelligent Facility Management. In George A. Tsihrintzis, Maria Virvou, Toyohide Watanabe, Lakhmi C. Jain, Robert J. Howlett. \textit{Proceedings of the 6th International Conference on Intelligent Interactive Multimedia Systems and Services (IIMSS2013)}. Amsterdam: IOS Press, 2013, s.~212-221. ISBN~978-1-61499-261-5. Dostupné z: https://dx.doi.org/10.3233/978-1-61499-262-2-212.

Podrobný výpis o publikaci