Sensor Network Analytics for Intelligent Facility Management

D 2013

Sensor Network Analytics for Intelligent Facility Management

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

Basic information

Original name

Sensor Network Analytics for Intelligent Facility Management

Authors

KRIKSCIUNIENE, Dalia (440 Lithuania, belonging to the institution), Tomáš PITNER (203 Czech Republic, guarantor, belonging to the institution), Adam KUČERA (203 Czech Republic, belonging to the institution) and Virgilijus SAKALAUSKAS (440 Lithuania)

Edition

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

Publisher

IOS Press

Other information

Language

English

Type of outcome

Stať ve sborníku

Field of Study

10201 Computer sciences, information science, bioinformatics

Country of publisher

Czech Republic

Confidentiality degree

není předmětem státního či obchodního tajemství

Publication form

printed version "print"

RIV identification code

RIV/00216224:14330/13:00068804

Organization unit

Faculty of Informatics

ISBN

978-1-61499-261-5

ISSN

DOI

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

UT WoS

000339340900023

Keywords in English

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

Abstract

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.

Links

LG13010, research and development project

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

Investor: Ministry of Education, Youth and Sports of the CR

Citovat

KRIKSCIUNIENE, Dalia, Tomáš PITNER, Adam KUČERA and 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, p. 212-221. ISBN 978-1-61499-261-5. Available from: 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 and 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, p.~212-221. ISBN~978-1-61499-261-5. Available from: https://dx.doi.org/10.3233/978-1-61499-262-2-212.

Detailed Information on Publication Record