Sensor Network Analytics for Intelligent Facility Management

Druh Článek ve sborníku
Citace 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, 10 s. ISBN 978-1-61499-261-5. doi:10.3233/978-1-61499-262-2-212.
Originální jazyk angličtina
Obor Informatika
Klíčová slova Facility management system;computational intelligence;machine learning;thermal comfort;sensor networks

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.

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