• Corpus ID: 8057027

Data Analysis in the Intelligent Building Environment

@article{Kriksciuniene2014DataAI,
  title={Data Analysis in the Intelligent Building Environment},
  author={Dalia Kriksciuniene and Tom{\'a}s Pitner and Adam Kucera and Virgilijus Sakalauskas},
  journal={Int. J. Comput. Sci. Appl.},
  year={2014},
  volume={11},
  pages={1-17}
}

• D. Kriksciuniene, T. Pitner, +1 author V. Sakalauskas
• Published 2014
• Engineering
• Int. J. Comput. Sci. Appl.

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.