Paper Info
Title
Occupancy driven building performance assessment.
Abstract
In this paper, we focus on the building performance assessment using big data and visual analytics techniques driven by building occupancy. Building occupancy is a paramount factor in building performance, specifically lighting, plug loads and HVAC equipment utilization. Extrapolation of patterns from big data sets, which consist of building information, energy consumption, environmental measurements and namely occupancy information, is a powerful analysis technique to extract useful semantic information about building performance. To this end, visual analytics techniques are exploited to visualize them in a compact and comprehensive way taking into account properties of human cognition, perception and sense making. Visual Analytics facilitates the detailed spatiotemporal analysis building performance in terms of occupancy comfort, building performance and energy consumption and exploits innovative data mining techniques and mechanisms to allow analysts to detect patterns and crucial point that are difficult to be detected otherwise, thus assisting them to further optimize the building’s operation. The presented tool has been tested on real data information acquired from a building located at southern Europe demonstrating its effectiveness and its usability for building managers.
Year
DOI
Venue
2016
10.1016/j.jides.2016.10.008
Journal of Innovation in Digital Ecosystems
Keywords
Field
DocType
Building performance assessment,Big data analytics,Visual analytics,Human presence,Occupancy extraction,Building occupancy visualization
Data science,HVAC,Usability,Visual analytics,Exploit,Occupancy,Engineering,Analytics,Big data,Energy consumption
Journal
Volume
Issue
ISSN
3
2
2352-6645
Citations 
PageRank 
References 
0
0.34
0
Authors
6
Name
Order
Citations
PageRank
Dimosthenis Ioannidis14316.72
Pantelis Tropios200.68
Stelios Krinidis39218.49
Thanos G. Stavropoulos414318.07
Dimitrios Tzovaras501.35
Spiridon Likothanasis642.14