TY - GEN
T1 - Challenges in the data collection for diagnostics of smart buildings
AU - Lazarova-Molnar, Sanja
AU - Mohamed, Nader
N1 - Publisher Copyright:
© Springer Science+Business Media Singapore 2016.
PY - 2016
Y1 - 2016
N2 - The rise of smart buildings, i.e. buildings equipped with latest technology and built according to cutting-edge architectural advances, implies increased buildings’ complexity. For this reason, both new and retrofitted buildings are often susceptible to new and unforeseen faults, whose timely detection and servicing can significantly affect buildings performance. Many Fault Detection and Diagnosis (FDD) methods are data-driven, where the quality of collected data can significantly affect the accuracy of results. However, data collection for FDD of buildings is a challenging task as needed data is not typically readily available. In this paper we focus on the data collection for FDD of smart buildings. This forms the motivation of this paper, i.e. to identify the challenges that relate to data collection processes for FDD of buildings, as well as propose workarounds of how to tackle the more important ones. Furthermore, we also look into how new technologies can be useful for this goal.
AB - The rise of smart buildings, i.e. buildings equipped with latest technology and built according to cutting-edge architectural advances, implies increased buildings’ complexity. For this reason, both new and retrofitted buildings are often susceptible to new and unforeseen faults, whose timely detection and servicing can significantly affect buildings performance. Many Fault Detection and Diagnosis (FDD) methods are data-driven, where the quality of collected data can significantly affect the accuracy of results. However, data collection for FDD of buildings is a challenging task as needed data is not typically readily available. In this paper we focus on the data collection for FDD of smart buildings. This forms the motivation of this paper, i.e. to identify the challenges that relate to data collection processes for FDD of buildings, as well as propose workarounds of how to tackle the more important ones. Furthermore, we also look into how new technologies can be useful for this goal.
KW - Challenges
KW - Data collection
KW - Diagnostics
KW - Smart buildings
UR - http://www.scopus.com/inward/record.url?scp=84959176506&partnerID=8YFLogxK
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U2 - 10.1007/978-981-10-0557-2_90
DO - 10.1007/978-981-10-0557-2_90
M3 - Conference contribution
AN - SCOPUS:84959176506
SN - 9789811005565
T3 - Lecture Notes in Electrical Engineering
SP - 941
EP - 951
BT - Information Science and Applications, ICISA 2016
A2 - Kim, Kuinam J.
A2 - Joukov, Nikolai
PB - Springer Verlag
T2 - International Conference on Information Science and Applications, ICISA 2016
Y2 - 15 February 2016 through 18 February 2016
ER -