Challenges in the data collection for diagnostics of smart buildings

Sanja Lazarova-Molnar, Nader Mohamed

Research output: Chapter in Book/Report/Conference proceedingConference contribution

11 Citations (Scopus)


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.

Original languageEnglish
Title of host publicationInformation Science and Applications, ICISA 2016
EditorsKuinam J. Kim, Nikolai Joukov
PublisherSpringer Verlag
Number of pages11
ISBN (Print)9789811005565
Publication statusPublished - 2016
Externally publishedYes
EventInternational Conference on Information Science and Applications, ICISA 2016 - Minh City, Viet Nam
Duration: Feb 15 2016Feb 18 2016

Publication series

NameLecture Notes in Electrical Engineering
ISSN (Print)1876-1100
ISSN (Electronic)1876-1119


OtherInternational Conference on Information Science and Applications, ICISA 2016
Country/TerritoryViet Nam
CityMinh City


  • Challenges
  • Data collection
  • Diagnostics
  • Smart buildings

ASJC Scopus subject areas

  • Industrial and Manufacturing Engineering


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