Mobile crowdsourcing of data for fault detection and diagnosis in smart buildings

Sanja Lazarova-Molnar, Halldór Pór Logason, Peter Grønbæk Andersen, Mikkel Baun Kjærgaard

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

9 Citations (Scopus)

Abstract

Energy use of buildings represents roughly 40% of the overall energy consumption. Most of the national agendas contain goals related to reducing the energy consumption and carbon footprint. Timely and accurate fault detection and diagnosis (FDD) in building management systems (BMS) have the potential to reduce energy consumption cost by approximately 15-30%. Most of the FDD methods are data-based, meaning that their performance is tightly linked to the quality and availability of relevant data. Based on our experience, faults and relevant events data is very sparse and inadequate, mostly because of the lack of will and incentive for those that would need to keep track of faults. In this paper we introduce the idea of using crowdsourcing to support FDD data collection processes, and illustrate our idea through a mobile application that has been implemented for this purpose. Furthermore, we propose a strategy of how to successfully deploy this building occupants' crowdsourcing application. Copyright is held by the owner/author(s). Publication rights licensed to ACM.

Original languageEnglish
Title of host publicationProceedings of the 2016 Research in Adaptive and Convergent Systems, RACS 2016
PublisherAssociation for Computing Machinery, Inc
Pages12-17
Number of pages6
ISBN (Electronic)9781450344555
DOIs
Publication statusPublished - Oct 11 2016
Externally publishedYes
Event2016 Research in Adaptive and Convergent Systems, RACS 2016 - Odense, Denmark
Duration: Oct 11 2016Oct 14 2016

Other

Other2016 Research in Adaptive and Convergent Systems, RACS 2016
Country/TerritoryDenmark
CityOdense
Period10/11/1610/14/16

Keywords

  • Buildings
  • Crowdsourcing
  • Data collection
  • Energy performance
  • Fault detection and diagnosis
  • Occupants

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Computer Science(all)

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