Mobile Crowdsourcing of Occupant Feedback in Smart Buildings

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

Research output: Contribution to journalJournal articleResearchpeer-review

220 Downloads (Pure)

Abstract

Energy consumption of buildings represents roughly 40% of the overall energy consumption. Most of the national agendas include rigorous measures aimed at reducing the energy consumption and, thereby, the 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 FDD methods are data-based, meaning that their performance is tightly linked to the quality and availability of relevant data about faults and related events. Based on our experience, such data is very sparse and inadequate, mostly because of the difficulty and lack of incentive to collect such data in a structured manner. In this article we introduce the idea of using crowdsourcing to support FDD-related data collection, and illustrate the concept through a mobile application that has been implemented for this purpose. Furthermore, we describe our experience from using the mobile application in a university building and propose a strategy of how to successfully deploy the application in new buildings.
Original languageEnglish
JournalApplied Computing Review
Volume17
Issue number1
Pages (from-to)5-14
ISSN1559-6915
DOIs
Publication statusPublished - 2017

Fingerprint

Dive into the research topics of 'Mobile Crowdsourcing of Occupant Feedback in Smart Buildings'. Together they form a unique fingerprint.

Cite this