research-article

Mobile Crowdsourcing of Data for Fault Detection and Diagnosis in Smart Buildings

Authors:

Sanja Lazarova-Molnar,

Halldór Þór Logason,

Peter Grønbæk Andersen,

Mikkel Baun KjærgaardAuthors Info & Claims

RACS '16: Proceedings of the International Conference on Research in Adaptive and Convergent Systems

Pages 12 - 17

https://doi.org/10.1145/2987386.2987416

Published: 11 October 2016 Publication History

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.

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Cited By

Artan DTekce IYilmaz NErgen E(2023)The contextual information requirements for collection and use of occupant feedback in BIM-enabled FMFacilities10.1108/F-03-2023-0028Online publication date: 1-Nov-2023
https://doi.org/10.1108/F-03-2023-0028
Sheikh Khan DKolarik J(2021)Can occupant voting systems provide energy savings and improved occupant satisfaction in buildings?—a reviewScience and Technology for the Built Environment10.1080/23744731.2021.197601728:2(221-239)Online publication date: 23-Sep-2021
https://doi.org/10.1080/23744731.2021.1976017
Sheikh Khan DKolarik JWeitzmann P(2021)Application of an occupant voting system for continuous occupant feedback on thermal and indoor air quality – Case studies in office spacesEnergy and Buildings10.1016/j.enbuild.2021.111363251(111363)Online publication date: Nov-2021
https://doi.org/10.1016/j.enbuild.2021.111363
Show More Cited By

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Published In

cover image ACM Conferences

RACS '16: Proceedings of the International Conference on Research in Adaptive and Convergent Systems

October 2016

266 pages

ISBN:9781450344555

DOI:10.1145/2987386

Copyright © 2016 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

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SIGAPP: ACM Special Interest Group on Applied Computing
ACCT: Association of Convergent Computing Technology

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 11 October 2016

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Refereed limited

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Innovation Fund Denmark

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RACS '16

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SIGAPP
ACCT

RACS '16: International Conference on Research in Adaptive and Convergent Systems

October 11 - 14, 2016

Odense, Denmark

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RACS '16 Paper Acceptance Rate 40 of 161 submissions, 25%;

Overall Acceptance Rate 393 of 1,581 submissions, 25%

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Citations

Cited By

Artan DTekce IYilmaz NErgen E(2023)The contextual information requirements for collection and use of occupant feedback in BIM-enabled FMFacilities10.1108/F-03-2023-0028Online publication date: 1-Nov-2023
https://doi.org/10.1108/F-03-2023-0028
Sheikh Khan DKolarik J(2021)Can occupant voting systems provide energy savings and improved occupant satisfaction in buildings?—a reviewScience and Technology for the Built Environment10.1080/23744731.2021.197601728:2(221-239)Online publication date: 23-Sep-2021
https://doi.org/10.1080/23744731.2021.1976017
Sheikh Khan DKolarik JWeitzmann P(2021)Application of an occupant voting system for continuous occupant feedback on thermal and indoor air quality – Case studies in office spacesEnergy and Buildings10.1016/j.enbuild.2021.111363251(111363)Online publication date: Nov-2021
https://doi.org/10.1016/j.enbuild.2021.111363
Li XXie KWang XXie GXie DLi ZWen JDiao ZWang T(2020)Quick and Accurate False Data Detection in Mobile Crowd SensingIEEE/ACM Transactions on Networking10.1109/TNET.2020.298268528:3(1339-1352)Online publication date: Jun-2020
https://doi.org/10.1109/TNET.2020.2982685
Lazarova-Molnar SMarkoska EMohamed NJohansson BJain S(2018)A zoning framework for enhanced smart building automationProceedings of the 2018 Winter Simulation Conference10.5555/3320516.3320990(3977-3986)Online publication date: 9-Dec-2018
https://dl.acm.org/doi/10.5555/3320516.3320990
Lazarova-Molnar SMohamed NZdravkova KEleftherakis GKefalas P(2017)On the Complexity of Smart Buildings Occupant BehaviorProceedings of the 8th Balkan Conference in Informatics10.1145/3136273.3136274(1-4)Online publication date: 20-Sep-2017
https://dl.acm.org/doi/10.1145/3136273.3136274
Lazarova-Molnar SMohamed N(2017)Collaborative data analytics for smart buildings: opportunities and modelsCluster Computing10.1007/s10586-017-1362-xOnline publication date: 15-Nov-2017
https://doi.org/10.1007/s10586-017-1362-x

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