A framework for collaborative cloud-based fault detection and diagnosis in smart buildings

Sanja Lazarova-Molnar, Nader Mohamed

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

9 Citations (Scopus)

Abstract

The potential for saving on energy related cost with timely and accurate Fault Detection and Diagnosis (FDD) in Building Management Systems (BMS) has been estimated to ca. 15-30% of the overall building energy-related cost. Due to the expansion of well-equipped smart buildings that feature multitudes of sensors and meters that enable collection of large amounts of data, FDD data-based methods have become very popular. Sensor and meter data, however, have been found as insufficient for FDD purposes, and it needs to be complemented with event/fault data that is more difficult to obtain. To account for the unavailability of event/fault data, BMS can benefit from sharing each other's data and utilize it for collaborative FDD. To support collaborative FDD and sharing of data, we rely on cloud computing. In this paper we present a framework for collaborative FDD of smart buildings that utilizes cloud computing and enables BMS to share and benefit from each other's data.

Original languageEnglish
Title of host publication2017 7th International Conference on Modeling, Simulation, and Applied Optimization, ICMSAO 2017
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781509054541
DOIs
Publication statusPublished - May 26 2017
Externally publishedYes
Event7th International Conference on Modeling, Simulation, and Applied Optimization, ICMSAO 2017 - Sharjah, United Arab Emirates
Duration: Apr 4 2017Apr 6 2017

Other

Other7th International Conference on Modeling, Simulation, and Applied Optimization, ICMSAO 2017
Country/TerritoryUnited Arab Emirates
CitySharjah
Period4/4/174/6/17

Keywords

  • Cloud computing
  • Collaborative processing
  • Fault detection and diagnosis
  • Smart buildings

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Applied Mathematics
  • Control and Optimization
  • Modelling and Simulation

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