Leveraging Machine Learning and Big Data for Smart Buildings: A Comprehensive Survey

Basheer Qolomany, Ala Al-Fuqaha, Ajay Gupta, Driss Benhaddou, Safaa Alwajidi, Junaid Qadir, Alvis C. Fong

Research output: Contribution to journalArticlepeer-review

26 Scopus citations

Abstract

Future buildings will offer new convenience, comfort, and efficiency possibilities to their residents. Changes will occur to the way people live as technology involves people's lives and information processing is fully integrated into their daily living activities and objects. The future expectation of smart buildings includes making the residents' experience as easy and comfortable as possible. The massive streaming data generated and captured by smart building appliances and devices contain valuable information that needs to be mined to facilitate timely actions and better decision making. Machine learning and big data analytics will undoubtedly play a critical role to enable the delivery of such smart services. In this paper, we survey the area of smart building with a special focus on the role of techniques from machine learning and big data analytics. This survey also reviews the current trends and challenges faced in the development of smart building services.

Original languageEnglish (US)
Article number8754678
Pages (from-to)90316-90356
Number of pages41
JournalIEEE Access
Volume7
DOIs
StatePublished - 2019

Keywords

  • Smart buildings
  • big data analytics
  • machine learning (ML)
  • smart homes
  • the Internet of Things (IoT)

ASJC Scopus subject areas

  • Computer Science(all)
  • Materials Science(all)
  • Engineering(all)

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