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Leveraging Artificial Intelligence in Indoor Air Quality Management: A Review of Current Status, Opportunities, and Future Challenges: AI and IAQ
KTH, School of Architecture and the Built Environment (ABE), Civil and Architectural Engineering, Building Technology and Design.ORCID iD: 0000-0002-9361-1796
2024 (English)In: The REHVA European HVAC Journal, ISSN 1307-3729, Vol. 61, no 1, p. 35-37Article in journal (Refereed) Published
Abstract [en]

Recent advancements in the fields of artificial intelligence, machine learning, and the Internetof Things have created opportunities to improve the performance, safety, and energyefficiency of building ventilation. This report explores the current state of AI technologiesin building ventilation and indoor air quality management by highlighting applications oftechnologies related to air quality monitoring, control, predictive maintenance, and energyoptimization. The report also examines the ethical and data privacy issues associated withdeploying these technologies and advocates AI integration in building HVAC systems byidentifying future challenges and avenues for research.

Place, publisher, year, edition, pages
Federation of European Heating, Ventilation and Air Conditioning Associations , 2024. Vol. 61, no 1, p. 35-37
Keywords [en]
Artificial Intelligence, Machine Learning, Internet of Things, Indoor Air Quality, Building Ventilation, Occupants' Health, HVAC, Energy Efficiency
National Category
Building Technologies
Research subject
Civil and Architectural Engineering, Building Technology; Civil and Architectural Engineering
Identifiers
URN: urn:nbn:se:kth:diva-346792OAI: oai:DiVA.org:kth-346792DiVA, id: diva2:1860405
Note

QC 20240524

Available from: 2024-05-24 Created: 2024-05-24 Last updated: 2024-06-24Bibliographically approved

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fulltext(162 kB)184 downloads
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Sadrizadeh, Sasan

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CiteExportLink to record
Permanent link

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Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf