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Machine learning applications for smart building energy utilization : a survey
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- Huotari, Matti (author)
- School of Science, Aalto University, Espoo, Finland; Metropolia University of Applied Sciences, Helsinki, Finland
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- Malhi, Avleen (author)
- School of Science, Aalto University, Espoo, Finland; Warwick University, Coventry, UK
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- Främling, Kary, 1965- (author)
- Umeå universitet,Institutionen för datavetenskap,School of Science, Aalto University, Espoo, Finland
- (creator_code:org_t)
- 2024
- 2024
- English.
- In: Archives of Computational Methods in Engineering. - : Springer Nature. - 1134-3060 .- 1886-1784.
- Journal article (peer-reviewed)
Abstract
Subject headings
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- The United Nations launched sustainable development goals in 2015 that include goals for sustainable energy. From global energy consumption, households consume 20–30% of energy in Europe, North America and Asia; furthermore, the overall global energy consumption has steadily increased in the recent decades. Consequently, to meet the increased energy demand and to promote efficient energy consumption, there is a persistent need to develop applications enhancing utilization of energy in buildings. However, despite the potential significance of AI in this area, few surveys have systematically categorized these applications. Therefore, this paper presents a systematic review of the literature, and then creates a novel taxonomy for applications of smart building energy utilization. The contributions of this paper are (a) a systematic review of applications and machine learning methods for smart building energy utilization, (b) a novel taxonomy for the applications, (c) detailed analysis of these solutions and techniques used for the applications (electric grid, smart building energy management and control, maintenance and security, and personalization), and, finally, (d) a discussion on open issues and developments in the field.
Subject headings
- NATURVETENSKAP -- Data- och informationsvetenskap -- Annan data- och informationsvetenskap (hsv//swe)
- NATURAL SCIENCES -- Computer and Information Sciences -- Other Computer and Information Science (hsv//eng)
Keyword
- data- och systemvetenskap
- computer and systems sciences
Publication and Content Type
- ref (subject category)
- art (subject category)
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