Computer Science > Machine Learning
arXiv:2211.14889 (cs)
[Submitted on 27 Nov 2022]
Title:Machine Learning for Smart and Energy-Efficient Buildings
Authors:Hari Prasanna Das,Yu-Wen Lin,Utkarsha Agwan,Lucas Spangher,Alex Devonport,Yu Yang,Jan Drgona,Adrian Chong,Stefano Schiavon,Costas J. Spanos
View a PDF of the paper titled Machine Learning for Smart and Energy-Efficient Buildings, by Hari Prasanna Das and 9 other authors
View PDFAbstract:Energy consumption in buildings, both residential and commercial, accounts for approximately 40% of all energy usage in the U.S., and similar numbers are being reported from countries around the world. This significant amount of energy is used to maintain a comfortable, secure, and productive environment for the occupants. So, it is crucial that the energy consumption in buildings must be optimized, all the while maintaining satisfactory levels of occupant comfort, health, and safety. Recently, Machine Learning has been proven to be an invaluable tool in deriving important insights from data and optimizing various systems. In this work, we review the ways in which machine learning has been leveraged to make buildings smart and energy-efficient. For the convenience of readers, we provide a brief introduction of several machine learning paradigms and the components and functioning of each smart building system we cover. Finally, we discuss challenges faced while implementing machine learning algorithms in smart buildings and provide future avenues for research at the intersection of smart buildings and machine learning.
| Subjects: | Machine Learning (cs.LG); Systems and Control (eess.SY) |
| Cite as: | arXiv:2211.14889 [cs.LG] |
| (orarXiv:2211.14889v1 [cs.LG] for this version) | |
| https://doi.org/10.48550/arXiv.2211.14889 arXiv-issued DOI via DataCite |
Submission history
From: Hari Prasanna Das [view email][v1] Sun, 27 Nov 2022 17:04:31 UTC (4,536 KB)
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View a PDF of the paper titled Machine Learning for Smart and Energy-Efficient Buildings, by Hari Prasanna Das and 9 other authors
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