Privacy preserved and decentralized thermal comfort prediction model for smart buildings using federated learning

Privacy preserved and decentralized thermal comfort prediction model for smart buildings using federated learning

Thermal comfort is a crucial element of smart buildings that assists in improving, analyzing, and realizing intelligent structures. Energy consumption forecasts for such smart buildings are crucial owing to the intricate decision-making processes surrounding resource efficiency. Machine learning (ML...

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Bibliographic Details
Main Authors: Sidra Abbas, Shtwai Alsubai, Gabriel Avelino Sampedro, Mideth Abisado, Ahmad Almadhor, Tai-hoon Kim
Format: Article
Language:English
Published: PeerJ Inc. 2024-02-01
Series:PeerJ Computer Science
Subjects:
Thermal comfort
Smart buildings
Federated deep learning
Machine learning
Privacy
Online Access:https://peerj.com/articles/cs-1899.pdf

Internet

https://peerj.com/articles/cs-1899.pdf

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