2024
DOI: 10.7717/peerj-cs.1899
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Privacy preserved and decentralized thermal comfort prediction model for smart buildings using federated learning

Sidra Abbas,
Shtwai Alsubai,
Gabriel Avelino Sampedro
et al.

Abstract: 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) techniques are employed to estimate energy consumption. ML algorithms, however, require a large amount of data to be adequate. There may be privacy violations due to collecting this data. To tackle this problem, t… Show more

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