Enhancing Building Energy Management: Adaptive Edge Computing for Optimized Efficiency and Inhabitant Comfort

Enhancing Building Energy Management: Adaptive Edge Computing for Optimized Efficiency and Inhabitant Comfort

<p dir="ltr">Nowadays, in contemporary building and energy management systems (BEMSs), the predominant approach involves rule-based methodologies, typically employing supervised or unsupervised learning, to deliver energy-saving recommendations to building occupants. However, these B...

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Bibliographic Details
Main Author: Sergio Márquez-Sánchez (19437985) (author)
Other Authors: Jaime Calvo-Gallego (10968849) (author), Aiman Erbad (14150589) (author), Muhammad Ibrar (9732177) (author), Javier Hernandez Fernandez (19418752) (author), Mahdi Houchati (16891560) (author), Juan Manuel Corchado (12582511) (author)
Published: 2023
Subjects:
Built environment and design
Building
Engineering
Communications engineering
Information and computing sciences
Machine learning
building and energy management systems (BEMSs)
edge computing
energy efficiency (EE)
federated learning (FL)
deep reinforcement learning (deep RL)
internet of things (IoT)
virtual organizations
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