The 2024 revision of the EU Energy Performance of Buildings Directive recognizes Indoor Environmental Quality (IEQ) as a key complement to energy efficiency in promoting sustainable buildings and ensuring occupant comfort and well-being. This review approaches the subject of Smart Building from a multidisciplinary perspective, focussing on residential applications. It examines the four IEQ components: Indoor Air Quality, Thermal Comfort, Visual Comfort and Acoustic Comfort. The discussion begins with technical standards and rating schemes, emphasising the physiological and psychological impacts of environmental conditions. It then investigates the state of research on smart sensors and IoT technologies, followed by recent advances in Building Management Systems, particularly the integration of Artificial Intelligence for adaptive comfort control. Finally, the paper outlines future directions, including personalised comfort models, standardised assessment methods, scalable and interoperable sensor networks and privacy-preserving data strategies.
Smart sensors for Indoor Environmental Quality in residential smart buildings: a review
Andrea Alongi;Luca Pacileo;Rossano Scoccia;Livio Mazzarella
In corso di stampa
Abstract
The 2024 revision of the EU Energy Performance of Buildings Directive recognizes Indoor Environmental Quality (IEQ) as a key complement to energy efficiency in promoting sustainable buildings and ensuring occupant comfort and well-being. This review approaches the subject of Smart Building from a multidisciplinary perspective, focussing on residential applications. It examines the four IEQ components: Indoor Air Quality, Thermal Comfort, Visual Comfort and Acoustic Comfort. The discussion begins with technical standards and rating schemes, emphasising the physiological and psychological impacts of environmental conditions. It then investigates the state of research on smart sensors and IoT technologies, followed by recent advances in Building Management Systems, particularly the integration of Artificial Intelligence for adaptive comfort control. Finally, the paper outlines future directions, including personalised comfort models, standardised assessment methods, scalable and interoperable sensor networks and privacy-preserving data strategies.| File | Dimensione | Formato | |
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DE_GSOL_2578592_Author_AU.pdf
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