Indoor air quality (IAQ) has emerged as a critical area of research, reflecting growing concerns regarding occupant health, well-being, and comfort in enclosed environments. The increasing complexity of modern indoor spaces, coupled with rapid advancements in sensing technologies and data analysis methodologies, has intensified scientific interest in effective IAQ assessment and management. This review aims to examine current technologies and methodologies for monitoring key indoor air quality indicators. Furthermore, it offers practical recommendations for enhancing IAQ in diverse built environments and explores the integration of artificial intelligence (AI) into monitoring systems. The findings underscore the potential of AI-enhanced approaches to optimize indoor environmental conditions and support proactive air quality management strategies.
Methodologies Used to Determine the Main Markers of Indoor Air Quality
Notardonato, IvanPrimo
;Di Fiore, Cristina;Avino, Pasquale
Ultimo
2025-01-01
Abstract
Indoor air quality (IAQ) has emerged as a critical area of research, reflecting growing concerns regarding occupant health, well-being, and comfort in enclosed environments. The increasing complexity of modern indoor spaces, coupled with rapid advancements in sensing technologies and data analysis methodologies, has intensified scientific interest in effective IAQ assessment and management. This review aims to examine current technologies and methodologies for monitoring key indoor air quality indicators. Furthermore, it offers practical recommendations for enhancing IAQ in diverse built environments and explores the integration of artificial intelligence (AI) into monitoring systems. The findings underscore the potential of AI-enhanced approaches to optimize indoor environmental conditions and support proactive air quality management strategies.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.


