ESTIMATION OF OCCUPANCY STATUS AND LEVELS FOR INDOOR SPACES
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Tarih
2020
Yazarlar
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
Scibulcom Ltd
Erişim Hakkı
info:eu-repo/semantics/closedAccess
Özet
Building energy use today accounts for over 40% of total primary energy consumption. The energy demand for buildings can be decreased through efficient building and facility management. The knowledge related to the use of indoor spaces is a key to successful management. The research aimed to investigate whether the occupancy levels of an indoor space can automatically be determined via machine learning algorithms based on data acquired from multiple indoor sensors. The study involved indoor data collection and a machine learning experiment. The results indicated that machine learning can be considered as a promising approach for the detection of indoor occupancy status and levels.
Açıklama
Anahtar Kelimeler
indoor; building; occupancy; machine learning; classification
Kaynak
Journal of Environmental Protection and Ecology
WoS Q Değeri
N/A
Scopus Q Değeri
Q3
Cilt
21
Sayı
4
