Artificial intelligence based anomaly detection of energy consumption in buildings: A review, current trends and new perspectives

Enormous amounts of data are being produced everyday by sub-meters and smart sensors installed in residential buildings. If leveraged properly, that data could assist end-users, energy producers and utility companies in detecting anomalous power consumption and understanding the causes of each anoma...

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Vydáno v:	Applied energy Ročník 287; s. 116601
Hlavní autoři:	Himeur, Yassine, Ghanem, Khalida, Alsalemi, Abdullah, Bensaali, Faycal, Amira, Abbes
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	Elsevier Ltd 01.04.2021
Témata:	Anomaly detection artificial intelligence data collection decision making Deep abnormality detection Energy consumption in buildings energy efficiency Energy saving energy use and consumption Machine learning surveys taxonomy Energy saving Energy consumption in buildings Anomaly detection Machine learning Deep abnormality detection
ISSN:	0306-2619, 1872-9118
On-line přístup:	Získat plný text
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