Estimation of Unmeasured Room Temperature, Relative Humidity, and CO2 Concentrations for a Smart Building Using Machine Learning and Exploratory Data Analysis

Smart buildings that utilize innovative technologies such as artificial intelligence (AI), the internet of things (IoT), and cloud computing to improve comfort and reduce energy waste are gaining popularity. Smart buildings comprise a range of sensors to measure real-time indoor environment variable...

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Vydáno v:	Energies Ročník 15; číslo 12; s. 4213
Hlavní autoři:	Kaligambe, Abraham, Fujita, Goro, Keisuke, Tagami
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	Basel MDPI AG 08.06.2022
Témata:	Accuracy Algorithms Artificial intelligence Case studies CO2 concentrations Communication Communications networks Data analysis Energy consumption estimation Forecasting Green buildings Human error Humidity HVAC Indoor air quality Internet of Things Machine learning Neural networks Performance evaluation relative humidity room temperature room temperature; relative humidity; CO2 concentrations; estimation; HVAC; machine learning; XGBoost algorithm; smart buildings; sensors; exploratory data analysis Sensors Simulation Software T Technology Variables Japan
ISSN:	1996-1073, 1996-1073
On-line přístup:	Získat plný text
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