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Sensor-Based Machine Learning Approach for Indoor Air Quality Monitoring in an Automobile Manufacturing
The alternative control concept using emission from the machine has the potential to reduce energy consumption in HVAC systems. This paper reports on a study of alternative inputs for a control system of HVAC using machine learning algorithms, based on data that are gathered in a welding area of an automotive factory. A data set of CO2, fine dust, temperatures and air velocity was logged using continuous and gravimetric measurements during two typical production weeks. The HVAC system wasdoi:10.3390/en14217271 fatcat:k23bnek6zvcbrcljm5fj2cfufe