Smart control of indoor thermal environment based on online learned thermal comfort model using infrared thermal imaging

The present indoor environment control is conducted according to the set-points given by room occupants or building managers. This control method might exist improper temperature set-points so that result in discomfort of overheating/overcooling and corresponding energy waste. For the purpose of solving these problems, a smart solution for indoor environment control, which is based on online learned thermal comfort model using infrared thermal imaging, is proposed to take place of the set-points based control. Experiments were conducted to study the feasibility, user acceptance, and energy performance of the proposed smart control method. The experiment results show that shows that the users are satisfactory with this control system, which means the proposed indoor thermal environment control method based on thermal sensation prediction is feasible for actual application and effective for achieve more satisfactory indoor thermal environment using a smarter way.