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

机译:基于在线学习热舒适模型的室内热环境智能控制使用红外线热成像

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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.
机译:根据房间乘客或建筑物管理人员给出的设定点进行本室内环境控制。该控制方法可能存在不正当的温度设定点,从而导致过热/过冷和相应的能量浪费的不适。为了解决这些问题,提出了一种基于使用红外热成像的在线学习热舒适模型的室内环境控制的智能解决方案,以进行基于设定点的控制。进行实验,研究了所提出的智能控制方法的可行性,用户验收和能量性能。实验结果表明,用户对该控制系统令人满意,这意味着所提出的基于热敏预测的室内热环境控制方法对于实际应用是可行的,并且可以使用更智能的方式实现更令人满意的室内热环境。

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