Heat Flux Sensing for Machine-Learning-Based Personal Thermal Comfort Modeling
Heat Flux Sensing for Machine-Learning-Based Personal Thermal Comfort Modeling
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DOI：
10.3390/s19173691
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发表时间：
2019-08
期刊：
影响因子：
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通讯作者：
Wooyoung Jung;F. Jazizadeh;T. Diller
中科院分区：
文献类型：
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作者：
Wooyoung Jung;F. Jazizadeh;T. Diller
近年来，生理特征在开发用于改善和准确的人在回路（HITL）加热、通风和空调（HVAC）系统的自适应操作的个人热舒适性模型中得到了更多的关注。为了识别有效的生理传感系统，以提高以人为中心和分布式控制的灵活性，使用机器学习算法，我们研究了热通量传感如何在瞬态环境条件下提高个人热舒适性。我们探讨了面部和手腕皮肤的热交换率的变化。这些区域通常暴露在室内环境中，并通过皮肤热交换促进温度调节机制，我们将皮肤和环境温度的变化与个人热偏好的推断相结合。采用实验和数据分析方法，我们已经评估了18个人类受试者的个人热偏好的建模知名的分类器，使用不同的学习场景。实验测量揭示了个人热偏好的差异以及它们如何反映在生理变量中。此外，我们已经表明，即使与使用皮肤温度相比，热交换率在提高个人推理模型的性能方面也具有很高的潜力。
In recent years, physiological features have gained more attention in developing models of personal thermal comfort for improved and accurate adaptive operation of Human-In-The-Loop (HITL) Heating, Ventilation, and Air-Conditioning (HVAC) systems. Pursuing the identification of effective physiological sensing systems for enhancing flexibility of human-centered and distributed control, using machine learning algorithms, we have investigated how heat flux sensing could improve personal thermal comfort inference under transient ambient conditions. We have explored the variations of heat exchange rates of facial and wrist skin. These areas are often exposed in indoor environments and contribute to the thermoregulation mechanism through skin heat exchange, which we have coupled with variations of skin and ambient temperatures for inference of personal thermal preferences. Adopting an experimental and data analysis methodology, we have evaluated the modeling of personal thermal preference of 18 human subjects for well-known classifiers using different scenarios of learning. The experimental measurements have revealed the differences in personal thermal preferences and how they are reflected in physiological variables. Further, we have shown that heat exchange rates have high potential in improving the performance of personal inference models even compared to the use of skin temperature.