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Application of smart wearable sensors in office buildings for modelling of occupants’ metabolic responses
Energy and Buildings ( IF 6.6 ) Pub Date : 2020-08-19 , DOI: 10.1016/j.enbuild.2020.110399
Sandro Nižetić , Nikolina Pivac , Vlasta Zanki , Agis M. Papadopoulos

This paper reports and discusses the results of a field study focusing on the examination of thermal comfort conditions in two public buildings in Croatia. The wearable sensors were used for monitoring the occupants’ metabolic responses, along with the standard equipment for measuring thermal comfort. The occupants’ subjective comfort sensation was also investigated through a survey questionnaire and was used in conjunction with the measured data. A total number of eight occupants participated in the study, located in two office buildings in different climates. The modeling of the metabolic responses was obtained by means of artificial neural networks and the simulated values were compared with the measured ones. The validation of the models showed overlapping of 90%. However, they should be tested on a larger number of occupants. The study results revealed that the MET response usually varied between values 1.0 and 2.0, no matter the season, which is rather high for office activities according to standards, and indicates the inapplicability of static MET value usage in the calculation of PMV indexes. The implementation of wearable sensors provided accurate information on the dynamic changes of the building occupant's metabolic rate during working hours, enabling the reliable model algorithm creation to increase occupant satisfaction and potential energy savings. Finally, the differences between the two examined buildings’ thermal conditions were analyzed and useful findings regarding age, gender and physical fitness of occupants and their satisfactory level of comfort conditions were presented.



中文翻译:

智能可穿戴传感器在办公大楼中用于模拟乘员的新陈代谢反应

本文报告并讨论了一项现场研究的结果,该研究的重点是检查克罗地亚两座公共建筑的热舒适条件。穿戴式传感器与标准设备一起用于监测乘员的新陈代谢反应,并测量热舒适度。还通过调查问卷调查了乘员的主观舒适感,并将其与测量数据结合使用。共有八名居住者参加了研究,这些研究位于不同气候的两座办公楼中。通过人工神经网络对代谢反应进行建模,并将模拟值与实测值进行比较。模型的验证显示出90%的重叠。但是,应该对大量乘员进行测试。研究结果表明,无论季节如何,MET响应通常在1.0到2.0之间变化,这对于按照标准的办公室活动来说是相当高的,并且表明静态MET值用法在PMV指数的计算中不适用。可穿戴式传感器的实施提供了有关工作时间内新陈代谢的动态变化的准确信息,从而使可靠的模型算法创建能够提高居住者的满意度和潜在的节能效果。最后,分析了两座被检查建筑物的热状况之间的差异,并提出了有关年龄,性别和居住者身体健康状况以及他们满意​​的舒适度水平的有用发现。无论是哪个季节,根据标准,这对于办公室活动来说都是相当高的水平,这表明静态MET值用法不适用于PMV指数的计算。可穿戴式传感器的实施提供了有关工作时间内新陈代谢的动态变化的准确信息,从而使可靠的模型算法创建能够提高居住者的满意度和潜在的节能效果。最后,分析了两座被检查建筑物的热状况之间的差异,并提出了有关年龄,性别和居住者身体健康状况以及他们满意​​的舒适度水平的有用发现。无论是哪个季节,根据标准,这对于办公室活动来说都是相当高的水平,这表明静态MET值用法不适用于PMV指数的计算。可穿戴式传感器的实施提供了有关工作时间内工作人员的新陈代谢率动态变化的准确信息,从而创建了可靠的模型算法,从而提高了工作人员的满意度并节省了潜在的能源。最后,分析了两座被检查建筑物的热状况之间的差异,并提出了有关年龄,性别和居住者身体健康状况以及他们满意​​的舒适度水平的有用发现。表示在计算PMV指标时静态MET值用法不适用。可穿戴式传感器的实施提供了有关工作时间内新陈代谢的动态变化的准确信息,从而使可靠的模型算法创建能够提高居住者的满意度和潜在的节能效果。最后,分析了两座被检查建筑物的热状况之间的差异,并提出了有关年龄,性别和居住者身体健康状况以及他们满意​​的舒适度水平的有用发现。并指出静态MET值用法在PMV指数计算中的不适用性。可穿戴式传感器的实施提供了有关工作时间内新陈代谢的动态变化的准确信息,从而使可靠的模型算法创建能够提高居住者的满意度和潜在的节能效果。最后,分析了两座被检查建筑物的热状况之间的差异,并提出了有关年龄,性别和居住者身体健康状况以及他们满意​​的舒适度水平的有用发现。支持可靠的模型算法创建,从而提高乘员满意度并节省潜在能源。最后,分析了两座检查过的建筑物的热工条件之间的差异,并提出了有关年龄,性别和居住者身体健康状况以及他们满意​​的舒适水平的有用发现。支持可靠的模型算法创建,从而提高乘员满意度并节省潜在能源。最后,分析了两座被检查建筑物的热状况之间的差异,并提出了有关年龄,性别和居住者身体健康状况以及他们满意​​的舒适度水平的有用发现。

更新日期:2020-08-27
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