Internet-of-Things (IoT) for Human Thermal Comfort: A Simulative Investigation
Keywords:Air Conditioning System Control, AndroidBased Application, Human Thermal Comfort, Internet-OfThings, Predictive Mean Vote (PMV),
AbstractHuman thermal comfort is very important especially in an indoor environment as it can influence human’s health and welfare. In tropical countries like Malaysia, air conditioning system has become a necessary tool in creating a thermally comfortable ambience in an indoor environment. However, the current control mechanism of the system would allow the user to set into maximum cooling – at minimum temperature with maximum fan speed – which not only consumes more energy, but is not creating a thermally comfortable environment as well, as extreme coolness could also bring negative effect towards the human. Therefore, it is essential to integrate human thermal comfort factor into air conditioning system control as well. This paper will highlight the possibility of integrating thermal comfort control into air conditioning system in creating a comfortable indoor environment. It adopts an enhanced version of Predictive Mean Vote (PMV) approach, specifically in creating thermal comfort ambience for a small sedentary work-based indoor space, in tropical countries. As the Internet-of-Things has become a trend in the smart home application, its element is also integrated here, where an Android-based application is developed and tested towards controlling a hardware simulative model which represents an air conditioning system based on the user-defined PMV value. It is shown that the application is able to control the fan speed and temperature through the LED brightness as demanded by the user. It is not only expected to work with a real air conditioning system in the future to create a thermally comfortable environment, but could also allow the system to be operated in energy and cost-efficient manner.
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