Investigating Thermal Comfort for the Classroom Environment using IoT

Abstract

In this modern century where fine comfort is a necessity especially in buildings and occupied space, the study to satisfy one aspect of human comfort is a must. This study encompasses of exploring the physiological and environmental factors in achieving thermal comfort which specifically considering the clothing insulation and metabolic rate of students as well as the deployment of dry-bulb temperature, mean radiant temperature, humidity, and air movement in order to obtain the level of comfort students are experiencing in class. The level of comfort are detected by using ASHRAE 55 to determine the average thermal sensation response through the Predicted Mean Vote (PMV) value. An android application were developed to read input of recognizing clothing level (thickness of clothing) and capturing metabolic rate to cater the inputs for physiological factors, while radiant temperature, humidity and air movement are captured through static sensors set up in the classroom space. This paper analyses both the physiological and environmental factors in affecting students in class and further determine their comfort levels that is a major influencing factor of focus in learning. Through cross referencing collected data from IoT enabled nodes, it is found that both physiological and environmental factors, and the combination of them greatly influence in getting the most comfortable state with PMV value of 0.