Application of IoT and Machine Learning techniques for the assessment of thermal comfort perception

Thermal comfort is traditionally assessed by using the PMV index defined according to the EN ISO 7730:2005 where the user passively interacts with the surrounding environment considering a physic-based model built on a steady-state thermal energy balance equation. The thermal comfort satisfaction is a holistic concept comprising behavioral, physiological and psychological aspects. This article describes a workflow for the assessment of the thermal conditions of users through the analysis of their specific psychophysical conditions overcoming the limitation of the physic-based model in order to investigate and consider other possible relations between the subjective and objective variables.