Thermal comfort of building occupants is a major criterion in evaluating the performance of building systems. It is also a dominant factor in designing and optimizing building's operation. However, existing thermal comfort models, such as Finger's model currently adopted by ASHRAE Standard 55, rely on factors that require bulky and expensive equipment to measure. This paper attempts to take a radically different approach towards measuring the thermal comfort of building occupants by leveraging the ever-increasing capacity and capability of mobile and wearable devices. Today's commercially-off-the-shelf (COST) wearable devices can unobtrusively capture a number of important parameters that may be used to measure thermal comfort of building occupants, including ambient air temperature, relative humidity, skin temperature, perspiration rate, and heart rate. This research evaluates such opportunities by fusing traditional environmental sensing data streams with newly available wearable sensing information. Furthermore, it identifies challenges for using existing wearable devices and to developing new models to predict human thermal comfort. Findings from this exploratory study identify the inaccuracy of sensors in cellphones and wearable as a challenge, yet one which can be improved using customized wearables. The study also suggests there exists a high potential for developing new models to predict human thermal sensation using artificial neural networks and additional factors that can be individually, unobtrusively, and dynamically measured using wearables.