## 2 Methodology
### Experimental Setup  
Since this study aims to develop individual thermal models which capture the fine-tuned differences between different people, instead of developing a generic thermal model based on large group of people, it makes more sense to develop individual thermal models. Moreover, for machine learning algorithms, the performance will increase with a greater amount of data. However, even if the common datasets like RP884 collected data from large group of participants, only less than 10 instances were collected for each individual. Therefore, unlike RP884, in this study, individual thermal models were developed based on a six-day experimental study to collect certain amount of data with two healthy subjects in their mid-twenties (one male and one female) between 3/11/2018 and 3/16/2018 in an office building in Tongji University, Shanghai. Based on the design of non-intrusive sensing systems and a literature review of principle factors related to thermal comfort, the measured variables are shown in the following Table 1. The interval of data collection is five minutes, which corresponds with the survey responses. The experiment used the IR camera to measure the side face skin temperature and clothing surface temperature by manually selecting the face area and clothing area in the high-resolution thermal images, and then calculating the average surface temperature within those areas in FLIR tools, respectively. Figure 2 shows the participants' status in the experimental study and the thermographic photos, respectively. Before each session, the participants' clothes were reported, and heart rates were measured by a free mobile app called Instant Heart Rate so as to ensure the participants have similar thermal status in the beginning. Lastly, clothing insulation was manually estimated based on ASHRAE 55 and was used for calculating PMV values. In order to get the accurate skin temperature, the emissivity was set to be 0.98. Even if neutral sensation doesn't necessarily mean thermal comfort, it is a precondition of comfort [28]. Therefore, the statement that an occupant feels thermally comfortable when they feel the thermal environment is neutral was utilized in this study, and a 7-point thermal sensation scale as a classification label was used, as shown in Table 2. \begin{table}
\begin{tabular}{l c c c} \hline \hline
**Variable** & **Sensor Tool** & **Resolution** & **Operating Range** \\ \hline Skin temperature (\({}^{\circ}\)C) & FLIR B8400 & 320 \(\times\) 240 pixels & \(-\)20 \({}^{\circ}\)C\(-\)120 \({}^{\circ}\)C \\ Clothing surface temperature (\({}^{\circ}\)C) & FLIR B8400 & 320 \(\times\) 240 pixels & \(-\)20 \({}^{\circ}\)C\(-\)120 \({}^{\circ}\)C \\ Indoor air temperature (\({}^{\circ}\)C) & DHT22 & 0.1 \({}^{\circ}\)C & \(-\)4 \({}^{\circ}\)C\(-\)80 \({}^{\circ}\)C \\ Indoor relative humidity (\%) & DHT22 & 0.1 \({}^{\circ}\)C & \(-\)40 \({}^{\circ}\)C\(-\)80 \({}^{\circ}\)C \\ \cline{2-3} Clothing insulation (do) & Manually identify the clothing type and find the insulation values based on & & \\  & ASHRAE 55 & & \\ \hline FLIR B8400: infrared camera; DHT22: temperature \& humidity sensor. & & \\ \end{tabular}
\end{table} 
Table 1: Measured variables and sensor tools. Figure 2: The RGB and IR images of the two subjects. In order to create different thermal environment conditions, an overhead air conditioner and four convective heaters were controlled in transient conditions where the air temperature increases no more than 0.2 \({}^{\circ}\)C/min on average, as shown Figure 3. Moreover, Figure 4 shows the floorplan of the testbed where two subjects were seated in two separate desks and the camera has two locations to take photos of each subject, respectively. To avoid discomfort due to high air velocity and asymmetric radiation, the participants were asked to adjust the locations of their working areas if they could feel a draft or if they could feel the sunlight before measurement. In addition, there were a total of 14 different sessions and each session lasted for at least two hours.