## 6 Discussion
Here, the \"human-centered closed loop control\"-platform (HCCLC-platform) developed by [PERSON] et al. [153], [PERSON] et al. [154] represents one way of applying personalized control algorithms to personal control systems within the building and vehicle sector. For this purpose, various personal local actuators can be simultaneously implemented and operated by the HCCLC-platform. The latter is capable of estimating body-part-specific equivalent temperatures, which are used to calculate the required local heating/cooling power of body parts that is required to provide overall thermal comfort to a person [153; 154]. The corresponding energy demand can be determined on the base of measured skin temperatures and/or simulation results generated with the thermophysiological model MORPHEUS. The implementation of energy-efficient personalized climatization systems requires models for the determination of human thermal comfort. The most commonly used model in the building sector for the determination of the overall thermal comfort of individuals is [PERSON]'s [32] PMV/PPD model. It predicts the overall thermal sensation and dissatisfaction for a group of individuals near thermal neutrality in a static manner and is the predominantly used model for designing central HVAC systems. Although [PERSON]'s model shows good prediction performance with respect to thermal discomfort of a group of individuals, the model is not applicable for the prediction of individual thermal comfort. Alternative models, such as the adaptive model described in EN ISO 15251 [47] or ASHRAE Standard 55 [18] correlate the operative indoor temperature with the mean running outdoor temperature over a specific time period (four days up to one month). In contrast to [PERSON]'s PMV/PPD the adaptive model takes the adaptive component of occupants into consideration, which is e.g., the change of clothing insulation or the change operations on windows. However, the model is restricted to non-air-conditioned buildings and defines temperature ranges that are comfortable for a group of individuals instead of a direct comfort quantity. Due to the reason that these models are targeting on a group of individuals, they cannot be applied for the prediction of individual human thermal comfort, which is necessary in connection with the use of personalized climatization systems. The model of [PERSON] and [PERSON] [58] predicts local thermal sensation depending on measured skin temperatures and considers thresholds for skin temperatures that correlate well with thermal discomfort. Some multi-segment comfort models also determine thermal sensation and comfort for single body parts as well as the body as a whole [19; 61; 66]. [PERSON] et al. [20; 61] introduced a model for the prediction of local and overall thermal sensation/comfort that can be applied to human individuals. In uniform environments the researchers showed that overall thermal sensation is dominated by local body parts such as the back/chest region and the pelvis. According to the researchers, the whole-body thermal sensation depends on the three body parts that show the most extreme local thermal sensation in cold and warm environments. This supports the thesis that improving local thermal sensation is of high importance for ensuring whole-body thermal sensation and comfort. However, the developed model is not generally applicable yet, since it is based on a small amount of data. It is furthermore questionable, if such a model should have a higher integration of personal factors, since these have a remarkable impact on individual thermal sensation and thermal preference. [PERSON] [62] showed that existing thermal sensation and comfort models need further improvements with respect to transient and asymmetrical environmental conditions. As a consequence, the researcher implemented a new model that represents a combination of the approaches of [PERSON] [32]and [PERSON] et al. [20; 61].