## 2 Background  
As main background, the Fanger model published in the _British Journal of Industrial Medicine_ can be mentioned [10]. It assesses thermal comfort status based on predictive mean vote (PMV) and predictive percentage of dissatisfied (PPD). The predictive mean vote is calculated by means of clothing insulation, metabolic rate, and environment characteristics (temperature, radiant temperature, relative humidity, and air velocity). This rate allows the determination of people dissatisfied with the environment, showing major progress in comparison with other thermal comfort rates. Nonetheless, as it is performed in controlled chambers with young people of European or North American descent (physiological model) at rest, it does not consider the lack of local thermal comfort, actual operability conditions, or regional working habits. [PERSON] [11] considers that the calculation of PMV and PPD allows the identification of thermal discomfort events perceived by the body. Moreover, there are a series of factors, such as drafts, differences in vertical temperature, and the existence of hot or cold ceilings, walls, or floors, that may cause discomfort in workers even when the overall situation has been assessed as satisfactory by the Fanger method. Thus, he concludes that the assessment should be completed with the study of \"local thermal discomfort\" in such cases. According to ISO 7730 Standard: Ergonomics of the thermal environment [4], another limitation of the Fanger model applicability is that the predictive mean vote (PMV) rate should only be used to assess thermal environments in which the variables in the calculation are within specific intervals of a metabolic rate (46 and 232 W/m\({}^{2}\)), clothing insulation (0 and 0.31 m\({}^{2}\) K/W), air temperature (10 \({}^{\circ}\)C and 30 \({}^{\circ}\)C), mean radiant temperature (10 \({}^{\circ}\)C and 40 \({}^{\circ}\)C), air velocity (0 and 1 m/s), and water vapor pressure (0 and 27 HPa). From another approach, adaptive models ([PERSON], [PERSON] and [PERSON] [12], [PERSON] and [PERSON] [13]) consider the outdoor climate to determine the preferences of indoor comfort, where the person is not a passive receptor but part of a dynamic system with the environment. These two theoretical approaches ([PERSON], [PERSON] et al. [14]) have not delivered answers for establishing design parameters of air conditioning installations. Furthermore, [PERSON] and [PERSON] [18] found that thermal environment conditions are one of the most important factors in workplaces from a productivity, occupational safety, and human health standpoint. In the simulation, they used an energy balance model to determine the thermal comfort area. They identified that the optimal operational temperature decreases while metabolic activity levels increase. This research paper considers air velocity, yet there is no evidence of the relative humidity influence. Another background study is the experience provided by [PERSON] et al., focusing on the combination between ambient temperature and the temperature of facilities while being ventilated by an air-conditioning unit. In this case, they used 18 test subjects and three temperature combinations, with low air speed to reduce one variable. For the authors, the results imply that the adoption of local ventilation could improve thermal comfort while consuming less energy, compared with the traditional air conditioning mode, which creates a uniform comfortable environment by setting air temperature at 26 \({}^{\circ}\)C [19]. The results of a case study in the History Museum of Valencia, Spain, about the thermal comfort of its visitors stressed the limitations of the Fanger model when used in this type of building, highlighting the need for further research in this field [20]. Activity incidence, building conditions for art preservation, and their impact on people whose clothing is fitted for outdoor temperature and does not guarantee their comfort within the building during warm season are stressed.