The object of the present project is those variables related to the psycho-physiological aspects and more specifically the thermal comfort in public urban spaces, that is, in streets, squares, parks, or areas of stay in our cities.
Likewise, the development of a thermal comfort model that considers the maximum possible of variables involved and that reflects the interrelation between the subjects, the environment and the climatic variables is sought. The model will be based on measurements made with real subjects and the use of Computational Intelligence techniques, using artificial neural networks (ANN), for the analysis of the relationship between the variables of said model.
The models of thermal comfort developed so far are based on the knowledge that is available about the thermoregulatory system of the human body, as well as direct measurements that use, in the case of indoor environments, simple balloon thermometers or, in the models more sophisticated, even thermal mannequins that consist of multiple temperature sensors distributed by its surface. The models are usually checked from the answers of subjects that are directly surveyed and the results contrasted with the measurements made.
This project is committed to investigate all these aspects using three main premises:
1) Use of real subjects in conjunction with the instrumentation usually used in other studies, to compare the results related to the total solar radiation absorbed by each person, and also measure their metabolic activity and heat loss by respiration, convention (according to their clothes) ) and radiation.
2) Use of different experimentation scenarios, simulated in a climate room and outdoors with the presence of buildings, or trees and taking advantage of the results provided by other existing models.
3) Use of RNA for the elaboration of a predictive model that is directly associated with the measurements made.