Analysis of the results of empirical research and surveys of perceived indoor temperature depending on gender and seasons

Thermal Comfort Evaluation Using Linear Discriminant Analysis (LDA) and Artificial Neural Networks (ANNs)

The thermal sensations of people differ from each other, even if they are in the same thermal conditions. The research was carried out in a didactic teaching room located in the building of the Faculty of Civil and Environmental Engineering in Poland. Tests on the temperature were carried out simultaneously with questionnaire surveys. The purpose of the survey was to define sensations regarding the thermal comfort of people in the same room, in different conditions of internal and external temperatures. In total 333 questionnaires were analyzed. After the discriminant and neural analyses it was found that it is not possible to forecast the thermal comfort assessment in the room based on the analyzed variables: gender, indoor air temperature, external wall radiant temperature, and outdoor air temperature. The thermal comfort assessments of men and women were similar and overlapped. The results of this study confirm that under the same thermal conditions about 85% of respondents assess thermal comfort as good, and about 15% of respondents assess thermal comfort as bad. The test results presented in this article are similar to the results of tests carried out by other authors in other climatic conditions.

Indoor Air-Quality Data-Monitoring System: Long-Term Monitoring Benefits

Indoor air pollution has been ranked among the top five environmental risks to public health. Indoor Air Quality (IAQ) is proven to have significant impacts on people’s comfort, health, and performance. Through a systematic literature review in the area of IAQ, two gaps have been identified by this study: short-term monitoring bias and IAQ data-monitoring solution challenges. The study addresses those gaps by proposing an Internet of Things (IoT) and Distributed Ledger Technologies (DLT)-based IAQ data-monitoring system. The developed data-monitoring solution allows for the possibility of low-cost, long-term, real-time, and summarized IAQ information benefiting all stakeholders contributing to define a rich context for Industry 4.0. The solution helps the penetration of Industrial Internet of Things (IIoT)-based monitoring strategies in the specific case of Occupational Safety Health (OSH). The study discussed the corresponding benefits OSH regulation, IAQ managerial, and transparency perspectives based on two case studies conducted in Spain.