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

Sulewska, Maria Jolanta; Gładyszewska-Fiedoruk, K.; Sztulc, Piotr

doi:10.1007/s11356-018-3029-4

Cited by 5 publications

(5 citation statements)

References 20 publications

(18 reference statements)

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“…In building science studies, thermal comfort has been related to productivity and health. Office workers who are satisfied with their thermal environment are more productive [38]. For example, it is valuable to provide the correct light intensity for each task or environment.…”

Section: Resultsmentioning

confidence: 99%

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

Sun

Zheng

Villalba-Díez

et al. 2019

Sensors

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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.

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Section: Resultsmentioning

confidence: 99%

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

Sun

Zheng

Villalba-Díez

et al. 2019

Sensors

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“…The research was carried out in Białystok in north-eastern Poland, in an area where the outside air is very clean. During the measurement period, the concentration of carbon dioxide in the outside air ranged between 360-400 ppm [18]. In the analysed room ( fig.…”

Section: Experimental Researchmentioning

confidence: 96%

“…The adaptive approach comes from field studies, aimed at analysing the real acceptability of the thermal environment, which strongly depends on the context, behaviour of people and their expectations [16][17][18][19][20]. In recent years, various authors have encouraged field studies to obtain more reliable information on the actual room conditions [17], [21][22][23][24][25].…”

Section: Introductionmentioning

confidence: 99%

IAQ in Conference Room whit Surveys

Gładyszewska-Fiedoruk

2019

E3S Web Conf.

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The work presents three basic air pollutants in the room, degrading the indoor air quality. The only source of pollution in the analysed room are people. The research was carried out in a building located in north-eastern Poland, in a temperate climate, in an area where the outside air is very clean. That is why air exchange is often carried out by opening windows (natural ventilation). That was also the case during the described experiment. In the room during the experiment there were 55 people, all of them doing the same physical activity, sitting work. The temperature and relative humidity of the air, the concentration of carbon dioxide in the room and the sound level were analysed. During the experiment, questionnaire surveys were also conducted. Respondents answered the same set of questions at the beginning and at the end of the meeting. The IAQ was low during measurements. Carbon dioxide concentration ranged from 1700-2000 ppm. The temperature was too low (18-19 o C). The smell for the respondents was not perceptible. The noise during measurements ranged within 50 dB. It was a parameter that aroused the greatest dissatisfaction among the surveyed. They didn't pay attention to a low temperature.

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“…The IAQ probe simultaneously measured the indoor air temperature, humidity, and CO 2 concentration. The accuracy of the measuring device is described in the publications [24][25][26]. Measurements of internal air parameters were carried out at a height of approx.…”

Section: Experimental Researchmentioning

confidence: 99%

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

Gładyszewska-Fiedoruk

Sulewska

2020

Energies

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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.

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

Cited by 5 publications

References 20 publications

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

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

IAQ in Conference Room whit Surveys

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

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