scholarly journals Human Thermal Comfort Study Based on Average Skin Temperature

2016 ◽  
Keyword(s):  
Thermal Comfort ◽  
Skin Temperature ◽  
Human Thermal Comfort ◽  
Average Skin

scholarly journals Effect of Landscape Microclimates on Thermal Comfort and Physiological Wellbeing

2019 ◽  
Vol 11 (19) ◽  
pp. 5387 ◽  
Author(s):  
Binyi Liu ◽  
Zefeng Lian ◽  
Robert D. Brown
Keyword(s):  
Heart Rate ◽  
Heart Rate Variability ◽  
Thermal Comfort ◽  
Skin Temperature ◽  
Skin Conductance ◽  
Thermal Sensation ◽  
Global Climate ◽  
Evidence Base ◽  
Climate Conditions ◽  
Human Thermal Comfort

Global climate change and intensifying heat islands have reduced human thermal comfort and health in urban outdoor environments. However, there has been little research that has focused on how microclimates affect human thermal comfort, both psychologically and physiologically. We investigated the effect of a range of landscape microclimates on human thermal comfort and health using questionnaires and physiological measurements, including skin temperature, skin conductance, and heart rate variability, and compared the results with the effect of prevailing climate conditions in open spaces. We observed that in landscape microclimates, thermal sensation votes significantly decreased from 1.18 ± 0.66 (warm–hot) to 0.23 ± 0.61 (neutral–slightly warm), and thermal comfort increased from 1.18 ± 0.66 (uncomfortable–neutral) to 0.23 ± 0.61 (neutral–comfortable). In the landscape microclimates, skin temperature and skin conductance decreased 0.3 ± 0.8 °C and 0.6 ± 1.0 μs, respectively, while in the control, these two parameters increased by 0.5 ± 0.9 °C and 0.2 ± 0.7 μs, respectively. Further, in landscape microclimates, subject heart rate variability increased significantly. These results suggest landscape microclimates improve human thermal comfort and health, both psychologically and physiologically. These findings can provide an evidence base that will assist urban planners in designing urban environments for the health and wellbeing of residents.

scholarly journals A Contactless Measuring Method of Skin Temperature based on the Skin Sensitivity Index and Deep Learning

2019 ◽  
Vol 9 (7) ◽  
pp. 1375 ◽  
Author(s):  
Xiaogang Cheng ◽  
Bin Yang ◽  
Kaige Tan ◽  
Erik Isaksson ◽  
Liren Li ◽  
...  
Keyword(s):  
Deep Learning ◽  
Individual Differences ◽  
Thermal Comfort ◽  
Skin Temperature ◽  
Real Time ◽  
Saturation Temperature ◽  
Measuring Method ◽  
Sensitivity Index ◽  
Skin Sensitivity ◽  
Human Thermal Comfort

In human-centered intelligent building, real-time measurements of human thermal comfort play critical roles and supply feedback control signals for building heating, ventilation, and air conditioning (HVAC) systems. Due to the challenges of intra- and inter-individual differences and skin subtleness variations, there has not been any satisfactory solution for thermal comfort measurements until now. In this paper, a contactless measuring method based on a skin sensitivity index and deep learning (NISDL) was proposed to measure real-time skin temperature. A new evaluating index, named the skin sensitivity index (SSI), was defined to overcome individual differences and skin subtleness variations. To illustrate the effectiveness of SSI proposed, a two multi-layers deep learning framework (NISDL method I and II) was designed and the DenseNet201 was used for extracting features from skin images. The partly personal saturation temperature (NIPST) algorithm was use for algorithm comparisons. Another deep learning algorithm without SSI (DL) was also generated for algorithm comparisons. Finally, a total of 1.44 million image data was used for algorithm validation. The results show that 55.62% and 52.25% error values (NISDL method I, II) are scattered at (0 °C, 0.25 °C), and the same error intervals distribution of NIPST is 35.39%.

scholarly journals Neural network-based thermal comfort prediction for the elderly

2021 ◽  
Vol 237 ◽  
pp. 02022
Author(s):  
JinJin Zhang ◽  
Hong Liu ◽  
YuXin Wu ◽  
Shan Zhou ◽  
MengJia Liu
Keyword(s):  
Neural Network ◽  
Thermal Comfort ◽  
Skin Temperature ◽  
Thermal Sensation ◽  
The Elderly ◽  
Learning Technology ◽  
Local Skin ◽  
Human Thermal Comfort ◽  
Network Algorithm ◽  
Neural Network Algorithm

Machine learning technology has become a hot topic and is being applied in many fields. However, in the prediction of thermal sensation in the elderly, there is not enough research on the neural network to predict the effect of human thermal comfort. In this paper, two neural network algorithms were used to predict the thermal expectation of the elderly, and the accuracy of the two algorithms was compared to find a suitable neural network algorithm to predict human thermal comfort. The dataset was collected from the laboratory study and included 10 local skin temperatures of the subjects, thermal perception voted at three temperatures (28/30/32°C), different wind speeds, and two forms of wind. Thirteen subjects with an average age of 63.5 years old were recruited for the subjective survey. These subjects sat for long periods of summer working conditions, wore uniform thermal resistance clothing, and collected votes on thermal sensation, as well as skin temperature. The results showed that the prediction accuracy of the two algorithms was related to the added influence factors, and the RBF neural network algorithm was the most accurate in predicting thermal sensation of the elderly. The main influencing factors were average skin temperature, wind speed and body fat rate.

Analysis of the Influence of Age on Human Thermal Comfort

ICCREM 2020 ◽  
2020 ◽  
Author(s):  
Boshuai Dong ◽  
Chunjing Shang ◽  
Ming Tong ◽  
Jianhong Cai
Keyword(s):  
Thermal Comfort ◽  
Human Thermal Comfort

OVERVIEW OF URBAN HEAT ISLAND (UHI) PHENOMENON TOWARDS HUMAN THERMAL COMFORT

2017 ◽  
Vol 16 (9) ◽  
pp. 2097-2111 ◽  
Author(s):  
Mohanadoss Ponraj ◽  
Yee Yong Lee ◽  
Mohd Fadhil Md Din ◽  
Zainura Zainon Noor ◽  
Kenzo Iwao ◽  
...  
Keyword(s):  
Thermal Comfort ◽  
Urban Heat Island ◽  
Heat Island ◽  
Human Thermal Comfort ◽  
Urban Heat

scholarly journals Evaporative Cooling Options for Building Air-Conditioning: A Comprehensive Study for Climatic Conditions of Multan (Pakistan)

Energies ◽  
2020 ◽  
Vol 13 (12) ◽  
pp. 3061 ◽  
Author(s):  
Shazia Noor ◽  
Hadeed Ashraf ◽  
Muhammad Sultan ◽  
Zahid Mahmood Khan
Keyword(s):  
Thermal Comfort ◽  
Co2 Emissions ◽  
Air Conditioning ◽  
Evaporative Cooling ◽  
Cooling Capacity ◽  
Climatic Conditions ◽  
Maximum Temperature ◽  
Human Thermal Comfort ◽  
Work Input ◽  
System Configurations

This study provides comprehensive details of evaporative cooling options for building air-conditioning (AC) in Multan (Pakistan). Standalone evaporative cooling and standalone vapor compression AC (VCAC) systems are commonly used in Pakistan. Therefore, seven AC system configurations comprising of direct evaporative cooling (DEC), indirect evaporative cooling (IEC), VCAC, and their possible combinations, are explored for the climatic conditions of Multan. The study aims to explore the optimum AC system configuration for the building AC from the viewpoints of cooling capacity, system performance, energy consumption, and CO2 emissions. A simulation model was designed in DesignBuilder and simulated using EnergyPlus in order to optimize the applicability of the proposed systems. The standalone VCAC and hybrid IEC-VCAC & IEC-DEC-VCAC system configurations could achieve the desired human thermal comfort. The standalone DEC resulted in a maximum COP of 4.5, whereas, it was 2.1 in case of the hybrid IEC-DEC-VCAC system. The hybrid IEC-DEC-VCAC system achieved maximum temperature gradient (21 °C) and relatively less CO2 emissions as compared to standalone VCAC. In addition, it provided maximum cooling capacity (184 kW for work input of 100 kW), which is 85% higher than the standalone DEC system. Furthermore, it achieved neutral to slightly cool human thermal comfort i.e., 0 to −1 predicted mean vote and 30% of predicted percentage dissatisfied. Thus, the study concludes the hybrid IEC-DEC-VCAC as an optimum configuration for building AC in Multan.

Design Range of Indoor Relative Humidity in Radiant Cooling Environment

2011 ◽  
Vol 243-249 ◽  
pp. 4905-4908
Author(s):  
Xue Min Sui ◽  
Xu Zhang ◽  
Guang Hui Han
Keyword(s):  
Relative Humidity ◽  
Thermal Comfort ◽  
Mean Radiant Temperature ◽  
Design Standards ◽  
Human Thermal Comfort ◽  
Radiant Cooling ◽  
Climate Parameter ◽  
Radiant Temperature ◽  
Thermal Comfort Model ◽  
The Impact

Relative humidity is an important micro-climate parameter in radiant cooling environment. Based on the human thermal comfort model, this paper studied the effect on PMV index of relative humidity, and studied the relationship of low mean radiant temperature and relative humidity, drew the appropriate design range of indoor relative humidity for radiant cooling systems.The results show that high relative humidity can compensate for the impact on thermal comfort of low mean radiant temperature, on the premise of achieving the same thermal comfort requirements. However, because of the limited compensation range of relative humidity, together with the constraints for it due to anti-condensation of radiant terminal devices, the design range of relative humidity should not be improved, and it can still use the traditional air-conditioning design standards.

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