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Taeyeon Kim
Department of Architecture and Architectural Engineering, Yonsei University, Seoul, 03722, South Korea

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Review
Published: 19 June 2021 in Building and Environment
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Vision-based (camera-based) systems, which can effectively sense occupant information, have garnered attention as a core technology in the Fourth Industrial Revolution. A detailed understanding of vision-based sensing systems is required to detect occupant information based on vision and use it for occupant-centric control. Therefore, in this study, we performed a comprehensive and structural literature review of vision-based occupant information systems. The contributions of this review can be summarized in the following six points: (1) a five-tier taxonomy of vision-based occupant information is proposed, (2) a systematic summary of vision-based occupant information is presented, (3) the quantitative and qualitative performance of sensing systems is reviewed, (4) an analysis of the applicability of deep-learning-based computer vision techniques is presented, (5) a summary of privacy-preserving techniques is included, and (6) a summary of vision-based control strategies and energy saving potential analysis is provided. The analysis in this review is an important contribution toward addressing the challenges in the field of research.

ACS Style

Haneul Choi; Chai Yoon Um; Kyungmo Kang; Hyungkeun Kim; Taeyeon Kim. Review of vision-based occupant information sensing systems for occupant-centric control. Building and Environment 2021, 203, 108064 .

AMA Style

Haneul Choi, Chai Yoon Um, Kyungmo Kang, Hyungkeun Kim, Taeyeon Kim. Review of vision-based occupant information sensing systems for occupant-centric control. Building and Environment. 2021; 203 ():108064.

Chicago/Turabian Style

Haneul Choi; Chai Yoon Um; Kyungmo Kang; Hyungkeun Kim; Taeyeon Kim. 2021. "Review of vision-based occupant information sensing systems for occupant-centric control." Building and Environment 203, no. : 108064.

Journal article
Published: 09 April 2021 in Journal of Hazardous Materials
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The rising indoor air pollution from particles is a cause for concern especially in houses where children and the elderly reside. In South Korea, assessment of exposure to particle number (PN) in residential apartments, which account for 76% of all houses, is limited. In our study, the indoor and outdoor PN (sizes 0.3–10.0 µm) concentrations were measured in ten typical apartments for 24 h each. In addition, the occupants’ schedules were examined by conducting a survey. Results showed that the average outdoor PN concentrations were 0.30–4.37 × 109/m3 with very large deviations. Indoor peak events were mainly caused by cooking, and total emitted particles were 0.01–81.3 × 1013 particles. Indoor PN concentrations were sustained for a long time because of inefficient ventilation that led to lowered attenuation. Indoor particles are generated during various indoor activities. The daily-integrated particle exposures were 21.4% and 78.6% for indoor and outdoor sources, respectively. Thus, outdoor sources were the predominant sources of particle exposure compared with indoor sources. In conclusion, penetration from outdoor sources needs to be reduced by adding air filtration to improve the airtightness of buildings when introducing outdoor air to lower the indoor PN concentration.

ACS Style

Kyungmo Kang; Taeyeon Kim; Hyungkeun Kim. Effect of indoor and outdoor sources on indoor particle concentrations in South Korean residential buildings. Journal of Hazardous Materials 2021, 416, 125852 .

AMA Style

Kyungmo Kang, Taeyeon Kim, Hyungkeun Kim. Effect of indoor and outdoor sources on indoor particle concentrations in South Korean residential buildings. Journal of Hazardous Materials. 2021; 416 ():125852.

Chicago/Turabian Style

Kyungmo Kang; Taeyeon Kim; Hyungkeun Kim. 2021. "Effect of indoor and outdoor sources on indoor particle concentrations in South Korean residential buildings." Journal of Hazardous Materials 416, no. : 125852.

Erratum
Published: 21 January 2021 in Building and Environment
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ACS Style

Kyungmo Kang; Taeyeon Kim; Cheol Woong Shin; Kichul Kim; Jiwoong Kim; Yun Gyu Lee. Corrigendum to “Filtration efficiency and ventilation performance of window screen filters” [Build. Environ. 178 (2020) 106878]. Building and Environment 2021, 191, 107612 .

AMA Style

Kyungmo Kang, Taeyeon Kim, Cheol Woong Shin, Kichul Kim, Jiwoong Kim, Yun Gyu Lee. Corrigendum to “Filtration efficiency and ventilation performance of window screen filters” [Build. Environ. 178 (2020) 106878]. Building and Environment. 2021; 191 ():107612.

Chicago/Turabian Style

Kyungmo Kang; Taeyeon Kim; Cheol Woong Shin; Kichul Kim; Jiwoong Kim; Yun Gyu Lee. 2021. "Corrigendum to “Filtration efficiency and ventilation performance of window screen filters” [Build. Environ. 178 (2020) 106878]." Building and Environment 191, no. : 107612.

Journal article
Published: 28 December 2020 in Energies
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Neural network models are data-driven and are effective for predicting and interpreting nonlinear or unexplainable physical phenomena. This study collected building information and heating energy consumption data from 16,158 old houses, selected key input variables that affect the heating energy consumption based on the collected datasets, and developed a deep neural network (DNN) model that showed the highest accuracy for the prediction of heating energy consumption in an old house. As a result, 11 key input variables were selected, and an optimal DNN model was developed. This optimal DNN model showed the highest prediction accuracy (R2 = 0.961) when the number of hidden layers was five and the number of neurons was 22. When the optimal DNN model was applied for the standard model of low-income detached houses, the prediction accuracy (Cv(RMSE)) of the optimal DNN model, compared to the EnergyPlus calculation result, was 8.74%, which satisfied the ASHRAE standard sufficiently.

ACS Style

Sungjin Lee; Soo Cho; Seo-Hoon Kim; JongHun Kim; Suyong Chae; Hakgeun Jeong; Taeyeon Kim. Deep Neural Network Approach for Prediction of Heating Energy Consumption in Old Houses. Energies 2020, 14, 122 .

AMA Style

Sungjin Lee, Soo Cho, Seo-Hoon Kim, JongHun Kim, Suyong Chae, Hakgeun Jeong, Taeyeon Kim. Deep Neural Network Approach for Prediction of Heating Energy Consumption in Old Houses. Energies. 2020; 14 (1):122.

Chicago/Turabian Style

Sungjin Lee; Soo Cho; Seo-Hoon Kim; JongHun Kim; Suyong Chae; Hakgeun Jeong; Taeyeon Kim. 2020. "Deep Neural Network Approach for Prediction of Heating Energy Consumption in Old Houses." Energies 14, no. 1: 122.

Journal article
Published: 05 November 2020 in Sustainability
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Due to the recent industrial development and COVID-19 pandemic, people are spending more time indoors. Therefore, indoor air quality is becoming more important for the health of occupants. Indoor fine particles are increased by outdoor air pollution and indoor occupant activities. In particular, smoking, cooking, cleaning, and ventilation are occupant activities that have the largest impact on indoor particle concentrations. In this study, indoor and outdoor particle concentrations were measured in ten apartment houses in South Korea for 24 h. Indoor particle concentrations were measured in the kitchen and living room to evaluate the impact of cooking, one of the most important sources of indoor particles. An occupant survey was also conducted to analyze the influence of occupant activities. It was found that the impact of outdoor particles on indoor particle concentrations in winter was not significant. The largest particle source was cooking. In particular, a large amount of particles was generated by broiling and frying. In addition, cooking-generated particles are rapidly dispersed to the living room, and this was more obvious for small particles. It is expected that this result will be statistically generalized if the particle concentration of more houses is analyzed in the future.

ACS Style

Hyungkeun Kim; Kyungmo Kang; Taeyeon Kim. Effect of Occupant Activity on Indoor Particle Concentrations in Korean Residential Buildings. Sustainability 2020, 12, 9201 .

AMA Style

Hyungkeun Kim, Kyungmo Kang, Taeyeon Kim. Effect of Occupant Activity on Indoor Particle Concentrations in Korean Residential Buildings. Sustainability. 2020; 12 (21):9201.

Chicago/Turabian Style

Hyungkeun Kim; Kyungmo Kang; Taeyeon Kim. 2020. "Effect of Occupant Activity on Indoor Particle Concentrations in Korean Residential Buildings." Sustainability 12, no. 21: 9201.

Journal article
Published: 25 October 2020 in International Journal of Environmental Research and Public Health
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Indoor cooking is the main cause of particulate matter (PM) within residential houses along with smoking. Even with the range hood turned on, cooking-generated PM can spread quickly into the living room due to the heat generated by the cookstove. In order to improve the PM spread prevention performance of the range hood, a supply of make-up air is needed. Generally, make-up air is supplied through a linear diffuser between the kitchen and living room. In such cases, it is necessary to determine the appropriate location of the supply diffuser. This study evaluates the spread of PM according to different locations of the supply diffuser, which feeds in make-up air. For this purpose, indoor airflow and PM spread were analyzed through CFD (Computational Fluid Dynamics) simulation analysis. By changing the location of the supply diffuser from the contaminant source, PM concentration was analyzed in the kitchen and living room of an apartment house in Korea. Based on the results, the optimal installation location was determined. In this study, 1.5 m from the source was the most effective location of make-up air supply to prevent the spread of cooking-generated particles.

ACS Style

Hyungkeun Kim; Kyungmo Kang; Taeyeon Kim. CFD Simulation Analysis on Make-up Air Supply by Distance from Cookstove for Cooking-Generated Particle. International Journal of Environmental Research and Public Health 2020, 17, 7799 .

AMA Style

Hyungkeun Kim, Kyungmo Kang, Taeyeon Kim. CFD Simulation Analysis on Make-up Air Supply by Distance from Cookstove for Cooking-Generated Particle. International Journal of Environmental Research and Public Health. 2020; 17 (21):7799.

Chicago/Turabian Style

Hyungkeun Kim; Kyungmo Kang; Taeyeon Kim. 2020. "CFD Simulation Analysis on Make-up Air Supply by Distance from Cookstove for Cooking-Generated Particle." International Journal of Environmental Research and Public Health 17, no. 21: 7799.

Journal article
Published: 12 October 2020 in Sustainability
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A household unit of an existing apartment in which residents lived was selected, and the indoor air quality in each space of the unit was measured for analysis. Analysis of the measurement data indicated that the concentration of carbon dioxide (CO2) constantly increased beyond 1000 ppm when a resident stayed indoors for an hour or more. Specifically, the concentration of CO2 increased when the resident was asleep to a level wherein negative impacts on health were observed. Moreover, the inflow of particulate matter (PM) was mainly caused by natural ventilation from the outside rather than the behavior of indoor residents, which generated an insignificant amount of PM. This study proposes a new ventilation system for solving the above-described problems. According to the system, when a window is closed, the window cavity created between a new frame and the existing frame is utilized as an air path for ventilation. The application of this system ensures a stable amount of ventilation through forced ventilation and prevents the inflow of external PM. Moreover, this system was designed to recover indoor heat through the window cavity and facilitate the pre-heating of outdoor air through heat collection based on solar radiation during the day.

ACS Style

Jinuk Lee; Sanghoon Park; Taeyeon Kim. Development of a Ventilation System Using Window Cavity. Sustainability 2020, 12, 8391 .

AMA Style

Jinuk Lee, Sanghoon Park, Taeyeon Kim. Development of a Ventilation System Using Window Cavity. Sustainability. 2020; 12 (20):8391.

Chicago/Turabian Style

Jinuk Lee; Sanghoon Park; Taeyeon Kim. 2020. "Development of a Ventilation System Using Window Cavity." Sustainability 12, no. 20: 8391.

Research article
Published: 02 September 2020 in Building Simulation
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Thermal comfort is an important factor in evaluating indoor environmental quality. However, accurately evaluating thermal comfort conditions is challenging owing to the lack of suitable methods for measuring individual factors such as the metabolic rate (M value). In this study, a M value evaluation method was developed using deep learning. The metabolic equivalent of task was measured for eight typical indoor tasks based on the ASHRAE Standard 55 (lying down, sitting, cooking, walking, eating, house cleaning, folding clothes, and handling 50 kg books) in 31 subjects (males: 16; and females: 15); the measurements were analyzed in terms of gender and body mass index (BMI). The experimental results were assessed using the reliability of the measured data, the M value difference in terms of gender and BMI, and the measurement accuracy. We developed a M value self-evaluation model using artificial intelligence, which achieved an average coefficient of variation (CV) of 12%. A third-party evaluation model was used to evaluate the M value of one subject based on the learning data acquired from the other 30 subjects; this model yielded a low CV of 54%. For high-activity tasks, males generally had higher M values than females, and the higher the BMI was, the higher was the M value. Contrarily, for low-activity tasks, the lower the BMI was, the higher was the M value. The breakthrough M value evaluation method presented herein is expected to improve thermal comfort control.

ACS Style

Hooseung Na; Haneul Choi; Taeyeon Kim. Metabolic rate estimation method using image deep learning. Building Simulation 2020, 13, 1077 -1093.

AMA Style

Hooseung Na, Haneul Choi, Taeyeon Kim. Metabolic rate estimation method using image deep learning. Building Simulation. 2020; 13 (5):1077-1093.

Chicago/Turabian Style

Hooseung Na; Haneul Choi; Taeyeon Kim. 2020. "Metabolic rate estimation method using image deep learning." Building Simulation 13, no. 5: 1077-1093.

Journal article
Published: 16 April 2020 in Building and Environment
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Efficient natural ventilation is an important approach to maintaining indoor air quality. However, owing to the increasing concentration of outdoor particulate matter (PM), natural ventilation without filtration results in the introduction of outdoor particles in buildings, thus increasing indoor exposure to PM. Indoor PM concentration is determined by the particle removal efficiency of window screen filters. In this study, using an experimental chamber and an actual building, the particle removal performance of window screen filters was evaluated for their potential application. To investigate the relationship between the outdoor and indoor concentrations of particles with diameter size ≤ 2.5 μm (PM2.5), and to evaluate the efficiency of the window screen filters in removing such particles, the window screen filters were installed in a full-scale test room. The results obtained showed that the average PM2.5 indoor/outdoor (I/O) ratio was within the range 0.24–0.72, and varied with the performance of the window screen filter. An analysis of the correlation between the ventilation rate and the air exchange rate (AER) showed that the I/O ratio increased as AER increased. Additionally, the particle size removal efficiency (PSE) of the window screen filters varied considerably with increasing particle diameter (0.3–10.0 μm), ranging from 0 to 82.4%, and the PSE results showed trends that were similar to those of PM2.5 removal efficiency based on the measurements performed in the test room. Therefore, window screen filters can be used to reduce the indoor concentration of outdoor particles.

ACS Style

Kyungmo Kang; Taeyeon Kim; Cheol Woong Shin; Kichul Kim; Jiwoong Kim; Yun Gyu Lee. Filtration efficiency and ventilation performance of window screen filters. Building and Environment 2020, 178, 106878 .

AMA Style

Kyungmo Kang, Taeyeon Kim, Cheol Woong Shin, Kichul Kim, Jiwoong Kim, Yun Gyu Lee. Filtration efficiency and ventilation performance of window screen filters. Building and Environment. 2020; 178 ():106878.

Chicago/Turabian Style

Kyungmo Kang; Taeyeon Kim; Cheol Woong Shin; Kichul Kim; Jiwoong Kim; Yun Gyu Lee. 2020. "Filtration efficiency and ventilation performance of window screen filters." Building and Environment 178, no. : 106878.

Journal article
Published: 09 April 2020 in Energies
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This study makes a novel attempt to analyse the effect of the bypass control and room control modes on ventilation energy saving in an 84 m2 housing unit, which is the most frequently constructed unit-type among newly constructed apartment buildings in Korea. A heat recovery ventilation system was installed. The fan power consumption was measured via field experiments and analyses were made for potential energy savings. Experiments to confirm the power-saving effect owing to the application of the room control mode were performed under the heat recovery and bypass modes, using three air flow rates (0.5, 1.0 and 1.5 ACH). Additionally, the annual energy saving based on the application of the mixed mode (both bypass and room control modes) was calculated. The results obtained showed that when the mixed mode was employed, ventilation energy saving up to 10.76%–16.56%, which is greater than that obtained using only the heat recovery mode, was realized. Additionally, compared with all-room-ventilation, 26.69%–61.84% of ventilation energy could be saved if the mixed mode was applied only to the living room.

ACS Style

Kyungjoo Cho; Dongwoo Cho; Taeyeon Kim. Effect of Bypass Control and Room Control Modes on Fan Energy Savings in a Heat Recovery Ventilation System. Energies 2020, 13, 1815 .

AMA Style

Kyungjoo Cho, Dongwoo Cho, Taeyeon Kim. Effect of Bypass Control and Room Control Modes on Fan Energy Savings in a Heat Recovery Ventilation System. Energies. 2020; 13 (7):1815.

Chicago/Turabian Style

Kyungjoo Cho; Dongwoo Cho; Taeyeon Kim. 2020. "Effect of Bypass Control and Room Control Modes on Fan Energy Savings in a Heat Recovery Ventilation System." Energies 13, no. 7: 1815.

Journal article
Published: 07 February 2020 in Environmental Pollution
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To improve the indoor air quality of apartments in Korea, a toluene adsorptive paint was manufactured and tested for its efficiency to remove the indoor toluene released from wallpaper adhesives. The toluene adsorptive paint was prepared by blending activated carbon and inorganic binder, and the pore characteristics and chemical functional groups of the activated carbon were analyzed to determine whether the micropores and surface functionalities of activated carbon affected toluene adsorption. Toluene adsorption performance of the toluene adsorptive paint was confirmed through static and verification experiments. The average adsorption efficiency of toluene adsorptive paint in the static experiment was 98.3% and the verification experiment confirmed that about 96.3% of toluene was adsorbed from the indoor air of the apartment. As a result, the use of toluene adsorptive paint effectively removes toluene, which may occur in the adhesive, and thus can be considered to have a good effect on the improvement of indoor air quality. Furthermore, toluene adsorptive paint has been found to be an effective way to achieve consumer wall finishing preferences and maintenance convenience.

ACS Style

Jisoo Jeon; Ji Hun Park; Seunghwan Wi; Beom Yeol Yun; Taeyeon Kim; Sumin Kim. Field study on the improvement of indoor air quality with toluene adsorption finishing materials in an urban residential apartment. Environmental Pollution 2020, 261, 114137 .

AMA Style

Jisoo Jeon, Ji Hun Park, Seunghwan Wi, Beom Yeol Yun, Taeyeon Kim, Sumin Kim. Field study on the improvement of indoor air quality with toluene adsorption finishing materials in an urban residential apartment. Environmental Pollution. 2020; 261 ():114137.

Chicago/Turabian Style

Jisoo Jeon; Ji Hun Park; Seunghwan Wi; Beom Yeol Yun; Taeyeon Kim; Sumin Kim. 2020. "Field study on the improvement of indoor air quality with toluene adsorption finishing materials in an urban residential apartment." Environmental Pollution 261, no. : 114137.

Journal article
Published: 15 January 2020 in Atmosphere
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For evaluating the thermal comfort of occupants, human factors such as clothing thermal insulation (clo level) and metabolic rate (Met) are one of the important parameters as well as environmental factors such as air temperature (Ta) and humidity. In general, a fixed clo level is commonly used for controlling heating, ventilation, and air conditioning using the thermal comfort index. However, a fixed clo level can lead to errors for estimating the thermal comfort of occupants, because clo levels of occupants can vary with time and by season. The present study assesses a method for predicting the clo level of occupants using a thermoregulation model and an infrared (IR) camera. The Tanabe model and the Fanger model were used as the thermoregulation models, and the predicted performance for high clo level (winter clothing) was compared. The skin and clothing temperatures of eight subjects using a non-contact IR camera were measured in a climate chamber. In addition, the measured values were used for the thermoregulation models to predict the clo levels. As a result, the Tanabe model showed a better performance than the Fanger model for predicting clo levels. In addition, all models tended to predict a clo level higher than the traditional method.

ACS Style

Kyungsoo Lee; Haneul Choi; Hyungkeun Kim; Daeung Danny Kim; Taeyeon Kim. Assessment of a Real-Time Prediction Method for High Clothing Thermal Insulation Using a Thermoregulation Model and an Infrared Camera. Atmosphere 2020, 11, 106 .

AMA Style

Kyungsoo Lee, Haneul Choi, Hyungkeun Kim, Daeung Danny Kim, Taeyeon Kim. Assessment of a Real-Time Prediction Method for High Clothing Thermal Insulation Using a Thermoregulation Model and an Infrared Camera. Atmosphere. 2020; 11 (1):106.

Chicago/Turabian Style

Kyungsoo Lee; Haneul Choi; Hyungkeun Kim; Daeung Danny Kim; Taeyeon Kim. 2020. "Assessment of a Real-Time Prediction Method for High Clothing Thermal Insulation Using a Thermoregulation Model and an Infrared Camera." Atmosphere 11, no. 1: 106.

Conference paper
Published: 23 October 2019 in IOP Conference Series: Materials Science and Engineering
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Korean public housing ventilation systems mainly use natural ventilation and local exhausts. When a local exhaust is operated in a narrow space such as a kitchen, the air pressure loss can lack balance. A decrease in hood capture efficiency and ventilation effectiveness causes the problem that people in the living room can be exposed to PM2.5 generated by cooking. Therefore, it is necessary to develop an effective ventilation strategy for the local exhaust, considering the make-up air supply. In this study, a ventilation system that integrates the range hood and ventilation systems (e.g., heat recovery equipment and auxiliary air supply) was developed to resolve this issue. Multi point measurement was conducted using five low-cost sensors to determine the location of the sensors in the kitchen and living room. TSI-DustTrak 8532 and OPS3330 were performed with different ventilation system operating types. When the range hood was operated for one hour, the concentrations in the kitchen and living room were significantly high; 676 μg/m3 and 373 μg/m3, respectively. After the integrated operating algorithm was installed, the kitchen concentration was 185 μg/m3, and the living room concentration was 68 μg/m3. With an additional flow rate of 50 CMH through Heat recovery ventilator (HRV) the reduction in the concentration of PM2.5 was more effective. As a result, this advanced system was able to remove up to 60% of PM2.5 generated by cooking. The integrated system of the auxiliary air supply and range hood was evaluated to be effective in preventing the distribution of kitchen pollutants.

ACS Style

Hangyeol Park; Haneul Choi; Kyung Mo Kang; Hyung Keun Kim; Taeyeon Kim. An effective ventilation system for preventing indoor PM2.5 dispersion. IOP Conference Series: Materials Science and Engineering 2019, 609, 042050 .

AMA Style

Hangyeol Park, Haneul Choi, Kyung Mo Kang, Hyung Keun Kim, Taeyeon Kim. An effective ventilation system for preventing indoor PM2.5 dispersion. IOP Conference Series: Materials Science and Engineering. 2019; 609 (4):042050.

Chicago/Turabian Style

Hangyeol Park; Haneul Choi; Kyung Mo Kang; Hyung Keun Kim; Taeyeon Kim. 2019. "An effective ventilation system for preventing indoor PM2.5 dispersion." IOP Conference Series: Materials Science and Engineering 609, no. 4: 042050.

Conference paper
Published: 23 October 2019 in IOP Conference Series: Materials Science and Engineering
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Currently, there are only a few conventional methods to measure individual factors affecting metabolic rate (MET) based on the thermal comfort of occupants in residential buildings. In this work, a deep learning based MET prediction using a Kinect camera, which is a non-contact sensor, was developed. The root mean squared error (RMSE) and the coefficient of variation (CV) of the RMSE were used as indicators to predict MET accuracy. A total of 31 subjects participated in the experiment (16 men and 15 women). The METs of eight representative activities in the ASHRAE Standard 55 were measured (lying down, sitting, cooking, walking, eating, house cleaning, folding clothes, and handling 50 kg of books). The predicted results for all eight activities were significantly high. (RMSE: 0.26, CV: 13%). Further, METs were analyzed according to the gender and body mass index (BMI). Results of the analysis based on gender reveal that METs of men are higher than those of women. Analysis based on BMI showed that MET increased with higher BMI. However, with respect to sitting and eating food, the higher the BMI, the lower is the MET. This paper suggest that, a creative method was developed herein for predicting MET in an indoor environment with fairly high accuracy. Moreover, the difference in MET considering behavior as a factor was analyzed according to gender and BMI; these results can be used to develop guidelines for more accurate thermal comfort control.

ACS Style

Hooseung Na; Taeyeon Kim. Development of metabolic rate prediction model using deep learning via Kinect camera in an indoor environment. IOP Conference Series: Materials Science and Engineering 2019, 609, 042036 .

AMA Style

Hooseung Na, Taeyeon Kim. Development of metabolic rate prediction model using deep learning via Kinect camera in an indoor environment. IOP Conference Series: Materials Science and Engineering. 2019; 609 (4):042036.

Chicago/Turabian Style

Hooseung Na; Taeyeon Kim. 2019. "Development of metabolic rate prediction model using deep learning via Kinect camera in an indoor environment." IOP Conference Series: Materials Science and Engineering 609, no. 4: 042036.

Journal article
Published: 15 October 2019 in Sustainability
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Clothing condition was selected as a key human-subject-relevant parameter which is dynamically changed depending on the user’s preferences and also on climate conditions. While the environmental components are relatively easier to measure using sensor devices, clothing value (clo) is almost impossible to visually estimate because it varies across building occupants even though they share constant thermal conditions in the same room. Therefore, in this study we developed a data-driven model to estimate the clothing insulation value as a function of skin and clothing surface temperatures. We adopted a series of environmental chamber tests with 20 participants. A portion of the collected data was used as a training dataset to establish a data-driven model based on the use of advanced computational algorithms. To consider a practical application, in this study we minimized the number of sensing points for data collection while adopting a wearable device for the user’s convenience. The study results revealed that the developed predictive model generated an accuracy of 88.04%, and the accuracy became higher in the prediction of a high clo value than in that of a low value. In addition, the accuracy was affected by the user’s body mass index. Therefore, this research confirms that it is possible to develop a data-driven predictive model of a user’s clo value based on the use of his/her physiological and ambient environmental information, and an additional study with a larger dataset via using chamber experiments with additional test participants is required for better performance in terms of prediction accuracy.

ACS Style

Kyungsoo Lee; Haneul Choi; Taeyeon Kim. Development of a Data-Driven Predictive Model of Clothing Thermal Insulation Estimation by Using Advanced Computational Approaches. Sustainability 2019, 11, 5702 .

AMA Style

Kyungsoo Lee, Haneul Choi, Taeyeon Kim. Development of a Data-Driven Predictive Model of Clothing Thermal Insulation Estimation by Using Advanced Computational Approaches. Sustainability. 2019; 11 (20):5702.

Chicago/Turabian Style

Kyungsoo Lee; Haneul Choi; Taeyeon Kim. 2019. "Development of a Data-Driven Predictive Model of Clothing Thermal Insulation Estimation by Using Advanced Computational Approaches." Sustainability 11, no. 20: 5702.

Journal article
Published: 27 September 2019 in Energy and Buildings
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Facing severe climate change, the rapid increase in building energy consumption has become the major challenge and much attention has been paid to reduce energy use by buildings and their components. Among factors relates the building components, HVAC (Heating, Ventilation, and Air-Conditioning) systems, and their operation have accounted for the largest share of total building energy consumption. The present study applied HVAC commissioning to a newly constructed office building in South Korea to investigate the impact on energy consumption. The energy demands for the case building were simulated by using data collected by BEMS and BAS and IPMVP Option D is used to calibrate the conditions of the energy simulation. Utilizing the calibrated energy model, several cases were created and examined to find out the energy effectiveness of the HVAC commissioning. Moreover, the cost-effectiveness of the case building with HVAC commissioning was analyzed. Implementing HVAC commissioning, about 2 % - 6 % of the total energy was reduced as per the occupancy rates and the payback period was also calculated. The obtained results of the present study showed the effectiveness of HVAC commissioning and the study can provide information for the development of HVAC commissioning for commercial buildings in Korea.

ACS Style

Dong-Bae Kim; Daeung Kim; Taeyeon Kim. Energy performance assessment of HVAC commissioning using long-term monitoring data: A case study of the newly built office building in South Korea. Energy and Buildings 2019, 204, 109465 .

AMA Style

Dong-Bae Kim, Daeung Kim, Taeyeon Kim. Energy performance assessment of HVAC commissioning using long-term monitoring data: A case study of the newly built office building in South Korea. Energy and Buildings. 2019; 204 ():109465.

Chicago/Turabian Style

Dong-Bae Kim; Daeung Kim; Taeyeon Kim. 2019. "Energy performance assessment of HVAC commissioning using long-term monitoring data: A case study of the newly built office building in South Korea." Energy and Buildings 204, no. : 109465.

Journal article
Published: 30 August 2019 in Energies
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In Kuwait, where the government subsidizes approximately 95% of residential electricity bills, most of the country’s energy consumption is for residential use. In particular, air-conditioning (AC) systems for cooling, which are used throughout the year, are responsible for residential electric energy consumption. This study aimed to reduce the amount of energy consumed for cooling purposes by developing a thermal comfort-based controller. Our study commenced by using a simulation model to investigate the possibility of energy reduction when using the predicted mean vote (PMV) for optimal control. The result showed that control optimization would enable the cooling energy consumption to be reduced by 33.5%. The influence of six variables on cooling energy consumption was then analyzed to develop a thermal comfort-based controller. The analysis results showed that the indoor air temperature was the most influential factor, followed by the mean radiant temperature, the metabolic rate, and indoor air velocity. The thermal comfort-based controller-version 1 (TCC-V1) was developed based on the analysis results and experimentally evaluated to determine the extent to which the use of the controller would affect the energy consumed for cooling. The experiments showed that the implementation of TCC-V1 control made it possible to reduce the electric energy consumption by 39.5% on a summer representative day. The results of this study indicate that it is possible to improve indoor thermal comfort while saving energy by using the thermal comfort-based controller in residential buildings in Kuwait.

ACS Style

Jaesung Park; Taeyeon Kim; Chul-Sung Lee. Development of Thermal Comfort-Based Controller and Potential Reduction of the Cooling Energy Consumption of a Residential Building in Kuwait. Energies 2019, 12, 3348 .

AMA Style

Jaesung Park, Taeyeon Kim, Chul-Sung Lee. Development of Thermal Comfort-Based Controller and Potential Reduction of the Cooling Energy Consumption of a Residential Building in Kuwait. Energies. 2019; 12 (17):3348.

Chicago/Turabian Style

Jaesung Park; Taeyeon Kim; Chul-Sung Lee. 2019. "Development of Thermal Comfort-Based Controller and Potential Reduction of the Cooling Energy Consumption of a Residential Building in Kuwait." Energies 12, no. 17: 3348.

Research article
Published: 22 July 2019 in Building Simulation
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Modern people spend most of their time indoors and so are chronically exposed to indoor air pollutants. To identify the health effects of pollutant exposure, it is necessary to understand the changes over time in indoor pollutant concentrations. There are two approaches for simulating pollutant concentration changes: mass balance model, computational fluid dynamics (CFD). Although the mass balance model is suitable for long-term simulation because it is simple, there is a limit to the detailed analysis considering concentration distribution. CFD can simulate the distribution of indoor air pollutants, but long-term analyses require too many computational resources. This study proposed a novel simulation method that couples the mass balance model with the contribution ratio of pollutant sources (CRPS) index, which indicates the individual impact of all pollutant sources and is extracted from CFD result. By introducing the CRPS index, long-term pollutant concentrations can be calculated as fast as the mass balance model while considering the pollutant distribution like CFD. The method was validated using previous experimental data. The case study was conducted and simulated changes in pollutant concentrations in a new residential unit for one week. The results showed that the CRPS-coupled method was different from conventional methods in that it more realistically calculates pollutant concentrations using relatively little computational resources.

ACS Style

Haneul Choi; Hyungkeun Kim; Taeyeon Kim. Long-term simulation for predicting indoor air pollutant concentration considering pollutant distribution based on concept of CRPS index. Building Simulation 2019, 12, 1131 -1140.

AMA Style

Haneul Choi, Hyungkeun Kim, Taeyeon Kim. Long-term simulation for predicting indoor air pollutant concentration considering pollutant distribution based on concept of CRPS index. Building Simulation. 2019; 12 (6):1131-1140.

Chicago/Turabian Style

Haneul Choi; Hyungkeun Kim; Taeyeon Kim. 2019. "Long-term simulation for predicting indoor air pollutant concentration considering pollutant distribution based on concept of CRPS index." Building Simulation 12, no. 6: 1131-1140.

Journal article
Published: 10 July 2019 in Applied Thermal Engineering
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A slim double-skin window (SDSW), which is a window that is naturally ventilated through a thin cavity of 20 mm, has recently been developed. This study aims to analyze the cooling energy performance of SDSW through field measurement and to numerically investigate its thermal characteristics and the influence of outer single glazing on it. The results of the field measurement showed that the room in which SDSW was installed had 9% less total cooling energy for a week in summer as compared to the room in which the triple glazing window was installed. The simulation results indicated that by changing the type of outer single glazing, the total solar heat gain (TSHG) differed by up to 34%. In addition, when the outer single glazing was low-emissivity glass, SDSW was the most effective. In the heat-transfer mode of the TSHG, the type of outer single glazing significantly affected short- and long-wavelength radiation rather than convection.

ACS Style

Haneul Choi; Youngsub An; Kyungmo Kang; Sunghoon Yoon; Taeyeon Kim. Cooling energy performance and thermal characteristics of a naturally ventilated slim double-skin window. Applied Thermal Engineering 2019, 160, 114113 .

AMA Style

Haneul Choi, Youngsub An, Kyungmo Kang, Sunghoon Yoon, Taeyeon Kim. Cooling energy performance and thermal characteristics of a naturally ventilated slim double-skin window. Applied Thermal Engineering. 2019; 160 ():114113.

Chicago/Turabian Style

Haneul Choi; Youngsub An; Kyungmo Kang; Sunghoon Yoon; Taeyeon Kim. 2019. "Cooling energy performance and thermal characteristics of a naturally ventilated slim double-skin window." Applied Thermal Engineering 160, no. : 114113.

Journal article
Published: 15 June 2019 in Building and Environment
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Predicting thermal comfort is one of the primary building research domains due to its technical and environmental significance. A metabolic rate, one of the significant variables for predicting an individual's thermal comfort, is primarily based on the human body's activity level. While other human and environmental factors, such as air temperature and relative humidity are easily measured and collected, with the help of sensory devices, a metabolic rate varies with time, and is not easy to measure to determine an accurate thermal comfort estimation in reality. Therefore, this study investigated the potential use of Deep Learning algorithm to accurately estimate the metabolic rate for a better thermal comfort estimation. A series of chamber tests were conducted with 23 test participants. The Kinect sensor was adopted to detect a user's physical motion, by capturing the motion images. With the help of a wearable sensor, a user's heart rate was also measured to estimate a metabolic rate. This study found that males showed higher MET than females, and the high BMI group generated higher MET than the low BMI group. The result also indicated that an estimated accurate range of 77%–89% was reasonably acceptable in the self-MET prediction modeling, while it was 65% in the third-party MET prediction. Therefore, the outcome of this research confirms that it is possible to use the Kinect sensor as a remote sensing device to estimate a user's metabolic rate, based on the use of a Deep Learning algorithm developed per individual.

ACS Style

Hooseung Na; Joon-Ho Choi; Hoseong Kim; Taeyeon Kim. Development of a human metabolic rate prediction model based on the use of Kinect-camera generated visual data-driven approaches. Building and Environment 2019, 160, 106216 .

AMA Style

Hooseung Na, Joon-Ho Choi, Hoseong Kim, Taeyeon Kim. Development of a human metabolic rate prediction model based on the use of Kinect-camera generated visual data-driven approaches. Building and Environment. 2019; 160 ():106216.

Chicago/Turabian Style

Hooseung Na; Joon-Ho Choi; Hoseong Kim; Taeyeon Kim. 2019. "Development of a human metabolic rate prediction model based on the use of Kinect-camera generated visual data-driven approaches." Building and Environment 160, no. : 106216.