• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2018.05a
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• pp.536-539
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• 2018

In this paper, we propose a system that analyzes environment information by using deep learning and then provides a suitable environment for users by predicting environmental information change. As the level of living improves, interest in improving the quality of life is increasing. In particular, as the air quality deteriorated due to the recent occurrence of dust, smog, fine dust, and ultrafine dust, the indoor air quality as well as the outdoor air became a serious problem. The increase of indoor pollution due to the lack of ventilation and the use of chemicals is a serious problem for modern people who have a lot of indoor living. In order to solve this indoor air pollution, a system has been proposed that measures the state of air quality through sensors and maintains proper temperature and humidity. However, existing system has a difficulty to apply most of the atmospheric environment information to various users depending on sensors only. The system proposed in this paper predicts the indoor environment by analyzing the indoor pollution information collected through the sensor using the deep learning. Then, the predicted indoor environment is modeled and learned in this system, and the environment suitable for the user is suggested. Afterwards, the system receives feedback from the user and repeats the process of re-learning the proposed environment so that it can create the optimal environment for the user.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.5
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• pp.17-25
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• 2016

In this study, the air quality of underground and overground railway stations was evaluated focusing on the degree of influence of the outside air quality. The measured components were particulate matter ($PM_{10}$), carbon dioxide ($CO_2$), carbon monoxide (CO), nitrogen dioxide ($NO_2$), formaldehyde (HCHO), ozone ($O_3$), total airborne bacteria (TAB), total volatile organic carbon (TVOC), and Radon (Rn), which are included in the maintenance standards and recommended standards of the Indoor Air Quality Management Act. Also, the indoor/outdoor concentration ratios of $PM_{10}$, $NO_2$, and $O_3$ were calculated to estimate the influence of the outdoor air quality. The concentrations of $PM_{10}$ HCHO, TVOC, $NO_2$, and Rn in the underground stations were found to be higher than those in the overground stations. These results indicate that the (present) generation of contaminants are caused by the indoor source of the underground station. The ozone concentration of the overground stations was higher than that of the underground stations, which indicates that the outdoor ozone concentration influenced that of the overground stations directly. Thus, methods of improving the IAQ should take into consideration the types of contamination.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.22 no.6
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• pp.361-368
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• 2010

Due to the insulation and the air-tightness requirement in modern buildings have resulted NBS(New Building Syndrome) and SBS(Sick Building Syndrome) of IAQ problems. Therefore, energy efficient way of solving such IAQ issues are of major concern in these days and building industries. This paper introduces a method to improve thermal performance with a DI(Dynamic Insulation) concept. The characteristic of the dynamic insulation is that the lower U-value as the higher air velocity through the DI in a micro level. A thermal performance monitoring study has been conducted to show the energy impact of porous DI over the static insulation material. The results show that up to 45% could be improved in the case with DI compared to the conventional insulation.

• Proceedings of the Korea Information Processing Society Conference
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• 2021.11a
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• pp.1088-1090
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• 2021

미세먼지가 인체에 유해한 영향을 끼칠 수 있다는 연구 결과가 꾸준히 발표되고 있다. 본 논문에서는 사물인터넷(IoT) 서비스를 활용하여 자동으로 창문을 개폐할 수 있는 시스템을 소개하고자 한다. 이 시스템에서는 측정한 실내 공기질과 오픈 API에서 받아온 실외 미세먼지 데이터를 비교하여 창문을 개폐하고, 사용자가 등록한 패턴에 따라 환기를 자동화하는 시스템이다.

• Horticultural Science & Technology
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• v.33 no.5
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• pp.751-762
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• 2015

This study was performed to investigate the stability of soil moisture in controlling air ventilation rate within a horizontal biofilter, and to compare removal efficiency (RE) of indoor air pollutants including fine dust, volatile organic compounds (VOCs), and formaldehyde (HCHO), depending on whether dieffenbachias (Diffenbachia amoena) were planted in the biofilter. The relative humidity, air temperature, and soil moisture contents showed stable values, regardless of the presence of D. amoena, and the plants grew normally in the biofilter. REs for number of fine dust particles (PM10 and PM2.5) within the biofilter filled with only soil were at least 30% and 2%, respectively. REs for number of fine dust particles (PM10 and PM2.5) within the biofilter including the plants were above 40% and 4%, respectively. RE for fine dust (PM10) weight was above 4% and 20%, respectively, in the biofilter containing only soil or soil together with plants. In the case of the biofilter filled with only soil, REs for xylene, ethylbenzene, toluene or total VOC (T-VOC) were each more than 63%; however, REs for benzene and formaldehyde (HCHO) were above 22% and 38%, respectively. In the biofilter with the plants, REs for xylene, ethylbenzene, toluene, and T-VOC were each above 72%, and REs for benzene and HCHO were above 39%. Thus, RE of the biofilter integrated with plants was found to be higher for volatile organic compounds than for fine dust. Hence, the biofilter was very effective for indoor air quality improvement and the effect was higher when integrated with plants.

• Journal of Environmental Science International
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• v.6 no.6
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• pp.659-670
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• 1997

Vehicle occupant exposure to volatile organic compounds (VOCs) has been a subject of concern In recent years because of higher levels of VOCs Inside vehicles as compared to the surrounding ambient atmosphere and because of the toxicity of VOCs. The effectiveness of two commercial ACDs for the removal of selected VOCs in the interior of automobiles was evaluated on 115 commutes throegh urban (Taegu) commutes by two cars and 9 idles. The idling and commuting studios conducted under four different driving conditions showed that the ho commercial ACDs were not effective for the removal of VOCs in the interior of vehicles. The concentrations of all target VOCs except benzene were significantly higher (p<0.05) in the interior of older car than of newer cu. The mean levels of benzene and toluene measured in thins study were well excess of earlier other studios In the United States, besides Los Angeles with which was comparable. It was reported that the in-vehicle exposure to benzene and corresponding upper-bound cancel risk were about 8 times higher than those for outdoor environment, while they were about half of those from Indoor environment.

• Korean Journal of Construction Engineering and Management
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• v.18 no.3
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• pp.63-73
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• 2017

In contemporary society, it is increasingly common to spend more time indoors. As such, there is a continually growing desire to build comfortable and safe indoor environments. Along with this trend, however, there are some serious indoor-environment challenges, such as the quality of indoor air and Sick House Syndrome. To address these concerns the government implements various systems to supervise and manage indoor environments. For example, green building certification is now compulsory for public buildings. There are three categories of green building certification related to indoor air in Korea: Health-Friendly Housing Construction Standards, Green Standard for Energy & Environmental Design(G-SEED), and Indoor Air Certification. The first two types of certification, Health-Friendly Housing Construction Standards and G-SEED, evaluate data in a drawing plan. In comparison, the Indoor Air Certification evaluates measured data. The certification using data from a drawing requires a considerable amount of time compared to other work. A 2D tool needs to be employed to measure the area manually. Thus, this study proposes an automatic assessment process using a Building Information Modeling(BIM) model based on 3D data. This process, using open source Industry Foundation Classes(IFC), exports data for the certification system, and extracts the data to create an Excel sheet for the certification. This is expected to improve the work process and reduce the workload associated with evaluating indoor air conditions.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.16 no.4
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• pp.2344-2349
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• 2015

In Korea, summer is hot and humid, and air-conditioners consume too much electricity due to large amount of latent heat. Simultaneous usage of dehumidifier may reduce the latent heat and save the electricity. In this study, dehumidification performance was measured in a constant temperature and humidity chamber for a small-sized dehumdification rotor made of inorganic fiber impregnated with metallic silicate. Variables were rotor speed, room temperature, regeneration temperature, room relative humidity and frontal velocity to the rotor. Results showed that there existed optimum rotor speed (1.0 rpm), and optimum regeneration temperature ($100^{\circ}C$). Above the optimum rotor speed, incomplete regeneration is responsible for reduced dehumidification. Above the optimum regeneration temperature, increased temperature difference between regeneration and dehumidification process is responsible for reduced dehumidification. The amount of dehumidification also increases with the increase of relative humidity, dehumidification temperature and flow velocity into the rotor.

• The Journal of the Convergence on Culture Technology
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• v.9 no.6
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• pp.1065-1071
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• 2023

In this paper discuss with research developing an LSTM model for classifying the behavior of occupants within a residence. The multi-sensor consists of an IAQ (Indoor Air Quality) sensor that measures indoor air quality, a UWB radar that tracks occupancy detection and location, and a Piezo sensor to measure occupants' biometric information, and collects occupant behavior data such as going out, staying, cooking, cleaning, exercise, and sleep by constructed an experimental environment similar to the actual residential environment. After the data with removed outliers and missing, the LSTM model is used to calculate accuracy, sensitivity, specificity of the occupant behavior classification model, T1 score.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.3
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• pp.483-490
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• 2019

Assessing the effect of forest fires and measuring the gas concentration around a fire has received little attention. Therefore, the concentrations of various gases in areas surrounding a fire need to be measured by the development of a suitable device. Unlike conventional portable devices, the AQS (Air Quality System) proposed in this paper is a portable instrument that measures five types of gases simultaneously, including CO, CO2, NOx, VOCs, and NH3, and has high durability through sensor protection algorithms. A PC-based program with an AQS connection was developed to monitor the real-time changes in the gas concentration. The reliability of the developed device was proven through a comparison of the results with other commercial gas analyzers. Measurements of the concentration due to indoor and outdoor fires were performed around a fire area to review the applicability and the predicted results were obtained.