• Journal of Environmental Health Sciences
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• v.32 no.2 s.89
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• pp.132-139
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• 2006

Number of aerosol, CO, $CO_2$ and TVOC after one-, two-, three-cigarettes smoking were monitored with time every 10 minute for 180 minutes in the seminar room (volume $51.1m^3$) when poorly-ventilated. IAQ monitor (IAQRAE, model PGM-5210) and PortCount (TSI, model 8020) were used for monitoring. Aerosol was decreased with exponential decay equation and it was estimated that number of aerosol would be long suspended (one cigarette 75/cc. two cigarettes 66/cc, three cigarettes 141/cc by 8hrs after smoking). While CO was also decreased with exponential or linear decay equation and correlated with number of aerosol strongly, TVOC and $CO_2$ were increased with linear equation in accordance with time lag. Most of TVOC and $CO_2$ were above standard levels of Korean Indoor Air Quality (Ministry of Environment) without regarding number of cigarettes. When naturally ventilated, all of CO, $CO_2$ and TVOC concentrations were dramatically decreased below standard levels of Korean Indoor Air Quality.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.46 no.4
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• pp.28-38
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• 2009

In this study, a remote air quality monitoring system for underground spaces was developed by using NDIR-based CO$_2$ sensor. And the remote monitoring system based on wireless sensor networks was installed practically on the subway station platform. More than 6.5 million citizens commutate everyday by the Seoul subway transportation that is the most typical public transportation. They concern about air quality with increasing interest on public health or many workers in subway stations or underground shopping centers. Recently, the Korean Ministry of Environment has operated the air quality monitoring system in some subway stations for testing phase. However, it showed many defects which are large-scale, high-cost and maintenance of precision sensors imported from abroad. Therefore this research includes the reliability test and a theoretical study about the inexpensive commercialized CO$_2$ sensor for reliable measurement of air quality which changes rapidly by the surrounding environments. And then we develop the wireless sensor nodes and the gateway applied for remote air quality monitoring. In addition, web server program was realized to manage air quality in the subway platform. This result will be valuable for a basic research for air quality management in underground spaces for future study.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.65 no.12
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• pp.2075-2083
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• 2016

The real time IAQ (Indoor Air Quality) management is very important for large buildings and underground facilities such as subways because poor IAQ is immediately harmful to human health. Such IAQ management requires monitoring, prediction and control in an integrated and real time manner. In this paper, we present three PM10 hourly prediction models for such realtime IAQ management as both Multiple Linear Regression (MLR) and Artificial Neural Network (ANN) models. Both MLR and ANN models show good performances between 0.76 and 0.88 with respect to R (correlation coefficient) between the measured and predicted values, but the MLR models outperform the corresponding ANN models with respect to RMSE (root mean square error).

• Prospectives of Industrial Chemistry
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• v.23 no.3
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• pp.32-41
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• 2020

사람들은 대부분의 시간을 실내에서 보내고 있으며, 실내에 존재하는 유해가스는 미량의 농도에도 불구하고 심각한 질환을 일으킬 수 있다. 금속산화물 반도체 가스센서는 감도가 우수하고, 구조가 간단하며, 초소형화가 가능한 장점이 있어 고가의 대형 장비를 사용하지 않고 실내 유해가스를 측정하는 데 효과적으로 이용될 수 있다. 본 기고문에서는 금속산화물 반도체를 이용한 가스 센서의 검지 원리를 고찰하고, 나노 구조 조절, 마이크로 리액터 및 이중층 구조를 이용한 가스 개질 등 실내 유해가스 측정을 위한 다양한 센서 설계방법을 소개하고자 한다.

• Journal of Environmental Health Sciences
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• v.43 no.3
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• pp.214-222
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• 2017

Objectives: A hospital is a complex building that serves many different purposes. The indoor environment in a hospital plays a major role in patient well-being and the work efficiency of the hospital staff. This study was conducted to evaluate overall comfort in two major hospitals over the course of one year. Methods: Various indoor environmental conditions were measured in two general hospitals for one year (April 2014 to April 2015). Monitoring alternated between the hospitals at one month per respective monitoring session. The indoor air temperature, relative humidity (RH), mean radiant temperature and air velocity were measured in order to calculate the predicted mean vote (PMV). Carbon dioxide concentration, noise level and illumination level were concurrently measured and applied to the overall IEQ acceptance model for the hospitals (IEQh). Results: The IEQh at the two general hospitals was different at five spaces within a building. The IEQh for summer and winter were significantly different. Real-time IEQh demonstrated that indoor comfort was affected by the hospital's operating hours due to operation of the HVAC system. The percentage of indoor comfort in the hospitals was higher using PMV than IEQh. Conclusion: IEQh in the hospitals was different at locations with different purposes. Indoor comfort assessment using IEQh was stricter than with PMV. Additional research is needed in order to optimize the IEQh model.

• Journal of Environmental Health Sciences
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• v.44 no.5
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• pp.421-432
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• 2018

Objectives: In this study, we started to develop an indoor garden integrated IoT solution based on IAQ (indoor air quality) and interconnection with an environmental database for smart management of indoor gardens. The purpose of this study was to develop and apply an integrated solution for customized air purification from an indoor garden through big data analysis using IoT technology. Methods: An IoT-based IAQ monitoring system was established in three households within a new apartment building. Based on real-time and long-term data collected, $PM_{2.5}$, $CO_2$, temperature, and humidity changes were compared to those of indoor garden applications and the analyzed results were indexed. Results As a result of the installation, all three households had no results exceeding the standard for indoor air pollution on average $PM_{2.5}$ and $CO_2$ indices. In the case of indoor garden installation, the IAQ index increased to the "Good" section after the installation, and readings in the "Bad" section shown before the installation disappeared. The comfort index also did not dip into the "Uncomfortable" section, where it had been preinstallation, and significantly lowered the average score from "Uncomfortable for sensitive groups" to "Good". Overall, the IAQ composite index for the generation of installations decreased the "Good" interval, but "Bad" did not appear. Conclusions In this study on developing an integrated solution for IAQ based on IoT indoor gardens, big data was analyzed to determine IAQ and comfort indexes and an IAQ composite index. Through this process, it became understood that it is necessary to monitor IAQ based on IoT.

• The Journal of the Korea institute of electronic communication sciences
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• v.17 no.3
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• pp.537-542
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• 2022

There is a limit to the current indoor air quality (IAQ) monitoring method using fixed sensors and devices. A mobile robot for IAQ monitoring was developed by mounting IAQ monitoring sensors on a small multi-legged robot to minimize vibration and protect the sensors from vibration while robot moves. The developed mobile robot used a simple gait mechanism to enable the robot to move forward, backward, and turns only with the combination of forward and reverse rotation of the two DC motors. Due to the simple gait mechanism, not only IAQ data measurements but also gait motion control were processed using a single Arduino board. Because the mobile robot has small number of electronic components and low power consumption, a relatively low-capacity battery was mounted on the robot to reduce the weight of the battery. The weight of mobile robot is 1.4kg including links, various IAQ sensors, motors, and battery. The gait and turning speed of the mobile robot was measured at 3.75 cm/sec and 14.13 rad/sec. The maximum height where the robot leg could reach was 33 mm, but the mobile robot was able to overcome the bumps up to 24 mm.

• Journal of the Korean Society of Visualization
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• v.20 no.1
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• pp.45-51
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• 2022

Airborne particulate matter(PM) has been a global environmental problem. PM whose diameter is smaller than 10 ㎛ can permeate respiratory organs and has harmful effects on human health. Therefore, PM monitoring systems are necessary for management of PM and prevention of PM-induced negative effects. Conventional PM monitoring techniques are expensive and cumbersome to handle. In the present study, two types of PM monitoring devices were designed for measuring indoor PM concentration, portably. We experimentally investigated the performance of three commercial PM concentration measurement sensors in a closed test chamber. As a result, PM2008 sensor showed the best PM concentration measurement accuracy. Linear regression method was applied to convert PM concentration value acquired from PM2008 sensor into ground truth value. A mobile application(app.) was also created for users to check the PM concentration, easily. The mobile app. also provides safety alarm when the PM₁₀ concentration exceeds 81 ㎛/m³. The developed hand-held system enables the facile monitoring of surrounding air quality.

• Journal of Environmental Health Sciences
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• v.35 no.2
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• pp.100-115
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• 2009

Secondhand smoke (SHS) is one of major public health threats. Since secondhand smoke is complex mixture of toxic chemicals, there has been no standardized method to measure SHS quantitatively. The purpose of this manuscript was to review various quantitative methods to measure SHS. There are two different methods: air monitoring and biological monitoring. Air monitoring methods include exhaled carbon monoxide level, ambient fine particulates, nicotine and 3-ethenylpyridine. Measurement of fine particulates has been utilized due to presence of real-time monitor, while fine particulates can have multiple indoor sources other than SHS. Ambient nicotine and 3-EP are more specific to SHS, although there is no real-time monitor for these chemicals. Biological monitoring methods include nicotine in hair, cotinine in urine, NNK in urine and DNA adducts. Nicotine in hair can provide chronic internal dose, while cotinine in urine can provide acute dose. Since biological monitoring can provide total internal dose, identification of specific exposure source may be difficult. NNK in urine can indicate carcinogenicity of the SHS exposure. DNA adducts can provide overall cancer causing exposure, but not specific to SHS. While there are many quantitative methods to measure SHS, selection of appropriate method should be based on purposes of assessment. Application of accurate and appropriate exposure assessment method is important for understanding health effects and establishing appropriate control measures.

• Proceedings of the KSR Conference
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• 2007.11a
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• pp.965-968
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• 2007

Two major parameters, i.e. carbon dioxide ($CO_2$) and particulate matters smaller than $10{\mu}m\;(PM_{10})$, were selected as the index pollutants in managing indoor air quality. The former pollutant, $CO_2$, is the index that shows the ventilation status and is exhaled by passengers when they breathe in train or subway. It is generally known that high $CO_2$ concentration in the vehicle may be decreased by insufficient air-tightening vehicle bodies and the air is ventilated when vehicles stop at the station and doors open. However, there is no established proof or quantitatively identified data on how much the $CO_2$ concentration is reduced when ventilation is done while doors are opened. In this study, $CO_2$ concentrations were measured in 6 lines of Korail and one line of Seoul Metro subway linesand a theoretical approach was takento predict the changing trend of $CO_2$ concentrations during the operation of vehicle by using $CO_2$ dilution factor through natural ventilation. As a result, the change could be quantified and it was found that app. 35% of indoor $CO_2$ was removed through natural ventilation.