• The Journal of Sustainable Design and Educational Environment Research
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• v.16 no.3
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• pp.69-76
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• 2017

Indoor Air Quality(IAQ) affects physical and mental state of person who is residing indoor. Also, it manages daily life condition of Indoor Air in the building. According to the study, office workers spend 23 hours and 12 minutes, about 97% of his/her day indoor. Therefore, Indoor air quality affects not only the health of the person whose staying inside for a long hours but also the productivity and efficiency of work. This study conduct investigations on employees' awareness of indoor air quality of office in university. By doing so, we are able to determine current situation and provide basic data of improvement for derived problems. As a result, most of the respondents were not satisfied with ventilation and moisture which are elements of Indoor Air Quality. These led people to struggle with symptoms of health. Therefore, to improve the indoor air quality of a university office, it is necessary to exchange the air six times an hour according to recommendation of Refrigeration and Air Conditioning Engineers (ASHRAE)in the United States. Also, plan for Ventilation system that consider temperature, humidity and air flow indoor shall be provided for high quality conformability. furthermore, It is necessary to consider the multilateral in factors of generation of revenue through health care savings of workers and improvement of productivity.

• Journal of Bio-Environment Control
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• v.6 no.1
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• pp.48-54
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• 1997

Among the various vegetables eggplant and gourd family can stand against high temperature environmental condition, about 35$^{\circ}C$. However, most of greenhouse farmers are giving up crop cultivation during hot summer season due to extreme temperature, 4$0^{\circ}C$ or above, condition of greenhouse interior. To improve this inferior crop growth condition, for nozzle system was installed in the pet greenhouse and the effect of fog system was investigated in order to determine fog water amount and the required fog nozzle numbers according to house volumes. MEE fog nozzle was selected for this Investigation which can produce water particle size of 27${\mu}{\textrm}{m}$ with water amount of 100$m\ell$ at pumping pressure of 70kg/$\textrm{cm}^2$. House cooling test was conducted in the pet greenhouse with one minute fogging and one minute air ventilation without stopping. It maintained 32$^{\circ}C$ at the house interior when the atmosphere and the house temperature were 35 and 4$0^{\circ}C$, respectively. And, an experimental equation was developed through calculating the changes of relative humidity and temperature with psychrometric equation which revealed the moisture transfer pattern between the house air and fog system. It showed that the required water fogging amounts to reduce 1$0^{\circ}C$, 40 to 3$0^{\circ}C$, needs 80.7$\ell$ for 1-2W(8,350㎥) and 99.9$\ell$ for 3-2G-3S(10,330㎥) type greenhouse with particle size of 27${\mu}{\textrm}{m}$.

• Korean Journal of Environmental Biology
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• v.40 no.2
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• pp.214-223
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• 2022

Among migratory insect pests, Mythimna seperata and Cnaphalocrocis medinalis are invasive pests introduced into South Korea through westerlies from southern China. M. seperata and C. medinalis are insect pests that use rice as a host. They injure rice leaves and inhibit rice growth. To understand the distribution of M. seperata and C. medinalis, it is important to understand environmental factors such as temperature and humidity of their habitat. This study predicted current and future habitat suitability models for understanding the distribution of M. seperata and C. medinalis. Occurrence data, SSPs (Shared Socio-economic Pathways) scenario, and RCP (Representative Concentration Pathway) were applied to MaxEnt (Maximum Entropy), a machine learning model among SDM (Species Distribution Model). As a result, M. seperata and C. medinalis are aggregated on the west and south coasts where they have a host after migration from China. As a result of MaxEnt analysis, the contribution was high in the order of Land-cover data and DEM (Digital Elevation Model). In bioclimatic variables, BIO_4 (Temperature seasonality) was high in M. seperata and BIO_2 (Mean Diurnal Range) was found in C. medinalis. The habitat suitability model predicted that M. seperata and C. medinalis could inhabit most rice paddies.

• Proceedings of the Korea Information Processing Society Conference
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• 2012.11a
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• pp.1146-1149
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• 2012

본 연구는 노지에서의 와인용 포도 재배에 있어서 병충해에 대한 실시간 모니터링과 선제적 예방활동을 위해 무선센서 네트워크(Wireless Sensor Network)를 활용하여 데이터를 수집하고 온습도정보, 이미지 등의 분석을 하고 병충해 지식은행을 통한 병충해 발생 확인 및 최적의 조치를 제안하여 와인용 포도의 병충해 피해를 예방하고 생산성을 높일 수 있도록 하는 시스템에 관한 것이다. WSN 센서 노드는 각 블럭 별 및 지형 특성상 높은 고도의 위치 등 다수의 지점에 설치되어 온도 습도 등 환경 데이터를 수집하고, 이미지 센서를 통해 주기적 이미지데이터를 전달하여 지식은행의 데이터를 바탕으로 병충해 발생으로 인한 와인용 포도 재배에 피해가 예상되는 현상을 미리 예측하고 그 해결방안을 제시하여 재배자가 선제적으로 대처할 수 있도록 하여 피해를 최소화한다.

• Proceedings of the Korea Information Processing Society Conference
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• 2021.11a
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• pp.1085-1087
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• 2021

이 논문에서는 다매체를 사용하여 데이터를 수집한 후 기계학습을 통해 분석하고 주어진 상황에 대응하기 위한 시스템의 개발을 기술한다. 개발 시스템은 센서데이터 수집부, 상황인지 및 상황대응부로 이루어지며, 아두이노와 라즈베리파이를 사용하여 구성한다. 구성된 시스템은 영상 카메라 및 온습도을 포함한 다수의 센서를 사용하여 환경정보를 수집한 후 수집자료를 전처리하고 주어진 상황을 인지하여 상황에 가장 적절하다고 판단되는 대응을 안내하도록 기능을 구성하였다. 상황인지를 위해서는 기계학습 알고리즘으로 의사결정트리를 사용하였으며 100%의 상황인지 정확률을 갖는다.

• Journal of Animal Environmental Science
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• v.20 no.2
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• pp.49-56
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• 2014

The climate of the earth is expected to change rapidly and continuously. Despite climate change is expected to impact on productivity of crop and livestock, a study for adaptation and impact of livestock to global warming is not enough. This study was performed to develop a method to evaluate the effects of heat stress on dairy cattle. Feedlot environment and health status of livestock were measured through an infrared thermography camera and a temperature-humidity sensor. Environmental factors such as temperature and humidity were measured to calculate the Temperature humidity index (THI). The change of the milk yield was similar to THI data pattern, suggesting that THI might play an important role to predict the effect of climate change on dairy cattle. THI data would be useful to predict long-term climate change effects on dairy cattle with RCP8.5 scenario.

• Proceedings of the Korean Society of Computer Information Conference
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• 2023.07a
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• pp.727-728
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• 2023

최근 국내 축산 인구의 감소 및 고령화가 빠르게 진행되고 AI, 구제역 등 가축 질병의 잦은 발생으로 축산업이 위기를 겪고 있고 기존의 축산 형태는 급이, 급수를 직접 관리하고 가축의 발정 및 분만 시기를 놓쳐 생산성이 감소하는 불편함이 있다. 본 논문은 기존의 축산 시스템에서 정보통신기술을 융합시킨 'ICT 기술을 활용한 스마트 축산'을 제안한다. 공기질센서, 온습도센서 등을 활용하여 축산 내부 환경을 체크하고, 자동으로 급수 및 급이기, 환기팬, 창문개폐, 생균제 분사가 작동하여 축산의 환경을 최적의 상태로 관리하여 준다. 그리고 스마트폰을 이용하여 원격으로 스마트 축산을 원격제어 및 감독할 수 있어 관리자의 불편함을 최소화 할 수 있다. 또한, 발정측정기를 사용해 소의 발정 시기를 탐지하여 생산성을 높일 것이다.

• Journal of Conservation Science
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• v.30 no.2
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• pp.169-179
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• 2014

After occurrence of Cyanobacteria in 1997, Songsan-ri tombs located in Gonju have been investigated to monitor for biological damage. The room temperature of Tomb No.6 was $18.6{\sim}19.8^{\circ}C$ and the relative humidity was 94.3~99.9%. The temperature of Royal Tomb of King Muryeong was $17.3{\sim}18.53^{\circ}C$ and the relative humidity was 73.2~96.45%. The variation of relative humidity increased after setting up air vents. If the outside temperature increases, dew condensation occurs on the floor and the north side. When conditioning equipment operates, the maximum temperature differences between walls is $2.8^{\circ}C$. Bacteria from the air of the tomb and on the surface of the walls outnumbered fungi. 20 species of fungi including Alternaria sp., Aspergillus sp., Penicillium sp., and 19 species of bacteria including Pseudomonas sp., Arthrobacter sp., are identified. Microbes in the tombs may damage cultural heritage. The growth possibility of microbes should be estimated because the microbes in the tombs may damage mural painting. The interrelation between microenvironmental condition and biological damage of mural painting should be researched to come up with an long-term conservation method.

• Journal of Bio-Environment Control
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• v.14 no.1
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• pp.46-51
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• 2005

This experiment was conducted to investigate planting depth, which applied the basic data for planting growth ability and mechanical planting of oriental melon. 'Gumssaragi-eunchun' variety was approach grafting to 'Shintozoa' and seedling was growing during 45 days in the 9cm pot and then planted on Jan. 16. The comparison of planting plots was carried out for four experimental plots, which were separated into 0cm, 4.5cm, 9cm, standard cultivation, and 12cm planting depth in soil. In the tunnel of vinyl house, the lowest and the highest temperature was $9.3^{\circ}C\;and\;41.2^{\circ}C$, respectively, and humidity was $59\~99\%$ during Jan. 18 and 19. The faster graft-take rate after planting was the deeper planting depth. The growth of 40 days after planting was not significant in each planting plot, except 0cm experimental plot. Fruit weight was the heaviest in 4.5cm planting depth of experimental plot but sugar content and flesh thickness were not significant in each planting depth. The more depth in planting meant the more increase in fermented fruit rate and decrease in marketable fruit rate. Marketable yield was 2,361kg per l0a in 9cm planting plot, which was $2\%\;and\;1\%$ lower than in 0cm and 4.5cm, respectively, and $11\%$ greater than in 12cm planting plot.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.10a
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• pp.25-27
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• 2022

Recently, with the development of the 4th industry, environmental issues such as air pollution have become serious, and in particular, a lot of air pollutants are generated in industrial sites. There are various types of air pollutants, and among them, carbon monoxide is essential for fires occurring in industrial sites, so it should be possible to monitor in real time. In addition, there is a need for a remote monitoring system that can measure various environmental factors other than air pollutants in real time. In this paper, we propose a monitoring system using wireless communication to remotely measure the industrial environment. The proposed monitoring system collects data to the Arduino of the transmitter by using a carbon monoxide sensor, a combustible gas sensor, a temperature and humidity sensor, and a flame sensor, and then transmits it to the receiver using ZigBee. The transmitted data is stored in the database of the receiver Raspberry Pi, and the stored data can be monitored in real time through the monitoring system.