• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.6
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• pp.766-773
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• 2021

This paper presents an implementation result and performance evaluation of pavilion management services that does not only provide real-time status of the pavilion in the forest but also prediction services through machine learning. The developed hardware prototype detects whether the pavilion is occupied using a motion detection sensor and then sends it to a cloud database along with location information, date and time, temperature, and humidity data. The real-time usage status of the collected data is provided to the user's mobile application. The performance evaluation confirms that the average response time from the hardware module to the applications was 1.9 seconds. The accuracy was 99%. In addition, we implemented a pavilion availability prediction service that applied a machine learning-based SVM (Support Vector Model) model to collected data and provided it through mobile and web applications.

• Journal of Biosystems Engineering
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• v.29 no.3
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• pp.243-250
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• 2004

본 연구에서는 국내 미곡도정공장의 도정기계 작동상태와 가공된 발 품질의 원격감시를 위해서 인터넷기반 감시시스템을 개발하고자 하였다. 인터넷 감시시스템은 Laboratory Virtual Instrument Engineering Workbench(Lab VIEW)를 이용하여 개발되었으며 Hypertext Transfer Protocol(HTTP)을 제공할 수 있는 중앙서버, 현장제어용 Programmable logic controller (PLC) 및 각종 센서 등으로 구성되었다. 비상상태를 대비하기 위하여 도정기계를 원격으로 제어(ON/OFF)할 수 있도록 제어알고리즘을 설계하였다. 개발된 인터넷기반 감시시스템은 미곡 도정공장에 설치한 모든 도정기계의 작동상태, 백미 탱크내의 백미 무게와 백미의 온도 및 평형상대습도를 실시간으로 감시할 수 있었으며, 원격으로 측정한 백미탱크내의 평형온도 및 평형상대습도를 이용하여 백미의 함수율도 예측할 수 있었다. 거리 및 인터넷속도에 의해 발생된 시간지연의 측정과 원격으로 수집된 자료의 검증을 통해 인터넷 감시시스템의 성능을 평가하였다. 인터넷상의 시간지연(서울-광주간)은 약 1.2$\pm$0.2s 이었다.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.39 no.5
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• pp.400-407
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• 2011

The stress distribution and stress amplitude of a membrane are major factors to decide the mechanical fatigue life of PEMFC (Polymer Electrolyte Membrane Fuel Cell). In this paper, mechanical stresses under operating hygro-thermal condition of the membrane are numerically modelled. Contact analysis between gas diffusion layer (GDL) and the membrane is performed under various temperature-humidity conditions. The structural model has nonlinear material properties depending on temperature and relative humidity. Several geometric conditions are applied to the model. The numerical analysis results indicate that deformations of the membrane are strongly related with assembly conditions of the fuel cell. The fatigue life is predicted for practical operating condition through experimental data.

• Journal of the Korea institute for structural maintenance and inspection
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• v.17 no.5
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• pp.113-121
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• 2013

The road icing forecast and snow detection system using state evaluation algorithm of multi sensor optimizes snow melting system to control spread time and amount of chemical spread application This system operates integrated of contact/non-contact sensor and infrared camera. The state evaluation algorithm of the system evaluates road freezing danger condition and snowfall condition (snowfall intensity also) using acquired data such as temperature/humidity, moisture detection and result of image signal processing from field video footage. In the field experiment, it proved excellent and reliable evaluated result of snowfall state detection rate of 89% and wet state detection rate of 94%.

• Journal of IKEEE
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• v.22 no.1
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• pp.53-60
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• 2018

Smart farm dissemination by continuously developing IoT is one of the best solution for decreasing labor in Korea farming area because of ageing. For this reason, the number of Smart farm in Korea is being increased. The Smart farm can control farming environment such as temperature for human. Specially, The important thing is controlling proper temperature for farming. In order to control the temperature, legacy smart farms are usually using pans or air conditioners which can control the temperature. However, those devices result in increasing production cost because the electric power consumption is high. For this reason, we propose a smart farm which can predict the proper temperature after an hour by using Deep learning to minimize the electric power consumption by controlling window instead of pans or air conditioners. We can see the 83% of electric power saving by means of the proposed smart farm.

• Korean Journal of Construction Engineering and Management
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• v.4 no.4 s.16
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• pp.155-163
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• 2003

There are a growing number of cases to expand balconies of apartments faced with open air in order to enhance functional satisfaction and efficiency of dwelling space. In case of the balcony expansion at the floor, however, it is difficult to exclude a possibility of bringing about internal condensation due to the difference of temperature between indoor air and outdoor air caused by the Inflow of outer low-temperature air through the upper part of ceilings by failure in completely putting together the outer composite wall panels on the aluminum curtain walls installed at outer walls This study is to forecast possible occurrence of internal condensation around parapets and H-beam located at the inside of balcony ceilings on the uppermost floor of super-high apartment buildings faced with open air in order to provide dwellers with more comfortable environment in the related space and get rid of their uneasiness about the condensation. In this study, we estimated internal condensation, which vary in accordance with humidity pressure distribution, at curtain walls, stone panels or lower parts of slabs that constitute outer space of the residence and are weak against heat, through temperature forecast and temperature distribution interpretation program at normal two-dimension temperature

• Proceedings of the SAREK Conference
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• 2008.06a
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• pp.937-942
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• 2008

In this paper, new methodology is proposed to estimate the cooling load using design parameters of building and predicted weather data. Only two parameters such as maximum and minimum temperature are necessary to obtain hourly distribution of cooling load for the next day. The maximum and minimum temperature that are used for input parameters can be obtained from forecasted weather data. Benchmarking building(research building) is selected to validate the performance of the proposed method, and the estimated cooling loads in hourly bases are calculated and compared with the measured data for benchmarking building. The estimated results show fairly good agreement with the measured data for benchmarking building.

• Journal of the Korean Wood Science and Technology
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• v.47 no.6
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• pp.732-750
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• 2019

Air drying was carried out on 15 Korean red pine logs to provide a prediction model of the moisture content (MC) change in the wood during drying. The final MC was 17.4% after 880 days since the beginning of air drying in the summer for 6 Korean red pine logs with 68.7% initial MC. The final MC was 16.0% after 760 days since the beginning of air drying in the winter for 9 Korean red pine logs with 35.8% initial MC. A regression model with R-squared of 0.925 was obtained as a result of multiple regression analyses with initial MC, top diameter, temperature, relative humidity, and wind speed as independent variable and and MC change during air drying as dependent variable. The initial MC and top diameter, which is the characteristic of Korean red pine, have greater effect on the MC decrease during air drying compared to meteorological factors such as the temperature, relative humidity, and wind speed. Two-dimensional mass transfer analysis was performed to predict the MC distribution of Korean red pine logs during air drying. Two prediction models with different air drying days and different meteorological factors for the determination of the diffusion coefficient and surface emission coefficient were presented. The error between the different two methods ranged from 0.1 to 0.8% and the difference from the measured value ranged from 2.2 to 3.6%. By measuring the internal MC during air drying of Korean pine logs with various initial MC and diameter, and calculating the moisture transfer coefficient in wood for each meteorological condition, the error of the prediction model can be reduced.

• Journal of Digital Convergence
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• v.12 no.10
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• pp.243-252
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• 2014

Many researches about the effect on politics, economics and Sociocultural phenomenon using the social media are in progress. Authors utilized NAVER Trend most famous web browsing service in korea, NAVER Blog social media, NAVER Cafe service and Open Data(API) and also used temperature, humidity index data of Korea Meteorological Administration. This study analyzed a change of the public's emotion in korea using Cluster analysis of vocabulary of taste among its of feelings and senses. K-means clustering was followed by decision of the number of groups which was used Chi-square goodness of fit test and ward analysis. Eight groups was made and it represented sensitive vocabulary. By Discriminant analysis, eight groups decided by Cluster analysis has 98.9% accuracy. The change of the public's emotion has capability to predict people's activity so they can share sensibility and a bond of sympathy developed between them.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.41 no.8
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• pp.759-764
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• 2017

This research investigated the hygrothermal effect on the strength of bolt jointed section and moisture contents of composites exposed to hygrothermal environment for composite aircraft radome. The decrease in strength in the test environment is mainly attributed to the change in the material properties of the matrix due to temperature and moisture. The composite specimens were tested in three different environmental conditions: RTD(room temperature and dry), CTD(cold temperature and dry) and ETW(elevated temperature and wet). The failure mode of the bolt jointed composite specimens were studied using tests and finite element analysis. Finite element analysis reasonably predicted the failure load and mode of the joints. A reliability-based design was carried out for the bolt jointed composites of radome.