• The Transactions of the Korean Institute of Electrical Engineers P
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• v.58 no.3
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• pp.357-361
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• 2009

This study performed analysis on the thermal pattern and current characteristics of an LED ((Light Emitting Diode) street lamp. It did this using a TVS (Thermal Video System) to analyze the LED street lamp's thermal pattern, and measured its characteristics using an oscilloscope. The ambient temperature and humidity during the experiment were maintained at $24{\pm}2[^{\circ}C]$ and 50~60[%]. The capacity of the LED street lamp was 120[W] and nine sets of modules were arranged at uniform intervals. On one module, 24 LED lamps were arranged in a radial pattern. The analysis of the thermal diffusion pattern at the front of the LED lamp showed that the maximum surface temperature was approximately $34[^{\circ}C]$. In addition, there was almost no change in the temperature of the upper cover, and the temperature at the side showed a uniform thermal diffusion pattern. The surface temperature of the converter converting AC to DC increased to approximately $46[^{\circ}C]$. The analysis results of the thermal characteristics of one LED indicated uniform thermal characteristics for an initial eight minutes. However, the temperature at the center of the LED increased to approximately $82[^{\circ}C]$ after 12 minutes had elapsed. It can be seen from this that the temperature at the center of the LED was higher than the allowable temperature, $70[^{\circ}C]$ of the insulating material for general electrical devices. Therefore, it is necessary to design a lamp in such a way that the plastic insulating material does not come into contact with or get close to the LED lamp. The voltage of the LED lamp converted by the AC/DC converter was measured at DC 27[V] and the current was DC 13[A]. Consequently, it can be seen that in order to secure an adequate light source, it is important to supply a stable current that was greater than the current of other light sources. Therefore, appropriate radiation of heat is required to secure the stability and reliability of the system.

• Journal of Sensor Science and Technology
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• v.29 no.5
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• pp.293-302
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• 2020

Food safety has emerged as a growing concern for human health in recent times. Consuming contaminated food may lead to serious health problems, and therefore, a system for monitoring food freshness that is both non-detrimental to the quality of food and highly accurate is required to ensure that only high-quality fresh food packages are provided to the customers. This paper proposes a method to monitor and detect food quality using a compact smart sensor tag. The smart tag is composed of three ultra-low-power sensors, which monitor four major indicators of food freshness: temperature, humidity, and the concentrations of ammonia and hydrogen sulfide gases. An RF energy scavenging circuit is integrated into the smart sensor tag to harvest energy from radio waves at a high frequency of 13.56 MHz to supply sufficient power to the tag. Experimental results show that the proposed energy harvester can efficiently obtain energy at a distance of approximately 40 cm from a 4 W reader. In addition, the proposed smart sensor tag can operate without any battery, thereby eliminating the requirement of frequent battery replacement and consequently decreasing the cost. Meanwhile, the freshness of preserved pork is continuously monitored under two conditions--room temperature and refrigerator temperature--both of which are the most common temperatures under which food is generally stored. The food-monitoring experiments are conducted over a period of one week using the proposed battery-less tag. Based on the experimental results, the food assessment is classified into four categories: fresh, normal, low, and spoiled.

• Journal of Environmental Science International
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• v.24 no.3
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• pp.281-290
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• 2015

Recent climate change has led to fluctuations in agricultural production, and as a result national food supply has become an important strategic factor in economic policy. As such, in this study, panel data was collected to analyze the effects of seven meteorological elements on the production of five types of grain with error component panel data regression method following the test results of LM tests, Hausman test. The key factors affecting the production of rice were average temperature, average relative humidity and average ground surface temperature. The fluctuations in the other four grains types are not well explained by meterological elements. For other grains and beans, only average temperature and time (year) affect the production of other grains while average temperature, ground surface temperature, and time (year) influence the production of beans. For barley and millet, only average temperature positively affects the production of barley while ground surface temperature and time (year) negatively influence the production of millet. The implications of this study are as follow. First, it was confirmed that the meteorological elements have profound effects on the rice production. Second, when compared to existing studies, this study was not limited to rice but encompassed all five types of grains and went beyond other studies that were limited to temperature and rainfall to include various meteorological elements.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.14 no.6
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• pp.1447-1452
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• 2010

Ubiquitous society to build basic infrastructure in the power supply and power equipment safety is important. u-City in order to prevent the disaster of u-IT Power Equipment Performance Module and the security for the safety of the u-City is necessary. In this paper, the power unit of u-IT module, temperature sensor, humidity sensor, equipped with sensors arranged throughout the fire, and home distribution boards, Home Network Wall-Pad, Blocker, MPNP black boxes, arc detection, arc safety equipment, outlet of the modular performance evaluation methods and security methods will be studied. u-IT power devices and sensors to analyze the information conveyed by proactive risk and ensure safety, access control, authentication, security safeguards, such as u-IT integrated management system for electrical safety and strengthen the security, safety and security with a u-City will contribute to the construction and operation.

• Journal of Institute of Control, Robotics and Systems
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• v.11 no.7
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• pp.578-586
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• 2005

Air mattress is now used widely to prevent the pressure ulcer by reducing the localized pressure peaks. The pressure control method based on the anthrophometric model of an air-cell mattress developed in this study is presented. The air-cell mattress has 18 cylindrical air cells made of porous material allowing air leakage. Even though the air leakage can contribute to reducing the development of pressure ulcer by lowering the pressure peak, temperature and humidity, the air pressure changes with time and the desired air-cell pressure has to be determined as an optimal value for each user. To select the desired air-cell pressure, we first divide the parts of the body into four sections such as head, trunk, hip, and leg. Then, the pressure of each section grouped with air-cells is calculated from the weight of each part estimated from the individual height and body weight. Air supply system for the air-cell mattress is implemented by using four electronic solenoid valves and an air compressor, and it is driven by a real-time microcontroller. We experimented with five subjects of the contact pressure on skin. The experimental results show that the proposed air-cell mattress is effective for the prevention of the pressure ulcer.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.39 no.1
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• pp.25-30
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• 2016

It is critical to forecast the maximum daily and monthly demand for power with as little error as possible for our industry and national economy. In general, long-term forecasting of power demand has been studied from both the consumer's perspective and an econometrics model in the form of a generalized linear model with predictors. Time series techniques are used for short-term forecasting with no predictors as predictors must be predicted prior to forecasting response variables and containing estimation errors during this process is inevitable. In previous researches, seasonal exponential smoothing method, SARMA (Seasonal Auto Regressive Moving Average) with consideration to weekly pattern Neuron-Fuzzy model, SVR (Support Vector Regression) model with predictors explored through machine learning, and K-means clustering technique in the various approaches have been applied to short-term power supply forecasting. In this paper, SARMA and intervention model are fitted to forecast the maximum power load daily, weekly, and monthly by using the empirical data from 2011 through 2013. $ARMA(2,\;1,\;2)(1,\;1,\;1)_7$ and $ARMA(0,\;1,\;1)(1,\;1,\;0)_{12}$ are fitted respectively to the daily and monthly power demand, but the weekly power demand is not fitted by AREA because of unit root series. In our fitted intervention model, the factors of long holidays, summer and winter are significant in the form of indicator function. The SARMA with MAPE (Mean Absolute Percentage Error) of 2.45% and intervention model with MAPE of 2.44% are more efficient than the present seasonal exponential smoothing with MAPE of about 4%. Although the dynamic repression model with the predictors of humidity, temperature, and seasonal dummies was applied to foretaste the daily power demand, it lead to a high MAPE of 3.5% even though it has estimation error of predictors.

• Journal of Korea Multimedia Society
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• v.17 no.11
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• pp.1313-1324
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• 2014

Korea has high quality level of ICT Technologies, however it still have a long way to go before invigoration of ICT in agriculture industry. The government of Korea supply to agriculture ICT systems, however these are the enclosed type and insufficient the level of connectivity, compatibility, and integrity between ICT systems. Farmers can not share crop information and one system can not use with others in combination. Recently, IoT(Internet of Things) become popular to emphasize the vision of a global internet and ICT industry. The IoT is a critical technology that leads future internet generation. We believe that IoT will change status of agriculture industry and appearance of various agriculture business model. Using IoT technology is provided a platform of opportunities to optimize work processes and efficient use of energy, time and labour in farm. It can automatically control temperature, humidity, sunshine system and so on for optimal growth conditions at greenhouse and plant factory. Growth setting can even be controlled and monitored crop condition and disease by a smartphone app or PC. It is possible to improve quality of farming and farm product. We suggest that construction of IoT platform through open API in agriculture industry.

• Journal of the Korea Safety Management & Science
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• v.12 no.4
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• pp.41-51
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• 2010

This paper describes the development of various lighting equipment adapting Ultra Constant Discharge Lamp that has newly been on commercial supply in the market. Meeting the required conditions of lighting equipment, various types of UCD Lamp equipment with excellent performances could be successfully developed. In order to provide a guideline for the economical lighting product selection, the analyzed data comparison between Hi-pressure Sodium Lamp which has been the most popular lamp for street lighting and UCD Lamp is provided. The conclusions of the study are made as follows; (1) The performance measurement result of UCD Lamp shows excellent Luminous Efficacy as 108Lm/W, daylight-like Color Rendering Index as 90Ra, and the best operating temperature range as $-50^{\circ}C{\sim}+85^{\circ}C$. Comparing to the Hi-pressure Sodium Lamp, UCD could be evaluated as much superior products. (2) In an assembled status with the lighting fixture (Type STB형-60W), UCD Lamp was tested OK for one hour duration at the temperature range form $-50^{\circ}C$ to $+85^{\circ}C$ and the humidity of 98%. The operation at the extremely low temperature can be an excellent feature to enable the export to the cold temperature regions such as Northern Europe and Russia and the specific applications for defense systems and special industry. (3) As UCD Lamp is a genuine Korea made product following Energy-saving and Eco-friendly policy, it should be appreciated as one of the best $CO^2$ reduction Green product.

• Journal of the Korea Concrete Institute
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• v.22 no.2
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• pp.159-169
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• 2010

A multiphysics model analysis including moisture transport, heat transfer and solid mechanics and experiments on the normal and light weight concrete were carried out in order to study the effect of preabsorbed water in the light weight aggregates on the drying and shrinkage characteristics of concrete. Consequently, with fixed water-cement ratio, loss of water content of normal and light weight concrete were compared and the results showed that the lightweight concrete lost less moist than the normal concrete in early age and long term which was by moist supply effect. Accordingly, shrinkage strain size and distribution of lightweight concrete were decreased, and shrinkage reducing effect was efficient in early age with water cement ratio 0.3 and in both early age, and long term with water cement ratio 0.5. The comparison of analysis results and exaperimental results indicate that characteristic values of moisture transport and the relation humidity and shrinkage strain from this study are resonable for application for other differential shrinkage analysis in lightweight concrete.

• Journal of the Korean Data and Information Science Society
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• v.27 no.4
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• pp.969-977
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• 2016

Climate change affects the growth of crops which were planted especially in fields, and it becomes more important to use climate data to predict the yields of the major vagetables. The variation of the crop products caused by climate change is one of the significant factors for the discrepancy of the demand and supply, and leads to the price instability. In this paper, using a panel regression model, we predicted the garlic yields with the weather conditions of different regions. More specifically we used the panel data of the several climate variables for 15 main garlic production areas from 2006 to 2015. Seven variables (average temperature, average maximum temperature, average minimum temperature, average surface temperature, cumulative precipitation, average relative humidity, cumulative duration time of sunshine) for each month were considered, and most significant 7 variables were selected from the total 84 variables by the stepwise regression. The random effects model was chosen by the Hausman test. The average maximum temperature (January), the cumulative precipitation (March, October), the cumulative duration time of sunshine (April, October) were chosen among the variables as the significant climate variables of the model