• 한국IT서비스학회:학술대회논문집
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• 2010.05a
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• pp.85-90
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• 2010

우리사회는 당면한 사회적인 문제가 많다. 수명연장 저출산에 의한 사회고령화가 가속되고 있지만 사회적 부담 해소를 위한 노년 일자리 창출이 요원한 실정이다. 700 만 명이 넘는 1차 베이비 붐 세대가 2012년을 시점으로 본격 은퇴가 예상되고 있는 반면 이들을 수용할 일자리가 절실할 때에 고용상황의 악화로 오히려 조기퇴직이 가속화되고 있다. 또한 농촌인구의 감소 및 노령화로 농촌의 황폐화가 심각한 실정이다. 본 논문에서는 영농분야에서 중장년층에게 안정적인 고용효과를 제공하면서 에너지절감이 가능한 IT 기반의 스마트영농 기술 및 특성을 소개하고 고용창출, 농촌활성화 및 녹색산업의 성장으로 연계하기 위한 전략과 정부의 정책을 제안하고 관련된 이슈에 대해서 기술하고자 한다.

• Journal of Electrical Engineering and Technology
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• v.13 no.5
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• pp.1874-1885
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• 2018

The customer side operation is getting more complex in a smart grid environment because of the adoption of renewable resources. In performing energy management planning or scheduling, it is essential to forecast non-controllable resources accurately and robustly. The PV system is one of the common renewable energy resources in customer side. Its output depends on weather and physical characteristics of the PV system. Thus, weather information is essential to predict the amount of PV system output. However, weather forecast usually does not include enough solar irradiation information. In this study, a PV system power output prediction model (PPM) under limited weather information is proposed. In the proposed model, meteorological radiation model (MRM) is used to improve cloud cover radiation model (CRM) to consider the seasonal effect of the target region. The results of the proposed model are compared to the result of the conventional CRM prediction method on the PV generation obtained from a field test site. With the PPM, root mean square error (RMSE), and mean absolute error (MAE) are improved by 23.43% and 33.76%, respectively, compared to CRM for all days; while in clear days, they are improved by 53.36% and 62.90%, respectively.

• Smart Media Journal
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• v.11 no.1
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• pp.67-80
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• 2022

Smart City Technology, which is significant in the era of the 4th industrial revolution, greatly increases the efficiency and productivity of cities nowadays. The purpose of this study is to present a strategic approach for industrial revitalization and overseas export by analyzing the current status of smart city-related companies and discovering high-priority smart city technologies. To this end, the smart city theory and ASEAN smart city were reviewed through prior research, and a survey of companies with domestic smart city technology was conducted. As a result of the survey, it is revealed that companies with smart city technology in Korea are highly willing to export to ASEAN countries. There is a strong desire to export the following technologies: construction, traffic, green·energy, etc. And there was a high willingness to export the following services: IoT, platform, AI, etc. The following solutions have been proposed as solutions to Strategic Plans to Promote the Export: 1) Deregulation and incentives, 2) Global human resource development, 3) Information provision and strengthening of local networks, 4) Financial and public relations support.

• Land and Housing Review
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• v.13 no.1
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• pp.131-140
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• 2022

A smart window is a new building material that can realize energy savings in a building. Smart windows can freely adjust Visible Light Transmittance (VLT) and solar gain coefficient (g-value) according to the situation. Smart windows include such technologies as Electrochromic (EC), Suspended Particle Device (SPD), and Polymer Dispersed Liquid Crystal (PDLC). Recent research on building energy savings through the VLT and g-value control functions of smart windows is being actively conducted and meaningful results are being drawn. However, since most of the research is focused on energy savings, research on the indoor environment is somewhat lacking. A building is a space where people live and the comfort of life should be prioritized before energy savings. Therefore, in this study, analysis on the daylight performance of an office space was carried out. Through green building standards such as LEED, BREEAM, CASBEE, and G-SEED, the daylight performance was reviewed according to VLT value changes of the smart window. In addition, a study was conducted on the VLT range of the electrochromic façade that can maintain a comfortable indoor environment. The smart window used electrochromic control with a wide range of VLT. The study showed that the minimum VLT of a smart window that can satisfy G-SEED is 25% or more. In addition, it was found that the VLT change of the electrochromic smart window did not significantly affect the uniformity of the room. When the LEED standard was applied, the minimum VLT value of the electrochromic smart window that must be maintained according to each orientation of the building was derived.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.38 no.6
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• pp.583-589
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• 2020

Recently, the utility of UAS (Unmanned Aerial System) for a smart farm using various sensors and ICT (Information & Communications Technology) is expected. In particular, it has proven its effectiveness as an outdoor crop monitoring method through various indices and is being studied in various fields. This study analyzes damage to crops caused by natural disasters and measures the damage area of rice plants. To this end, data is acquired using BG-NIR (Blue Green_Near Infrared Red) and RGB sensors, and image analysis and NDWI (Normalized Difference Water Index) index performed to review crop damage caused by in the rainy season. Also, point cloud data based on image analysis is generated, and damage is measured by comparing data before and after the typhoon through an inspection map. As a result of the study, the growth and rainy season damage of rice was examined through NDWI index analysis, and the damage area caused by typhoon was measured by analysis of the inspection map.

• Journal of The Korean Society of Agricultural Engineers
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• v.64 no.2
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• pp.47-55
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• 2022

The objective of this study was to analyze the effect of the duration and time distribution of probability rainfall on farmland inundation for the paddy fields in the drainage improvement project site. In this study, eight drainage improvement project sites were selected for inundation modeling. Hourly rainfall data were collected, and 20- and 30-year frequency probability rainfalls were estimated for 14 different durations. Probability rainfalls were distributed using Intensity-Duration-Frequency (IDF) and Huff time distribution methods. Design floods were calculated for 48 hr and critical duration, and IDF time distribution and Huff time distribution were used for 48 hr duration and critical duration, respectively. Inundation modeling was carried out for each study district using 48 hr and critical duration rainfalls. The result showed that six of the eight districts had a larger flood discharge using the method of applying critical duration and Huff distribution. The results of inundation depth analysis showed similar trends to those of design flood calculations. However, the inundation durations showed different tendencies from the inundation depth. The IDF time distribution is a distribution in which most of the rainfall is concentrated at the beginning of rainfall, and the theoretical background is unclear. It is considered desirable to apply critical duration and Huff time distribution to agricultural production infrastructure design standards in consideration of uniformity with other design standards such as flood calculation standard guidelines.

• The Journal of the Korea institute of electronic communication sciences
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• v.8 no.4
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• pp.595-604
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• 2013

Currently, registered number of imported vehicles is increasing rapidly over the years. Accordingly, environment improvements of vehicle maintenance company for maintenance of luxury vehicle such as imported vehicle are continuously being made. In this paper, we propose a key frame extraction method based on HSV color model for smart vehicle management system implementation to offer for customer reliability of maintenance vehicle. After automatically recognize the license plates of the vehicle using vehicle license plate recognition system when the vehicle come in the car center, we check the repair history and request of the vehicle based on it. We implement mobile services which provide extracted key frame images to the user after extract key frames from vehicle repair video. In addition, we verify the superiority of key frame extraction method by applying a smart vehicle management system. Finally, we convert the RGB color to HSV color to improve the performance of proposed key frame extraction scheme. As a result, we confirmed that our scheme is more excellence about 30% in terms of recall than RGB color model from the performance evaluations.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.40 no.1
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• pp.59-67
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• 2020

In this study, a suitable algorithm for each BRT stop type is presented through the network construction and algorithm design effect analysis through the LISA, a traffic signal program, for the BRT stop type in the BRT Design Guidelines, Ministry of Land, Transport and Maritime Affairs, 2010.6. It was. The phase insert technique is the most effective method for the stop before passing the intersection, the early green technique for the stop after the intersection, and the extend green technique for the mid-block type stop. The extension green technique is used only because it consists of BRT vehicles, general vehicles and pedestrians. Analyzed. After passing through the intersection, the stop was analyzed as 56.4 seconds for the total crossing time and 29.8 seconds for the delay time. In the mid-block type stop, the total travel time of the intersection was 40.5 seconds, the delay time was 9.6 seconds, the average travel time of up and down BRT was 70.2 seconds, the delay time was 14.0 seconds, and the number of passages was 29.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.25 no.4
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• pp.15-31
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• 2022

The Green Purification Unit System (GPUS) is a green infrastructure facility applicable to the roadside to reduce particulate matter from road traffic. This study introduces two types of GPUS (type1 and type2) and assesses the performance and maintenance costs of each of them. The GPUS's performance analysis used the data collected in November 2021 after the installation of the GPUS type1 and type2 at the study site in Suwon. The changes in the particulate matter concentration near the GPUS were measured. The maintenance cost of GPUS type1 and type2 was assessed by calculating the initial installation cost and the management and repair cost after installation. The results of the performance analysis showed that the GPUS type1, which was manufactured by combining plants and electric dust collectors, had a superior particulate matter reduction performance. In particular, type1 produced a greater effect of particulate matter reduction in the time with a high concentration (50㎍/m³ or higher) of particulate matter due to the operation of electric dust collectors. GPUS type2, which was designed in the form of a plant wall without applying an electric dust collector, showed lower reduction performance than type1 but showed sufficiently improved performance compared to the existing band green area. Meanwhile, the GPUS type1 had three times higher costs for the initial installation than GPUS type2. In terms of costs for managing and repairing, it was evaluated that type1 would be slightly more costly than type2. Finally, this study discussed the applicability of two types of GPUS based on the result of the analysis of their particulate matter performance and maintenance cost at the same time. Since GPUS type2 has a cheaper cost than type1, it could be more economical. However, in the area suffering a high concentration of particulate matter, GPUS type1 would be more effective than type2. Therefore, the choice of GPUS types should rely on the status of particulate matter concentration in the area where GPUS is being installed.

• Journal of the Korean Association of Geographic Information Studies
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• v.25 no.4
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• pp.63-80
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• 2022

As a technology to analyze and predict an issue has been developed by constructing real space into virtual space, it is becoming more important to acquire precise spatial information in complex cities. In this study, images were acquired using an unmanned aerial vehicle for urban area with complex landscapes, and land cover classification was performed object-based image analysis and semantic segmentation techniques, which were image classification technique suitable for high-resolution imagery. In addition, based on the imagery collected at the same time, the replicability of land cover classification of each artificial intelligence (AI) model was examined for areas that AI model did not learn. When the AI models are trained on the training site, the land cover classification accuracy is analyzed to be 89.3% for OBIA-RF, 85.0% for OBIA-DNN, and 95.3% for U-Net. When the AI models are applied to the replicability assessment site to evaluate replicability, the accuracy of OBIA-RF decreased by 7%, OBIA-DNN by 2.1% and U-Net by 2.3%. It is found that U-Net, which considers both morphological and spectroscopic characteristics, performs well in land cover classification accuracy and replicability evaluation. As precise spatial information becomes important, the results of this study are expected to contribute to urban environment research as a basic data generation method.