• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.38 no.6
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• pp.511-519
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• 2020

For camera calibration, a checkerboard is generally used to determine the principal point, focal length, and lens distortions. The checkerboard has a planar and three-dimensional shape, and camera calibration parameters are affected by the size of the checkerboard, the placement of the target, and the number of target points. In this study, the accuracies of the types of checkerboards were compared using checkpoints for stereo camera calibration, and the purpose of this study was to propose the best performance checkerboard. The checkerboard with large flat shape showed comparatively high accuracy through comparison with the check points. However, due to the size of the checkerboard, it was inconvenient to move and rotate, and there was a disadvantage in that it was difficult to shoot so that the target points could all appear in the stereo camera. The checkerboard, which was manufactured in a small size in a flat shape, was easy to move and rotate but had the lowest three-dimensional accuracy. The checkerboard with targets with height values had the hassle of having to determine the three-dimensional coordinates of the target points by using observation equipment for camera calibration, but it was small in size, convenient to move and rotate, and showed the highest three-dimensional accuracy.

• Tunnel and Underground Space
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• v.33 no.4
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• pp.209-227
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• 2023

The government continues to announce measures to revitalize smart construction technology based on BIM for productivity innovation in the construction industry. In the design phase, the goal is design automation and optimization by converging BIM Data and other advanced technologies. Accordingly, in the basic design of the Namhae Seomyeon-Yeosu Sindeok National Road Construction Project, a domestic undersea tunnel project, BIM-based design was carried out by developing tunnel design automation technology using 3D spatial information according to the tunnel design process. In order to derive the optimal alignment, more than 10,000 alignment cases were generated in 36hr using the generative design technique and a quantitative evaluation of the objective functions defined by the designer was performed. AI-based ground classification and 3D Geo Model were established to evaluate the economic feasibility and stability of the optimal alignment. AI-based ground classification has improved its precision by performing about 30 types of ground classification per borehole, and in the case of the 3D Geo Model, its utilization can be expected in that it can accumulate ground data added during construction. In the case of 3D blasting design, the optimal charge weight was derived in 5 minutes by reviewing all security objects on the project range on Dynamo, and the design result was visualized in 3D space for intuitive and convenient construction management so that it could be used directly during construction.

• Smart Media Journal
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• v.12 no.10
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• pp.93-101
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• 2023

Climate change has emerged as a global problem, with frequent temperature increases, droughts, and floods, and it is predicted that it will have a great impact on the characteristics and productivity of crops. Cnidium officinale is used not only as traditionally used herbal medicines, but also as various industrial raw materials such as health functional foods, natural medicines, and living materials, but productivity is decreasing due to threats such as continuous crop damage and climate change. Therefore, this paper proposes a model that can predict the physiologically active ingredient index according to the climate change scenario of Cnidium officinale, a representative medicinal crop vulnerable to climate change. In this paper, data was first augmented using the CTGAN algorithm to solve the problem of data imbalance in the collection of environment information, physiological reactions, and physiological active ingredient information. Column Shape and Column Pair Trends were used to measure augmented data quality, and overall quality of 88% was achieved on average. In addition, five models RF, SVR, XGBoost, AdaBoost, and LightBGM were used to predict phenol and flavonoid content by dividing them into ground and underground using augmented data. As a result of model evaluation, the XGBoost model showed the best performance in predicting the physiological active ingredients of the sacrum, and it was confirmed to be about twice as accurate as the SVR model.

• Smart Media Journal
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• v.12 no.11
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• pp.185-197
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• 2023

This study was conducted using text mining and network theory to extract useful information for application for occupancy and performance of permit tasks contained in the permit contents from the permit register, which is used only for the simple purpose of recording occupancy permit information. Based on text mining, we analyzed and compared the frequency of vocabulary occurrence and topic modeling in five regions, including Seoul, Gyeonggi, Gyeongsang, Jeolla, Chungcheong, and Gangwon, as well as normalization processes such as stopword removal and morpheme analysis. By applying four types of centrality algorithms, including stage, proximity, mediation, and eigenvector, which are widely used in network theory, we looked at keywords that are in a central position or act as an intermediary in the network. Through a comprehensive analysis of vocabulary appearance frequency, topic modeling, and network centrality, it was found that the 'installation' keyword was the most influential in all regions. This is believed to be the result of the Ministry of Environment's permit management office issuing many permits for constructing facilities or installing structures. In addition, it was found that keywords related to road facilities, flood control facilities, underground facilities, power/communication facilities, sports/park facilities, etc. were at a central position or played a role as an intermediary in topic modeling and networks. Most of the keywords appeared to have a Zipf's law statistical distribution with low frequency of occurrence and low distribution ratio.

• Journal of Korean Tunnelling and Underground Space Association
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• v.19 no.1
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• pp.95-107
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• 2017

In this study, a preliminary study was undertaken for development of a tunnel incident automatic detection system based on a machine learning algorithm which is to detect a number of incidents taking place in tunnel in real time and also to be able to identify the type of incident. Two road sites where CCTVs are operating have been selected and a part of CCTV images are treated to produce sets of training data. The data sets are composed of position and time information of moving objects on CCTV screen which are extracted by initially detecting and tracking of incoming objects into CCTV screen by using a conventional image processing technique available in this study. And the data sets are matched with 6 categories of events such as lane change, stoping, etc which are also involved in the training data sets. The training data are learnt by a resilience neural network where two hidden layers are applied and 9 architectural models are set up for parametric studies, from which the architectural model, 300(first hidden layer)-150(second hidden layer) is found to be optimum in highest accuracy with respect to training data as well as testing data not used for training. From this study, it was shown that the highly variable and complex traffic and incident features could be well identified without any definition of feature regulation by using a concept of machine learning. In addition, detection capability and accuracy of the machine learning based system will be automatically enhanced as much as big data of CCTV images in tunnel becomes rich.

• Journal of the Korean GEO-environmental Society
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• v.19 no.10
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• pp.13-19
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• 2018

Following the 2016 Gyeongju earthquake, the Pohang Earthquake occurred in 2017, and the south-east region in Korea is under the threat of an earthquake. Especially, in the Pohang Earthquake, the liquefaction phenomenon occurred in the sedimentation area of the coast, and preparation of countermeasures is very important. The soil liquefaction can affect the underground facilities directly as well as various structures on the ground. Therefore, it is necessary to identify the liquefaction risk of facilities and the structures against the possible earthquakes and to prepare countermeasures to minimize them. In this study, we investigated the seismic liquefaction risk about the electric power utility tunnels in the southeast area where the earthquake occurred in Korea recently. In the analysis of seismic liquefaction risk, the earthquake with return period 1000 years and liquefaction potential index are used. The liquefaction risk analysis was conducted in two stages. In the first stage, the liquefaction risk was analyzed by calculating the liquefaction potential index using the ground survey data of the location of electric power utility tunnels in the southeast region. At that time, the seismic amplification in soil layer was considered by soil amplification factor according to the soil classification. In the second stage, the liquefaction risk analysis based on the site response analyses inputted 3 earthquake records were performed for the locations determined to be dangerous from the first step analysis, and the final liquefaction potential index was recalculated. In the analysis, the site investigation data were used from the National Geotechnical Information DB Center. Finally, it can be found that the proposed two stage assessments for liquefaction risk that the macro assessment of liquefaction risk for the underground facilities including the electric power utility tunnel in Korea is carried out at the first stage, and the second risk assessment is performed again with site response analysis for the dangerous regions of the first stage assessment is reasonable and effective.

• Journal of Korean Tunnelling and Underground Space Association
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• v.20 no.6
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• pp.899-915
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• 2018

In this study, in order to construct an eco-friendly advanced road transportation network, the multi-layer tunnel, which is a small-sized car road, is designed to have a height of less than 60 cm. However, the shape of the tunnel is low and the height of the traffic sign is small. In order to solve these problems, traffic sign characters were designed in three dimensions, and the possibility of applying the design of the three - dimensional sign that can obtain greater visibility than the existing signs at the same distance and the possibility verification through virtual simulation were performed. The three-dimensional sign is horizontally installed on the ceiling of the multi-layer tunnel. To be seen vertically, it is enlarged by a certain ratio by the perspective, and the width and height are enlarged. Respectively. In addition, 3D simulation was performed to verify the visibility of the stereoscopic signs when the driver ran through the stereoscopic sign design specifications. As a result of the design and experimental study, it was confirmed that the stereoscopic sign could be designed through the theoretical formula and that it could provide the driver with a larger traffic sign character because there is no limitation of the facility limit compared to the existing vertical traffic sign. Also, we confirmed that it can be implemented in the side wall by using the stereoscopic sign design principle installed on the ceiling part. It was confirmed that the design of the stereoscopic sign can be designed to be smaller as the distance that the driver visually recognizes the sperm is shorter, the height of the protrusion vertically at the lower part of the stereoscopic sign becomes higher. As a result of 3D simulation running experiment based on the design information of the stereoscopic sign, it was confirmed that the stereoscopic sign is visually the same as the vertical sign at the planned distance. Although the detailed research and institutional improvement of stereoscopic signs have not been made in Korea and abroad, it is evolved into a core technology of new road traffic facilities through various studies through the possibility of designing and applying stereoscopic signs developed through this study Expect.

• Journal of Korean Tunnelling and Underground Space Association
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• v.23 no.6
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• pp.469-484
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• 2021

Rock mass classification results have a great influence on construction schedule and budget as well as tunnel stability in tunnel design. A total of 3,526 tunnels have been constructed in Korea and the associated techniques in tunnel design and construction have been continuously developed, however, not many studies have been performed on how to assess rock mass quality and grade more accurately. Thus, numerous cases show big differences in the results according to inspectors' experience and judgement. Hence, this study aims to suggest a more reliable rock mass classification (RMR) model using machine learning algorithms, which is surging in availability, through the analyses based on various rock and rock mass information collected from boring investigations. For this, 11 learning parameters (depth, rock type, RQD, electrical resistivity, UCS, V_p, V_s, Young's modulus, unit weight, Poisson's ratio, RMR) from 13 local tunnel cases were selected, 337 learning data sets as well as 60 test data sets were prepared, and 6 machine learning algorithms (DT, SVM, ANN, PCA & ANN, RF, XGBoost) were tested for various hyperparameters for each algorithm. The results show that the mean absolute errors in RMR value from five algorithms except Decision Tree were less than 8 and a Support Vector Machine model is the best model. The applicability of the model, established through this study, was confirmed and this prediction model can be applied for more reliable rock mass classification when additional various data is continuously cumulated.

• Proceedings of the Korean Society of Crop Science Conference
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• 2023.04a
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• pp.7-7
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• 2023

Currently, the main technologies of various fourth industries are big data, the Internet of Things, artificial intelligence, blockchain, mixed reality (MR), and drones. In particular, "digital twin," which has recently become a global technological trend, is a concept of a virtual model that is expressed equally in physical objects and computers. By creating and simulating a Digital twin of software-virtualized assets instead of real physical assets, accurate information about the characteristics of real farming (current state, agricultural productivity, agricultural work scenarios, etc.) can be obtained. This study aims to streamline agricultural work through automatic water management, remote growth forecasting, drone control, and pest forecasting through the operation of an integrated control system by constructing digital twin data on the main production area of the nojinot industry and designing and building a smart farm complex. In addition, it aims to distribute digital environmental control agriculture in Korea that can reduce labor and improve crop productivity by minimizing environmental load through the use of appropriate amounts of fertilizers and pesticides through big data analysis. These open-field agricultural technologies can reduce labor through digital farming and cultivation management, optimize water use and prevent soil pollution in preparation for climate change, and quantitative growth management of open-field crops by securing digital data for the national cultivation environment. It is also a way to directly implement carbon-neutral RED++ activities by improving agricultural productivity. The analysis and prediction of growth status through the acquisition of the acquired high-precision and high-definition image-based crop growth data are very effective in digital farming work management. The Southern Crop Department of the National Institute of Food Science conducted research and development on various types of open-field agricultural smart farms such as underground point and underground drainage. In particular, from this year, commercialization is underway in earnest through the establishment of smart farm facilities and technology distribution for agricultural technology complexes across the country. In this study, we would like to describe the case of establishing the agricultural field that combines digital twin technology and open-field agricultural smart farm technology and future utilization plans.

• Journal of Korean Society for Geospatial Information Science
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• v.22 no.3
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• pp.57-69
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• 2014

As of 2013, Korean population density is 505 persons per $1km^2$ and is ranked 3rd place in the most densely populated countries exception of city-states. It shows clearly the population is concentrated in the city area. To fulfil this urban concentration population demand, the enlargement and complexation of buildings, subway and other underground spaces connection tendency has been intensified, and it is need to construct the indoor spatial information DB as well as the accurate indoor surveying DB to promote people's safety and social welfare. In this study, Sadang station and Incheon National Airport were aimed for the construction of Wi-Fi AP location DB and RadioMap DB by collecting the indoor AP raw datas by using mobile device and those collected results were ran through the process of verification, supplementation, and analyzation. To evaluate the performance of constructed DB, 10 points in Incheon Airport- 3rd flr in block A, and 9 points in Sadang station-B1 were selected and calculated the estimated points and ran evaluation experiment using survey positioning error, which is distance between real position and the estimated position. The result shows that Incheon international airport's average and standard deviation was separately 17.81m, 17.79m and Sadang station's average and standard deviation was separately 22.64m, 23.74m. In Sadang station's case, the areas near the exit has low performance of surveying position due to fewer visible AP points than other areas. As total datas were examined except those position, it was verified that the user's location was mapping close position in surveying positioning by using constructed DB. It means that constructed DB contains correct Wi-Fi AP locations and radio wave patterns in object region, so it is considered that the indoor spatial information service based on constructed DB would be available.