• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.10a
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• pp.376-378
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• 2021

According to the 2020 Global Climate Report released by the World Meteorological Organization, the average temperature of the Earth in 2019 was measured 1.1℃ higher on average than the temperature measured between 1850 and 1900 before industrialization. The change in average temperature affects the distribution of plants, and according to the vulnerability analysis paper, it can be seen that there is a change in the distribution area of plants when the average temperature rises. In this paper, to cope with these environmental changes, we propose a method of fabricating intermittent flow hydroponic smart farms using Arduino and sensors and controlling them through PCs and applications. The manufactured hydroponic smart farm identifies the farm's temperature and humidity, positive pH concentration, illumination, and water quality to check the amount of pumping, supplement LED control, sensor condition, overall management and cultivation of the farm, and grows in an appropriate environment.

• Journal of Soil and Groundwater Environment
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• v.26 no.5
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• pp.60-76
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• 2021

The concept of resilience seems applicable for sustainable groundwater management. The resilience is broadly defined as the ability of a system to resist changes by external forces (EFs), and has been used for disaster management and climate change adaptation, including the groundwater resilience to climate change in countries where groundwater is a major water resource, whereas not yet in the geological society of South Korea. The resilience is qualitatively assessed using the absorptive, adaptive, and restorative capacity representing the internal robustness, self-organization, and external recovery resources, respectively, while quantitatively using the system impact (SI) and recovery effort (RE). When the groundwater is considered a complicated system where physicochemical, biological, and geological components interact, the groundwater resilience can be defined as the ability of groundwater to maintain the targeted quality and quantity at any EFs. For the quantitative assessment, however, the resilience should be specified to an EF and measurable parameters should be available for SI and RE. This study focused on groundwater resilience to two EFs in urban areas, i.e., pollution due to land use change and groundwater withdrawal for underground structures. The resilience to each EF was assessed using qualitative components, while measurements for SI and RE were discussed.

• 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 The Korean Society of Agricultural Engineers
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• v.64 no.2
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• pp.71-83
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• 2022

In this study, an indicator and assessment system for evaluating the monthly hydrological cycle was prepared using simple factors such as the landuse status of the watershed and topographic characteristics to the dynamic water balance model (DWBM) based on the Budyko framework. The parameters a1 of DWBM are introduced as hydrologic cycle indicators. An indicator estimation regression model was developed using watershed characteristics data for the introduced indicator, and an assessment system was prepared through K-means cluster analysis. The hydrological cycle assessment system developed in this study can assess the hydrological cycle with simple data such as land use, CN, and watershed slope, so it can quickly assess changes in hydrological cycle factors in the past and present. Because of this advantage is expected that the developed assessment system can predict changes in the hydrological cycle and use an auxiliary tool for policymaking.

• Proceedings of the Korea Water Resources Association Conference
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• 2023.05a
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• pp.77-77
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• 2023

네팔은 6천여 개가 넘는 강이 존재하며 불안정한 기후로 인해 산사태와 홍수가 빈번하게 발생하고 있고, 노후된 상수도 시설 문제도 있어 효과적인 물관리 대책이 필요하다. 이 연구는 네팔 카트만두 인근의 소도시인 둘리켈시를 대상지역으로 하여 스마트 물관리 도입 방안에 대한 타당성 연구조사를 수행하였다. 이를 통해 스마트물관리(SWM) 사업계획을 수립하고, 상수도 관리 기술이 둘리켈시 수돗물 공급 전과정에서 수량·수질을 체계적으로 관리할 수 있도록 계기를 마련하는 것을 목표로 하였다. 주요 연구로 국내 스마트물관리 기술의 네팔 적용성 분석, 수운영 자료및 현황 조사, 스마트 물관리 도입을 위한 수도 시설의 설계 방향을 수립하였고, 기술 도입과 확대 방안을 제시하였다. 스마트 물관리 기술의 적용 타당성 분석을 위하여 현장 조사를 수행하였고, 수리 계측데이터의 분석, 수원지, 정수장, 주요 관로에서의 수질을 분석하였다. 이외에 관망수리해석을 기반으로 대상지역 내 공급가능한 수량을 산정하였고, 상수도 공급이 어려운 지역에 대한 추가시설 확보방안을 제시하였다. 현재 조건에서의 상수도 운영, 관리체계를 분석하여 노후화된 상수도 시설의 개선 및 보완 방안, 스마트 물관리 기술 도입 가능성도 제시하고자 하였다. 연구 결과를 기반으로 기본계획과 실시설계를 통하여 스마트 물관리 인프라가 둘리켈시에 도입될 경우, 물 공급의 불균형으로 인한 피해를 최소화하고, 수돗물의 안정적인 공급 및 수질 안정성 확보, 상수관망에서 수질 및 누수 사고에 대처가 가능할 것으로 보이며 인근 카트만두를 비롯한 지방 소도시에도 스마트 물관리 기술적용에 기틀이 될 것으로 기대된다.

• Proceedings of the Korea Water Resources Association Conference
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• 2023.05a
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• pp.30-30
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• 2023

This study aims to establish the multi-reservoir operation system model in the Upper Mun River Basin which includes 5 main dams namely, Mun Bon (MB), Lamchae (LC), Lam Takhong (LTK), Lam Phraphoeng (LPP), and Lower Lam Chiengkrai (LLCK) Dams. The knowledge and AI technology were applied aiming to develop innovative prototype for SMART dam-reservoir operation in future. Two different sorts of reservoir operation system model namely, Fuzzy Logic (FL) and Constraint Programming (CP) as well as the development of rainfall and reservoir inflow prediction models using Machine Learning (ML) technique were made to help specify the right amount of daily reservoir releases for the Royal Irrigation Department (RID). The model could also provide the essential information particularly for the Office of National Water Resource of Thailand (ONWR) to determine the short-term and long-term water resource management plan and strengthen water security against flood and drought in this region. The simulated results of base case scenario for reservoir operation in the Upper Mun from 2008 to 2021 indicated that in the same circumstances, FL and CP models could specify the new release schemes to increase the reservoir water storages at the beginning of dry season of approximately 125.25 and 142.20 MCM per year. This means that supplying the agricultural water to farmers in dry season could be well managed. In other words, water scarcity problem could substantially be moderated at some extent in case of incapability to control the expansion of cultivated area size properly. Moreover, using AI technology to determine the new reservoir release schemes plays important role in reducing the actual volume of water shortfall in the basin although the drought situation at LTK and LLCK Dams were still existed in some periods of time. Meanwhile, considering the predicted inflow and hydrologic factors downstream of 5 main dams by FL model and minimizing the flood volume by CP model could ensure that flood risk was considerably minimized as a result of new release schemes.

• Journal of Internet Computing and Services
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• v.24 no.1
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• pp.61-69
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• 2023

Recently, as the fishery resources are depleted, expectations for productivity improvement by 'rearing fishery' in land farms are greatly rising. In the case of land farms, unlike ocean environments, it is easy to control and manage environmental and breeding factors, and has the advantage of being able to adjust production according to the production plan. On the other hand, unlike in the natural environment, there is a disadvantage in that operation costs may significantly increase due to the artificial management for fish growth. Therefore, profit maximization can be pursued by efficiently operating the farm in accordance with the planned target shipment. In order to operate such an efficient farm and nurture fish, an accurate growth prediction model according to the target fish species is absolutely required. Most of the growth prediction models are mainly numerical results based on statistical analysis using farm data. In this paper, we present a growth prediction model from a stochastic point of view to overcome the difficulties in securing data and the difficulty in providing quantitative expected values for inaccuracies that existing growth prediction models from a statistical point of view may have. For a stochastic approach, modeling is performed by introducing a Gaussian process regression method based on water temperature, which is the most important factor in positive growth. From the corresponding results, it is expected that it will be able to provide reference values for more efficient farm operation by simultaneously providing the average value of the predicted growth value at a specific point in time and the confidence interval for that value.

• Journal of Korea Water Resources Association
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• v.55 no.8
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• pp.589-601
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• 2022

Although drought is a natural phenomenon, its damage occurs in combination with regional physical and social factors. Especially, related to the supply and demand of various waters, drought causes great socio-economic damage. Even meteorological droughts occur with similar severity, its impact varies depending on the regional characteristics and water supply system. Therefore, this study assessed regional drought risk considering regional socio-economic factors and water supply system. Drought hazard was assessed by grading the joint drought management index (JDMI) which represents water shortage. Drought vulnerability was assessed by weighted averaging 10 socio-economic factors using Entropy, Principal Component Analysis (PCA), and Gaussian Mixture Model (GMM). Drought response capacity that represents regional water supply factors was assessed by employing Bayesian networks. Drought risk was determined by multiplying a cubic root of the hazard, vulnerability, and response capacity. For the drought hazard meaning the possibility of failure to supply water, Goesan-gun was the highest at 0.81. For the drought vulnerability, Daejeon was most vulnerable at 0.61. Considering the regional water supply system, Sejong had the lowest drought response capacity. Finally, the drought risk was the highest in Cheongju-si. This study identified the regional drought risk and vulnerable causes of drought, which is useful in preparing drought mitigation policy considering the regional characteristics in the future.

• Journal of Korea Water Resources Association
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• v.56 no.10
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• pp.619-629
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• 2023

Recent intensification of climate change has led to an increase in damages caused by droughts. Currently, in Korea, the Standardized Precipitation Index (SPI) is used as a criterion to classify the intensity of droughts. Based on the accumulated precipitation over the past six months (SPI-6), meteorological drought intensities are classified into four categories: concern, caution, alert, and severe. However, there is a limitation in classifying drought intensity solely based on precipitation. To overcome the limitations of the meteorological drought warning criteria based on SPI, this study collected emergency water supply damage data from the National Drought Information Portal (NDIP) to classify drought intensity. Factors of SPI, such as precipitation, and factors used to calculate evapotranspiration, such as temperature and humidity, were indexed using min-max normalization. Coefficients for each factor were determined based on the Genetic Algorithm (GA). The drought intensity based on emergency water supply was used as the dependent variable, and the coefficients of each meteorological factor determined by GA were used as coefficients to derive a new Drought Severity Classification Index (DSCI). After deriving the DSCI, cumulative distribution functions were used to present intensity stage classification boundaries. It is anticipated that using the proposed DSCI in this study will allow for more accurate drought intensity classification than the traditional SPI, supporting decision-making for disaster management personnel.

• Journal of the Korea Convergence Society
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• v.6 no.1
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• pp.29-34
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• 2015

As smart grid techniques developed, public attention is concentrating on energy efficiency. So it is necessary to study on new renewable energy in order to manage the energy within micro grid consisting smart grid. Among them, small hydro energy has the advantage of being installable anywhere depending the amount of water used by the users within micro grid. This study examines if the measured value is appropriate for small hydro power generation by measuring generation quantity and operation rate of generator based on the sewage flow used by apartments and multi-unit dwellings where those users live. Some appropriate apartments and multi-unit dwellings generate electricity with small hydro generator using sewage as potential energy. This study intends to suggest more effective management by introducing energy management system and electricity storage device of micro grid.