• Journal of The Korean Society of Agricultural Engineers
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• v.65 no.2
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• pp.21-33
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• 2023

While the main purpose of irrigation reservoirs is to supply agricultural water, the needs of environmental flow and flood control has been expanded. The agricultural reservoirs have been operated in the form of carry-over system until now. Therefore, the supply of agricultural water is difficult when the storage rate is not sufficiently secured after large volume of irrigation. In addition, there are regulation of the upper storage rate for some large reservoirs during the flood season, but lower storage rate is not regulated. Accordingly, this study aims to evaluate the capacity of agricultural water and environmental flow supply by setting the management lower storage rate of reservoir. The changes in the supply of agricultural and environmental flow was simulated according to the three different regulating lower storage rate scenarios. As a result, it was judged effective in terms of water supply managing the lower storage rate up to 30% when the initial storage rate of farming period is above annual average for the Naju reservoir considering existing water management practice. If the lower storage rate would have been controlled above 30%, the supply of agricultural water might be increased and non-effective discharge amount would be decreased compared to other scenarios during dry period of 2016-2018.

• Journal of People, Plants, and Environment
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• v.23 no.6
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• pp.655-665
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• 2020

Background and objective: This study was conducted to compare the cultivation environment, growth of cut flowers, and management performance of conventional farms and smart farms growing the standard cut chrysanthemum, 'Jinba'. Methods: Conventional and smart farms were selected, and facility information, cultivation environment, cut flower growth, and management performance were investigated. Results: The conventional and smart farms were located in Muan, Jeollanam-do, and conventional farming involved cultivating with soil culture in a plastic greenhouse, while the smart farm was cultivating with hydroponics in a plastic greenhouse. The conventional farm did not have sensors for environmental measurement such as light intensity and temperature and pH and EC sensors for fertigation, and all systems, including roof window, side window, thermal screen, and shading curtain, were operated manually. On the other hand, the smart farm was equipped with sensors for measuring the environment and nutrient solution, and was automatically controlled. The day and night mean temperatures, relative humidity, and solar radiation in the facilities of the conventional and the smart farm were managed similarly. But in the floral differentiation stage, the floral differentiation was delayed, as the night temperature of conventional farm was managed as low as 17.7℃ which was lower than smart farm. Accordingly, the harvest of cut flowers by the conventional farm was delayed to 35 days later than that of the smart farm. Also, soil moisture and EC of the conventional farm were unnecessarily kept higher than those of the smart farm in the early growth stage, and then were maintained relatively low during the period after floral differentiation, when a lot of water and nutrients were required. Therefore, growth of cut flower, cut flower length, number of leaves, flower diameter, and weight were poorer in the conventional farm than in the smart farm. In terms of management performance, yield and sales price were 10% and 38% higher for the smart farm than for the conventional farm, respectively. Also, the net income was 2,298 thousand won more for the smart farm than for the conventional farm. Conclusion: It was suggested that the improved growth of cut flowers and high management performance of the smart farm were due to precise environment management for growth by the automatic control and sensor.

• Smart Media Journal
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• v.11 no.2
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• pp.39-52
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• 2022

In the context of the evolution of automation and intelligence, deep learning and machine learning algorithms have been widely applied in aquaculture in recent years, providing new opportunities for the digital realization of aquaculture. Especially, water quality management deserves attention thanks to its importance to food organisms. In this study, we proposed an end-to-end deep learning-based TabNet model for water quality prediction. From major indexes of water quality assessment, we applied novel deep learning techniques and machine learning algorithms in innovative fish aquaculture to predict the number of water cells counting. Furthermore, the application of deep learning in aquaculture is outlined, and the obtained results are analyzed. The experiment on in-house data showed an optimistic impact on the application of artificial intelligence in aquaculture, helping to reduce costs and time and increase efficiency in the farming process.

• Journal of The Korean Society of Agricultural Engineers
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• v.65 no.1
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• pp.73-81
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• 2023

To understand salinity status of fresh water and paddy soils and the susceptibility of rice to salinity stress of Gunnae reclaimed tidelands, salinity monitoring was conducted in rainy and dry seasons. For fresh water, a high salinity was observed at the sampling location near the sluice gate and decreased with distance from the gate. This spatial pattern of fresh water salinity indicates the necessity of spatial distribution of salinity in the assessment of salinity status of fresh water. Interestingly, there was significant correlation between rainfall amount and salinity, implying that salinity of fresh water varies with rainfall and thus it may be possible to predict salinity of water using rainfall. Soil salinity also higher near the gate, reflecting the influence of high saline water. In addition, the groundwater salinity also high to threat rice growth. Though soil salinity status indicated low possibility of sodium injury, there was changes in soil salinity status during the course of rice growth, suggesting that more intensive monitoring of soil salinity may be necessary for soil salinity assessment. Our study suggests the necessity of intensive salinity monitoring to understand the spatio-temporal variations of salinity of water and soil of reclaimed tideland areas.

• Journal of the Korean Association of Geographic Information Studies
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• v.16 no.1
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• pp.15-25
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• 2013

The RIMGIS(River Information Management GIS) has been developed since 2000 for public service and practical applications of related works after the standardization of national river data such as the river facility register report, river survey map, attached map, and etc. The RIMGIS has been improved in order to respond proactively to change in the information environment. Recently, Smart River-based river information services and related data have become so large as to be overwhelming, making necessary improvements in managing big data. In this study a plan was suggested both to respond to these changes in the information environment and to provide a future Smart River-based river information service by understanding the current state of RIMGIS, improving RIMGIS itself, redesigning the database, developing distribution, and integrating river information systems. Therefore, primary and foreign key, which can distinguish attribute information and entity linkages, were redefined to increase the usability of RIMGIS. Database construction of attribute information and entity relationship diagram have been newly redefined to redesign linkages among tables from the perspective of a river standard database. In addition, this study was undertaken to expand the current supplier-oriented operating system to a demand-oriented operating system by establishing an efficient management of river-related information and a utilization system capable of adapting to the changes of a river management paradigm.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.05a
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• pp.296-299
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• 2022

The rapid urban expansion and the increase in natural disasters due to the increase of population after industrialization and climate change are causing numerous urban management problems. The IP based hyper-connectivity caused by the initiation of the 4th industrial revolution enables a variety of technologies and services that produce vast amounts of data and solve urban management problems based on this. Especially, the quality of life is improved by providing the necessary information for life that are produced through a sensor network on wired and wireless communication. In this study, we intend to propose the method of optimal communcation network composition for innovative and futuristic city management technology through the case of K-water Smart Village Communication System

• Proceedings of the Korea Water Resources Association Conference
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• 2019.05a
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• pp.161-161
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• 2019

Water security issues, stimulated by increasing population and changing climate, are growing and pausing major challenges for water resources managers around the world. Proper utilization, management and distribution of all available water resources is key to sustainable development for achieving water security To alleviate the water shortage, most of the current research on multi-sources combined water supplies depends on an overall generalization of regional water supply systems, which are seldom broken down into the detail required to address specific research objectives. This paper proposes the concept of optimization framework on multi water sources selection. A multi-objective water allocation model with four objective functions is introduced in this paper. Harmony search algorithm is employed to solve the applied model. The objective functions addresses the economic, environmental, and social factors that must be considered for achieving a sustainable water allocation to solve the issue of water security.

• Journal of Information Technology Applications and Management
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• v.25 no.3
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• pp.55-66
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• 2018

Early smart-work of company K was a technology-led way of applying ICT such as smart phones and mobile devices to business. After company K perceived the limitations of ICT-driven smart work, it propelled the work-smart, doing a work smart toward the way that human beings become central and a creative organizational culture is engendered. Company K propelled work-smart strategy in eight categories: simplification of data requirements, establishment efficient meeting culture, streamlining reporting and approval process, simplified document creation, overtime decrease, spreading flexible work system, settlement of healing leave, creating work-smart place. Company K set up an organizational culture secretariat dedicated to work-smart promotion and selected task priorities in consideration of urgency and effectiveness. Owing to such efforts, the company K's work-smart index rose sharply to 72 points this year from 56 points in the previous year. At the organizational culture survey, employees responded that organizational culture improved in all area. For a better future, company K analyzed its work-smart outcomes and planned progressively to improve its work-smart efforts based on employees opinions. This case study will serve as a guideline, for companies to make efforts to going forward to today work-smart beyond yesterday smart-work.

• Journal of The Korean Society of Agricultural Engineers
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• v.65 no.5
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• pp.51-68
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• 2023

Due to the recent integrated water management policy, it is important to identify a reliable supply amount for establishing an agricultural water supply plan. In order to identify the amount of agricultural water supply, it is essential to calculate the discharge by measuring the water level and flow velocity of reservoirs and canal agricultural water, and quality control to ensure reliability must be preceded. Unlike agricultural reservoirs, canal agricultural water are more sensitive to the surrounding environment and reservoir irrigation methods (continuous, intermittent irrigation, etc.), making it difficult to estimate general water level patterns and at the same time a lot of erroneous data. The Korea Rural Community Corporation is applying a filter technique as a quality control method capable of processing large quantities and real-time processing of canal agricultural water level data, and applicability evaluation is needed. In this study, the types of errors generated by the automatic water level measurement system were first determined. In addition, by using the manual quality control data, a technique with high applicability is derived by comparing and analyzing data calibrated with Gaussian, Savitzky-Golay, Hampel, and Median filter techniques, RMSE, and NSE, and the optimal parameters of the technique range was derived. As a result, the applicability of the Median filter was evaluated the highest, and the optimal parameters were derived in the range of 120min to 240min. Through the results of this study, it is judged that it can be used for quantitative evaluation to establish an agricultural water supply plan.

• Proceedings of the Korean Society of Crop Science Conference
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• 2023.04a
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• pp.79-79
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• 2023

With the development of digital technology, the size of the smart agriculture market at home and abroad is rapidly expanding. It is necessary to establish a foundation for sustainable precision agriculture in order to respond to the aging of rural areas and labor shortages. This study was conducted to establish an automated digital agricultural test bed for soybean production management using data suitable for agricultural environmental conditions in Korea and to demonstrate the field of leading complexes. In order to manage water smartly, we installed a subsurface drip irrigation system in the upland field and an underground water level control system in the paddy field. Based on data collected from sensors, water management was controlled by utilizing an integrated control system. Irrigation was carried out when the soil moisture was less than 20%. For effective water management, soil moisture was measured at the surface, 15cm, and 30cm depth. The main growth characteristics and yield, such as stem length, number of branches, and number of nodes of the main stem, were investigated during the main growth period. During the operation of the test bed, drought appeared during the early vegetative growth period and maturity period, but in the open field smart agriculture test bed, water was automatically supplied, reducing labor by 53% and increasing yield by 2%. A test bed was installed for each field digital farming element technology, and it is planned to verify it once more this year. In the future, we plan to expand the field digital farming technology developed for leading farmers to the field.