• The Journal of Fisheries Business Administration
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• v.46 no.2
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• pp.43-57
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• 2015

The study aims to identify the current status of aquaculture information in Korea and suggests policy directions for its integrated management. Firstly, the study focuses on the identification of the current status of aquaculture information by reviewing how aquaculture information is managed. Secondly, this study identifies problems such as lacks in necessary aquaculture information, inefficiency caused by dispersion and overlapping of information, absence of integrated management system and insufficient sharing of information. After identifying the current status of aquaculture information and its problems, the study suggests three basic directions to systematically integrate and manage the information such as establishment of infrastructure for promoting the integrated management of aquaculture information, generation and systematic management of useful aquaculture information and enhancement of user convenience. Finally, the study suggests detailed strategies such as establishment of a foundation to facilitate integrated management of aquaculture information, organization of organic network, sharing of more information, creation of necessary information through demand survey, creation of systematic management system, provision of a customized total service, and increase in education and PR activities on information use.

• Proceedings of the Korean Association of Geographic Inforamtion Studies Conference
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• 2004.03a
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• pp.493-498
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• 2004

The objective of the present study is to compare various conventional and recently evolved satellite image-processing techniques and to ascertain the best possible technique that can identify and position of aquaculture farms accurately in and around the Younggwang coastal area. Several conventional techniques performed to extract such information fiom the Landsat-TM imagery do not seem to yield better information about the aquaculture farms, and lead to misclassification. The large errors between the actual and extracted aquaculture farm information are due to existence of spectral confusion and inadequate spatial resolution of the sensor. This leads to possible occurrence of mixture pixels or 'mixels' of the source of errors in the classification techniques. Understanding the confusing and mixture pixel problems requires the development of efficient methods that can enable more reliable extraction of aquaculture farm information. Thus, the more recently evolved methods such as the step-by-step partial spectral end-member extraction and linear spectral unmixing methods are introduced. The farmer one assumes that an end-member, which is often referred to as 'spectrally pure signature' of a target feature, does not appear to be a spectrally pure form, but always mix with the other features at certain proportions. The assumption of the linear spectral unmxing is that the measured reflectance of a pixel is the linear sum of the reflectance of the mixture components that make up that pixel. The classification accuracy of the step-by-step partial end-member extraction improved significantly compared to that obtained from the traditional supervised classifiers. However, this method did not distinguish the aquaculture ponds and non-aquaculture ponds within the region of the aquaculture farming areas. In contrast, the linear spectral unmixing model produced a set of fraction images for the aquaculture, water and soil. Of these, the aquaculture fraction yields good estimates about the proportion of the aquaculture farm in each pixel. The acquired proportion was compared with the values of NDVI and both are positively correlated (R$^2$ =0.91), indicating the reliability of the sub-pixel classification.ixel classification.

• Journal of Internet Computing and Services
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• v.24 no.4
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• pp.93-105
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• 2023

In order to transform the traditional aquaculture industry, which is dependent on experience, labor-intensive and natural environment, into future intelligent smart aquaculture, digital aquaculture improves aquaculture reproducibility and efficiency of production process through digitization of the aquaculture industry based on ICT equipments, Data analysis and utilization for promoted to increase the acceptability of aquaculturist. Europe's advanced fisheries countries have achieved rapid growth not only in aquaculture technology but also in the aquaculture equipment industry through digitization that combines information and communication technology with aquaculture farms. However, it is not possible to collect aquacultural data in Korea because it has not secured a Korean aquaculture industry for multi-variety, small-scale production and aquaculturists' refusal of reception for digital transformation. Therefore, this study intends to suggest the development direction of digital aquaculture to convert to intelligent smart aquaculture in the future by analyzing trends and critical technology.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.11
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• pp.3083-3098
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• 2023

As demands for efficient and echo-friendly production of marine products increase, smart aquaculture based on information and communication technology (ICT) has become a promising trend. The smart aquaculture is expected to control fundamental farm environment variables including water temperature and dissolved oxygen (DO) levels with less human intervention. A recirculating aquaculture system (RAS) is required for the smart aquaculture which utilizes a purification tank to reuse water drained from the water tank while blocking the external environment. Elaborate water treatment should be considered to properly operate RAS. However, analyzing the water treatment performance is a challenging issue because fish farm circumstance continuously changes and recursively affects water fluidity. To handle this issue, we introduce computational fluid dynamics (CFD) aided water treatment analysis including water fluidity and the solid particles removal efficiency. We adopt RAS parameters widely used in the real aquaculture field to better reflect the real situation. The simulation results provide several indicators for users to check performance metrics when planning to select appropriate RAS without actually using it which costs a lot to operate.

• Korean Journal of Fisheries and Aquatic Sciences
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• v.56 no.6
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• pp.759-765
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• 2023

Owing to the increase in the elderly population at aquaculture farm and decrease in the number of aquaculture farmers, the need to improve aquaculture production system is increasing. In addition, asvirtual interactions become new normal after COVID-19 pandemic, the speed at which science and technology such as the internet of things (IoT), information and communications technology (ICT), and artificial intelligence (AI) are applied to each field is accelerating. Efforts are being made to enhance the quality of life of aquaculture farmer and competitiveness of the aquaculture industry by incorporating digital technology. This study analyzed national and global aquaculture technology development and policy trends, smart aquaculture terminology application scenarios, and prior research cases to propose smart aquaculture industrialization models and technology development directions considering technology, economy, and environment. This study can also provide valuable reference for promoting smart and efficient development of aquaculture.

• Journal of Environmental Impact Assessment
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• v.14 no.3
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• pp.127-134
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• 2005

Recently, aquaculture farm sites have been increased with demand of the expensive fish species and sea food like as seaweed, laver and oyster. Therefore coastal water quality have been deteriorated by organic contamination from marine aquaculture farm sites. For protecting of coastal environment, we need to control the location of aquaculture sites. The purpose of this study is to detect the laver aquaculture sites using multispectral remotely sensed data with autodetection algorithm. In order to detect the aquaculture sites, density slice and contour and vegetation index methods were applied with SPOT and IKONOS data of Shinan area. The marine aquaculture farm sites were extracted by density slice and contour methods with one band digital number(DN) carrying 65% accuracy. However, vegetation index algorithm carried out 75% accuracy using near-infra red and red bands. Extraction of the laver aquaculture site using remotely sensed data will provide the efficient digital map for coastal water management strategies and red tide GIS management system.

• Journal of the Korean Association of Geographic Information Studies
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• v.19 no.4
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• pp.63-75
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• 2016

Aquaculture has historically delivered marine products because the country is surrounded by ocean on three sides. Surveys on production have been conducted recently to systematically manage aquaculture facilities. Based on survey results, pricing controls on marine products has been implemented to stabilize local fishery resources and to ensure minimum income for fishermen. Such surveys on aquaculture facilities depend on manual digitization of aerial photographs each year. These surveys that incorporate manual digitization using high-resolution aerial photographs can accurately evaluate aquaculture with the knowledge of experts, who are aware of each aquaculture facility's characteristics and deployment of those facilities. However, using aerial photographs has monetary and time limitations for monitoring aquaculture resources with different life cycles, and also requires a number of experts. Therefore, in this study, we investigated an automatic prototype system for detecting boundary information and monitoring aquaculture facilities based on satellite images. KOMPSAT-3 (13 Scene), a local high-resolution satellite provided the satellite imagery collected between October and April, a time period in which many aquaculture facilities were operating. The ANN classification method was used for automatic detecting such as cage, longline and buoy type. Furthermore, shape files were generated using a digitizing image processing method that incorporates polygon generation techniques. In this study, our newly developed prototype method detected aquaculture facilities at a rate of 93%. The suggested method overcomes the limits of existing monitoring method using aerial photographs, but also assists experts in detecting aquaculture facilities. Aquaculture facility detection systems must be developed in the future through application of image processing techniques and classification of aquaculture facilities. Such systems will assist in related decision-making through aquaculture facility monitoring.

• Proceedings of the Korean Society of Fisheries Technology Conference
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• 2003.05a
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• pp.223-224
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• 2003

Information on the fate of the added nutrients is essential for the assessment of the food utilization, pond fertility, water quality and processes in the sediment (Boyd, 1985). Also, they are useful for qualifying environmental impacts of aquaculture and for environmental management. The purpose of this experiment was to assess the fate of nitrogen and organic matter entering aquaculture ponds and the relative importance of the different resources. (omitted)

• Journal of Fisheries and Marine Sciences Education
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• v.20 no.1
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• pp.23-35
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• 2008

The purposes of this study are to analyze problems in industrial classification of fisheries in Korea and to suggest future directions. Based on a thorough review of relevant literature, the study proposes a five-level scheme for classifying fisheries. The highest level should be the fisheries industry, and the next highest level ought to be fisheries. The medium level should include fishing, aquaculture, and fishery service industries. At the fourth level, fishing is to be further divided into sea fishery and inland fishery, aquaculture into sea-surface aquaculture and inland aquaculture, and fishery service industries into integrated fishery service and fishery distribution service. The lowest level is the most detailed. At this level, sea fishery is split into deep sea fishery, offshore fishery, and coastal fishery; sea-surface aquaculture consists of sea aquaculture, seed production aquaculture, and food organism aquaculture; integrated fishery service is further classified into fishery-related service and fishery information service.

• Proceedings of the Korea Information Processing Society Conference
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• 2018.10a
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• pp.350-352
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• 2018

In this paper, we propose a smart indoor garden aquaculture system using PIC. In the proposed smart indoor garden aquaculture system, the aquaphonics system circulates the nutrient solution of the aquarium, the filtrate tank, and the flowerpot. The automated control system that controls the state of the nutrient solution through the various sensors and controls the pump and valve is designed. As a result of the verification of the smart indoor garden aquaculture system proposed in this paper, it was confirmed that the environment suitable for the survival of fish and plants was maintained by monitoring water temperature, DO, pH measured in real time. The water level in aquarium and flower pot was controlled through automatic operation of the Electric vale and pump.