• Journal of the Korean Society of Industry Convergence
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• v.23 no.2_2
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• pp.351-359
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• 2020

The algae biomass is considered as one of the potential sources of ocean renewable energy because it can be easily mass-produced with abundant sunshine in the vast ocean space. However, the practical use of the biomass has been hindered by the lack of efficient and cost-effective harvesting and maintenance system so far. The algae biomass aquaculture systems are installed in far offshore locations in much larger scales compared to the conventional aquaculture systems so that the automatic seaweed planting and harvesting system needs to operate in heavy sea conditions in far offshore location. In this research, we develop a concept design of a mega-scaled aquaculture system and an automatic seaweed planting and harvesting system, which can operate in heavy seas and mass-produce the algae biomass.

• Electronics and Telecommunications Trends
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• v.36 no.5
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• pp.62-73
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• 2021

A stable protein source is required to support the rapidly increasing global population, and fishery products are a particularly important part of the required protein supply. However, due to continued overfishing, fishery resources are depleted, and the number of fish caught by fishing boats has stagnated. Consequently, the aquaculture industry is becoming increasingly important. Internationally, smart aquaculture technology that minimizes labor and environmental pollution has been established through technological developments supported by large investments in automation and water treatment technology over the last several decades. In the case of Korea, the aquaculture industry has not yet emerged as a labor-intensive primary industry. However, in recent years various attempts have been made to apply ICT technology to aquaculture to overcome these problems. In this study, domestic and foreign technologies and patent trends for smart aquaculture are analyzed. In addition, the current status of the smart aquaculture cluster business that the Ministry of Oceans and Fisheries has been promoting since 2019 to utilize ICT technology in aquaculture is introduced.

• 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 Fisheries and Ocean Technology
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• v.35 no.3
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• pp.328-334
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• 1999

A fish pump makes very important roles in an automation system of an aquaculture farm, thus it has been used widely in order to transfer fishes from one place to the other place automatically. In spite of its significant roles, the efforts for developing performance and promoting efficiency of the fish pump are not sufficient yet. In this paper, a method which makes the fish pump automation system is suggested. Automation of the fish pump can be accomplished by using variable voltage and variable frequency inverter system including induction motors. Especially, very simple logic to generate Pulse width Modulation(PWM) wave to control induction motor efficiently and three steps speed control method to regulate liquid quantity of the fish pump simply are suggested. Owing to the simplifies speed control and PWM wave generation technique, a cheaper microprocessor, 80C196KC, than a digital signal Processor(DSP) can be used to operate control algorithm in induction motor systems for real time control Also, a new idea of remote control for the simplifies novel inverter system by Programmable logic Controller(PLC) without special output unit, digital to analog converter(D/A), is suggested in this paper. Consequently the function of reliability, availability and serviceability of the fish pump system are developed. It will be expected to contribute expanding of application of the fish pump in aquaculture farms because the system can reduce energy consumption and some difficulties according to manual operation prominently.

• Proceedings of the Korea Committee for Ocean Resources and Engineering Conference
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• 2003.05a
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• pp.79-82
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• 2003

An aquaculture system for feeding the caged fishes in the open water is suggested for ocean application. Survival and operation conditions are defined at the conceptual design. Wave and current drag forces are discussed to determine the proper dimension of the aquaculture system and the related mooring system. Second order wave drift force at the survival condition is the dominant force, which be reduced by minimizing the superstructure open to the surface. Automation in feeding, sorting, cleaning is introduced to use the ongoing technology for quality product. The suggested system has advantage compared to onshore culturing, but not to shallow water culturing system. There is room for real application in future by the countries, such as Korea and Japan, which are in short of fish supply and have willingness to venture towards the ocean aquaculture.

• Journal of Internet Computing and Services
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• v.25 no.2
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• pp.49-55
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• 2024

This paper proposes PredFeed Net, a neural network model that mimics the food distribution of fish farming experts. Unlike existing food distribution automation systems, PredFeed Net predicts food distribution by learning the food distribution patterns of experts. This has the advantage of being able to learn using only existing environmental data and food distribution records from food distribution experts, without the need to experiment by changing food distribution variables according to the environment in an actual aquarium. After completing training, PredFeed Net predicts the next food ration based on the current environment or fish condition. Prediction of feed ration is a necessary element for automating feed ration, and feed ration automation contributes to the development of modern fish farming such as smart aquaculture and aquaponics systems.

• Korean Journal of Fisheries and Aquatic Sciences
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• v.55 no.5
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• pp.638-644
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• 2022

The measurement of morphological features is essential in aquaculture, fish industry and the management of fishery resources. The measurement of fish requires a large investment of manpower and time. To save time and labor for fish measurement, automated and reliable measurement methods have been developed. Automation was achieved by applying computer vision and machine learning techniques. Recently, machine learning methods based on deep learning have been used for most automatic fish measurement studies. Here, we review the current status of automatic fish measurement with traditional computer vision methods and deep learning-based methods.

• Journal of the Korean Society of Fisheries and Ocean Technology
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• v.59 no.4
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• pp.328-335
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• 2023

In this paper, among the various facilities used in marine farming, young bivalves of the Mytilus galloprovincialis of marine farming was placed on the deck of the fishing vessel to evaluate the environment conditions and drive shaft movement by rolling affecting the separator for the young bivalves and a clean process. There were a few studies on stress analysis of development facilities because it was difficult to access the fishing site due to the use of imported equipment and the lack of development of domestic equipment. In this study, stress analysis of the fixed part of separator for young bivalves and its adjacent part was performed on various phases when the vessel was tilted by rolling using the finite element method. In addition, the structural safety of the internal blade under the driving conditions according to the movement of the drive shaft by the hydraulic motor was confirmed through structural analysis. As a result, the connection part between the deck and the separator by rolling was confirmed to have higher stress than that of other parts due to stress concentration. In addition, it was confirmed that the maximum stress occurred on the connection part between blades. Even though the safety of the separator for marine farming was confirmed by structural analysis, it is necessary to comprehensively consider the age of vessels, the material of the deck, and the corrosion of the deck.

• Fisheries and Aquatic Sciences
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• v.25 no.3
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• pp.151-157
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• 2022

Various approaches have been applied to transform aquaculture from a manual, labour-intensive industry to one dependent on automation technologies in the era of the fourth industrial revolution. Technologies associated with the monitoring of physical condition have successfully been applied in most aquafarm facilities; however, real-time biological monitoring systems that can observe fish condition and behaviour are still required. In this study, we used a video recorder placed on top of a fish tank to observe the swimming patterns of rock bream (Oplegnathus fasciatus), first one fish alone and then a group of five fish. Rock bream in the video samples were successfully identified using the you-only-look-once v3 algorithm, which is based on the Darknet-53 convolutional neural network. In addition to recordings of swimming behaviour under normal conditions, the swimming patterns of fish under abnormal conditions were recorded on adding an anaesthetic or lowering the salinity. The abnormal conditions led to changes in the velocity of movement (3.8 ± 0.6 cm/s) involving an initial rapid increase in speed (up to 16.5 ± 3.0 cm/s, upon 2-phenoxyethanol treatment) before the fish stopped moving, as well as changing from swimming upright to dying lying on their sides. Machine learning was applied to datasets consisting of normal or abnormal behaviour patterns, to evaluate the fish behaviour. The proposed algorithm showed a high accuracy (98.1%) in discriminating normal and abnormal rock bream behaviour. We conclude that artificial intelligence-based detection of abnormal behaviour can be applied to develop an automatic bio-management system for use in the aquaculture industry.

• Journal of Fisheries and Marine Sciences Education
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• v.12 no.1
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• pp.98-121
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• 2000

The Korean fishery encountered a difficulty situation, due to the new regime of the Exclusive Economic Zone (EEZ) and the decreasing fisheries resources in Korean waters. In addition, the coastal areas are deteriorated by industrial wastes, sewage, farming wastes and pollution from aquaculture. In this situation, it is necessary to study the TAC (total allowable catch) - based management system, the development of fishing gears and appropriate fishing methods for stock conservation, and the automation system of fishing gears for improving the efficiency of fisheries. The objective of this study is to look for an appropriate system in marine production and resource management under the new UNCLOS (United National Convention for the Law of the Sea) regime for subjects in fishing gears and methods, production system, and information, and fisheries resources management. The results of this study could be used as scientific information to maintain and develop the Korean fisheries and to establish fisheries policy for the management of fisheries resources in Korean waters.