• Journal of The Korean Society of Agricultural Engineers
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• v.62 no.6
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• pp.51-62
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• 2020

The objective of this study was to estimate an optimum ecological flow rate in the Banbyeon stream based on the two representative fish species. Hydraulic stream environment was simulated with HEC-RAS for two water flow regimes and used for the PHABSIM hydraulic simulation. A dominant species of Zacco platypus and an endemic species of Squalidus chankaensis tsuchigae were selected as the representative fishes whose habitat conditions were evaluated for the spawning and adult stages. Weighted usable area (WUA) was estimated based on habitat suitability index (HSI) and PHABSIM habitat simulation. Overall deep water zone in the stream demonstrated greater WUA which implies better habitat status. The estimated WUA for Zacco platypus as the dominant species was about five times greater than Squalidus chankaensis tsuchigae at the stream flow of 12 ㎥/s. The optimum ecological flow rates were 15 ㎥/s and 25 ㎥/s for the respective spawning and adult stages of Zacco platypus, while 5 ㎥/s was estimated for both the life cycles of Squalidus chankaensis tsuchigae. Assuming that the dominant species may survive better in wider flow regimes, the optimum ecological flow rate should be determined rater based on the endemic species and flow rate of 5 ㎥/s was suggested for the Banbyeon stream.

• International Journal of Advanced Culture Technology
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• v.8 no.3
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• pp.269-274
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• 2020

It has used buoy for efficient domestic farm operations and fishermen fish. Buoy uses IoT-based communication to transmit water temperature, salinity, humidity, wind speed, etc. to fishers in real time. In this paper, we utilize LoRa, which enables communication in the marine environment, to construct a network and apply it to an actual buoy for monitoring. The implemented LoRa uses the 900MHz band to configure the network. The sensor consisted of a sensor that can monitor the atmospheric environment and a sensor that can monitor the marine environment. In addition, the information received in real time will be provided to the fishing village host. The fishermen were fully aware of this and took appropriate measures to conduct sea trials.

• Journal of Internet Computing and Services
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• v.24 no.2
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• pp.37-45
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• 2023

In line with the 4th Industrial Revolution, facility maintenance technologies for building smart factories are receiving attention and are being advanced. In addition, technology is being applied to smart farms and smart fisheries following smart factories. Among them, in the case of a recirculating aquaculture system, there is a motor pump that circulates water for a stable quality environment in the tank. Motor pump maintenance activities for recirculating aquaculture system are carried out based on preventive maintenance and data obtained from vibration sensor. Preventive maintenance cannot cope with abnormalities that occur before prior planning, and vibration sensors are affected by the external environment. This paper proposes an anomaly detection algorithm that utilizes ADTK, a Python open source, for motor pump anomaly detection based on data collected through current sensors that are less affected by the external environment than noise, temperature and vibration sensors.

• Smart Media Journal
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• v.5 no.1
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• pp.130-136
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• 2016

In this paper, the real time monitoring system for the abnormal state of marine algae does not detect the plankton which may directly cause the red tide or the water bloom. But checks both oxygen reduction and nitrogen reduction in water, which indicates the characteristics of zooplankton and phytoplankton respectively, and this system makes a module that monitors in real time the temperature and the illumination of the water, which are indirect factors, with sensors placed in and outside the water, and this module transmits signals periodically at specific intervals to a sever that builds up data base, and the data collected in these ways will be analyzed and compared with the standard data from Ministry of Oceans and Fisheries, and then these data will be made the adequate form of information to be provided to the users as visual information, thus, this system intends to make a red tide and water bloom monitoring system tailored for individual fish farm businesses that has local characteristics and can quickly operate outside working hours, which differs from the existing wide area detecting and monitoring systems.

• Smart Media Journal
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• v.12 no.10
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• pp.71-84
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• 2023

Paralichthys olivaceus accounts for a large proportion, accounting for more than half of Korea's aquaculture industry. However, about 25-30% of the total breeding volume throughout the year occurs due to diseases, which has a very bad impact on the economic feasibility of fish farms. For the economic growth of Paralichthys olivaceus farms, it is necessary to quickly and accurately diagnose disease symptoms by automating the diagnosis of Paralichthys olivaceus diseases. In this study, we create training data using innovative data collection methods, refining data algorithms, and techniques for partitioning dataset, and compare the Paralichthys olivaceus disease symptom detection performance of four object detection deep learning models(such as YOLOv8, Swin, Vitdet, MvitV2). The experimental findings indicate that the YOLOv8 model demonstrates superiority in terms of average detection rate (mAP) and Estimated Time of Arrival (ETA). If the performance of the AI model proposed in this study is verified, Paralichthys olivaceus farms can diagnose disease symptoms in real time, and it is expected that the productivity of the farm will be greatly improved by rapid preventive measures according to the diagnosis results.

• Food Science and Industry
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• v.55 no.2
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• pp.188-202
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• 2022

In the insect industry, as the scope of application of insects is expanded from pet insects and natural enemies to feed, edible and medicinal insects, the demand for quality control of insect raw materials is increasing, and interest in securing the safety of insect products is increasing. In the process of expanding the industrial scale, controlling the temperature and humidity and air quality in the insect breeding room and preventing the spread of pathogens and other pollutants are important success factors. It requires a controlled environment under the operating system. European commercial insect breeding facilities have attracted considerable investor interest, and insect companies are building large-scale production facilities, which became possible after the EU approved the use of insect protein as feedstock for fish farming in July 2017. Other fields, such as food and medicine, have also accelerated the application of cutting-edge technology. In the future, the global insect industry will purchase eggs or small larvae from suppliers and a system that focuses on the larval fattening, i.e., production raw material, until the insects mature, and a system that handles the entire production process from egg laying, harvesting, and initial pre-treatment of larvae., increasingly subdivided into large-scale production systems that cover all stages of insect larvae production and further processing steps such as milling, fat removal and protein or fat fractionation. In Korea, research and development of insect smart factory farms using artificial intelligence and ICT is accelerating, so insects can be used as carbon-free materials in secondary industries such as natural plastics or natural molding materials as well as existing feed and food. A Korean-style customized breeding system for shortening the breeding period or enhancing functionality is expected to be developed soon.