• Journal of Korea Multimedia Society
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• v.12 no.1
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• pp.130-138
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• 2009

As time spent in front of the computer screens increases, an increasing number of people are using natural landscapes or virtual aquariums as their desktop and screen saver that can provide them with mental comfort. A virtual aquarium is constructed by an animation work that creates a variety of fish that freely move in a random virtual underwater environment to analyze their movement. This paper suggests a method that constructs an immersive virtual aquarium, using fluid animation method that expresses changes of shape of fluid in real time and the Smart Fish technology which is capable of an interaction according to the diverse characteristics of virtual fish. The suggested method can be used in a virtual aquarium, aquarium screen saver, virtual fish-raising game, etc., which express diverse undersea environment.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.8
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• pp.2259-2277
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• 2023

We propose a probabilistic fish growth model for smart aquaculture systems equipped with IoT sensors that monitor the ecological environment. As IoT sensors permeate into smart aquaculture systems, environmental data such as oxygen level and temperature are collected frequently and automatically. However, there still exists data on fish weight, tank allocation, and other factors that are collected less frequently and manually by human workers due to technological limitations. Unlike sensor data, human-collected data are hard to obtain and are prone to poor quality due to missing data and reading errors. In a situation where different types of data are mixed, it becomes challenging to develop an effective fish growth model. This study explores the unique characteristics of such a combined environmental and weight dataset. To address these characteristics, we develop a preprocessing method and a probabilistic fish growth model using mixed data sampling (MIDAS) and overlapping mixtures of Gaussian processes (OMGP). We modify the OMGP to be applicable to prediction by setting a proper prior distribution that utilizes the characteristic that the ratio of fish groups does not significantly change as they grow. We conduct a numerical study using the eel dataset collected from a real smart aquaculture system, which reveals the promising performance of our model.

• KIPS Transactions on Computer and Communication Systems
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• v.9 no.7
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• pp.157-164
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• 2020

As the consumption of fishery products continues to increase, aquaculture industry has emerged instead of fishing industry facing limitations of fish stock resources. Recently, smart fish farming industry has rapidly developed through convergence with 4th Industrial Revolution technology. Accordingly, it is important to derive a future model of smart fish farming platforms in order to secure the superiority of the aquaculture industry and the technology standard hegemony. In this study, the future direction of smart fish farm platform was derived through the analysis of environment related to politics, economy, society, and technology related to smart fish farming by applying PEST methodology of macro-environment analysis. It is expected that it will help the public and industrial circles in planning and implementing related projects by including the entire process of value chain of aquaculture industry of breeding, production, management and distribution, and by presenting advanced models based on artificial intelligence and digital twin.

• IEMEK Journal of Embedded Systems and Applications
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• v.17 no.3
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• pp.177-183
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• 2022

To measure the size and weight of the fish, we developed an automatic fish size measurement system using a deep neural network, where the YOLO (You Only Look Once)v3 model was used. To detect fish, an IP camera with infrared function was installed over the fish pool to acquire image data and used as input data for the deep neural network. Using the bounding box information generated as a result of detecting the fish and the structure for which the actual length is known, the size of the fish can be obtained. A GUI (Graphical User Interface) program was implemented using LabVIEW and RTSP (Real-Time Streaming protocol). The automatic fish size measurement system shows the results and stores them in a database for future work.

• IEMEK Journal of Embedded Systems and Applications
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• v.16 no.6
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• pp.299-305
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• 2021

Dissolved oxygen, pH, and temperature are the most important factors for fish farming because they affect fish growth and mass mortality of the fish. Therefore, fish farm workers must always check all pools on the farm, but this is very difficult in reality. That's why we developed a control system for smart fish farms. This system includes a gateway, sensor gatherers, and a PC program using LabVIEW. One sensor gatherer can cover up to four pools. The sensor gatherers are connected to the gateway in the form of a bus. For the gateway, the ATmega2560 is used as the main processor for communication and the STM32F429 is used as a sub-processor for displaying LCD. For the sensor gatherer, ATmega2560 is used as the main processor for communication. MQTT (Message Queuing Telemetry Transport), RS-485, and Zigbee are used as the communication protocols in the control system. The users can control the temperature and the dissolved oxygen using the PC program. The commands are transferred from the PC program to the gateway through the MQTT protocol. When the gateway gets the commands, it transfers the commands to the appropriate sensor gatherer through RS-485 and Zigbee.

• Smart Structures and Systems
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• v.8 no.1
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• pp.107-117
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• 2011

Biological sensory systems continuously monitor and analyze changes in real-world environments that are relevant to an animal's specific behavioral needs and goals. Understanding the sensory mechanisms and information processing principles that biological systems utilize for efficient sensory data acquisition may provide useful guidance for the design of smart-sensing systems in engineering applications. Weakly electric fish, which use self-generated electrical energy to actively sense their environment, provide an excellent model system for studying biological principles of sensory data acquisition. The electrosensory system enables these fish to hunt and navigate at night without the use of visual cues. To achieve reliable, real-time task performance, the electrosensory system implements a number of smart sensing strategies, including efficient stimulus encoding, multi-scale virtual sensor arrays, task-dependent filtering and online subtraction of sensory expectation.

• Journal of Information Processing Systems
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• v.17 no.6
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• pp.1179-1190
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• 2021

A data acquisition and monitoring system was developed for an automated system of a smart fish farm. The fish farm is located in Jang Hang, South Korea, and was designed as circulation filtration system. Information of every aquaculture pool was automatically measured by pH sensors, dissolved oxygen sensors, and water temperature sensors and the data were stored in the database in a remoted server. Modbus protocol was used for gathering the data which were further used to optimize the pool water quality to predict the rate of growth and death of fish, and to deliver food automatically as planned by the fish farmer. By using JSON protocol, the collected data was delivered to the user's PC and mobile phone for analysis and easy monitoring. The developed monitoring system allowed the fish farmers to improve fish productivity and maximize profits.

• Journal of The Korean Society of Agricultural Engineers
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• v.63 no.6
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• pp.89-100
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• 2021

The conservation of stream habitats has been gaining more public attention and fish habitat suitability index (HSI) is an important measure for ecological stream habitat assessment. The fish habitat preference is affected not only by physical stream conditions but also by water quality of which HSI was not available due to the lack of field data. The purpose of this study is to estimate the HSI of Zacco platypus for water quality parameters of water temperature, dissolved oxygen (DO), and biochemical oxygen demand (BOD) using the water environment monitoring data provided by the Ministry of Environment (ME). Fish population data merged with water quality were constructed by spatio-temporal matching of nationwide water quality monitoring data with bio-monitoring data of the ME. Two types of the HSI were calculated by the Instream Flow and Aquatic Systems Group (IFASG) method and probability distribution (Weibull) fitting for the four major river basins. Both the HSIs by the IFASG and Weibull fitting appeared to represent the overall distribution and magnitude of fish population and this can be used in stream fish habitat evaluation considering water quality.

• Journal of the Korean Society of Food Science and Nutrition
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• v.39 no.12
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• pp.1903-1907
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• 2010

Drying curves for raw Alaska pollack seemed to follow typical food dehydration process with a very short initial settling down period. It was evident that there are some differences in drying rates between each part of fish body showing the highest drying rate for fish head followed by that for fish skin and that for flesh, presumably because of differences in water holding capacity of the components of each part. Specifically, the drying curve of fish flesh revealed that a boundary layer, thereby, a time period, existed which showed a big difference in moisture content and/or water activity as drying proceeds. The boundary layer in fish flesh with high moisture content between the layer contributes to reduce drying rate mainly as a consequence of protein aggregation resulting in hardening of fish flesh. The first boundary layer in this work appeared to show within several hours after initiation of drying. For Hwangtae, a naturally cyclic freeze-thaw dried and aged Alaska pollack which was popular in Korea, manufacturing process, it is clear that periodic moistening of boundary layer in fish flesh prohibits hardening fish flesh in boundary layer and enables steady moisture diffusion from inside of the fish flesh to surface of the fish body.

• Journal of Digital Convergence
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• v.20 no.3
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• pp.333-341
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• 2022

Despite rapidly increasing demand for fishing, there is a lack of studies and information related to fishing, and there is a limit to obtaining the data on the global distribution of fish resources. Since the existing method of investigating fish resource distribution is designed to collect the fish resource information by visiting the investigation area using a throwing net, it is almost impossible to collect nation-wide data, such as streams, rivers, and seas. In addition, the existing method of measuring the length of fish used a tape measure, but in this study, a FishingTAG's smart measure was developed. When recording a picture using a FishingTAG's smart measure, the length of the fish and the environmental data when the fish was caught are automatically collected, and there is no need to carry a tape measure, so the user's convenience can be increased. With the development of a global fishing application using a FishingTAG's smart measure, first, it is possible to collect fish resource samples in a wide area around the world continuously on a real time basis. Second, it is possible to reduce the enormous cost for collecting fish resource data and to monitor the distribution and expansion of the alien fish species disturbing the ecosystem. Third, by visualizing global fish resource information through the Google Maps, users can obtain the information on fish resources according to their location. Since it provides the fish resource data collected on a real time basis, it is expected to of great help to various studies and the establishment of policies.