• The Journal of the Korea Contents Association
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• 제20권10호
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• pp.167-176
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• 2020

The automated fish feed system currently used in Korea supplies a certain amounts of feed to water tanks at a certain time. This automated system can reduce the labor cost of managing aqua farms, but it is very difficult to control intelligently and appropriately the amount of expensive feed that is critical to aqua farm productivity. In this paper, we propose the FIIFF Inference Model( Fuzzy Inference-based Intelligent Fish Feeding Model) that can solves the problems of these existing automatic fish feeding devices and maximizes the efficiency of feed supply while properly maintaining the growth rate of fish in aqua farms. The proposed FIIFF inference model has the advantage of being able to control feed amounts appropriately since it computes the amount of feed using the current water environments and fish activity state of the aqua farms. The result of the feed amount yield experiment with the proposed FIIFF Inference Model represents the effect of saving 14.8% over the eight months of actual feed amount in the aqua farm.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• 제12권3호
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• pp.201-210
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• 2019

This paper proposes the AMCS(Agricultural Machine Control System that distinguishes farms using satellite photos or drone photos of farms and controls the self-driving and operation of farm drones and tractors. The AMCS consists of the LSM(Local Server Module) which separates farm boundaries from sensor data and video image of drones and tractors, reads remote control commands from the main server, and then delivers remote control commands within the management area through the link with drones and tractor sprinklers and the PSM that sets a path for drones and tractors to move from the farm to the farm and to handle work at low cost and high efficiency inside the farm. As a result of AMCS performance analysis proposed in this paper, the PSM showed a performance improvement of about 100% over Dijkstra algorithm when setting the path from external starting point to the farm and a higher working efficiency about 13% than the existing path when setting the path inside the farm. Therefore, the PSM can control tractors and drones more efficiently than conventional methods.

• The Journal of the Korea institute of electronic communication sciences
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• 제19권1호
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• pp.209-216
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• 2024

Land shrimp farms can control the growth environment more stably than coastal ones, making them advantageous for high-quality, large-scale production. In order to maintain an optimal shrimp growth environment, various factors such as water circulation, maintaining appropriate water temperature, oxygen supply, and feed supply must be managed. In particular, failure to properly manage water quality can lead to the death of shrimp, making it difficult to have people stationed at the farm 24 hours a day to continuously manage them. In this paper, to solve this problem, we design an integrated monitoring system for land farms that can be operated with minimal manpower. The proposed design plan uses IoT technology to collect real-time images of land farms, pump status, water quality data, and energy usage and transmit them to the server. Through web interfaces and smartphone apps, administrators can check the status of the farm stored on the server anytime, anywhere in real time and take necessary measures. Therefore, it is possible to significantly reduce field work hours without the need for managers to reside in the farm.

• The Journal of Korean Institute of Next Generation Computing
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• 제15권6호
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• pp.60-71
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• 2019

As IoT systems such as smart farms and smart cities become popular, a large amount of data collected from many sensor nodes is sent to a server in the Internet, which causes network traffic explosion, delay in delivery, and increase of server's workload. To solve these problems, the concept of fog computing has been proposed to store data between IoT systems and servers. In this study, we implemented a software platform of the fog node and applied it to the prototype smart farm system in order to check whether the problems listed above can be solved when using the fog node. When the fog node is used, the time taken to control an IoT device is lower than the response time of the existing IoT device-server case. We confirmed that it can also solve the problem of the Internet traffic explosion and the workload increase in the server. We also showed that the intelligent control of IoT system is feasible by having the data visualization in the server and real time remote control, emergency notification in the fog node as well as data storage which is the basic capability of the fog node.

• Wind and Structures
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• 제28권2호
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• pp.129-140
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• 2019

Accurately simulating the wind field of large-scale region, for instant urban areas, the locations of large span bridges, wind farms and so on, is very difficult, due to the complicated terrains or land surfaces. Currently, the regional wind field can be simulated through the combination of observation data and numerical model using observation-nudging in the Weather Research and Forecasting model (WRF). However, the main drawback of original observation-nudging method in WRF is the effects of observation on the surrounding field is fully mathematical express in terms of temporal and spatial, and it ignores the effects of terrain, wind direction and atmospheric circulation, while these are physically unreasonable for the turbulence. For these reasons, a spatial correlation-based observation-nudging method, which can take account the influence of complicated terrain, is proposed in the paper. The validation and comparation results show that proposed method can obtain more reasonable and accurate result than original observation-nudging method. Finally, the discussion of wind field along bridge span obtained from the simulation with spatial correlation-based observation-nudging method was carried out.

• Journal of Platform Technology
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• 제9권4호
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• pp.42-50
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• 2021

Recently, the need to introduce smart farms is increasing in order to solve the problems of intensifying competition such as a decrease in rural population due to aging, a decrease in production, and the inflow of foreign agricultural products, and accordingly, the need for education is increasing. This paper is a study on the implementation of an Android-based IoT smart farm for education so that it can be used in a real environment by reducing the farm's smart farm system. To confirm that Android-based education can be applied in a real environment using the IoT smart farm for education, experiments were performed in automatic mode and manual mode using Bluetooth, Wi-Fi, and server/client communication methods. In the automatic mode, the current status can be checked in real time by receiving all data, and in the manual mode, commands are transmitted in real time using the received sensor data and remote control is performed. As a result of the experiment, it was possible to understand the characteristics of each communication method, and it was confirmed that remote monitoring and remote control of the smart farm using the Android App was possible.

• Journal of the Korean Society for Geothermal and Hydrothermal Energy
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• 제18권3호
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• pp.19-30
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• 2022

In this study, comparative analysis of energy performance in Taebaek city, a test area, by applying hydrothermal, geothermal source and hybrid heat pump system to office, school and smart farms with different internal heat loads. The conclusion is as follows. In the load characteristics by use of buildings, it was found that office had a large cooling load compared to heating load, school had a large heating load compared to cooling load, and smart farm had only cooling load year-round. Performance analysis of the heat pump system in office shows that the cooling COP of the hydrothermal source is 5.12% and the heating COP is 3.22% lower based on the geothermal source, the cooling COP of the hybrid is 0.41% higher, and the heating COP is the difference in performance appeared sparsely. The performance analysis of the heat pump system in school showed that the cooling COP of the hydrothermal source was 10.44% and the heating COP 3.22% lower based on the geothermal source, and the performance difference between the hybrid cooling and heating COP was insignificant. Heat pump system performance analysis in smart farm only occurred with cooling load. Based on geothermal sources, the cooling COP of the hydrothermal source was 46% and the cooling COP of the hybrid was 19.65%, respectively.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• 제39권6호
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• pp.419-427
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• 2021

Due to the effects of climate change and the reduction of the labor force due to COVID-19, the crop yield, harvest time, and cultivated area are rapidly changing every year. In order to respond flexibly to this situation, attempts to apply smart farm technology based on ICT (Information and Communication Technology) to individual farms are increasing. On the other hand, various stakeholders are trying to predict the yield of crops using artificial intelligence and IoT technology, but accurate prediction is difficult due to the lack of learning data. In this study, in order to overcome the data collection problem limited to a specific institution, a smart farmer service technology based on community mapping was developed in which farmers directly participate, input and share accurate data to predict production. In the process, analysis was performed on napa cabbage, which is a vegetable with a large price change compared to production.

• Journal of Internet Computing and Services
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• 제24권4호
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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.

• Smart Media Journal
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• 제12권10호
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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.