• Journal of the Korea Society of Computer and Information
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• v.26 no.12
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• pp.255-264
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• 2021

In this paper, we propose operations and maintenance (O&M) planning approach for floating offshore wind farm using the mathematical optimization. To be specific, we present a MILP (Mixed Integer Linear Programming that suggests the composition of vessels, technicians, and maintenance works on a weekly basis. We reflect accessibility to wind turbines based on weather data and loss of power generation using the Jensen wake model to identify downtime cost that vary from time to time. This paper also includes a description of two-stage approach for maintenance planning & detailed scheduling and numeric analysis of the number of vessels and technicians on the O&M cost. Finally, the MILP model could be utilized in order to establish the suitable and effective maintenance planning reflecting domestic situation.

• The Journal of the Korea Contents Association
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• v.21 no.1
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• pp.552-560
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• 2021

Currently, the domestic aquaculture industry is pursuing smartization, but it is still proceeding with human subjective judgment in many processes in the aquaculture stage. The prerequisite for the smart aquaculture industry is to effectively grasp the condition of fish in the farm. If real-time monitoring is possible by identifying the number of fish populations, size, pathways, and speed of movement, various forms of automation such as automatic feed supply and disease determination can be carried out. In this study, we proposed an algorithm to identify the state of fish in real time using underwater video data. The fish detection performance was compared and evaluated by applying the latest deep learning-based object detection models, and an algorithm was proposed to measure fish object identification, path tracking, and moving speed in continuous image frames in the video using the fish detection results. The proposed algorithm showed 92% object detection performance (based on F1-score), and it was confirmed that it effectively tracks a large number of fish objects in real time on the actual test video. It is expected that the algorithm proposed in this paper can be effectively used in various smart farming technologies such as automatic feed feeding and fish disease prediction in the future.

• Korean Journal of Construction Engineering and Management
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• v.23 no.1
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• pp.98-105
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• 2022

It is essential for vertical smart farms that artificially grow crops in an enclosed space to properly utilize air environment facilities to create an appropriate growth environment. However, domestic vertical smart farm companies are creating a growing environment by relying on empirical data rather than systematic methods. Using IoT to create a growing environment based on systematic and precise monitoring can increase crop production yield and maximize profitability. This study aims to construct a monitoring system using IoT and to analyze the cause by demonstrating the imbalance of temperature environment, which is a significant factor in crop cultivation. 1) The horizontal temperature distribution of the multi-layer shelf was measured with different operating methods of LED and air conditioner. As a result, there was a temperature difference of "up to 1.7℃" between the sensors. 2) As a result of measuring the vertical temperature distribution, the temperature difference was "up to 6.3℃". In order to reduce this temperature gap, a strategy for proper arrangement and operation of air conditioning equipment is required.

• The Journal of the Korea institute of electronic communication sciences
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• v.12 no.5
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• pp.907-914
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• 2017

Recently, industrialization and automation for crops has enabled the development of smart farm technology over the world This is due to the need for the automation and convenience of the agricultural system to aging the population and reducing the labor force. In this system, the smart app can control the temperature and humidity that can be conveniently managed by the farmers. It is possible to check the status of the greenhouses in real time in the smartphone and maintain the optimum temperature and humidity, thereby helping to prevent pests and diseases, to grow crops, and to improve the labor force and productivity of farmers and fishermen.

• Proceedings of the Korean Society of Crop Science Conference
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• 2022.10a
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• pp.58-58
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• 2022

With the development of advanced technology, automation of agricultural work is spreading. In association with the 4th industrial revolution-based technology, research on field smart farm technology is being actively conducted. A state-of-the-art unmanned automated agricultural production demonstration complex was established in Naju-si, Jeollanam-do. For the operation of the demonstration area platform, it is necessary to build a sophisticated, advanced, and intelligent field smart farming model. For the operation of the unmanned automated agricultural production demonstration area platform, we are building data on the growth of soybean for smart cultivated crops and conducting research to determine the optimal time for agricultural work. In order to operate an unmanned automation platform, data is collected to discover digital factors for water management immediately after planting, water management during the growing season, and determination of harvest time. A subsurface drip irrigation system was established for smart water management. Irrigation was carried out when the soil moisture was less than 20%. For effective water management, soil moisture was measured at the surface, 15cm, and 30cm depth. Vegetation indices were collected using drones to find key factors in soybean production prediction. In addition, major growth characteristics such as stem length, number of branches, number of nodes on the main stem, leaf area index, and dry weight were investigated. By discovering digital factors for effective decision-making through data construction, it is expected to greatly enhance the efficiency of the operation of the unmanned automated agricultural production demonstration area.

• 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 the Korean Solar Energy Society
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• v.33 no.4
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• pp.23-30
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• 2013

This paper presents the determination method of the hybrid energy storage capacity for compensating the output of wind power when disconnecting from the grid. In the wind power output compensation, a lot of charging and discharging time with lithium-ion battery will be deteriorated the life time. And also, this fluctuation will cause some problems of the power quality and power system stability. To solve these kind of problems, many researchers in the world have been studied with BESS(Battery Energy Storage System) in the wind farm. But, BESS has the limitation of its output during very short term period, this means that it is difficult to compensate the very short term output of wind farm. Using the EDLC (Electric Double Layer Capacitor), it is possible to solve the problem. Installing the battery system in the wind farm, it will be possible to decrease the total capacity of BESS consisting of HESS (Hybrid Energy Storage System). This paper shows simulation results when not only BESS is connected to wind farm but also to HESS. To verify the proposed system, results of computer simulation using PSCAD/EMTDC program with actual output data of wind farms of Jeju Island will be presented.

• Journal of Bio-Environment Control
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• v.25 no.1
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• pp.30-41
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• 2016

Korean government has planned to increase the productivity of horticultural crops and to expand supply smart greenhouse for energy saving by modernization of horticultural facilities based on ICT in policy. However, the diversity and linkages of monitoring and control are significantly insufficient in the agricultural sector in the current situation. Therefore, development of a service system with smart-farm based on the internet of things(IoT) for intelligent systemization of all the process of agricultural production through remote control using complex algorithm for diverse monitoring and control is required. In this study, domestic and international research trend related to ICT-based horticultural facilities was briefly introduced and limits were analyzed in the domestic application of the advanced technology. Finally, future core technologies feasible to graft in agricultural field were reviewed.

• Journal of Internet of Things and Convergence
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• v.6 no.3
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• pp.45-52
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• 2020

In the paper, we propose a system that measures various agricultural parameters that affect crop yield and monitors location information. According to an analysis by international organizations, 60% of the world's population lives on agriculture. In addition, 11% of the world's soil is used for growing crops. For this reason, agriculture plays an important role in national development. If a problem occurs in agriculture due to weather or environmental problems, it can be a problem for national development. In order to solve these problems, it is important to modernize agriculture using modern IoT technology. It is possible to improve the agricultural environment by applying IoT technology in agriculture to build a smart environment. Through such a smart environment, it is possible to increase the yield of agricultural products, reduce water waste, and prevent overuse of fertilizers. In order to verify the proposed system, an experiment was performed in a soybean cultivation farm. Experimental results showed that using the proposed system, the moisture in the cultivated soil can be automatically maintained at 40%.

• Korean Journal of Agricultural and Forest Meteorology
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• v.21 no.4
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• pp.373-379
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• 2019

Smart-farm has been spreading across Korea to improve the labor efficiency and productivity of greenhouse crops. Although notable improvements have been made in the monitoring technologies and environmental-controlling systems in greenhouses, only a few simple decision-support systems are available for predicting the optimum environmental conditions for crop growth. In this study, a tomato growth model (GreenTom), which was developed by Seoul National University in 1997, was calibrated and validated to examine if the model can be used as a decision-supporting system. The original GreenTom model was not able to simulate artificial defoliation, which resulted in overestimation of the leaf area index in the late growth. Thus, an algorithm for simulating the artificial defoliation was developed and added to the original model. The node development, leaf growth, stem growth, fruit growth, and leaf area index were generally well simulated by the modified model indicating that the model could be used effectively in the decision-making of smart greenhouse.