• Proceedings of the KIPE Conference
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• 2018.07a
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• pp.278-279
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• 2018

Due to the frequent occurrence of dangerous wild animals in rural or mountainous areas. it has been increasing damage of crops in every year. Fight bell or electric fence is typically installed to chase those wild animals. But there are problems that it is impossible to drive out birds and spends high installation and maintenance cost. In addition, it is inefficient to the risk of electric shock effect. In this study, the proposed system can drive out hazardous wildlife and birds regardless of installation location through realtime detection with the multi-sensing based IoT platform technology. This study showed a very large significance effect that can reduce crop damage by wildlife and birds.

• Annual Conference of KIPS
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• 2014.11a
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• pp.790-793
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• 2014

농촌의 많은 농장에서는 데이터 처리 및 분석 시스템에 대한 필요성을 느끼면서 지내오고 있다. 본 논문에서는 데이터베이스 시스템을 접목시켜서 기존 엑셀에서 간단한 계산만 이루어지던 농장 데이터 관리 시스템을 효율적으로 개편하여 데이터 분석 및 확인 시스템을 개발하였다. 본 연구에서 개발한 데이터 시스템을 실제 버섯농장에 설치 후 실험을 통하여 기존 방법 대비의 정확성, 실용성 그리고 신뢰할 수 있는 분석 시스템을 구축하였다.

• Annual Conference of KIPS
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• 2015.10a
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• pp.583-585
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• 2015

도시농촌을 대상으로 스마트팜(Smart-Farm) 솔루션은 현재 많이 출시되어 운용되고 있다. 하지만, 대부분의 스마트팜 제품들은 시설재배의 유형, 재배대상 작물의 특성 및 시설재배관리자(사용자)의 요구를 반영할 수 있는 개방형 시스템과는 거리가 멀다. 본 연구팀에서는 대규모의 시설 농가를 대상으로 통합관제기술과 스마트제어, 센서기술을 적용한 단동형 스마트팜 관리시스템을 개발 및 상용화를 목표로 하고 있으며, 이는 각 작물의 특징과 사용자의 요구에 따라 관리시스템의 유연성 및 확장성을 고려하여 설계하고 있다. 본 논문에서는 해당 연구의 일환으로 단일시설재배작물로는 세계 최대 생산지인 경상북도 성주참외를 대상으로 사용자 편의성이 증진된 단동형 농작물관리시스템을 설계하였다.

• Proceedings of The Korean Society of Agricultural and Forest Meteorology Conference
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• 2014.10a
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• pp.74-85
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• 2014

This study is a part of "Early Warning Service for Weather Risk Management in Climate-smart Agriculture", describes the delivery techniques from 840 catchment scale weather warning information using 150 counties unit special weather report(alarm, warning) released from KMA(Korea Meteorological Administration) and chronic weather warning information based on daily weather data from 76 synoptic stations. Catchment weather hazard warning service express a sequential risk index map generated by countries report occurs and report grade(alarm, warning) convert to catchment scale using zonal summarizing method. Additional services were chronic weather warning service at crop growth and accumulated more than 4 weeks, based on an unsuitable weather conditions, representing a relative risk compared to its catchment climatological normal conditions (normal distribution ) in addition to special weather report. Service provided by a real-time catchment scale map overlaid with VWORLD open platform operated by Ministry of Land, Infrastructure and Transport. Also provide a foundation for weather risk information to inform individual farmers to farm located within the catchment zone warning occur.

• Annual Conference of KIPS
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• 2019.05a
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• pp.711-713
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• 2019

본 논문은 기존의 단순 감지 센서형 양식장 관리 시스템을 벗어나기 위해 IoT와 AI기술을 이용한 무인 양식장 관리 시스템 개발에 관한 것이다. 국내 양식장 상황에 맞는 유해 조류와 한국형 어선 이미지를 학습시켜 실시간 카메라 영상을 통해 유해 및 무해 물체를 판단하도록 하였으며 이에 따라 적절한 퇴치 기능을 수행하도록 하였다. 또한 현존하는 양식장 관리 시스템이 환경 관리 시스템과 감시 및 퇴치 시스템으로 이분화 된 경향을 보여 하나로 통합하는 과정의 필요성이 대두되었다. 따라서 감시 및 퇴치 기능 수행뿐만 아니라 양식장 내 환경 데이터를 실시간으로 받아오고 사용자가 단말기를 통해 양식장 상황을 확인 및 관리가 가능하도록 구현하고자 하였다.

• Journal of Environmental Impact Assessment
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• v.32 no.4
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• pp.230-241
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• 2023

At a time when it is urgent to establish a management system for landscape quality assessment of offshore wind farms in Korea, we analyzed foreign cases to draw implications for improving the landscape quality assessment of offshore wind farms in Korea and to explore the direction of efficient landscape assessment. The main contents derived from the analysis of overseas cases and systems are as follows. First, offshore wind farms are large-scale projects, and it is necessary to consider the landscape from the pre-planning stage, as in overseas cases. Second, the evaluation items for marine landscape quality should be expanded and systematized. Third, a flexible evaluation system that can consider new landscape impacts is required. In order to identify the landscape impacts of offshore wind farm projects, we refer to the landscape assessment items and procedures derived from overseas cases, but reflect them appropriately to the domestic maritime conditions, and specifically introduce a plan to minimize the landscape impacts that may occur during offshore wind farm projects to contribute to the sustainable use of offshore wind power.

• Smart Media Journal
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• v.12 no.10
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• pp.63-70
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• 2023

Recently, energy consumption for heating costs, which is 35% of smart farm energy costs, has increased, requiring energy consumption efficiency, and the importance of new and renewable energy is increasing due to concerns about the realization of electricity bills. Renewable energy belongs to hydropower, wind, and solar power, of which solar energy is a power generation technology that converts it into electrical energy, and this technology has less impact on the environment and is simple to maintain. In this study, based on the greenhouse heat storage tank and heat pump data, the factors that affect the heat storage tank are selected and a heat storage tank supply temperature prediction model is developed. It is predicted using Long Short-Term Memory (LSTM), which is effective for time series data analysis and prediction, and XGBoost model, which is superior to other ensemble learning techniques. By predicting the temperature of the heat pump heat storage tank, energy consumption may be optimized and system operation may be optimized. In addition, we intend to link it to the smart farm energy integrated operation system, such as reducing heating and cooling costs and improving the energy independence of farmers due to the use of solar power. By managing the supply of waste heat energy through the platform and deriving the maximum heating load and energy values required for crop growth by season and time, an optimal energy management plan is derived based on this.

• Journal of Electrical Engineering and Technology
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• v.12 no.2
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• pp.726-737
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• 2017

The use of energy storage systems (ESSs) has become a feasible solution to solve the wind power intermittency issue. However, the use of ESSs increases the system cost significantly. In this paper, an optimal power flow control scheme to minimize the ESS capacity is proposed by using the zero-phase delay low-pass filter which can eliminate the phase delay between the dispatch power and the wind power. In addition, the filter time constant is optimized at the beginning of each dispatching interval to ensure the fluctuation mitigation requirement imposed by the grid code with a minimal ESS capacity. And also, a short-term power dispatch control algorithm is developed suitable for the proposed power dispatch based on the zero-phase delay low-pass filter with the predetermined ESS capacity. In order to verify the effectiveness of the proposed power management approach, case studies are carried out by using a 3-MW wind turbine with real wind speed data measured on Jeju Island.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.10a
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• pp.379-381
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• 2021

As information and communication technologies develop, many studies are being conducted to maintain an efficient production environment by applying network and computing technologies to existing production systems. Unlike classical control systems, these smart production systems need to collect data about the production environment in real time, and operate fluidly as it changes. In this paper, we present a measurement system that can collect data in real time through network-based sensors and respond effectively to environmental changes. We also proved this smart system can cope with external environmental changes and maintain an effective production environment.

• Journal of the Korea Society of Computer and Information
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• v.28 no.4
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• pp.113-120
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• 2023

Smart farms are steadily increasing in research to minimize labor, energy, and quantity put into crops as IoT technology and artificial intelligence technology are combined. However, research on efficiently managing crop growth information in smart farms has been insufficient to date. In this paper, we propose a management technique that can efficiently monitor crop growth information by applying autonomous sensors to smart farms. The proposed technique focuses on collecting crop growth information through autonomous sensors and then recycling the growth information to crop cultivation. In particular, the proposed technique allocates crop growth information to one slot and then weights each crop to perform load balancing, minimizing interference between crop growth information. In addition, when processing crop growth information in four stages (sensing detection stage, sensing transmission stage, application processing stage, data management stage, etc.), the proposed technique computerizes important crop management points in real time, so an immediate warning system works outside of the management criteria. As a result of the performance evaluation, the accuracy of the autonomous sensor was improved by 22.9% on average compared to the existing technique, and the efficiency was improved by 16.4% on average compared to the existing technique.