• 한국농공학회논문집
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• 제61권4호
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• pp.1-10
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• 2019

Unmanned aerial vehicle(UAV) can acquire images with lower cost than conventional manned aircraft and commercial satellites. It has the advantage of acquiring high-resolution aerial images covering in the field area more than 50 ha. The purposes of this study is to develop the rice grain yield distribution using UAV. In order to develop a technology for estimating the rice yield using UAV images, time series UAV aerial images were taken at the paddy fields and the data were compared with the rice yield of the harvesting area for two rice varieties(Singdongjin, Dongjinchal). Correlations between the vegetation indices and rice yield were ranged from 0.8 to 0.95 in booting period. Accordingly, rice yield was estimated using UAV-derived vegetation indices($R^2=0.70$ in Sindongjin, $R^2=0.92$ in Donjinchal). It means that the rice yield estimation using UAV imagery can provide less cost and higher accuracy than other methods using combine with yield monitoring system and satellite imagery. In the future, it will be necessary to study a variety of information convergence and integration systems such as image, weather, and soil for efficient use of these information, along with research on preparing management practice work standards such as pest control and nutrient use based on UAV image information.

• 한국가금학회지
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• 제46권1호
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• pp.47-53
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• 2019

The aim of this study was to investigate the difficulties that Korean farmers and processors currently experience with respect to the market for Korean native chicken (KNC). This study also provides suggestions by which they can overcome these difficulties. In all, sixty-nine farmers and sixty-two processors participated in our investigation, which addressed 1) the current difficulties that KNC farmers face, 2) the current importance-satisfaction measures among KNC farmers and processors, and 3) the future direction of the KNC market: farmer and processor opinions. The respondents stated that the limited number of sales stores was the most difficult market condition they faced in raising KNC, followed by feed cost, animal disease, and poor production environment. Regarding issues of importance and satisfaction, origin in raising step and slaughtering in the processing and distribution step were considered the areas most in urgent need of improvement, given farmers' and processors' high levels of dissatisfaction with these. Both the free-range farming system and the concept of animal welfare are growing in importance, given consumers' interests in these areas. As to opinions on the direction of KNC development, menu development was cited as most important, followed by public advertisement, accessibilities, business aid, and breed development. Consequently, the results show that well-organized support from both the government and related industries is needed, as chicken farmers and processors cannot resolve certain limitations inherent in the KNC industry on their own.

• 농촌계획
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• 제25권2호
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• pp.15-21
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• 2019

The agricultural environment is changing and becoming more advanced due to the influence of the 4th Industrial Revolution. From the basic plan of Rural Informatics to the current level of 2nd generation smart farms aimed at improving productivity using Big data, cloud network and more IoT technology. We are continuing to provide support and research and development. However, many problems remain to be solved in order to supply and settle smart farms in Korea. The purpose of this study is to provide a method of collecting and sharing data on farming environment and to help improve the income and productivity of farmers based on collected data. In the case of hog farm, the multiple sensors for environmental data like temperature, humidity and gases and the network environment for connecting the internet were established. The environment sensor was made using the ESP8266 Node MCU board as micro-controller, DHT22 sensor for temperature and humidity, and MQ series sensors for various gases in the hog pens. The network sensor was applied experimentally for one month and the environmental data of the hog farm was stored on a web database. This study is expected to raise the importance of collecting and managing the agricultural and environmental data, for the next generation farmers to understand the smart farm more easily and to try it by themselves.

• 한국인터넷방송통신학회논문지
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• 제19권2호
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• pp.169-174
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• 2019

본 논문은 스마트팜 ICT기기의 고장 오작동으로 인한 이상을 탐지하여 사용자에게 알리는 시스템을 제안한다. 4차 산업혁명이 다가오면서 농업도 경쟁력 향상을 위해 ICT기술과 융합하고 있다. 매년마다 스마트 농업 시장 규모는 빠르게 성장하고 있지만 아직까지 기기의 표준화와 인증제도가 부족한 실정이다. 특히 국내에서 보급되고 있는 스마트팜 기기는 업체마다 제품 규격이 상이하고 소프트웨어와 하드웨어가 별도로 개발되고 있는 등 품질과 호환성이 떨어져 저가의 스마트 팜 기기를 사용하는 농가의 피해가 빈번하게 발생하여 기기의 이상을 인지할 수 있는 시스템이 필요한 상황이다. 본 논문에서는 스마트팜 국내외 정책 동향과 국내 스마트 농업 동향을 알아보고 스마트팜 고장 오작동에 의한 이상 상황을 분석하여 사전에 예방하고 문제 상황이 발생할 경우 사용자에게 알리는 시스템을 제안한다.

• 한국전자통신학회논문지
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• 제16권4호
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• pp.743-748
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• 2021

전 세계적인 인구증가와 기후변화로 인해 식량부족 문제가 대두되는 가운데 우리나라에서는 농·축산업 인구 감소 등 지속가능성 위기를 해결하기 위해 농업과 ICT를 융합한 첨단 스마트팜 기술이 활발히 연구되고 있다. 기존 스마트팜은 개별 가격경쟁력이 낮은 작물 위주로 재배하고 있다. 식품 소비구조가 고급화, 다양화되고 있으며 농산물 소비패턴의 변화에 따라 스마트팜 시스템 또한 고부가가치 특용작물 재배를 위한 최적화가 필요하다. 이를 위해 새싹인삼(새싹삼) 재배에 특화된 컨테이너형 스마트팜 환경설비를 구축하고 ICT 융합통합관리시스템을 설계하고 구현하였다. 이를 통해 ICT와 농업, 최신 기술과 농사의 융합으로 첨단농업생산구현 및 미래융합 신산업 선도가 가능하다.

• Animal Bioscience
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• 제34권7호
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• pp.1235-1242
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• 2021

Objective: The purpose of this study was to identify through infrared thermal imaging technology the facial surface temperature (FST) of laying hens in response to the variations in their thermal environment, and to identify the regional differences in FST to determine the most stable and reliable facial regions for monitoring of thermoregulatory status in chickens. Methods: Thirty Hy-Line Brown hens (25-week-old) were sequentially exposed to three different thermal conditions; optimal (OT, 22℃±2℃), low (LT, 10℃±4℃), and high temperature (HT, 30℃±2℃). The mean values of FST in five facial regions including around the eyes, earlobes, wattles, beak and nose, and comb were recorded through infrared thermography. The maximum FST (MFST) was also identified among the five face-selective regions, and its relationship with temperature-humidity index (THI) was established to identify the range of MFST in response to the variations in their thermal environment. Results: Hens exposed to OT condition at 15:00 displayed a higher temperature at wattles and around the eyes compared to other regions (p<0.001). However, under LT condition at 05:00 to 08:00, around the eyes surface temperature showed the highest value (p<0.01). In HT, wattles temperature tended to show the highest temperature over almost time intervals. Main distribution regions of MFST were wattles (63.3%) and around the eyes (16.7%) in OT, around the eyes (50%) in LT, and wattles (62.2%) and comb (18.3%) in HT. The regression equation between MFST and THI was estimated as MFST = 35.37+0.2383×THI (R² = 0.44; p<0.001). Conclusion: The FST and the frequency of MFST in each facial region of laying hens responded sensitively to the variations in the thermal environment. The findings of this experiment provide useful information about the effect of the thermal conditions on the specific facial regions, thus offering an opportunity to stress and welfare assessment in poultry research and industry.

• 전자통신동향분석
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• 제36권1호
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• pp.54-63
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• 2021

Since the recent COVID-19 pandemic, countries have been strengthening trade protection for their security, and the importance of securing strategic materials, such as food, is drawing attention. In addition to the cultural aspects, the global preference for food produced in Korea is increasing because of the Korean Wave. Thus, the Korean food industry can be developed into a high-value-added export food industry. Currently, Korea has a low self-sufficiency rate for foodstuffs apart from rice. Korea also suffers from problems arising from population decline, aging, rapid climate change, and various animal and plant diseases. It is necessary to develop technologies that can overcome the production structures highly dependent on the outside world of food and foster them into export-type system industries. The global agricultural industry-related technologies are actively being modified via data accumulation, e.g., environmental data, production information, and distribution and consumption information in climate and production facilities, and by actively expanding the introduction of the latest information and communication technologies such as big data and artificial intelligence. However, long-term research and investment should precede the field of living organisms. Compared to other industries, it is necessary to overcome poor production and labor environment investment efficiency in the food industry with respect to the production cost, equipment postmanagement, development tailored to the eye level of field workers, and service models suitable for production facilities of various sizes. This paper discusses the flow of domestic and international technologies that form the core issues of the site centered on the 4th Industrial Revolution in the field of agriculture, livestock, and fisheries. It also explains the environmental awareness production technologies centered on sustainable intelligence platforms that link climate change responses, optimization of energy costs, and mass production for unmanned production, distribution, and consumption using the unstructured data obtained based on detection and growth measurement data.

• Journal of Ecology and Environment
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• 제45권2호
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• pp.88-96
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• 2021

Background: Sika deer, Cervus nippon, were originally introduced to South Korea from Japan and Taiwan for commercial farming purposes. Unfortunately, they were released into the wild during religious events and have since begun to impact the native ecosystem and species endemic to South Korea. The study of activity patterns can improve our understanding of the environmental impact of non-native species and their association with sympatric species. Using camera traps, we studied the diel and seasonal activity patterns of non-native sika deer and quantified the temporal overlap with sympatric mammalian species in the Muljangori-oreum wetlands of Hallasan National Park, South Korea. Results: A total of 970 trap events were recorded for five mammalian species from nine locations during the camera-trap survey. Siberian roe deer (Capreolus pygargus tianschanicus) had the highest number of recorded events (72.0%), followed by sika deer (Cervus nippon) (16.2%), wild boar (Sus scrofa) (5.0%), Asian badger (Meles leucurus) (4.5%), and the Jeju weasel (Mustela sibirica quelpartis) (2.0%). Sika deer had bimodal activity patterns throughout the year, with peaks throughout the spring-autumn twilight, and day and night time throughout the winter. Relating the daily activity of sika deer with other mammalian species, roe deer expressed the highest degree of overlap (Δ₄ = 0.80) while the Asian badger demonstrated the lowest overlap (Δ₄ = 0.37). Conclusions: Our data show that sika deer are a crepuscular species with seasonal variations in daily activity patterns. Additionally, we identified the temporal differences in activity peaks between different mammals in the Muljangori-oreum wetlands and found higher degree of overlap between sika deer and roe deer during twilight hours.

• 한국농공학회논문집
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• 제64권1호
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• pp.51-63
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• 2022

Up-to-date statistics of crop cultivation status is essential for farm land management planning and the advancement in remote sensing technology allows for rapid update of farming information. The objective of this study was to develop a classification model of rice paddy or winter crop fields based on NDWI, NDVI, and HSV indices using Sentinel-2 satellite images. The 18 locations in central Korea were selected as target areas and photographed once for each during summer and winter with a eBee drone to identify ground truth crop cultivation. The NDWI was used to classify summer paddy fields, while the NDVI and HSV were used and compared in identification of winter crop cultivation areas. The summer paddy field classification with the criteria of -0.195

• 한국주조공학회지
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• 제42권4호
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• pp.209-217
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• 2022

본 연구에서는 전통 유기 주조 시 발생하는 미충전 결함을 방지하기 위하여, 주조 공정 조건 선택 방안을 제시하고자 한다. 공정 조건에 따라 발생하는 결함 유무를 학습하여 어떠한 공정 조건이 주어질 때, 결함 발생 여부를 예측하는 인공지능 모델을 개발하고 검증하였다. 이를 응용하여 적합한 공정 조건을 결정하였고, 추가적인 시뮬레이션의 결과를 상호 비교하여 결정된 조건을 검증하였다. 이를 통해 원하는 사형 모델에서 결함을 방지할 수 있는 주조 공정 조건을 결정할 수 있다. 이와 같은 기계학습 및 전통기술 표준화를 통해 향후 전통 유기의 스마트 공방화에 기여할 수 있을 것으로 판단된다.