• Title/Summary/Keyword: smartfarm

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Optimization of Heat Exchange Network of SOFC Cogeneration System Based on Agricultural By-products (농산부산물 기반 SOFC 열병합발전 시스템 열교환망 최적화)

  • Gi Hoon Hong;Sunghyun Uhm;Hyungjune Jung;Sungwon Hwang
    • Journal of the Korean Institute of Gas
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    • v.28 no.1
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    • pp.1-10
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    • 2024
  • In this study, we constructed a process simulation model for an agricultural by-products based Solid Oxide Fuel Cell (SOFC) combined heat and power generation system as part of the introduction of technology for energy self-sufficiency in the agricultural sector. The aim was to reduce the burden of increasing fuel and electricity consumption due to rapid fluctuations in international oil prices and the expansion of smart farming in domestic farms, while contributing to the national greenhouse gas reduction goals. Based on the experimental results of 0.3 ton/day torrefied agricultural by-product gasification experiment, a model for an agricultural by-product-based SOFC cogeneration system was constructed, and optimization of the heat exchange network was conducted for SOFC capacities ranging from 4 to 20 kW. The results indicated that an 8 kW agricultural by-product-based SOFC cogeneration system was optimal under the current system conditions. It is anticipated that these research findings can serve as foundational data for future commercial facility design.

A Study on Modeling of Watering Control status by Regions Using the Measurement Device of the Ministry of Root Environment (근권 환경부 측정장치를 이용한 지역별 관수제어 모델링 연구)

  • Jeong, Jin-Hyoung;Jo, Jae-Hyun;Kim, Seung-Hun;Choi, Ahnryul;Lee, Sang-Sik
    • The Journal of Korea Institute of Information, Electronics, and Communication Technology
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    • v.14 no.2
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    • pp.168-174
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    • 2021
  • According to the World Agricultural Productivity Report, the current annual average growth rate of agriculture is 1.63%, which is lower than 1.73% to support the world's 10 billion people, which is growing by 2050. The demand for food, feed, and bioenergy is not growing enough to continue to meet the demand, and it is predicting a future food shortage. The purpose of this study was to create a regional irrigation control model for the purpose of reducing the production cost of crops, increasing production, and improving quality, and presenting a model that can give advice to farmers who start farming in the region. The irrigation control modeling presented in this study means to represent the change of medium weight·supply liquid·drainage amount due to changes in the root zone environment according to the passage of time and climate in a graph model. For water control modeling, we collected data on the change in the amount of the root zone environment and the weight of the badge·supply amount·drainage amount from March to June in Nonsan, Buyeo, and Yesan regions in Chungnam Province through the measuring device of the Ministry of Environment in the root region. We set up the parameters for derivation and derived an irrigation control model that can confirm the change in weight·supply liquid·drainage amount over time through the parameters.

Regional irrigation control modeling and regional climate characteristics Research on the correlation (지역별 관수제어 모델링 및 지역별 기후 특성과의 연관성에 관한 연구)

  • Jeong, Jin-Hyoung;Jo, Jae-Hyun;Kim, Seung-Hun;Choi, Ahnryul;Lee, Sang-Sik
    • The Journal of Korea Institute of Information, Electronics, and Communication Technology
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    • v.14 no.3
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    • pp.184-192
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    • 2021
  • Domestic agriculture is facing real problems, such as a decrease in the population in rural areas, a shortage of labor due to an aging population, and increased risks due to the deepening of climate change. Smart farming technology is being developed to solve these problems. In the development of smart agricultural technology, irrigation control plays an important role in creating an optimal growth environment and is an important issue in terms of environmental protection. This paper is about the study of collecting and analyzing the rhizosphere environmental data of domestic paprika farms for the purpose of improving the quality of crops, reducing production costs, and increasing production. Irrigation control modeling presented in this paper Control modeling is to graphically present changes in a medium weight, feed, and drainage due to regional climatic features. To derive the graph, the parameters were determined through data collection and analysis, and the suggested irrigation control modeling method was applied to the collected rhizosphere environmental data to control irrigation in 6 regions (Gangwon-do, Chungnam, Jeonbuk, Jeonnam, Gyeongbuk, and Gyeongnam). The parameters were obtained and graphs were derived from them. After that, a study was conducted to analyze the derived parameters to verify the validity of the irrigation control modeling method and to correlate them with climatic features (average temperature and precipitation).

Study on the photosynthetic characteristics of Eutrema japonica (Siebold) Koidz. under the pulsed LEDs for simulated sunflecks

  • Park, Jae Hoon;Kim, Sang Bum;Lee, Eung Pill;Lee, Seung Yeon;Kim, Eui Joo;Lee, Jung Min;Park, Jin Hee;Cho, Kyu Tae;Jeong, Heon Mo;Choi, Seung Se;Park, Hoey Kyung;You, Young Han
    • Journal of Ecology and Environment
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    • v.45 no.1
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    • pp.54-61
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    • 2021
  • Background: The sunfleck is an important light environmental factor for plants that live under the shade of trees. Currently, the smartfarm has a system that can artificially create these sunfleks. Therefore, it was intended to find optimal light conditions by measuring and analyzing photosynthetic responses of Eutrema japonica (Miq.) Koidz., a plant living in shade with high economic value under artificial sunflecks. Results: For this purpose, we used LED pulsed light as the simulated sunflecks and set the light frequency levels of six chambers to 20 Hz, 60 Hz, 180 Hz, 540 Hz, 1620 Hz, and 4860 Hz of a pulsed LED grow system in a plant factory and the duty ratio of the all chambers was set to 30%, 50%, and 70% every 2 weeks. We measured the photosynthetic rate, transpiration rate, stomatal conductance, and substomatal CO2 partial pressure of E. japonica under each light condition. We also calculated the results of measurement, A/Ci, and water use efficiency. According to our results, the photosynthetic rate was not different among different duty ratios, the transpiration rate was higher at the duty ratio of 70% than 30% and 50%, and stomatal conductance was higher at 50% and 70% than at 30%. In addition, the substomatal CO2 partial pressure was higher at the duty ratio of 50% than 30% and 70%, and A/Ci was higher at 30% than 50% and 70%. Water use efficiency was higher at 30% and 50% than at 70%. While the transpiration rate and stomatal conductance generally tended to become higher as the frequency level decreased, other physiological items did not change with different frequency levels. Conclusions: Our results showed that 30% and 50% duty ratios could be better in the cultivation of E. japonica due to suffering from water stress as well as light stress in environments with the 70% duty ratio by decreasing water use efficiency. These results suggest that E. japonica is adapted under the light environment with nature sunflecks around 30-50% duty ratio and low light frequency around 20 Hz.

Strawberry Pests and Diseases Detection Technique Optimized for Symptoms Using Deep Learning Algorithm (딥러닝을 이용한 병징에 최적화된 딸기 병충해 검출 기법)

  • Choi, Young-Woo;Kim, Na-eun;Paudel, Bhola;Kim, Hyeon-tae
    • Journal of Bio-Environment Control
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    • v.31 no.3
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    • pp.255-260
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    • 2022
  • This study aimed to develop a service model that uses a deep learning algorithm for detecting diseases and pests in strawberries through image data. In addition, the pest detection performance of deep learning models was further improved by proposing segmented image data sets specialized in disease and pest symptoms. The CNN-based YOLO deep learning model was selected to enhance the existing R-CNN-based model's slow learning speed and inference speed. A general image data set and a proposed segmented image dataset was prepared to train the pest and disease detection model. When the deep learning model was trained with the general training data set, the pest detection rate was 81.35%, and the pest detection reliability was 73.35%. On the other hand, when the deep learning model was trained with the segmented image dataset, the pest detection rate increased to 91.93%, and detection reliability was increased to 83.41%. This study concludes with the possibility of improving the performance of the deep learning model by using a segmented image dataset instead of a general image dataset.

A Study on the AI Analysis of Crop Area Data in Aquaponics (아쿠아포닉스 환경에서의 작물 면적 데이터 AI 분석 연구)

  • Eun-Young Choi;Hyoun-Sup Lee;Joo Hyoung Cha;Lim-Gun Lee
    • The Journal of the Convergence on Culture Technology
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    • v.9 no.3
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    • pp.861-866
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    • 2023
  • Unlike conventional smart farms that require chemical fertilizers and large spaces, aquaponics farming, which utilizes the symbiotic relationship between aquatic organisms and crops to grow crops even in abnormal environments such as environmental pollution and climate change, is being actively researched. Different crops require different environments and nutrients for growth, so it is necessary to configure the ratio of aquatic organisms optimized for crop growth. This study proposes a method to measure the degree of growth based on area and volume using image processing techniques in an aquaponics environment. Tilapia, carp, catfish, and lettuce crops, which are aquatic organisms that produce organic matter through excrement, were tested in an aquaponics environment. Through 2D and 3D image analysis of lettuce and real-time data analysis, the growth degree was evaluated using the area and volume information of lettuce. The results of the experiment proved that it is possible to manage cultivation by utilizing the area and volume information of lettuce. It is expected that it will be possible to provide production prediction services to farmers by utilizing aquatic life and growth information. It will also be a starting point for solving problems in the changing agricultural environment.

Effects of Combination of Air Temperature and Soil Moisture Contents on Growth, Clove Initiation, Physiological Disorders, and Yield of Garlic (기온과 토양수분 함량에 따른 난지형 마늘의 생장, 인편분화, 생리장해 및 수량에 미치는 영향)

  • Lee, Hee Ju;Lee, Sang Gyu;Kim, Sung Kyeom;Mun, Boheum;Lee, Jin Hyoung;Lee, Hee Su;Kwon, Young Seok;Han, Ji Won;Kim, Cheol Woo
    • Journal of Bio-Environment Control
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    • v.27 no.3
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    • pp.191-198
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    • 2018
  • The objective of this study was to determine the effects of combination of air temperature and soil water contents on growth, physiological disorder rate, and yield of garlic. This experiments has been carried out in the typical plastic house (one side open and other side installed ventilation fans) which was maintained gradient air temperature (maximum different value of air temperature : $6^{\circ}C$). The excessive irrigation (EI) set at $0.34m^3/m^3$ soil moisture contents. The significant differences found in the growth parameters of garlics as affected by air temperature and soil moisture conditions. The plant height of garlic with combination of ambient $(A)+6^{\circ}C$ and optimal irrigation (OI; set at $0.22m^3/m^3$ soil moisture contents) treatments represented 47.4 cm/plant, which was the highest among all the tested treatments. The leaf length and width showed the greatest, which were 16.1 and 2.4 cm/plant, respectively, in $A+6^{\circ}C-OI$. The physiological disorder ratio was higher as 12.9% at $A+6^{\circ}C-OI$ and was not occurred at ambient temperature with EI compared with OI treatment. The bulb and clove weight were dramatically decreased at $A+6^{\circ}C$ temperature treatment. The yields were decreased by 51% in OI at $A+6^{\circ}C$ and $A+3^{\circ}C$ temperature treatment. Those results indicated that yields were decreased and ratio of physiological disorders was increased by high temperature treatments.

Current status and future of insect smart factory farm using ICT technology (ICT기술을 활용한 곤충스마트팩토리팜의 현황과 미래)

  • Seok, Young-Seek
    • Food Science and Industry
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    • v.55 no.2
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    • pp.188-202
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    • 2022
  • In the insect industry, as the scope of application of insects is expanded from pet insects and natural enemies to feed, edible and medicinal insects, the demand for quality control of insect raw materials is increasing, and interest in securing the safety of insect products is increasing. In the process of expanding the industrial scale, controlling the temperature and humidity and air quality in the insect breeding room and preventing the spread of pathogens and other pollutants are important success factors. It requires a controlled environment under the operating system. European commercial insect breeding facilities have attracted considerable investor interest, and insect companies are building large-scale production facilities, which became possible after the EU approved the use of insect protein as feedstock for fish farming in July 2017. Other fields, such as food and medicine, have also accelerated the application of cutting-edge technology. In the future, the global insect industry will purchase eggs or small larvae from suppliers and a system that focuses on the larval fattening, i.e., production raw material, until the insects mature, and a system that handles the entire production process from egg laying, harvesting, and initial pre-treatment of larvae., increasingly subdivided into large-scale production systems that cover all stages of insect larvae production and further processing steps such as milling, fat removal and protein or fat fractionation. In Korea, research and development of insect smart factory farms using artificial intelligence and ICT is accelerating, so insects can be used as carbon-free materials in secondary industries such as natural plastics or natural molding materials as well as existing feed and food. A Korean-style customized breeding system for shortening the breeding period or enhancing functionality is expected to be developed soon.