• International journal of advanced smart convergence
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• 제12권4호
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• pp.458-463
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• 2023

This study presents a paper on the implementation of a Raspberry Pi-based educational smart farm system. It confirms that in a real smart farm environment, the control of temperature, humidity, soil moisture, and light intensity can be smoothly managed. It also includes remote monitoring and control of sensor information through a web service. Additionally, information about intruders collected by the Pi camera is transmitted to the administrator. Although the cost of existing smart farms varies depending on the location, material, and type of installation, it costs 400 million won for polytunnel and 1.5 billion won for glass greenhouses when constructing 0.5ha (1,500 pyeong) on average. Nevertheless, among the problems of smart farms, there are lax locks, malfunctions to automation, and errors in smart farm sensors (power problems, etc.). We believe that this study can protect crops at low cost if it is complementarily used to improve the security and reliability of expensive smart farms. The cost of using this study is about 100,000 won, so it can be used inexpensively even when applied to the area. In addition, in the case of plant cultivators, cultivators with remote control functions are sold for more than 1 million won, so they can be used as low-cost plant cultivators.

• 스마트미디어저널
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• 제12권10호
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• pp.38-46
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• 2023

Farming activities are transforming from traditional skill-based agriculture into knowledge-based and technology-driven digital agriculture. The use of intelligent information and communication technology introduces the idea of smart farming that enables farmers to collect weather data, monitor crop growth remotely and detect crop diseases easily. The introduction of Plantix, a pest and disease management tool in the form of a mobile application has allowed farmers to identify pests and diseases of the crop using their mobile devices. Hence, this study collected the reviews of Plantix to explore the response of the users on the Google Play Store towards the application through Latent Dirichlet Allocation (LDA) topic modeling. Results indicate four latent topics in the reviews: two positive evaluations (compliments, appreciation) and two suggestions (plant options, recommendations). We found the users suggested the application to additional plant options and additional features that might help the farmers with their difficulties. In addition, the application is expected to benefit the farmer more by having an early alert of diseases to farmers and providing various substitutes and a list of components for the remedial measures.

• Journal of Microbiology and Biotechnology
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• 제31권9호
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• pp.1241-1255
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• 2021

This study was carried out to explore a non-chemical strategy for enhancing productivity by employing some antagonistic rhizobacteria. One hundred eighteen bacterial isolates were obtained from the rhizospheric zone of various crop fields of Gangwon-do, Korea, and screened for antifungal activity against Fusarium wilt (Fusarium oxysporum f. sp. lactucae) in lettuce crop under in vitro and in vivo conditions. In broth-based dual culture assay, fourteen bacterial isolates showed significant inhibition of mycelial growth of F. oxysporium f. sp. lactucae. All of the antagonistic isolates were further characterized for the antagonistic traits under in vitro conditions. The isolates were identified on the basis of biochemical characteristics and confirmed at their species level by 16S rRNA gene sequencing analysis. Arthrobacter sulfonivorans, Bacillus siamensis, Bacillus amyloliquefaciens, Pseudomonas proteolytica, four Paenibacillus peoriae strains, and Bacillus subtilis were identified from the biochemical characterization and 16S rRNA gene sequencing analysis. The isolates EN21 and EN23 showed significant decrease in disease severity on lettuce compared to infected control and other bacterial treatments under greenhouse conditions. Two bacterial isolates, EN4 and EN21, were evaluated to assess their disease reduction and growth promotion in lettuce in field conditions. The consortium of EN4 and EN21 showed significant enhancement of growth on lettuce by suppressing disease caused by F. oxysporum f. sp. lactucae respectively. This study clearly indicates that the promising isolates, EN4 (P. proteolytica) and EN21 (Bacillus siamensis), can be commercialized and used as biofertilizer and/or biopesticide for sustainable crop production.

• 한국콘텐츠학회지
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• 제15권2호
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• pp.21-24
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• 2017

• 스마트미디어저널
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• 제13권8호
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• pp.16-25
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• 2024

Recently, there has been a growing emphasis on identifying both known and unknown diseases in plant disease recognition. In this task, a model trained only on images of known classes is required to classify an input image into either one of the known classes or into an unknown class. Consequently, the capability to recognize unknown diseases is critical for model deployment. To enhance this capability, we are considering three factors. Firstly, we propose a new logits-based scoring function for unknown scores. Secondly, initial experiments indicate that a compact feature space is crucial for the effectiveness of logits-based methods, leading us to employ the AM-Softmax loss instead of Cross-entropy loss during training. Thirdly, drawing inspiration from the efficacy of transfer learning, we utilize a large plant-relevant dataset, PlantCLEF2022, for pre-training a model. The experimental results suggest that our method outperforms current algorithms. Specifically, our method achieved a performance of 97.90 CSA, 91.77 AUROC, and 90.63 OSCR with the ResNet50 model and a performance of 98.28 CSA, 92.05 AUROC, and 91.12 OSCR with the ConvNext base model. We believe that our study will contribute to the community.

• 한국균학회지
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• 제52권1호
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• pp.61-71
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• 2024

버섯 배지에 첨가되는 재료에 따라 변하는 수확 후 배지내의 세균 군집도를 확인하여 더 넓은 재활용 연구에 기여하고자 춘천, 여주, 홍천, 광주, 의령, 아산에서 수집한 표고, 느타리, 새송이버섯의 수확 후 배지를 대상으로 차세대 염기서열 분석을 진행하였다. ASV 값을 기반으로 α-diversity인 Rarefaction, Chao1, Shannon, Gini-Simpson를 분석한 결과, 유일하게 폐면이 혼합되어 있는 느타리버섯 수확 후 배지인 H-NT 처리구의 세균다양성이 매우 풍부하였다. 또한 β-diversity의 WPGMA를 이용하여 처리구간 세균 군집의 유사성을 분석한 결과, 버섯 종류에 따라 유연관계가 가까운 것을 확인하였다. 본 연구를 시작으로 작물 및 토양에 유용한 특정 세균 비율이 높게 분포하고 있는 수확 후 배지를 연구한다면 맞춤형 유기농자재로서의 활용 가능성이 있음을 시사한다.

• 한국전자통신학회논문지
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• 제16권4호
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• pp.719-724
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• 2021

본 논문에서 식물 생산성 향상을 위해 온, 습도뿐만 아니라 조도까지 제어 가능한 스마트팜 동작 특성을 연구하였다. 연구된 스마트팜에서는 각 센서로부터 입력 값을 받아 제어부인 아두이노를 거쳐 제어부들이 동작할 수 있게 설계하였다. 그뿐만 아니라 스마트팜의 편리성을 극대화하기 위해서 블루투스 통신 모듈을 이용하여 모바일 폰에서도 제어가 가능할 수 있게 앱을 설계하였다. 연구를 통해 스마트팜의 자동화 기능이 식물이 자라기에 적합한 환경을 만들 수 있음을 확인할 수 있었다.

• 전기학회논문지
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• 제64권3호
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• pp.375-383
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• 2015

The virtual power plant (VPP) is a new technology to achieve flexibility as well as controllability, like traditional centralized power plants, by integrating and operating different types of distributed energy resources (DER) with the information communication technology (ICT). Though small-sized DERs may not be controlled in a centralized manner, these are more likely to be utilized as power plants for centralized dispatch and participate in the energy trade given that these are integrated into a unified generation profile and certain technical properties such as dispatch schedules, ramp rates, voltage control, and reserves are explicitly implemented. Unfortunately, the VPP has been in a conceptual stage thus far and its common definition has not yet been established. Such a lack of obvious guidelines for VPP may lead to a further challenge of coming up with the business model and reinforcing the investment and technical support for VPP. In this context, this paper would aim to identify the definition of VPP as a critical factor in smart grid and, at the same time, discuss the details required for VPP to actively take part in the electricity market under the smart grid paradigm.

• 농업과학연구
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• 제49권3호
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• pp.483-493
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• 2022

It is important to improve the efficiency of plant breeding and crop yield to fulfill increasing food demands. In plant phenotyping studies, the capability to correlate morphological traits such as plant height, stem diameter, leaf length, leaf width, leaf angle and size of panicle of the plants has an important role. However, manual phenotyping of plants is prone to human errors and is labor intensive and time-consuming. Hence, it is important to develop techniques that measure plant phenotypic traits accurately and rapidly. The aim of this study was to determine the feasibility of point cloud data based on a 3D light detection and ranging (LiDAR) system for plant phenotyping. The obtained results were then verified through manually acquired data from the sorghum samples. This study measured the plant height, plant crown diameter and the panicle height and diameter. The R² of each trait was 0.83, 0.94, 0.90, and 0.90, and the root mean square error (RMSE) was 6.8 cm, 1.82 cm, 5.7 mm, and 7.8 mm, respectively. The results showed good correlation between the point cloud data and manually acquired data for plant phenotyping. The results indicate that the 3D LiDAR system has potential to measure the phenotypes of sorghum in a rapid and accurate way.

• 한국원자력학회:학술대회논문집
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• 한국원자력학회 2003년도 춘계학술발표대회 요약집
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• pp.449.1-449.1
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• 2003