• The Plant Pathology Journal
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• 제39권1호
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• pp.1-20
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• 2023

In the past, rice bakanae was considered an endemic disease that did not cause significant losses in Korea; however, the disease has recently become a serious threat due to climate change, changes in farming practices, and the emergence of fungicide-resistant strains. Since the bakanae outbreak in 2006, its incidence has gradually decreased due to the application of effective control measures such as hot water immersion methods and seed disinfectants. However, in 2013, a marked increase in bakanae incidence was observed, causing problems for rice farmers. Therefore, in this review, we present the potential risks from climate change based on an epidemiological understanding of the pathogen, host plant, and environment, which are the key elements influencing the incidence of bakanae. In addition, disease management options to reduce the disease pressure of bakanae below the economic threshold level are investigated, with a specific focus on resistant varieties, as well as chemical, biological, cultural, and physical control methods. Lastly, as more effective countermeasures to bakanae, we propose an integrated disease management option that combines different control methods, including advanced imaging technologies such as remote sensing. In this review, we revisit and examine bakanae, a traditional seed-borne fungal disease that has not gained considerable attention in the agricultural history of Korea. Based on the understanding of the present significance and anticipated risks of the disease, the findings of this study are expected to provide useful information for the establishment of an effective response strategy to bakanae in the era of climate change.

• 산업경영시스템학회지
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• 제45권4호
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• pp.180-186
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• 2022

Agrophotovoltaic (APV) system is an integrated system producing crops as well as solar energy. Because crop production underneath Photovoltaic (PV) modules requires delicate management of crops, smart farming equipment such as real-time remote monitoring sensors (e.g., soil moisture sensors) and micro-climate monitoring sensors (e.g., thermometers and irradiance sensors) is installed in the APV system. This study aims at introducing a decision support system (DSS) for smart farming in an APV system. The proposed DSS is devised to provide a mobile application service, satellite image processing, real-time data monitoring, and performance estimation. Particularly, the real-time monitoring data is used as an input of the DSS system for performance estimation of an APV system in terms of production yields of crops and monetary benefit so that a data-driven function is implemented in the proposed system. The proposed DSS is validated with field data collected from an actual APV system at the Jeollanamdo Agricultural Research and Extension Services in South Korea. As a result, farmers and engineers enable to efficiently produce solar energy without causing harmful impact on regular crop production underneath PV modules. In addition, the proposed system will contribute to enhancement of the smart farming technology in the field of agriculture.

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2023년도 학술발표회
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• pp.168-168
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• 2023

The frequent occurrence of cyanobacterial harmful algal blooms (CHABs) in inland waters under climate change seriously damages the ecosystem and human health and is becoming a big problem in South Korea. Satellite remote sensing is suggested for effective monitoring CHABs at a larger scale of water bodies since the traditional method based on sparse in-situ networks is limited in space. However, utilizing a standalone variable of satellite reflectances in common CHABs dual-models, which relies on both chlorophyll-a (Chl-a) and phycocyanin or cyanobacteria cells (Cyano-cell), is not fully beneficial because their seasonal variation is highly impacted by surrounding meteorological and bio-environmental factors. Along with the development of Artificial Intelligence (AI), monitoring CHABs from space with analyzing the effects of environmental factors is accessible. This study aimed to investigate the potential application of AI in the dual-model strategy (Chl-a and Cyano-cell are output parameters) for monitoring seasonal dynamics of CHABs from satellites over Korean inland waters. The Sentinel-3 satellite was selected in this study due to the variety of spectral bands and its unique band (620 nm), which is sensitive to cyanobacteria. Via the AI-based feature selection, we analyzed the relationships between two output parameters and major parameters (satellite water-leaving reflectances at different spectral bands), together with auxiliary (meteorological and bio-environmental) parameters, to select the most important ones. Several AI models were then employed for modelling Chl-a and Cyano-cell concentration from those selected important parameters. Performance evaluation of the AI models and their comparison to traditional semi-analytical models were conducted to demonstrate whether AI models (using water-leaving reflectances and environmental variables) outperform traditional models (using water-leaving reflectances only) and which AI models are superior for monitoring CHABs from Sentinel-3 satellite over a Korean inland water body.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제17권3호
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• pp.958-979
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• 2023

Due to laws, regulations, privacy, etc., between 70-90 percent of providers do not share medical data, forming a "data island". It is essential to collaborate across multiple institutions without sharing patient data. Most existing methods adopt distributed learning and centralized federal architecture to solve this problem, but there are problems of resource heterogeneity and data heterogeneity in the practical application process. This paper proposes a collaborative deep learning modelling method based on the blockchain network. The training process uses encryption parameters to replace the original remote source data transmission to protect privacy. Hyperledger Fabric blockchain is adopted to realize that the parties are not restricted by the third-party authoritative verification end. To a certain extent, the distrust and single point of failure caused by the centralized system are avoided. The aggregation algorithm uses the FedProx algorithm to solve the problem of device heterogeneity and data heterogeneity. The experiments show that the maximum improvement of segmentation accuracy in the collaborative training mode proposed in this paper is 11.179% compared to local training. In the sequential training mode, the average accuracy improvement is greater than 7%. In the parallel training mode, the average accuracy improvement is greater than 8%. The experimental results show that the model proposed in this paper can solve the current problem of centralized modelling of multicenter data. In particular, it provides ideas to solve privacy protection and break "data silos", and protects all data.

• 한국IT서비스학회지
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• 제22권2호
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• pp.71-92
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• 2023

Globally, under the leadership of advanced ICT countries, the private sector is promoting various policies to promote the digital transformation of public services. Looking at the research trend, design of public service indicators, development of evaluation system, and empirical research are being carried out steadily, but there are insufficient research cases on models in which the private sector participates in the planning, development, and operation of public services. In this study, Private-centric digital public service suitability evaluation indicators were discovered through interviews with experts in various fields, and weights for each indicator were analyzed through AHP evaluation. In addition, by applying the analysis results to 18 digital public services on a trial basis, the importance and priority of evaluation indicators for each service were derived, and at the same time, the evaluation framework was designed and applied to diagnose implications. As a result of the study, 'social utility', 'corporate acceptability', and 'public acceptability' were selected as the top three indicators of suitability evaluation. At this time, it was analyzed that the weight of the 'company acceptability' index, which includes sub-indices such as 'service profitability', 'service scalability', and 'private initiative possibility', was the highest among the three top indicators. As a result of the demonstration for public services, "IoT facility unmanned remote monitoring service", "blockchain real estate transaction service", and "digital twin disaster prediction service" were evaluated as the most suitable public services for the transition to the private sector.

• 한국가스학회지
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• 제27권2호
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• pp.57-64
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• 2023

가스계량기의 검침방식이 발전하면서 원격검침이 가능한 스마트 가스 계량기(누출점검용 계량기 및 다기능 안전 계량기)가 사용되고 있다. 이러한 계량기는 부가기능으로 수집하는 유량 및 압력 데이터를 활용하여 누출 판단을 하는 기능이 있다. 유량 데이터를 이용한 누출판단 기능은 실제 현장에서 유효한 사례가 있지만 압력 데이터 기반 누출 판단 기준은 누출로 인한 압력 값 변화뿐만 아니라 여러 요인(정압기 압력 크기, 인접 계량기 연계, 인접 주택 사용량, 계량기 위치 등)으로 압력 크기 변화(레벨)가 있는 문제점이 있다. 본 논문에서는 스마트 가스계량기에서 수집되는 압력데이터를 활용하여 누출여부를 판단 할 수 있는 기법으로 압력 데이터 전처리 방법과 누출 여부 관련 압력 값 범위 기준, 누출판단 기법 및 적용 사례 검증을 통해 개발하였다.

• 융합보안논문지
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• 제22권3호
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• pp.3-11
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• 2022

갈수록 정교해지는 사이버 위협, 클라우드 도입의 가속, 코로나19 팬데믹으로 인한 원격 및 하이브리드 근무환경 도입 등으로 인하여 많은 기업이 경계 안에 있는 모든 것을 암묵적으로 신뢰하는 전통적인 보안 모델이 경계가 존재하지 않고 데이터와 사용자가 갈수록 탈중앙화되는 오늘날 환경에 적합하지 않다는 사실이 부각되면서 제로 트러스트라(Zero Trust)는 개념이 갈수록 주목받고 있다. 제로 트러스트는 '아무도 신뢰하지 않는다'는 전제의 사이버 보안 모델로, 전체 시스템에서 안전한 영역 또는 이용자는 전무하다는 것을 원칙으로 내부 이용자도 검증을 거치며, 네트워크 접속 환경에 따른 정보 접근 범위도 차등 및 최소화하는 방안이다. 코로나19 팬데믹으로 인하여 재택근무가 일상화되고, 기존 사이버 보안방안이 한계에 부딪히면서 제로 트러스트(Zero Trust) 기술이 한층 더 주목을 받고 있다. 이에 따라 우리 정부도 NIST 표준을 참고로 제로 트러스트 도입 시 국내 공공 및 민간부문의 수용 가능성 현황, 개선이 필요한 과제 등을 점검할 것으로 예상된다. 이 논문에서는 이러한 제로 트러스트와 제로 트러스트의 기본원리, 철학, 고려사항에 대해 설명하고, 제로 트러스트의 기술을 접목시켜 보안을 강화하는 실무적인 기초 방안에 대하여 제시한다.

• 한국컴퓨터정보학회논문지
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• 제28권4호
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• pp.113-120
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• 2023

스마트 팜은 IoT 기술과 인공지능 기술이 접목되면서 농작물에 투입되는 노동력·에너지·양분 등을 최소화는 연구가 꾸준히 증가하고 있는 상황이다. 그러나, 스마트 팜에서 농작물의 생육 정보를 효율적으로 관리하는 연구는 현재까지 미진한 상태이다. 본 논문에서는 스마트 팜에 자율 센서를 적용하여 농작물의 생육 정보를 효율적으로 모니터링할 수 있는 관리 기법을 제안한다. 제안 기법은 농작물의 생육 정보를 자율 센서를 통해 수집한 후 생육 정보를 농작물 재배에 재활용하는데 초점을 갖는다. 특히, 제안 기법은 농작물의 생육 정보를 한 슬롯으로 할당한 후 로드밸런싱을 수행하도록 농작물별로 가중치를 부여하며, 농작물의 생육 정보 간의 간섭을 서로 최소화한다. 또한, 제안 기법은 농작물의 생육 정보를 4단계 (센싱 탐지 단계, 센싱 전송 단계, 애플리케이션 처리 단계, 데이터 관리 단계 등)로 처리할 때, 농작물의 중요 관리점을 실시간으로 전산화하기 때문에 관리 기준 이외의 경우에는 즉각적인 경고 시스템이 동작한다. 성능평가 결과, 자율 센서의 정확도는 기존 기법보다 평균 22.9%의 향상된 결과를 얻었으며, 효율성은 기존 기법보다 평균 16.4% 향상된 결과를 얻었다.

• 한국환경복원기술학회지
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• 제26권6호
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• pp.85-96
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• 2023

This study proposes a method for forest vegetation monitoring using high-resolution aerial imagery captured by unmanned aerial vehicles(UAV) and deep learning technology. The research site was selected in the forested area of Mountain Dogo, Asan City, Chungcheongnam-do, and the target species for monitoring included Pinus densiflora, Quercus mongolica, and Quercus acutissima. To classify vegetation species at the pixel level in UAV imagery based on characteristics such as leaf shape, size, and color, the study employed the semantic segmentation method using the prominent U-net deep learning model. The research results indicated that it was possible to visually distinguish Pinus densiflora Siebold & Zucc, Quercus mongolica Fisch. ex Ledeb, and Quercus acutissima Carruth in 135 aerial images captured by UAV. Out of these, 104 images were used as training data for the deep learning model, while 31 images were used for inference. The optimization of the deep learning model resulted in an overall average pixel accuracy of 92.60, with mIoU at 0.80 and FIoU at 0.82, demonstrating the successful construction of a reliable deep learning model. This study is significant as a pilot case for the application of UAV and deep learning to monitor and manage representative species among climate-vulnerable vegetation, including Pinus densiflora, Quercus mongolica, and Quercus acutissima. It is expected that in the future, UAV and deep learning models can be applied to a variety of vegetation species to better address forest management.

• 융합신호처리학회논문지
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• 제24권4호
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• pp.241-248
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• 2023

최근 드론의 짧은 역사에도 불구하고 최근 드론의 활용 분야는 매우 다양한 영역과 분야에서 다양한 용도로 활용되고 있다. 이와 같이 수년 동안 다양한 형태의 드론 출현으로 드론에 대한 새로운 정의를 넓은 의미에서 유선 또는 무선으로 조종되는 유무선 조종 운동체라 하는 것이 가장 적절한 정의라고 생각이 된다. 본 논문에서는 이처럼 빠르게 발전하는 드론에 대해 항공 드론 뿐만 아니라 무인 수상정, 무인 잠수정 등 다양한 드론의 역사와 활용 분야 및 미래의 전망에 대해 관련 논문 및 다양한 매체와 자료를 통해서 살펴 봄으로서 드론에 관한 연구 및 개발과 사용하고자 하는 독자들에게 도움을 주고자 한다. 본 논문을 통해 이러한 드론들은 향후에도 지속적으로 다양한 분야에서 활용될 것이고, 미래 개발 전망 또한 끊임없이 이어질 것이라 기대한다. 그러나 국내 드론 기술과 드론 산업의 발전을 위해서는 정부의 드론 관련 규제에 대한 과감한 개혁이 필요할 것으로 사료된다.