• Proceedings of the Korea Information Processing Society Conference
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• 2015.10a
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• pp.1431-1434
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• 2015

24시간 모니터링 환경에서 돈사 내 개별 돼지들의 상태를 자동으로 탐지하는 연구는 효율적인 돈사 관리 측면에서 중요한 이슈로 떠오르고 있다. 특히 돼지 호흡기 질병은 전염성이 매우 강하여, 막대한 경제적 손실을 최소화하기 위해서는 조기에 탐지하는 것이 매우 중요하다. 본 논문에서는 마이크를 통한 소리 정보뿐 아니라 카메라를 통한 영상 정보를 동시에 활용하여 호흡기 질병에 걸린 개별 돼지를 조기에 탐지하는 방법을 제안한다. 즉, 돈사의 천장에 설치된 마이크로부터 호흡기 질병에 걸린 소리 정보를 먼저 탐지한 후 카메라로부터 획득된 영상 정보의 MHI 분석을 수행하여 호흡기 질병에 걸린 돼지를 특정한다. 실험결과, 소리와 영상 정보를 동시에 활용하는 제안 방법을 이용하여 호흡기 질병에 걸린 돼지를 특정할 수 있음을 확인하였다.

• Journal of fish pathology
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• v.32 no.1
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• pp.29-35
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• 2019

A monitoring was performed to survey the mortalities that had occurred in the aquaculture farms of olive flounder (Paralichthys olivaceus) in South Korea from 2015 to 2017. The indirect inquiry for entire farms and the sample survey for selected farms were carried out. The aquatic organism disease inspectors, who have a national license for the diagnosis and prevention of aquatic organism diseases and a have close relationship with the farms, investigated the rates and causes of mortalities according to the standard manual. The mortality rate by sample survey of farms in 2015, 2016, and 2017 were 24.78% (Chunnam: 17.86%, Jeju: 28.69), 30.19% (Chunnam: 24.45%, Jeju: 32.65), and 21.59% (Chunnam: 10.57%, Jeju: 26.00%), respectively. The major cause of mortality was scuticociliatosis, and the mortality caused by viral hemorrhagic septicemia and emaciation disease (Jeju) were also high. Our results can contribute to effective establishment prevention of epidemics system and acquired status as a disease-cleansing country.

• Proceedings of the Korea Information Processing Society Conference
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• 2007.05a
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• pp.1301-1302
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• 2007

유비쿼터스 시대를 맞이해서 휴대용 진단 진료 기기를 환자가 쉽게 휴대 및 착용해서 환자의 질병 및 건강 상태를 모니터링 하여 위험한 상황을 미리 예측, 통지가 가능한 시스템을 발전시켜야 할 필요성이 대두되고 있다. 이를 위하여 다양한 특성을 가진 휴대용 의료 계측 기기 센서들을 환자의 신체에 부착하고 다양한 센서들이 네트워크를 형성하여 인터넷과 통신하는 것은 물론 이동이 가능해야 한다. 즉, 센서 네트워크 기술과 이동성 기술이 접목된 네트워킹 기술이 필요하지만 아직까지 실질적인 적용에 대한 구체적인 연구는 없는 형편이다. 따라서 본 논문에서는 이러한 요구사항을 만족시키는 U-헬스케어 시스템을 구축하기 위해 각 센서 노드에 IPv6 를 적용하여 항상 인터넷에 연결되어 실시간 모니터링이 가능함과 동시에 네트워크 단위의 이동성을 지원하는 프로토콜과 연동하는 시나리오와 구조를 제시한다.

• Proceedings of the Korea Information Processing Society Conference
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• 2011.11a
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• pp.1126-1128
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• 2011

병원 이외의 환경, 특히 댁내 기반의 헬스 모니터링 관련 연구는 최근 헬스케어 시스템 관련 연구자 및 개발자들의 많은 관심을 받고 있다. 심장병이나 당뇨병 같은 만성질환을 앓고 있는 경우에는 생리학적 요소들을 일상 생활 중 지속적으로 모니터링 하는 과정이 특히 중요하다. 본 논문에서는 댁내 환경에서 서비스되고 있는 헬스케어 시스템과 병원에서 운용되고 있는 헬스케어 시스템과의 연동을 지원하고, 클라우드 환경을 활용한 생리학적 데이터 분석을 지원하는 통합 헬스케어 시스템의 구조를 제안한다. 또한, 제안된 통합 헬스케어 시스템의 구조를 활용한 질병진단 시나리오도 제시한다.

• Journal of fish pathology
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• v.27 no.2
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• pp.91-97
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• 2014

Since the "Aquatic life disease control act" was established in 2009, we have monitored OIE notifiable and legally designated diseases which are associated with white shrimp Litopenaeus vannamei but are as yet outbreak in South Korea. We had monitored only two viral diseases of YHD and IMN, but further added IHHN, TS and WTD in an attempt to reinforce monitoring as a countermeasure against the increasing possibility of imported diseases led by continuous growth in global fisheries trade. We also increased the number of monitoring areas, and shrimp farms. In 2013, we examined a total of 2,650 white shrimp from 29 hatcheries and farms to check whether they were infected with any of the 5 diseases (YHD, IMN, IHHN, TS, WTD). The result showed that none of the samples contained the viruses. To regulation of the exotic diseases from landing in our country and to strengthen prevention, management and control of the diseases on a national level, we must continue the surveillance monitoring of the diseases.

• Journal of Convergence Society for SMB
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• v.6 no.4
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• pp.79-84
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• 2016

A novel diagnosis scheme PCADP(personalized computer aided diagnosis probability) is proposed to overcome the problems mentioned above. PCADP scheme is a personalized diagnosis method based on ontology and it makes the bio-data analysis just a 'process' in the Smart healthcare service system. In addition, we offer a semantics modeling of the smart healthcare ontology framework in order to describe smart healthcare data and service specifications as meaningful representations based on this PCADP. The PCADP scheme is a kind of statistical diagnosis method which has real-time processing, characteristics of flexible structure, easy monitoring of decision process, and continuous improvement.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.20 no.6
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• pp.1189-1194
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• 2016

While increasing the convenience of life is a high population BMI (Body Mass Index) is increasing rapidly. Accordingly, the development of the monitoring system to manage and prevent obesity is the time that is required. But most of the monitoring system, the less information it receives management and show to have only simple information calculated this was a low efficiency problem. Also Users with normal and disease Management accuracy is low. In this paper shows the user in a graph of Body Mass Index, BMR (Basal metabolic rate) divided by grade increased accuracy for users to manage their own. Also represented by recovery with exercise machines you used, select a balanced movement mechanism, expressed as a Kcal consumption. If the graph recent data show only increased the visibility. We developed an efficient web-based monitoring system for design a exercise plan.

• Journal of the Korea Society of Computer and Information
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• v.27 no.11
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• pp.157-163
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• 2022

In this paper, we propose to develop a Bluetooth Health Device Profile (HDP)-based smartphone system to utilize it for early detection of urinary tracts diseases that occur a lot in cats. Therefore, based on Bluetooth HDP, we developed a device and mobile application system (Mycatner®) that can monitor cat activity, toilet usage, urinary disease, and health status, and evaluated its availability to monitor cat health status. The specific feature of this system is that it can measure the number of cat urination frequencies to identify abnormal conditions suspected of urinary tract diseases early, and second, it can be tested with urine test paper and shared with animal hospitals, reducing time and cost. As a result, it is evaluated that the developed device capable of wireless monitoring the urinary system health status of cats is the first in our knowledge.

• Journal of fish pathology
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• v.36 no.2
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• pp.239-250
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• 2023

Disease monitoring was conducted to investigate the recent disease occurrence in Japanese eels (Anguilla japonica). Between May 2021 and March 2022, an investigation was conducted on eels from seven farms experiencing mortality. JEECV (Japanese eel endothelial cells-infecting virus) was detected in all examined farms, each exhibiting co-infections with 1 or 2 bacteria, including Edwardsiella anguillarum, E. piscisida, Aeromonas sp., Citrobacter freundii, Lactococcus garviae, or Vibrio sp. From March 2022 to October 2023, monthly periodic inspections were carried out at a farm in Yeonggwang, Jeollanam-do, for a total of 22 times. JEECV was detected in 10 out of 22 times, even when mortality was not recorded. Bacteria such as E. anguillarum, C. freundii, Aeromonas sp., and Vibrio sp. were isolated, but consistent clinical signs of liver abscess and hemorrhagic lesions were only recognized in fish infected with E. anguillarum. Other bacteria were often isolated from apparently healthy fish. In conclusion, mortality in eel farms frequently occurs due to co-infections of JEECV with bacteria rather than JEECV alone. Therefore, to reduce eel mortality, it is crucial to decrease co-infections, with a particular emphasis of JEECV and E. anguillarum.

• Smart Media Journal
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• v.11 no.4
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• pp.62-68
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• 2022

To prevent the spread of disease in aquaculture, it is a need for a system to predict fish diseases while monitoring the water quality environment and the status of growing fish in real time. The existing research in predicting fish disease were image processing techniques. Recently, there have been more studies on disease prediction methods through deep learning techniques. This paper introduces the research results on how to predict diseases of Paralichthys Olivaceus with deep learning technology in aquaculture. The method enhances the performance of disease detection rates by including data augmentation and pre-processing in camera images collected from aquaculture. In this method, it is expected that early detection of disease fish will prevent fishery disasters such as mass closure of fish in aquaculture and reduce the damage of the spread of diseases to local aquaculture to prevent the decline in sales.