• Title/Summary/Keyword: 모니터링 및 진단 시스템

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Cat Monitoring and Disease Diagnosis System based on Deep Learning (딥러닝 기반의 반려묘 모니터링 및 질병 진단 시스템)

  • Choi, Yoona;Chae, Heechan;Lee, Jonguk;Park, Daihee;Chung, Yongwha
    • Journal of Korea Multimedia Society
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    • v.24 no.2
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    • pp.233-244
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    • 2021
  • Recently, several ICT-based cat studies have produced some successful results, according to academic and industry sources. However, research on the level of simply identifying the cat's condition, such as the behavior and sound classification of cats based on images and sound signals, has yet to be found. In this paper, based on the veterinary scientific knowledge of cats, a practical and academic cat monitoring and disease diagnosis system is proposed to monitor the health status of the cat 24 hours a day by automatically categorizing and analyzing the behavior of the cat with location information using LSTM with a beacon sensor and a raspberry pie that can be built at low cost. Validity of the proposed system is verified through experimentation with cats in actual custody (the accuracy of the cat behavior classification and location identification was 96.3% and 92.7% on average, respectively). Furthermore, a rule-based disease analysis system based on the veterinary knowledge was designed and implemented so that owners can check whether or not the cats have diseases at home (or can be used as an auxiliary tool for diagnosis by a pet veterinarian).

Implementation of Self Diagnostics Low-power Embedded Linux System using Telematics (텔레매틱스을 통한 자가진단 저전력 임베디드 리눅스 시스템 구현)

  • Ju, Jae-han
    • Journal of Advanced Navigation Technology
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    • v.21 no.3
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    • pp.300-305
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    • 2017
  • It is necessary to establish a system suitable for the driving vehicle so that it can effectively search for and modify various data anywhere and anytime by effectively linking communication with the computer system in the running vehicle and to control the equipment properly for smooth operation on a limited platform do. Also, vehicle CAN communication is used to extract system engine information, and data is transmitted using ZigBee for this information transmission. Therefore, OBD-II protocol, which is provided by the vehicle itself, is used for vehicle CAN to obtain vehicle status information and exhaust gas using various sensor information of the vehicle and O2 sensor value, and transmits it to the ZigBee main control system. In this study, we implemented a system that can reduce the battery load damage to the maximum by reducing the power consumption to the maximum, and to monitor the internal state of the vehicle through ZigBee communication with the embedded system for low power vehicles.

A Diet Prescription System for U-Healthcare Personalized Services (유헬스케어 개인화 서비스를 위한 식단 처방 시스템)

  • Kim, Jong-Hun;Park, Jee-Song;Jung, Eun-Young;Park, Dong-Kyun;Lee, Young-Ho
    • The Journal of the Korea Contents Association
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    • v.10 no.2
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    • pp.111-119
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    • 2010
  • U-Healthcare provides healthcare and medical services, such as prevention, diagnosis, treatment, and follow-up services whenever and wherever it is needed, and its ultimate goal is to improve quality of life. This study defines the figure of U-Healthcare personalized services for providing U-Healthcare personalized services and proposes a healthcare model. A diet prescription system for personalized services can draw customized calories and rates of nutrition factors and represent a personalized diet through analyzing the personal preference in foods. This system changes the personal preference by monitoring the diet selection behavior of users. Also, this system is designed to be interactively operated with some sensors and devices in various environments using Java-based OSGi middleware.

Case Analysis for Introduction of Machine Learning Technology to the Mining Industry (머신러닝 기술의 광업 분야 도입을 위한 활용사례 분석)

  • Lee, Chaeyoung;Kim, Sung-Min;Choi, Yosoon
    • Tunnel and Underground Space
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    • v.29 no.1
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    • pp.1-11
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    • 2019
  • This study investigated use cases of machine learning technology in domestic medical, manufacturing, finance, automobile, urban sectors and those in overseas mining industry. Through a literature survey, it was found that the machine learning technology has been widely utilized for developing medical image information system, real-time monitoring and fault diagnosis system, security level of information system, autonomous vehicle and integrated city management system. Until now, the use cases have not found in the domestic mining industry, however, several overseas projects have found that introduce the machine learning technology to the mining industry for improving the productivity and safety of mineral exploration or mine development. In the future, the introduction of the machine learning technology to the mining industry is expected to spread gradually.

Policy-Based Emergency Bio Data Transmission Architecture for Smart Healthcare Service (스마트 헬스케어 서비스를 위한 정책기반 응급 생체 데이터 전송 구조)

  • Chun, Seung-Man;Nah, Jae-Wook;Lee, Ki-Chun;Park, Jong-Tae
    • Journal of the Institute of Electronics Engineers of Korea TC
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    • v.48 no.10
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    • pp.43-52
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    • 2011
  • In this paper, we propose the architecture of the policy-based emergency bio data transmission for the smart healthcare service. the medical staff can quickly and accurately monitor the emergency bio data of the remote patient through the proposed architecture. The proposed system consists of three parts: IEEE 11073-based agents and managers performing the aggregation function and transmission function of the bio data; the emergency management server performing the converting function between IEEE 11073 and HL7 and auto-diagnosis function of the policy-based; HL7 medical system based on HL7. Finally, by implementing the proposed system, we shows that the aggregation of the bio data and management of the emergency bio data in the smart healthcare service are possible.

Plant-wide On-line Monitoring and Diagnosis Based on Hierarchical Decomposition and Principal Component Analysis (계층적 분해 방법과 PCA를 이용한 공장규모 실시간 감시 및 진단)

  • Cho Hyun-Woo;Han Chong-hun
    • Journal of the Korean Institute of Gas
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    • v.1 no.1
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    • pp.27-32
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    • 1997
  • Continual monitoring of abnormal operating conditions i a key issue in maintaining high product quality and safe operation, since the undetected process abnormality may lead to the undesirable operations, finally producing low quality products, or breakdown of equipment. The statistical projection method recently highlighted has the advantage of easily building reference model with the historical measurement data in the statistically in-control state and not requiring any detailed mathematical model or knowledge-base of process. As the complexity of process increases, however, we have more measurement variables and recycle streams. This situation may not only result in the frequent occurrence of process Perturbation, but make it difficult to pinpoint trouble-making causes or at most assignable source unit due to the confusing candidates. Consequently, an ad hoc skill to monitor and diagnose in plat-wide scale is needed. In this paper, we propose a hierarchical plant-wide monitoring methodology based on hierarchical decomposition and principal component analysis for handling the complexity and interactions among process units. This have the effect of preventing special events in a specific sub-block from propagating to other sub-blocks or at least delaying the transfer of undesired state, and so make it possible to quickly detect and diagnose the process malfunctions. To prove the performance of the proposed methodology, we simulate the Tennessee Eastman benchmark process which is operated continuously with 41 measurement variables of five major units. Simulation results have shown that the proposed methodology offers a fast and reliable monitoring and diagnosis for a large scale chemical plant.

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Development of Smart Concrete adopting Light-emitting Diode and the Resistance Property of Electric Fuse (LED와 전기 저항적 특성을 적용한 스마트 콘크리트의 개발)

  • Kim, Wha-Jung;Kim, Ie-Sung;Kim, Boung-Yong;Ko, Kwan-Ho
    • Proceedings of the Korea Concrete Institute Conference
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    • 2008.04a
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    • pp.173-176
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    • 2008
  • Use of concrete has undoubtedly become widespread in construction. Sensors are used to add functional characteristics to concrete. Self-diagnosing, smart concrete is also being developed. Development of these functional materials and structures will play an important role in protecting buildings and structures against external factors brought about by unusual weather among others. In this study, the innovative measurement system is presented where material damages and internal stress can simply be detected against the compressive and bending force of the structure using light-emitting diode and the resistance property of electric fuse.

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Safety Assessment and Behavior Control System using Monitoring of Segmental PSC Box Girder Bridges during Construction (세그멘탈 PSC박스거더교량의 시공간 계측모니터링을 통한 확률적 구조안정성 평가 및 제어 시스템)

  • Shin, Jae-Chul;Cho, Hyo-Nam;Park, Kyung-Hoon;Bae, Yong-Il
    • Journal of the Korea institute for structural maintenance and inspection
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    • v.5 no.3
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    • pp.191-201
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    • 2001
  • In spite of the increasing construction of segmental PSC box girder bridges, the techniques associated with real-time monitoring, construction control and safety assessment during construction have been less developed compared with the construction techniques. Thus, the development of an integrated system including real-time measurement and monitoring, control and safety assessment system during construction is necessary fur more safe and precise construction of the bridges. This study presents a prototype integrated monitoring system for preventing abnormal behavior and accidents under construction stages, that consist of behavior control system for precise construction, reliability-based safety assessment system, and structural analysis. Also, a prototype software system is developed on the basis of the proposed model. It is successfully applied to the Sea-Hae Grand Bridge built by FCM. The integrated system model and software system can be utilized for the safe and precise construction of segmental PSC bridges during construction.

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The Power Line Deflection Monitoring System using Panoramic Video Stitching and Deep Learning (딥 러닝과 파노라마 영상 스티칭 기법을 이용한 송전선 늘어짐 모니터링 시스템)

  • Park, Eun-Soo;Kim, Seunghwan;Lee, Sangsoon;Ryu, Eun-Seok
    • Journal of Broadcast Engineering
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    • v.25 no.1
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    • pp.13-24
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    • 2020
  • There are about nine million power line poles and 1.3 million kilometers of the power line for electric power distribution in Korea. Maintenance of such a large number of electric power facilities requires a lot of manpower and time. Recently, various fault diagnosis techniques using artificial intelligence have been studied. Therefore, in this paper, proposes a power line deflection detect system using artificial intelligence and computer vision technology in images taken by vision system. The proposed system proceeds as follows. (i) Detection of transmission tower using object detection system (ii) Histogram equalization technique to solve the degradation in image quality problem of video data (iii) In general, since the distance between two transmission towers is long, a panoramic video stitching process is performed to grasp the entire power line (iv) Detecting deflection using computer vision technology after applying power line detection algorithm This paper explain and experiment about each process.

The Development of Automatic Chemical Processing System for $^{67}Ga$ Production ($^{67}Ga$ 생산용 화학처리 자동화 장치 개발)

  • Lee, Dong-Hoon;Kim, Yoon-Jong;Suh, Yong-Sup;Yang, Seung-Dae;Chun, Kwon-Soo;Hur, Min-Goo;Yun, Yong-Ki;Hong, Seung-Hong
    • Journal of Radiation Protection and Research
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    • v.28 no.1
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    • pp.25-33
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    • 2003
  • The automatic system for $^{67}Ga$ production using for the diagnosis of malignant tumor has been developed. A solvent extraction and an ion exchange chromatography were used for the separation $^{67}Ga$ from the irradiated enriched $^{68}Zn$. This system consisted of a solvent separation unit which was composed of micro conductivity cells, air supply tubes, solvent transfer tubes, solenoid valves and glasses, a PLC based controller and a PMU user interface unit for automation. The radiation exposure to the workers and the production time can both be reduced by employing this system during the $^{67}Ga$ production phase. After all, the mass production of $^{67}Ga$ with high efficiency was possible.