• 중소기업융합학회논문지
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• 제6권4호
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• pp.79-84
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• 2016

본 논문에서는 스마트 헬스케어 서비스 시스템의 바이오 데이터 분석 과정을 프로세스로 해석하기 위하여, 온톨로지 기반 통계학적 개인 맞춤형 질병예측 기법인 PCADP(Personalized Computer Aided Diagnosis Probability)를 제안하였다. 또한 이러한 개인 맞춤형 질병예측 기법을 바탕으로 스마트 헬스케어 데이터 및 헬스케어 서비스 명세의 의미 있는 표현을 위하여 헬스케어 온톨로지 프레임워크를 시맨틱스형으로 모델링하였다. PCADP 기법은 스마트 헬스케어 환경에서 개인 맞춤형 판별 기법이 갖추어야 할 조건인 실시간 처리, 유연한 구조, 판별과정의 모니터링, 지속적인 개선 등에 부합하는 통계학적 질병예측 기법임을 확인하였다.

• 대한임베디드공학회논문지
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• 제14권4호
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• pp.187-195
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• 2019

In the fourth industrial revolution era, various commercial smart platforms for smart system implementation are being developed and serviced. However, since most of the smart platforms have been developed for general purposes, they are difficult to apply / utilize because they cannot satisfy the requirements of real-time data management, data visualization and data storage of smart factory system. In this paper, we implemented an open source based smart manufacturing big data platform that can manage highly efficient / reliable data integration for the diagnosis diagnostic system of manufacturing robots.

• Journal of information and communication convergence engineering
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• 제6권2호
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• pp.207-212
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• 2008

There are several sensors in the liquid cargo ship. In the liquid cargo ship, we can get values from various sensors that are level sensor, temperature sensor, pressure sensor, oxygen sensor, VOCs sensor, high overfill sensor, etc. It is important to guarantee the reliability of sensors. In order to guarantee the reliability of sensors, we have to study the diagnosis of sensor fault. The technology of smart sensor is widely used. In this paper, the technology of smart sensor is applied to diagnosis of level sensor fault for liquid cargo ship. In order to diagnose sensor fault and find the sensor position, in this paper, we proposed algorithms of diagnosis of sensor fault using independent sensor diagnosis unit and self fault diagnosis using sensor modeling. Proposed methods are demonstrated by experiment and simulation. The results show that the proposed approach is useful. Proposed methods are useful to develop smart level sensor.

• International Journal of Computer Science & Network Security
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• 제22권7호
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• pp.1-12
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• 2022

The current progression in the Internet of Things (IoT) and Machine Learning (ML) based technologies converted the traditional healthcare system into a smart healthcare system. The incorporation of IoT and ML has changed the way of treating patients and offers lots of opportunities in the healthcare domain. In this view, this research article presents a new IoT and ML-based disease diagnosis model for the diagnosis of different diseases. In the proposed model, vital signs are collected via IoT-based smart medical devices, and the analysis is done by using different data mining techniques for detecting the possibility of risk in people's health status. Recommendations are made based on the results generated by different data mining techniques, for high-risk patients, an emergency alert will be generated to healthcare service providers and family members. Implementation of this model is done on Anaconda Jupyter notebook by using different Python libraries in it. The result states that among all data mining techniques, SVM achieved the highest accuracy of 0.897 on the same dataset for classification of Parkinson's disease.

• 산업경영시스템학회지
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• 제42권3호
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• pp.25-38
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• 2019

This study is to develop a diagnostic model for the effective introduction of smart factories in the manufacturing industry, to diagnose SMEs that have difficulties in building their own smart factory compared to large enterprise, to identify the current level and to present directions for implementation. IT, AT, and OT experts diagnosed 18 SMEs using the "Smart Factory Capacity Diagnosis Tool" developed for smart factory level assessment of companies. They analyzed the results and assessed the level by smart factory diagnosis categories. Companies' smart factory diagnostic mean score is 322 out of 1000 points, between 1 level (check) and 2 level (monitoring). According to diagnosis category, Factory Field Basic, R&D, Production/Logistics/Quality Control, Supply Chain Management and Reference Information Standardization are high but Strategy, Facility Automation, Equipment Control, Data/Information System and Effect Analysis are low. There was little difference in smart factory level depending on whether IT system was built or not. Also, Companies with large sales amount were not necessarily advantageous to smart factories. This study will help SMEs who are interested in smart factory. In order to build smart factory, it is necessary to analyze the market trends, SW/ICT and establish a smart factory strategy suitable for the company considering the characteristics of industry and business environment.

• 한국소음진동공학회:학술대회논문집
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• 한국소음진동공학회 2008년도 춘계학술대회논문집
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• pp.809-816
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• 2008

With increasing demands for reducing cost of maintenance which can detect machine fault automatically; low cost and intelligent functionality sensors are required. Rapid developments, in semiconductor, computing, and communication have led to a new generation of sensor called "smart" sensors with functionality and intelligence. The purpose of this research is comparison of machine fault classification between general analyzer signals and smart sensor signals. Three types of sensors are used in induction motors faults diagnosis, which are vibration, current and flux. Classification results are satisfied.

• 전기학회논문지P
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• 제67권3호
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• pp.160-167
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• 2018

In this paper, a black box, which is provided the reliability and user safety of home battery energy storage system connected with solar energy generation, is developed. In the developed scheme, a status and diagnosis data of battery management system, power conditioning system, solar energy generation and grid is measured. This status and diagnosis data is stored and displayed in the developed black box. In addition, this status and diagnosis data is stored and displayed in a monitoring system and a smart phone of user. A performance evaluation of the developed black box is carried out using emulator of home battery energy storage system connected with solar energy generation. Consequently, the developed black box is proved its superiority of the reliability and user safety.

• 정보처리학회논문지:컴퓨터 및 통신 시스템
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• 제5권9호
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• pp.285-292
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• 2016

최근 차량에 블루투스와 와이파이 등 근거리 통신기능을 부가하여 스마트폰과 연동함으로써, 최신 자동차는 차량 전자제어장치인 ECU를 통하여 자동차 위치정보, 고장 진단정보 등 다양한 정보를 파악할 수 있도록 엔터테인먼트화 되어 가고 있다. 본 연구를 통하여, 온보드 진단기와 스마트폰의 근거리 통신 기능을 활용하여, 차량 온보드 진단기와 연관하여 여러 가지 스마트폰 모델과 블루투스 및 근거리 무선통신인 NFC와의 호환성 시험을 실시하고, 이를 분석해 보았다. 더 나아가, 스마트폰 연동 블루투스 및 NFC 인터페이스 기능을 갖는 온보드 진단기의 단말기 구성과 고장진단 기능 구현을 비롯하여, 고장진단용 디버깅 프로그램을 개발하였다. 또한, OBD-II 인터페이스를 통해 차량의 고장진단 데이터를 추출하였으며, 끝으로 온보드 진단기 CAN 프로토콜 구현 제시와 함께 이의 결과를 분석하였다.

• 한국산학기술학회논문지
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• 제10권10호
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• pp.2741-2749
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• 2009

스마트 홈에서 발생하는 다양한 형태의 오류는 스마트 홈의 신뢰성을 저하시키기 때문에 스마트 홈에서 오류의 검출 및 복구를 위한 연구가 그 동안 진행되어 왔으나, 이들 대부분은 장치의 기능적 고장이나 소프트웨어의 오동작 등에 한정되어 있고, 장치간의 연관 관계에서 발생하는 오류에 대한 것은 없었다. 본 논문에서는 장치간의 연관 관계를 규칙으로 정의하고, 규칙의 만족 여부에 따라 컨텍스트를 두 집합으로 구분한 다음, 장치간의 연관 관계에서 발생하는 오류의 증상과 원인을 정의하는 오류 진단 지식 생성 방법을 제시한다. 향후, 스마트 홈에 적용하여 이 방법을 장치들의 연관성에 의해 발생하는 오류의 탐지와 그 원인의 식별이 실시간으로 가능하다.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2015년도 제46회 하계학술대회
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• pp.55-56
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• 2015

A smart meter is a kind of electronic meters that measures and records consumption of electric energy in intervals of an hour or less and transmits that information to the remote places. AMI provides two-way communication path between utilities and consumers and should be able to support smart grid's new functionalities such as demand-response actions and real time pricing. The main objective of this paper is to provide a new diagnosis method and system for testing of smart meters in AMI neighborhood area network.