• 한국해양공학회지
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• 제18권1호
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• pp.10-15
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• 2004

For effective conservation of the oceans and harbors, long-term and systematic development of the ocean and harbor monitoring system is essential. A monitoring system capable of real-time and accurate data acquisition is necessary for dealing with the level of contamination by situations, such as red tide and foods. This paper introduces an effective and economical real-time harbor environmental monitoring system that utilizes PCS wireless data communication technology. The monitoring system has various functions, such as multiple communication, TCP/IP protocol for wireless internet access, system time synchronization, and bi-directional communication between the measuring device and the server. The system has been implemented at Shinseondae harbor pier in Busan to validate the system's stability and effectiveness in data acquisition. The acquired real-time ocean and harbor environmental data is expected to have a large effect, when shared with the public through the Internet.

• 한국해양공학회:학술대회논문집
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• 한국해양공학회 2003년도 춘계학술대회 논문집
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• pp.63-68
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• 2003

For effective conservation of ocean and harbor, long-term and systematic development of the ocean and harbor monitoring system is essential. The monitoring system capable of real-time and accurate data acquisition is necessary for dealing with contamination such as red tide and the flood. This paper introduces the effective and economical real-time harbor environmental monitoring system that utilizes PCS wireless data communication technology. The monitoring system has various functions such as multiple communication, TCP/IP protocol for wireless internet access, system time synchronization, bi-directional communication between the measuring device and the server. The system has been implemented at Shinseondae harbor pier in Busan to validate the systems stability and effectiveness in data acquisition. The acquired real-time ocean and harbor environmental data is expected to have a large effect, when shared by public through internet.

• 제어로봇시스템학회논문지
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• 제17권11호
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• pp.1074-1081
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• 2011

As robotics systems are becoming more complex there is the need to promote component based robot development, where systems can be constructed as the composition and integration of reusable building block. One of the most important challenges facing component based robot development is safeguarding against software component failures and malfunctions. The health monitoring of the robot software is most fundamental factors not only to manage system at runtime but also to analysis information of software component in design phase of the robot application. And also as a lot of monitoring events are occurred during the execution of the robot software components, a simple data treatment and efficient memory management method is required. In this paper, we propose an efficient events monitoring and data management method by modeling robot software component and monitoring factors based on robot software framework. The monitoring factors, such as component execution runtime exception, Input/Output data, execution time, checkpoint-rollback are deduced and the detail monitoring events are defined. Furthermore, we define event record and monitor record pool suitable for robot software components and propose a efficient data management method. To verify the effectiveness and usefulness of the proposed approach, a monitoring module and user interface has been implemented using OPRoS robot software framework. The proposed monitoring module can be used as monitoring tool to analysis the software components in robot design phase and plugged into self-healing system to monitor the system health status at runtime in robot systems.

• International Journal of Fuzzy Logic and Intelligent Systems
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• 제8권1호
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• pp.11-17
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• 2008

Typical wireless sensor networks used in structural monitoring are continuous types wherein data transmission is progressive at all time that may include irrelevant and insignificant data and information. Continuous types of wireless monitoring systems often pose problems of handling large-sized data that may deteriorate the performance of the system. The proposed method is to suggest an event-triggered monitoring system that captures and transmits relevant data only. An error signal generated by the Principal Components Analysis (PCA) is utilized as an index for event detection and selective data transmission. With this new monitoring scheme, the remote server is relieved of unwanted data by receiving only relevant information from the wireless sensor networks. The performance of the proposed scheme was verified with simulation studies.

• 한국산학기술학회논문지
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• 제8권5호
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• pp.1082-1086
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• 2007

본 연구는 국내에서 발생되는 소각재를 재활용하여 벽돌 생산을 하는 공장에서의 이원화된 작업현황을 일원화 할 수 있는 데이터 모니터링 시스템 구축을 목적으로 한다. 모니터링 시스템은 상태관리 프로세스, 위치관리 프로세스, 불량관리 프로세스, 상황관리 프로세스 등의 데이터 관리 프로세스를 이용해 데이터를 자동 관리하도록 설계하였다. 본 연구에서는 RFID 태그를 이용하여 각 공정의 상황 정보를 수집하고 수집된 정보를 가공하여 데이터 모니터링 시스템에 전송한다. 이러한 시스템을 통해 분석된 데이터는 소각재를 재활용하여 벽돌 생산을 하는 공장에서 공정자동화, 불량률 최소화, 실시간 모니터링, 적재 관리를 통해 생산 공정을 효율적으로 관리할 수 있다.

• 한국지반환경공학회 논문집
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• 제16권5호
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• pp.43-53
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• 2015

본 연구에서는 빅데이터 범주에 포함되는 각종 계측 데이터를 대상으로 각종 이상치를 판단하기 위한 기법을 고안하고, 인공 데이터 및 실 계측 데이터를 이용한 이상치 분석을 수행하였다. 계측결과에 대한 1차 차분 값 및 오차율을 적용한 규칙기반 방법은 큰 규모의 Short fault 분석 및 일정 기간 계측값에 변화가 발생하지 않는 경우의 Constant fault 분석에 효과적으로 적용될 수 있었으나, 독립적인 단일 데이터셋만을 이용하는 관계로 큰 변화폭을 보이는 실 계측 데이터의 정상 데이터를 이상치로 오판하는 문제점이 있었다. 규칙기반 방법을 이용한 Noise fault 분석은 적정 데이터 윈도우 사이즈의 선택 및 이상치 판정용 한계값 선정상의 문제로 인해 실 계측 데이터 적용에 한계가 있었다. 이종 데이터 간 상관분석 방법은 학습 데이터의 적정범위 선정이 선행된다면 장단기 계측 데이터의 이상 거동 및 국부적 이상치 판정에 매우 효과적으로 이용될 수 있음을 알 수 있었다.

• 한국철도학회:학술대회논문집
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• 한국철도학회 2002년도 추계학술대회 논문집(I)
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• pp.497-502
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• 2002

TGIS(Train General Information System) is monitoring Train status and analyzing fault happened. TGIS informed a lot of Passenger data, Driving data, Status data and Fault data to 'Depot'. For dealing them more properly, TGIS need specified data and specialized data handling method. This paper suggest Optimize data of Train Monitoring System and Apply that to Main Line Car.

• 한국컴퓨터정보학회논문지
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• 제15권4호
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• pp.99-106
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• 2010

본 논문에서는 MFC(Mass Flow Controller) 유닛으로부터 전송된 유체의 압력을 모니터하고 흐름 제어 기능을 수행하는 유체 유동 모니터링 시스템을 제안한다. 이 시스템은 MFC 유닛과 채널 디바이스, 모니터 및 관리 소프트웨어로 구성된다. MFC 유닛은 유체 압력 값을 측정하여 채널 디바이스로 전송하고, 채널 디바이스는 MFC 유닛과 모니터 및 관리 소프트웨어간의 입출력 인터페이스를 제공하는 기능을 한다. 모니터 및 관리 소프트웨어는 각 채널의 MFC 유닛에서 실시간으로 측정한 유체 압력 값을 모니터링하여 분석하고 제어한다. 이 소프트웨어는 20개의 채널과 0.1의 모니터링 주기로 구성하여 1초당 200개 즉, 1시간당 72만개의 데이터를 처리한다. 이때 입력 데이터 수의 증가에 따라 저장 공간도 비례하여 증가한다. 이러한 데이터 수의 증가와 저장 공간의 증가는 데이터 조회 성능을 저하시키기 때문에 데이터를 효율적으로 관리할 수 있는 변경값 감지 기법과 변경 범위 감지 기법으로 구현한다.

• 디지털산업정보학회논문지
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• 제13권2호
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• pp.77-85
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• 2017

Due to the expansion of accommodation space caused by increase of population along with lifestyle changes, most of people spend their time indoor except for the travel time. Because of this, environmental change of indoor is very important, and it affects people's health and economy in resources. But, most of people don't acknowledge the importance of indoor environment. Thus, monitoring system for sustaining and managing indoor environment systematically is needed, and big data clusters should be used in order to save and manage numerous sensor data collected from many spaces. In this paper, we design a big data cluster for the indoor environment monitoring in order to store the sensor data and monitor unit of the huge building Implementation design big data cluster-based system for the analysis, and a distributed file system and building a Hadoop, HBase for big data processing. Also, various sensor data is saved for collection, and effective indoor environment management and health enhancement through monitoring is expected.

• Smart Structures and Systems
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• 제17권4호
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• pp.669-690
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• 2016

Advances in sensor technologies have led to the instrumentation of sensor networks for bridge monitoring and management. For a dense sensor network, enormous amount of sensor data are collected. The data need to be managed, processed, and interpreted. Data management issues are of prime importance for a bridge management system. This paper describes a data management infrastructure for bridge monitoring applications. Specifically, NoSQL database systems such as MongoDB and Apache Cassandra are employed to handle time-series data as well the unstructured bridge information model data. Standard XML-based modeling languages such as OpenBrIM and SensorML are adopted to manage semantically meaningful data and to support interoperability. Data interoperability and integration among different components of a bridge monitoring system that includes on-site computers, a central server, local computing platforms, and mobile devices are illustrated. The data management framework is demonstrated using the data collected from the wireless sensor network installed on the Telegraph Road Bridge, Monroe, MI.