• Smart Structures and Systems
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• 제33권6호
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• pp.399-414
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• 2024

This study discusses the long-term deformation monitoring and shape sensing of bridge girder surfaces with an automated extraction scheme for point clouds in the Region Of Interest (ROI), invariant to the position of a Light Detection And Ranging system (LiDAR). Advanced smart construction necessitates continuous monitoring of the deformation and shape of bridge girders during the construction phase. An automated scheme is proposed for reconstructing geometric model of ROI in the presence of noisy non-stationary background. The proposed scheme involves (i) denoising irrelevant background point clouds using dimensions from the design model, (ii) extracting the outer boundaries of the bridge girder by transforming and processing the point cloud data in a two-dimensional image space, (iii) extracting topology of pre-defined targets using the modified Otsu method, (iv) registering the point clouds to a common reference frame or design coordinate using extracted predefined targets placed outside ROI, and (v) defining the bounding box in the point clouds using corresponding dimensional information of the bridge girder and abutments from the design model. The surface-fitted reconstructed geometric model in the ROI is superposed consistently over a long period to monitor bridge shape and derive deflection during the construction phase, which is highly correlated. The proposed scheme of combining 2D-3D with the design model overcomes the sensitivity of 3D point cloud registration to initial match, which often leads to a local extremum.

• 한국산학기술학회논문지
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• 제11권6호
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• pp.2256-2262
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• 2010

비즈니스 프로세스의 자동화된 처리와 이에 대한 모니터링 요구는 기업마다 특화된 형태를 지니는 것이 일반적이다. 비즈니스 프로세스는 일반적인 데이터베이스 트랜잭션과는 달리 수행에 장시간이 소요되며, 비즈니스 상황에 따라 매우 복잡한 처리 로직을 가진다. 이러한 처리 로직들은 사업 정책이나 환경이 변함에 따라 자주 변경되기 때문에 기업은 특정 비즈니스 프로세스의 모니터링 과정에서 해당 프로세스 인스턴스의 전체적 의미를 종합적으로 파악하고자 한다. 본 연구에서는 비즈니스 프로세스의 종합적인 모니터링을 위해 GMA(Grid Monitoring Architecture)를 사용하였다. GMA는 이종 시스템 환경 하에서 모니터링 정보를 효과적으로 관리하고 감독하기 위하여 제시된 확장성이 높은 아키텍처이다. 다양한 처리 로직을 지원할 수 있도록 GMA 모델에 복합 이벤트의 처리 기능을 부가함으로써, 비즈니스 프로세스에 대한 자동화된 실행과 상위수준의 모니터링이 가능한 시스템을 구축할 수 있었다.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 2013년도 춘계학술대회 논문집
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• pp.719-720
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• 2013

• 한국해양환경ㆍ에너지학회지
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• 제4권4호
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• pp.61-69
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• 2001

최근 들어, 컴퓨터와 전자장비의 기술 발전에 힘입어 대부분의 유조선에서도 자동 적ㆍ양하 시스템 장비들이 도입되고 있다. 그러나 과도한 자동화에 따른 기기 조작이 복잡해짐에 따라 사감의 조작 실수에 따른 사고의 가능성이 논아지고 있는 것이 사실이다. 즉, 비록 적ㆍ양하 작업이 전문가들에 조작되지만 전체 작업 과정에서의 인적 오류 가능성을 배제할 수 없으며, 현재 도입되어 있는 시스템들은 오조작에 대한 방지 및 시스템의 이상 상황을 진단하여 대안을 제시할 수 있는 기능을 보유하고 있지 않다. 유류와 관련된 사고는 엄청난 피해를 초래하기 때문에 본 시스템의 개발 목적은 완전 자동화 시스템을 지양하고, 안전을 고려한 시스템 개발을 추구하고 있다. 본 논문에서는 지식기반 모니터링 시스템 개발을 위한 적ㆍ양하 작업 분석과 시스템 작동 가이드 및 시스템의 이상 상환과 작업자의 오조작을 모니터링하여 이에 신속히 대응할 수 있는 시스템 설계에 대해 언급하였다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제7권1호
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• pp.99-118
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• 2013

Electrocardiograms (ECGs) are widely used by clinicians to identify the functional status of the heart. Thus, there is considerable interest in automated systems for real-time monitoring of arrhythmia. However, intra- and inter-patient variability as well as the computational limits of real-time monitoring poses significant challenges for practical implementations. The former requires that the classification model be adjusted continuously, and the latter requires a reduction in the number and types of ECG features, and thus, the computational burden, necessary to classify different arrhythmias. We propose the use of adaptive learning to automatically train the classifier on up-to-date ECG data, and employ adaptive feature selection to define unique feature subsets pertinent to different types of arrhythmia. Experimental results show that this hybrid technique outperforms conventional approaches and is therefore a promising new intelligent diagnostic tool.

• Journal of Korean Society for Atmospheric Environment
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• 제17권E1호
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• pp.25-33
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• 2001

This paper presents an overview of the UK Hydrocarbon Monitoring Network and summarises some of the lessons learnt from running and automated VOC monitoring network in th UK. The paper will describe the operation of the network and the Quality Control and Quality Assurance (QA/QC) procedures used to ensure that the data qality objectives are met. The provision of accurate measurements of ambient air pollutant concentrations is a valuable and high-profile service of Governments, assisting policy decisions and allowing members of the public to be well-informed. The need for such measurements has been increased in the UK by the National Air Quality Strategy and European Air Quality Directives, with the National Networks playing a central role in delivering the information. The Hydrocarbon Network provides measurements directly in support of monitoring requirements for benzene and 1,3-butadiene, and of 23 other hydrocarbon species important for their role in ozone and secondary particulate formation.

• Smart Structures and Systems
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• 제6권3호
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• pp.335-347
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• 2010

Recent advances in hardware and instrumentation technology have allowed the possibility of deploying very large sensor arrays on structures. Exploiting the huge amount of data that can result in order to perform vibration-based structural health monitoring (SHM) is not a trivial task and requires research into a number of specific problems. In terms of pressing problems of interest, this paper discusses: the design and optimisation of appropriate sensor networks, efficient data reduction techniques, efficient and automated feature extraction methods, reliable methods to deal with environmental and operational variability, efficient training of machine learning techniques and multi-scale approaches for dealing with very local damage. The paper is a result of the ESF-S3T Eurocores project "Smart Sensing For Structural Health Monitoring" (S3HM) in which a consortium of academic partners from across Europe are attempting to address issues in the design of automated vibration-based SHM systems for structures.

• 한국공간정보시스템학회 논문지
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• 제11권2호
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• pp.45-53
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• 2009

The fast progress on multimedia data acquisition technologies has enabled collecting vast amount of videos in real time. Although the amount of information gathered from these videos could be high in terms of quantity and quality, the use of the collected data is very limited typically by human-centric monitoring systems. In this paper, we propose a framework for analyzing long traffic video using series of content-based analyses tools. Our framework suggests a method to integrate theses analyses tools to extract highly informative features specific to a traffic video analysis. Our analytical framework provides (1) re-sampling tools for efficient and precise analysis, (2) foreground extraction methods for unbiased traffic flow analysis, (3) frame property analyses tools using variety of frame characteristics including brightness, entropy, Harris corners, and variance of traffic flow, and (4) a visualization tool that summarizes the entire video sequence and automatically highlight a collection of frames based on some metrics defined by semi-automated or fully automated techniques. Based on the proposed framework, we developed an automated traffic flow analysis system, and in our experiments, we show results from two example traffic videos taken from different monitoring angles.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제14권12호
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• pp.4889-4908
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• 2020

With the advances in Information Technology (IT), users can download or stream copyrighted works, such as videos, music, and webtoons, at their convenience. Thus, the frequency of use of copyrighted works has increased. Consequently, the number of unauthorized copies and sharing of copyrighted works has also increased. Monitoring is being conducted on sites suspected of conducting copyright infringement activities to reduce copyright holders' damage due to unauthorized sharing of copyrighted works. However, suspected copyright infringement sites respond by changing their domains or blocking access requests. Although research has been conducted for improving the effectiveness of suspected copyright infringement site detection by defining suspected copyright infringement sites' response techniques as a lifecycle step, there is a paucity of studies on automation techniques for lifecycle detection. This has reduced the accuracy of lifecycle step detection on suspected copyright infringement sites, which change domains and lifecycle steps in a short period of time. Thus, in this paper, an automated detection technique for suspected copyright infringement sites is proposed for efficient detection and response to suspected copyright infringement sites. Using our proposed technique, the response to each lifecycle step can be effectively conducted by automatically detecting the lifecycle step.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1997년도 한국자동제어학술회의논문집; 한국전력공사 서울연수원; 17-18 Oct. 1997
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• pp.403-406
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• 1997

This paper presents a Petri net approach for the control and monitoring of discrete event system. The proposed model is fuzzy Petri nets based on the fuzzy logic with Petri nets and the hierarchy concept. Fuzzy Petri nets have been used to model the imprecise situations which can arise within automated manufacturing system, and also the hierarchy concept allow to handle the refinement of places and transition in Petri nets model. These will form the foundation of a simulator-tool with manipulation interface for application of fuzzy Petri nets.