• The Journal of the Convergence on Culture Technology
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• v.8 no.2
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• pp.355-360
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• 2022

In this paper, we present design and developing method for EMS(environment monitoring system) of micro data center. This developing EMS monitors operating environment of micro data center and analyze sensing data through IoT(Internet of things) sensors in real time. Firstly we present configuration method of IoT sensing package and design method EMS hardware platform. Secondly we design data collector software for data collection of IoT sensor with different protocol and develop monitoring software of EMS. The data collector software consists of sensor collector module and collector manager module. Also we design EMS software which has micro service architecture structural style and component based business logic.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.9
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• pp.316-325
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• 2018

In this paper, to integrate distributed IT resources and manage human resource efficiently as purpose of cost reduction, infrastructure of wind turbine monitoring system have been designed and developed on the basis of SaaS cloud. This infrastructure hierarchize data according to related task and services. Softwares to monitor conditions via the infrastructure are also developed. Softwares are made up of DB design, field measurement, data transmission and monitoring programs. The infrastructure is able to monitor conditions from SCADA data and additional sensors. Total time delay from field measurement to monitoring is defined by modeling of step-wise time delay in condition monitoring algorithms. Since vibration data are acquired by measurements of high resolution, the delay is unavoidable and it is essential information for application of O&M program. Monitoring target is gearbox in wind turbine of MW-class and it is operating for 10 years, which means that accurate monitoring is essential for its efficient O&M in the future. The infrastructure is in operation to deal with the gearbox conditions with high resolution of 50 TB data capacity, annually.

• Journal of Digital Convergence
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• v.18 no.11
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• pp.187-194
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• 2020

This study present to Framework & R&D direction of the 3d printing Integrated Control & Monitoring System. To ensure this purpose, we developed integrated 3d printing control system Framework for DED & PBF and we introduce 4 monitoring system include photo diode, gas flow, acoustic and spectrometer sensors. For this study, we utilize metal 3d printing system from Conception., OKE Tech and DE&T who are still developing Metal 3D Printing Technology since 2017. In the result, we represent the latest 3D Printing Control and Monitoring System for the next 3D Printing researcher and we hope this study will be used as a basic reference and data for Cooperation between mechanic, electronic and material fields.

• ETRI Journal
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• v.38 no.4
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• pp.767-775
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• 2016

Automatic container code recognition from a captured image is used for tracking and monitoring containers, but often fails when the code is not captured clearly. In this paper, we increase the accuracy of container code recognition using multiple views. A character-level integration method combines recognized codes from different single views to generate a new code. A decision-level integration selects the most probable results from the codes from single views and the new integrated code. The experiment confirmed that the proposed integration works successfully. The recognition from single views achieved an accuracy of around 70% for the test images collected on a working pier, whereas the proposed integration method showed an accuracy of 96%.

• ETRI Journal
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• v.39 no.2
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• pp.202-212
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• 2017

With the advent of the Internet-of-Things paradigm, the amount of data production has grown exponentially and the user demand for responsive consumption of data has increased significantly. Herein, we present DART, a fast and lightweight stream processing framework for the IoT environment. Because the DART framework targets a geospatially distributed environment of heterogeneous devices, the framework provides (1) an end-user tool for device registration and application authoring, (2) automatic worker node monitoring and task allocations, and (3) runtime management of user applications with fault tolerance. To maximize performance, the DART framework adopts an actor model in which applications are segmented into microtasks and assigned to an actor following a single responsibility. To prove the feasibility of the proposed framework, we implemented the DART system. We also conducted experiments to show that the system can significantly reduce computing burdens and alleviate network load by utilizing the idle resources of intermediate edge devices.

• KIPS Transactions on Computer and Communication Systems
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• v.4 no.8
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• pp.259-270
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• 2015

In this paper, we study and implement ways for users to easily apply and manage the DNSSEC in a domestic environment. DNSSEC is the DNS cache information proposed to address the vulnerability of modulation. However, DNSSEC is difficult to apply and manage due to insufficient domestic applications. In signing keys for efficient and reliable management of DNSSEC, we propose proactive monitoring SW and signing keys. This is an automatic management s/w signing key for DNSSEC efficient and reliable management and to provide a monitoring of the signing key. In addition to the proposed details of how DNSSEC signing key update and monitoring progress smoothly, we expect that the present study will help domestic users to apply and manage DNSSEC easily.

• Proceedings of the Korea Information Processing Society Conference
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• 2012.04a
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• pp.1290-1293
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• 2012

오픈 소스 기반 ESB 모니터링 시스템 설계에 EIP(Enterprise Integration Pattern)을 적용하여 비즈니스 요구사항을 처리하는 통합 로직과 메시지 추적 관리를 위한 관리 로직을 분리하여, 메시지 관리 로직 처리에 따른 성능 저하 및 오류에 의한 영향도를 최소화하며 메시지 데이터를 중앙 저장 장치에 저장하여 메시지 추적 관리를 용이한 모니터링 시스템 구축 사례.

• ETRI Journal
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• v.41 no.4
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• pp.494-505
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• 2019

In this paper, we propose a new framework for detecting the unauthorized dumping of garbage in real-world surveillance camera. Although several action/behavior recognition methods have been investigated, these studies are hardly applicable to real-world scenarios because they are mainly focused on well-refined datasets. Because the dumping actions in the real-world take a variety of forms, building a new method to disclose the actions instead of exploiting previous approaches is a better strategy. We detected the dumping action by the change in relation between a person and the object being held by them. To find the person-held object of indefinite form, we used a background subtraction algorithm and human joint estimation. The person-held object was then tracked and the relation model between the joints and objects was built. Finally, the dumping action was detected through the voting-based decision module. In the experiments, we show the effectiveness of the proposed method by testing on real-world videos containing various dumping actions. In addition, the proposed framework is implemented in a real-time monitoring system through a fast online algorithm.

• Journal of Satellite, Information and Communications
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• v.7 no.2
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• pp.54-58
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• 2012

In this paper, we implemented total monitoring system in which LED light turned on only when user detected and LED light turned out only when user disappeared. This system is composed of two modules, one is HW board based on Micro Controller and the other is SW control system based on Web server. Micro controller board is based on ATMega2560 chip which is connected with Infra Red and Ultra sonic sensors. Web based monitoring system was designed can be used in smart device. The validity of this monitoring system was proved by integration test of two modules.

• ETRI Journal
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• v.37 no.2
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• pp.395-405
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• 2015

We address the problem of uncooperative person recognition through continuous monitoring. Multiple modalities, such as face, height, clothes color, and voice, can be used when attempting to recognize a person. In general, not all modalities are available for a given frame; furthermore, only some modalities will be useful as some frames in a video sequence are of a quality that is too low to be able to recognize a person. We propose a method that makes use of stochastic information updates of temporal modalities and environment estimators to improve person recognition performance. The environment estimators provide information on whether a given modality is reliable enough to be used in a particular instance; such indicators mean that we can easily identify and eliminate meaningless data, thus increasing the overall efficiency of the method. Our proposed method was tested using movie clips acquired under an unconstrained environment that included a wide variation of scale and rotation; illumination changes; uncontrolled distances from a camera to users (varying from 0.5 m to 5 m); and natural views of the human body with various types of noise. In this real and challenging scenario, our proposed method resulted in an outstanding performance.