• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2016.05a
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• pp.539-541
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• 2016

In this paper, we proposed real time free-length monitoring systems interlocking with the spring free-length sorter which shows the state of production connected to the spring production device. This systems enable the administrator to check the quality or quantity of product and the defect rate, etc., in the remote place. The proposed systems are comprised of the wireless device interlocking with PLC device, the server program, and user GUI program. The wireless device transmits the received data from PLC device to server program using Wi-Fi. Server program represents the data from the wireless device on the screen and insert those data into database. User GUI program shows data stored in database and supports the function which converts the stored data in DB to excel file.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.29 no.6
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• pp.1403-1412
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• 2019

Effect of damage and loss cost for downtime is huge, if physical devices such as turbines, pipe, and storage tanks are in the abnormal state originated from not only aging, but also cyber attacks on the control and monitoring system like PLC (Programmable Logic Controller). To improve availability and dependability of the physical devices, we design and implement an indirect health monitoring system which sense temperature, acceleration, current, etc. indirectly, and put sensor data into Influx DB in real-time. Then, the actual performance of detecting abnormal state is shown using the indirect health monitoring system. Analyzing data are acquired using the real-time indirect health monitoring system, abnormal state and security threats can be double-monitored and lower maintenance cost utilizing prognostics and health management.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.10a
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• pp.25-27
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• 2022

Recently, with the development of the 4th industry, environmental issues such as air pollution have become serious, and in particular, a lot of air pollutants are generated in industrial sites. There are various types of air pollutants, and among them, carbon monoxide is essential for fires occurring in industrial sites, so it should be possible to monitor in real time. In addition, there is a need for a remote monitoring system that can measure various environmental factors other than air pollutants in real time. In this paper, we propose a monitoring system using wireless communication to remotely measure the industrial environment. The proposed monitoring system collects data to the Arduino of the transmitter by using a carbon monoxide sensor, a combustible gas sensor, a temperature and humidity sensor, and a flame sensor, and then transmits it to the receiver using ZigBee. The transmitted data is stored in the database of the receiver Raspberry Pi, and the stored data can be monitored in real time through the monitoring system.

• Aerospace Engineering and Technology
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• v.11 no.2
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• pp.73-79
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• 2012

Because the contact time between satellite and ground station is very limited in LEO (Low Earth Orbit) satellite, all telemetry data generated on spacecraft bus are stored in a mass memory and downlinked to the ground together with real time data during the contact time. The mass memory is initialized in the first system initialization phase and the page status of each memory block is generated step by step. After the completion of the system initialization, the telemetry data are continuously stored and the stored data are played back to the ground by command. And the memory scrubbing is periodically performed for correction of single bit error which can be generated on harsh space environment. This paper introduces the mass memory operation method for telemetry processing of LEO satellite. It includes a general mass memory data structure, the methods of mass memory initialization, scrubbing, data storage and downlink, and mass memory management of primary and redundant mass memory.

• Journal of IKEEE
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• v.17 no.4
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• pp.550-558
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• 2013

In this paper, we propose an efficient hybrid lighting management system implementation on multiple protocol. The proposed hybrid lighting management system was implemented by configured as the data display part for management and control of lighting device and the data conversion-processing part the communication part of gateway. The data were designed the DB to enable to storage in real-time, and implemented able to manage by real time wireless remote control and schedule setting. The proposed an efficient hybrid lighting management system, it was possible the real-time monitoring and remote lighting control by peristalsis with smart devices and portable PC etc., and it could be obtained reduction effect of energy and electricity, communication cost.

• Journal of IKEEE
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• v.17 no.3
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• pp.301-308
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• 2013

In this paper, we propose the hybrid lighting control system on multiple sensor. The proposed hybrid lighting control system was designed for management and control of street lightings by configured as the data display part of integration-interworking part, the data conversion-processing part of integrated management part, and the communication part of gateway system. The data are implemented to designing the DB to enable to storage in real-time by enable to monitoring by wireless remote control and schedule set. As a result of the efficiency verification of the proposed hybrid lighting control system, the hybrid lighting control system be to the real-time monitoring and remote lighting control was possible, because to peristalsis with smart devices and portable PC etc., and it could be obtained the effect of energy and electricity, communication cost reduction.

• Proceedings of the Korean Information Science Society Conference
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• 2003.10b
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• pp.85-87
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• 2003

최근 들어 이동통신 환경의 급격한 발달로 이를 활용한 위치기반 서비스에 대한 관심이 높아지고 있다. 효율적인 위치기반 서비스를 위해서는 실시간으로 위치를 변화시키는 이동객체에 대한 저장. 관리 및 질의를 담당할 수 있는 시공간 데이타베이스 관리 시스템의 존재가 필수적이다. 본 논문은 클러스터 기반 분산 컴퓨팅 구조를 바탕으로 제안된 시공간 데이타베이스 관리 시스템인 GALIS 구조 중에서 이동객체의 과거 위치 데이타를 디스크를 기반으로 저장 및 관리하는 노드인 LDP와 이동객체 데이터 생성기를 TMO 프로그래밍 스킴과 상용 데이타베이스 엔진을 사용하여 구현하였다. 제안 시스템은 대용량 이동객체의 효율적인 관리를 위한 실시간 엔진 개발에 활용될 수 있다.

• Annual Conference of KIPS
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• 2013.11a
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• pp.425-428
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• 2013

최근 서버 구축 및 유지 비용을 절검하고, 용량이 큰 동영상과 클라이언트의 수가 점차 증가함에 따라 서버의 용량과 성능을 용이하게 향상시킬 수 있는 클라우드 컴퓨팅을 이용한 개발이 증가하고 있다. 이에 본 논문은 Windows Azure 클라우드 컴퓨팅에 기반한 모바일 학습 시스템을 제시한다. 제시된 시스템은 학생이 강사의 비디오, 오디오, 슬라이드 그리고 애노테이션을 실시간으로 받을 수 있으며, 텍스트 형태로 질문을 실시간으로 할 수 있게 해준다. 그리고 강의내용을 저장하여 학생이 나중에 원하는 강의를 경험하게 할 수 있게 해주는 비동기식 기능도 제공한다. 그리고 본 시스템은 클라우드를 이용함으로써, 서비스 제공자가 별도의 서버를 구축할 필요가 없으며 나중에 저장되는 동영상데이터의 크기 및 클라이언트의 수가 증가하더라도 그에 대응한 서버의 확장이 용이하다.

• The Journal of the Korea institute of electronic communication sciences
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• v.9 no.11
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• pp.1255-1266
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• 2014

This thesis presents MPU module, Base board and sensor module which are efficient industrial control through design and manufacture as developing S5PV210 CPU of SAMSUNG used by ARM Cortex-A8 based on Android which is Open mobile platform is installed to embedded system. Data for temperature and humidity which are received by sensor module proved the suitability and validity for the real time framework design as implementing application program employed the smart phone App with hybrid application based on DB of web server.

• Journal of KIISE
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• v.42 no.1
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• pp.54-67
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• 2015

Nowadays, studies on the fusion of Semantic Web technologies are being carried out to promote the interoperability and value of sensor data in an IoT environment. To accomplish this, the semantic translation of sensor data is essential for convergence with service domain knowledge. The existing semantic translation technique, however, involves translating from static metadata into semantic data(RDF), and cannot properly process real-time and large-scale features in an IoT environment. Therefore, in this paper, we propose a technique for translating large-scale streaming sensor data generated in an IoT environment into semantic data, using real-time and parallel processing. In this technique, we define rules for semantic translation and store them in the semantic repository. The sensor data is translated in real-time with parallel processing using these pre-defined rules and an ontology-based semantic model. To improve the performance, we use the Apache Storm, a real-time big data analysis framework for parallel processing. The proposed technique was subjected to performance testing with the AWS observation data of the Meteorological Administration, which are large-scale streaming sensor data for demonstration purposes.