• Journal of Korea Society of Digital Industry and Information Management
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• v.16 no.1
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• pp.33-39
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• 2020

A smart grid is a next-generation power grid that can improve energy efficiency by applying information and communication technology to the general power grid. The smart grid makes it possible to exchange information about electricity production and consumption between electricity providers and consumers in real-time. Advanced metering infrastructure (AMI) is the core technology of the smart grid. The AMI provides two-way communication by installing a modem in an existing digital meter and typically include smart meters, data collection units, and meter data management systems. Because the AMI requires data collection units to control multiple smart meters, it is essential to ensure network availability under heavy network loads. If the load on the work done by the data collection unit is high, it is necessary to allocation new data collection units to ensure availability and improve energy efficiency. In this paper, we discuss the allocation scheme of data collection units for the energy efficiency of the AMI.

• Journal of the Korean Institute of Gas
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• v.26 no.5
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• pp.10-15
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• 2022

Currently, some urban gas companies are conducting their own gas AMI meter verification projects, along with the demonstration of gas AMI (Advanced Metering Infrastructure) meters under the supervision of the government. There are many positive factors such as remote meter reading and ensuring user gas safety through AMI meter installation, but on the other hand, there are also many problems such as battery discharge, expensive price, and decreased reliability of remote meter data. This study sought various improvements in gas AMI meters along with prevention of serious civil disasters by preemptively eliminating structural safety problems and potential risks from gas leakage due to the expansion of gas AMI meters, and it is expected that this study will contribute to the government's policy to advance gas AMI.

• The KIPS Transactions:PartC
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• v.18C no.6
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• pp.397-404
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• 2011

Recently the existing one-way electricity system that combines information and communications technology to develop smart grid technology is made active. The core infrastructure of the smart grid, AMI smart meters to AMR system, the amount of power measured at the top to MDMS transmits data store. Smart meters utilizing information and communication technology to transfer data and power because of the existing security threats are expected, including the additional security threats. It exposes the privacy of consumers and industrial systems, such as paralysis is likely to result in the loss. In this paper to respond to these security threats in the environment smart grid. Also, We propose data transfer methods between smartmeter and MDMS and between home device and MDMS.

• Korean Journal of Remote Sensing
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• v.37 no.6_1
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• pp.1767-1772
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• 2021

Global satellite observation surface albedo data over a long period of time are actively used to monitor changes in the global climate and environment, and their utilization and importance are great. Through the generational shift of geostationary satellites COMS (Communication, Ocean and Meteorological Satellite)/MI (Meteorological Imager sensor) and GK-2A (GEO-KOMPSAT-2A)/AMI (Advanced Meteorological Imager sensor), it is possible to continuously secure surface albedo outputs. However, the surface albedo outputs of COMS/MI and GK-2A/AMI differ between outputs due to Differences in retrieval algorithms. Therefore, in order to expand the retrieval period of the surface albedo of COMS/MI and GK-2A/AMI to secure continuous climate change monitoring linkage, the analysis of the two satellite outputs and errors should be preceded. In this study, error characteristics were analyzed by performing comparative analysis with ground observation data AERONET (Aerosol Robotic Network) and other satellite data GLASS (Global Land Surface Satellite) for the overlapping period of COMS/MI and GK-2A/AMI surface albedo data. As a result of error analysis, it was confirmed that the RMSE of COMS/MI was 0.043, higher than the RMSE of GK-2A/AMI, 0.015. In addition, compared to other satellite (GLASS) data, the RMSE of COMS/MI was 0.029, slightly lower than that of GK-2A/AMI 0.038. When understanding these error characteristics and using COMS/MI and GK-2A/AMI's surface albedo data, it will be possible to actively utilize them for long-term climate change monitoring.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.59 no.12
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• pp.2337-2343
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• 2010

AMR(Automatic Meter Reading)/AMI(Advanced Metering Infrastructure) is actively deployed all over the world. efficient, economical, stable and reliable system need to push forward the AMR/AMI business, so various researchs are in progress. In electric power system of domestic, a transformer is connected average twenty to thirty households and PLC is possible to communication within household connected same transformer. So if server and data concentrator unit(DCU) share circuit line through communication between transformers, communication network is able to efficient. Therefore we design new communication method between DCUs and test it and demonstrate the performance.

• The Korean Journal of Emergency Medical Services
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• v.17 no.1
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• pp.21-39
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• 2013

Purpose : The purpose of this study is to provide the basic data to improve pre-hospital phase emergency care for acute myocardial infarction (AMI) patients by analyzing AMI patients' clinical characteristics and emergency care situations. Methods : Data were collected through medical records of 385 AMI patients including ambulance records of 107 AMI patients transferred to the emergency medical center for three and a half years. Results : Regarding emergency care for AMI patients in pre-hospital phase, 47% of the care revealed moderate level or higher, and appropriateness of pre-hospital phase emergency care for cardiopulmonary complaints practiced by paramedics showed statistically significant improvement in recent years (p<.001). The time from onset of symptom to ballooning intervention by 119 emergency services was shorter than that in other cases. However, emergency care by paramedic was mainly basic life support. Conclusion : Since prognosis of AMI shows vast differences depending on prompt detection and medical intervention, cooperation between pre-hospital and in-hospital phase is highly required. 119 paramedics should be trained focusing on the accurate assessment and emergency care, and medical direction should be activated. In addition, regulation on 12-lead EKG, cardiac enzyme analysis, use of analgesics and thrombolytic agents should be legally implemented.

• Proceedings of the Korea Water Resources Association Conference
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• 2018.05a
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• pp.223-223
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• 2018

취수원에서 정수장과 배수지를 거쳐 수용가에 이르기까지 공급되는 급수량을 결정하는데 있어 각 수용가별 물 사용 패턴은 수요량을 예측하여 취수량을 결정하는데 있어 매우 중요한 지표이다. 생활용수 추정은 용도별(가정용, 상업용, 공업용 등)로 분류하여 경향성이 나타날 수 있도록 과거 사용실적을 바탕으로 장래 용도별 사용량을 추정한다. 이는 경험을 바탕으로 한 것으로 일반적으로 시계열 모형을 이용하는데 수요예측의 실패 가능성이 높으며 효율적인 방법이라 할 수 없다. 이에 본 연구에서는 최근 통신기술의 발달로 양방향 통신이 가능한 AMI(Advanced Metering Infrastructure, 원격검침인프라)센서를 영종도 112블록의 528개의 수용가에 설치하였다. AMI는 스마트 미터에서 측정한 데이터를 원격 검침기를 통해 물 사용량을 자동으로 계측할 수 있다. AMI 데이터를 이용하여 영종도 112블록의 운북동과 운서동의 각 용도별, 요일별, 그리고 도심지와 농가의 실시간 물 사용 패턴을 분석하였다. 분석 결과 운북동과 운서동의 물 사용 패턴은 비슷한 경향을 보이는 것으로 보이나 도시화된 운서동에 비해 운북동의 물사용량이 상대적으로 적고 첨두사용량의 발생시간 또한 빠른 것으로 나타났다. 또한 가정용과 공공용의 경우 시간별 물 사용량이 요일에 따라 일정한 경향이 있으나 상업용과 공업용은 일정한 사용량을 보였다. 향후 112블록의 관망해석에 실시간 물사용 패턴을 적용하여 효율적으로 급수량 결정을 할 수 있을 것으로 사료된다.

• Journal of IKEEE
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• v.23 no.4
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• pp.1373-1380
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• 2019

In order to increase energy efficiency, developments of the advanced metering infrastructure (AMI) in the smart grid technology have recently been actively conducted. An essential part of AMI is analyzing power consumption and forecasting consumption patterns. In this paper, we analyze the power consumption and summarized the data errors. Monthly power consumption patterns are also analyzed using the k-means clustering algorithm. Forecasting the consumption pattern by each household is difficult. Therefore, we first classify the data into 100 clusters and then predict the average of the next day as the daily average of the clusters based on the deep neural network. Using practically collected AMI data, we analyzed the data errors and could successfully conducted power forecasting based on a clustering technique.

• KIPS Transactions on Computer and Communication Systems
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• v.1 no.3
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• pp.171-180
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• 2012

In the development of MDMS(Meter Data Management System) based on CIM(Common Information Model), which is international standard in information model and data exchange on power system, the two focused issues are the effective management of data collected in a shorter time period and the way to integrate services supporting legacy system to use the AMI(AMI, Advanced Metering Infrastructure) data. In this paper, we propose MDMS implementation methods and functions in AMI environment which are differ from existing AMR system environments in that the methods support bi-directional service infrastructure. The proposed MDMS in this paper has two unique features, one is the secure of interoperability by utilizing the CIM and ESB, the other is the improvement of field application by implementing system module based on components. On an implementation of smart grid, the result of proposed methods is expected to contribute to the efficient development and operation of CIM-based power system.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.60 no.10
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• pp.1795-1803
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• 2011

Advanced Metering Infrastructure (AMI) is one of the important components to form a smart-gird, which is an advanced power system by combining the power system with the communication systems. This AMI makes it possible to exchange information between operators and consumers for the efficient and reliable operation of the power system through a smart meter or a In-Home Display. However, according to the increase of the demanded information such as the power quality, the accurate load-profile, and the billing data to help customers manage their power consumption, it is necessary to gather more accurate analytical data from each house appliances and transfer it to the smart meter for synthesizing the information and controlling each loads. In this paper, the development of the wireless data acquisition device for the individual load data metering, which is connected with the smart meter for advanced functions, is proposed. AVR, a kind of microcontroller, and Bluetooth are used and integrated into the proposed the wireless data acquisition device to transmit the detailed power data (voltage and current) to the smart meter. To verify the effectiveness of the proposed system, a hardware experiment is carried out including the confirmation of the possibility for providing the more various information by applying analysis algorithms to the obtained data. Also, the application structure of the wireless data acquisition device to gather the data from the various house appliances is presented.