• Annual Conference of KIPS
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• 2017.11a
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• pp.1216-1219
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• 2017

산업이 해를 거듭할수록 발전하면서 매연, 분진, 폐기물과 같은 물질의 발생과 동반하는 황사, 스모그 같은 환경적인 오염 문제가 현재 큰 문제로 대두되고 있는데 이는 인간의 신체에 해로운 영향을 준다. 우리는 이런 오염에 대해 특정 기관의 정보를 통해서 환경 오염에 관한 수치를 정보로써 취학 이 정보를 바탕으로 신체에 대한 오염을 대비하는 방식으로 생존하고 있는데 사물인터넷 중에서도 인간과의 접근성이 가장 뛰어난 거울을 이용하여 환경적인 정보 알림을 통해 IoT 스마트 미러 시스템의 새로운 환경적 가치 창출 과정을 설명한다.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2015.10a
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• pp.536-538
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• 2015

전기 에너지가 우리 생활에 유용하게 사용되는 부분이 정말 많다. 최근에는 자전거 열풍이 불면서 덩달아 전동 자전거 업계에도 호황이 일고 있는데, 21C 기후 변화와 환경오염, 교통체증 등의 문제해결을 위한 저탄소 녹색성장의 인식 전환으로 전동 자전거 이용이 늘어나고 있다. 이는 전동 자전거도 전기 에너지가 사용되고 있다 점이다. 하지만 이런 장점을 가지고 있는 전동 자전거를 많은 사람들이 구입하지 못하는 이유가 있다. 대부분의 이유가 '집에 자전거 1대씩 가지고 있는데, 굳이 비싼 돈을 주고 전동 자전거를 구입해야하나?' 라는 생각을 가지게 된다. 또 다른 이유로는 기존의 전동 자전거가 탈 부착 형식이 아닌 일체형으로 나오기 때문에 다른 신제품의 전동 자전거가 나온다면 기존의 전동 자전거의 부품을 사용하지 못 하고 새로운 자전거를 사야 한다는 단점 때문이다. 따라서 본 논문에서는 탈 부착이 가능한 전기 자전거 시스템을 구현하고자 한다.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.22 no.4
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• pp.133-139
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• 2022

Recently, livestock farms in Korea are introducing data-based technologies to improve productivity, such as livestock environment and breeding management, safe livestock production, and animal welfare. In addition, the government has been conducting a smart livestock distribution project since 2017 through the modernization of ICT-based livestock facilities in order to improve the productivity of livestock products and improve the livestock environment as a policy. However, the current smart livestock house has limitations in connection, diversity, and integration between monitoring and control. Therefore, in order to intelligently systemize all processes of livestock with intelligent algorithms and remote control in order to link and integrate various monitoring and control, the Internet of Things, big data, artificial intelligence, cloud computing, and mobile It is necessary to develop a smart livestock system. In this study, domestic and foreign research trends related to smart livestock based on intelligent information technology were introduced and the limitations of domestic application of advanced technologies were analyzed. Finally, future intelligent information technology applicable to the livestock field was examined.

• Journal of Digital Convergence
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• v.17 no.9
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• pp.147-152
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• 2019

Infrastructure is rapidly growing as Internet business grows with the latest IT technologies such as IoT, BigData, and AI. However, in most companies, a limited number of people need to manage a lot of hardware and software. Therefore, Polestar Enterprise Management System(PEMS) is applied to monitor the system operation status, IT service and key KPI monitoring. Real-time monitor screening prevents system malfunctions and quick response. With PEMS, you can see configuration information related to IT hardware and software at a glance, and monitor performance throughout the entire end-to-end period to see when problems occur in real time.

• Journal of Digital Convergence
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• v.14 no.8
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• pp.223-232
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• 2016

This study focuses on the new teaching assistance robot platform and the cloud-based education service model to support the server. In the client area we would like to use the teacher assistant robot in elementary school classrooms to utilize the language education service platform. Emerging IoT technology will be adopted to provide a comfortable classroom environment and various media interfaces. Extensive precedent review and case study have been conducted to identify basic requirements of proposed service platform. Embedded system and technology for image recognition, speech recognition, autonomous movement, display, touch screen, IR sensor, GPS, and temperature-humidity sensor were extensively investigated to complete the service. Key findings of this paper are optimized service platform with cloud server system and possibilities of potential smart classroom with intelligent robot by adopting IoT and BIM technology.

• Journal of the Korea Convergence Society
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• v.12 no.7
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• pp.263-271
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• 2021

Optoelectronic shooting training systems are used in shooting training sites to improve the accuracy of shooting by tracking the trajectories of gun movements. However, optoelectronic-based systems have limitations in terms of cost, complexity of installation, and the risk that electronic targets may be broken. In this study, we developed and verified a shooting training system that measures postural tremors using a low-cost accelerometer. The acceleration sensor module was designed to be attached to the air cylinder of a gun. Postural tremors were evaluated based on amplitude, frequency, and spatial pattern index, which were computed using acceleration data. The postural tremor indices between the accelerometer and optoelectronic-based system were highly correlated (left-right and up-down directions: r = 0.76 and r = 0.70, respectively). We validated the developed shooting training system using an independent two-sample t-test, which identified a significant difference (p < 0.05) in the calculated postural tremor index according to the athlete's shooting score (i.e., best and worst shots).

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.22 no.6
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• pp.83-89
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• 2022

Internet of Things technology is rapidly developing due to the recent development of information and communication technology. IoT technology utilizes various sensors to generate unique data from each sensor, enabling diagnosis of system status. However, the equipment management system currently in effect is a post-preservation concept in which administrators must deal with the problem after the problem occurs, which could mean system reliability and availability problems due to system errors, and could result in economic losses due to negative productivity disruptions. Therefore, this study confirmed that edge controller control decision algorithms for more efficient operation of rectifiers in the factory by applying intelligent IoT (AIoT) technology and domain knowledge-based modeling for each sensor data collected based on this, outputting appropriate status messages for each scenario.

• The Journal of the Convergence on Culture Technology
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• v.7 no.1
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• pp.615-619
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• 2021

This study focuses on memory systems that are optimized to increase performance and energy efficiency in many embedded systems such as IoT, cloud computing, and edge computing, and proposes a performance improvement technique. The proposed technique improves memory system performance based on machine learning algorithms that are widely used in many applications. The machine learning technique can be used for various applications through supervised learning, and can be applied to a data classification task used in improving memory system performance. Data classification based on highly accurate machine learning techniques enables data to be appropriately arranged according to data usage patterns, thereby improving overall system performance.

• Journal of Internet of Things and Convergence
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• v.8 no.6
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• pp.55-63
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• 2022

In recent years, with the rapid development of large and medium-sized urban rail transit in China, the total operating mileage of high-speed railway and the total number of EMUs(Electric Multiple Units) are rising. The system complexity of high-speed EMU is constantly increasing, which puts forward higher requirements for the safety of equipment and the efficiency of maintenance.At present, the maintenance mode of high-speed EMU in China still adopts the post maintenance method based on planned maintenance and fault maintenance, which leads to insufficient or excessive maintenance, reduces the efficiency of equipment fault handling, and increases the maintenance cost. Based on the intelligent operation and maintenance technology of PHM(prognostics and health management). This thesis builds an integrated PHM platform of "vehicle system-communication system-ground system" by integrating multi-source heterogeneous data of different scenarios of high-speed EMU, and combines the equipment fault mechanism with artificial intelligence algorithms to build a fault prediction model for traction motors of high-speed EMU.Reliable fault prediction and accurate maintenance shall be carried out in advance to ensure safe and efficient operation of high-speed EMU.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.22 no.6
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• pp.855-860
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• 2018

The IT technologies applying to IoT(Internet of Things), Big Data, and AI(Artificial Intelligence) are needed in the era of 4th industrial revolution. So, the IT convergence courses of computer science major which will be required in the companies in order to prepare the crises of 4th industry revolution are necessary. And, one approach to cope with this problem is the training of IT convergence man power based on NCS(National Competency Standard) education. In this paper, we propose and analyze the NCS education courses for computer science major in order to teach the students who are needed in the Korean domestic companies preparing the 4th industrial revolution. The skills and applications of Chatbot, Blockchain, and CPS(Cyber Physical System) for the post mobile and post Internet technologies are included in the proposed courses.