• Journal of Digital Convergence
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• 제14권4호
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• pp.251-258
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• 2016

Big data processing is a broad term for processing data sets so large or complex that traditional data processing applications are inadequate. Widespread use of smart devices results in a huge impact on the way we process data. Many organizations are contemplating how to incorporate or integrate those devices into their enterprise data systems. We have proposed a way to process big data by way of integrating Raspberry Pi into a Hadoop cluster as a computational grid. We have then shown the efficiency through several experiments and the ease of scaling of the proposed system.

• The Journal of the Korea institute of electronic communication sciences
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• 제13권1호
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• pp.53-60
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• 2018

The ICT concept has been introduced to realize a highly productive smart factory and respond to the demand for small quantity and mass production between textile processes. ICT convergence monitoring system that can produce high productivity textile products by improving product development period, cost, quality and delivery time through ICT based production and optimization of manufacturing process is needed. In this paper, we propose and implement a system design that senses the amount of remaining sewing material using a non-contact sensor that can be mounted on a sewing machine and displays it on a display using IOT-based LATTE-PANDA board.

• Proceedings of the Korean Society of Computer Information Conference
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• 한국컴퓨터정보학회 2014년도 제49차 동계학술대회논문집 22권1호
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• pp.139-142
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• 2014

앉아서 생활하는 시간이 많은 현대인들에게 올바르게 앉는 자세는 매우 중요하다. 따라서 현대인들이 올바른 자세를 유지할 수 있도록 도와주는 자세 모니터링 시스템을 고안하게 되었다. 이 시스템의 주요 구성으로는 전원부와 계측부, 제어부, 통신부, 안드로이드기반 어플리케이션으로 나눌 수 있다. 전원부는 9V의 건전지 하나로 구성되어 있고, 2개의 레귤레이터를 통해 아날로그 회로(3.3V)와 MCU(5V)에 전원이 공급되어진다. 그리고 계측부는 6개의 압력센서를 이용하여 아날로그 값을 계측한다. 제어부와 통신부는 MCU 보드(MSP430 Launchpad)와 FB155BC Bluetooth Module로 구성되어 있고, 안드로이드기반 어플리케이션은 Bluetooth Module에서 받은 디지털 신호들을 스마트폰의 화면에 UI공정을 거쳐 디스플레이 한다. 본 연구는 잘못된 자세로 의자에 앉는 습관을 스마트폰의 화면을 통해 실시간으로 확인하고, 바른 자세로 앉을 수 있도록 하여 척추교정 및 척추질환 예방에 기여할 것으로 예상된다.

• Smart Media Journal
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• 제11권11호
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• pp.40-48
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• 2022

In this paper, an educational kit that can be used in AI education was developed to solve the difficulties of AI education. Through this, object detection and person detection in computer vision using CNN and OpenCV to learn practical-oriented experiences from theory-centered and user image recognition (Your Own) that learns and recognizes specific objects Image Recognition), user object classification (Segmentation) and segmentation (Classification Datasets), IoT hardware control that attacks the learned target, and Jetson Nano GPIO, an AI board, are developed and utilized to develop and utilize textbooks that help effective AI learning made it possible.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 한국정보통신학회 2021년도 춘계학술대회
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• pp.200-203
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• 2021

This paper introduces a smart mirror technology that recognizes a person's facial expressions through image classification among several artificial intelligence technologies and presents them in a mirror. 5 types of facial expression images are trained through artificial intelligence. When someone looks at the smart mirror, the mirror recognizes my expression and shows the recognized result in the mirror. The dataset fer2013 provided by kaggle used the faces of several people to be separated by facial expressions. For image classification, the network structure is trained using convolution neural network (CNN). The face is recognized and presented on the screen in the smart mirror with the embedded board such as Raspberry Pi4.

• Journal of Advanced Marine Engineering and Technology
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• 제39권9호
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• pp.953-958
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• 2015

Raspberry Pi is a credit card-sized computer with support for a large number of input and output peripherals. This makes it the perfect platform for interaction with many different devices and for usage in a wide range of applications. When combined with Wi-Fi, it can communicate remotely, therefore increasing its suitability for the construction of wireless sensor nodes. In addition, data processing and decision-making can be based on artificial intelligence, what is performed in developed testbed on the example of monitoring and determining the confidence of fire. In this paper, we demonstrated the usage of Raspberry Pi as a sensor web node for fire-safety monitoring in a building. When the UV-flame sensors detect a flame as thin as that of a candle, the Raspberry Pi sends a push-message to notify the assigned smartphone of the on-site situation through the GCM server. A mobile app was developed to provide a real-time video streaming service in order to determine a false alarm. If an emergency occurs, one can immediately call for help.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• 제20권4호
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• pp.115-121
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• 2020

As the participation of blockchain increases, governance to maintain the ecosystem is being activated. Governance must be managed/supervised to maintain and improve the blockchain. However, as the usage of blockchain increases, there is a limit for people to manage it individually. In addition, smart contracts applied from Ethereum need to be verified for trade that are determined according to status values, as new trade types are possible. This research proposes a surveillance system, Blockchain Watchdog, based on the state monitoring of the blockchain smart contract as a tool for maintaining and developing the blockchain ecosystem of governance, and implemented and tested the surveillance system. As a case study, we conducted experiments on Ropsten and Ganache, and were able to see real-time information collection and visualization using dashboards, graphs, and charts. We expect to contribute to the maintenance and development of the ecosystem of blockchain governance through Blockchain Watchdog.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• 제19권1호
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• pp.77-83
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• 2019

Major causes of industrial accidents include falls and gas leak. The existing safety helmet and smart device combination products are focused on convenience, so the functions to prevent such accidents are insufficient. We developed a smart helmet focusing on fall accident detection and gas leak detection. We also developed management system to manage workers efficiently. Its core function is to detect dangerous conditions of employees, to communicate with managers and to confirm the situations of workers. The effectiveness of the combustible gas measurement capability was verified through experiments. However, since a significant amount of power consumption is founded due to continuous operation of the board and the sensor, countermeasures such as replacing with a large capacity battery are required.

• Proceedings of the Korean Information Science Society Conference
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• 한국정보과학회 2012년도 한국컴퓨터종합학술대회논문집 Vol.39 No.1(A)
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• pp.191-193
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• 2012

본 논문은 차량용 스마트에어백 시스템이 탑승자의 머리 위치를 파악하여 지능적으로 에어백을 전개하도록 돕기 위한 얼굴 위치 검출 알고리즘을 제안한다. 차량용 임베디드 시스템은 한정된 자원에서 기능을 동작시키기 때문에 여러 가지 구현상 제한 조건들이 존재한다. 이러한 제한 조건들을 만족시키기 위해 알고리즘의 경량화 및 최적화 작업이 수반 되어져야한다. 제안하는 알고리즘에서는 이진화된 오브젝트에 거리변환(Distance Transform)을 사용하여 사람의 형태학적 모양을 분석/판단한다. 그리하여 얼굴의 위치를 검출하는 방법이다. 여러 가지 배경 상황에 관계없이 사람의 형태학적 모습을 이용하므로 사람 형태 검출에 용이하다. 설계된 알고리즘은 TI사의 TMS320DM6437 EVM 보드에서 구현하였고 구현 결과 제안한 알고리즘이 IR 영상에서 높은 인식률 및 빠른 처리 속도를 보임을 확인할 수 있었다.

• Proceedings of the KIEE Conference
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• 대한전기학회 2006년도 제37회 하계학술대회 논문집 D
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• pp.2019-2020
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• 2006

전력선 통신(Power Line Communication)은 전력선과 연결되어 있는 디바이스들을 간단히 제어하기 위한 기술로 제안되었으며 홈오토메이션, 원격 검침(AMR) 분야에서 많이 사용되고 있다. 그리고 최근에는 스마트 홈, 유비쿼터스와 관련해 다양한 홈 네트워크 시스템들이 제안되면서 이들 시스템을 효과적으로 구현할 수 있는 방안으로 많은 각광을 받고 있다. 그러나 전력선 통신은 많은 유용성에도 불구하고 전력선 채널에 대한 정확한 채널 모델링과 전력선 모뎀에 관해서는 많은 문제점을 나타내고 있다. 본 논문에서는 전력선 통신을 위한 전송선로의 주파수에 대한 잡음과 임피던스 특성 및 전력선 채널에 데이터 신호를 BPSK 변조기법으로 전송하였을 때의 시뮬레이션 결과와 설계된 FPGA 보드를 비교 분석 하였다. 채널 모델은 배경잡음과 전송 선로의 감쇄 특성을 고려하여 모델링 하였으며, 전력선 채널 상에서의 BPSK 변조 기법을 적용한 전력선 모뎀의 성능을 분석하였다.