• Proceedings of the Korean Society of Computer Information Conference
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• 2019.07a
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• pp.427-428
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• 2019

칠교놀이는 해외에서는 Tangram이라고 불리며 아주 예전부터 전해져 내려오는 세계적인 놀이이다. 친구와 여럿이서 놀이를 할 수 있을 뿐만아니라 혼자서도 즐길 수 있다. 칠교놀이는 특히 창의력 향상에 도움을 주는데 이번 논문에서는 혼자서 쉽게 칠교놀이를 즐길 수 있도록 비전시스템과 라즈베리파이를 이용해서 칠교를 카메라로 인식해 성공하면 보상으로 사탕을 지급하는 놀이를 개발해 보았다. 자판기에 동전을 넣으면, 게임을 시작해서 칠교놀이의 문제를 하나씩 맞출 때 마다 사탕 한 개가 지급되는 방식으로 4차산업혁명 시대에 걸맞는 재미있는 칠교놀이 게임을 만들어 보았다. 본 논문은 OPENCV라이브러리와 라즈베리파이 GPIO라이브러리를 사용하였다. 사용한 부품은 웹캠, 초음파 센서, 서보모터이다. 라즈베리파이를 서버로 설정하고, PC를 클라이언트로 설정하여 서로 데이터를 주고 받을 수 있게 하였다. 라즈베리파이에 OPENCV를 설치하지 않은 이유는 OPENCV가 꽤 높은 사양이 필요하다고 판단하여 비전영상처리는 PC(클라이언트)에서 진행하고, 게임의 진행상황(정답의 여부)을 라즈베리파이(서버)에 보내는 방식으로 정하였다. 반대로 라즈베리파이에서도 동전의 투입 유무를 판단하여 PC(클라이언트)에 게임 시작 신호를 보내는 방식으로 설정하였다. 언어는 라즈베리파이와 PC둘다 Pythond으로 구현하였다.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.10a
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• pp.643-645
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• 2021

Minecraft Pi edition is a distinct version of Minecraft developed for Raspberry Pi and was mostly used as an educational instrument for upcoming programmers. In this paper, the basic method to control GPIO pin of Raspberry Pi 4 board using python 3 and Minecraft Pi software was implemented. The implemented scheme can be easily applicable to the area of educational platform and metaverse application if a plenty of python libraries embedded in raspberry pi and excellent gaming capability of Minecraft Pi software are efficiently merged to meet application-specific hardware and software requirements.

• Proceedings of the Korea Information Processing Society Conference
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• 2022.11a
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• pp.6-8
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• 2022

병렬처리시스템이 설계와 구축에서 가장 중요한 관점 중의 하나는 비용 대비 성능이다. 본 연구에서는 라즈베리파이 4를 클러스터 방식으로 연결하여 병렬처리 시스템을 구축하였을 때, 클러스터의 병렬처리 성능이 다른 병렬처리 시스템과 유사한 확장성과 병렬처리 성능을 보여주는지를 HPL 벤치마크를 통하여 검증하였다. 실험 결과 라즈베리파이 기반의 병렬처리 시스템이 클러스터의 크기에 따른 병렬 확장성이 있고, 다른 병렬처리 시스템들과 유사한 처리 성능을 가질 수 있음을 확인하였으며, 이를 통하여 라즈베리파이와 같은 저가의 처리장치로도 충분한 크기의 클러스터를 구성할 경우 높은 성능을 기대할 수 있음을 알 수 있다.

• The Journal of the Korea institute of electronic communication sciences
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• v.17 no.4
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• pp.679-686
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• 2022

In this paper, we implemented an algae removal device that recognizes and removes algae existing in water using Raspberry Pi camera and DO (Dissolved Oxygen) sensor. The Raspberry Pi board recognizes the color of green algae by converting the RGB values obtained from the camera into HSV. Through this, the location of the algae is identified and when the amount of dissolved oxygen's decrease at the location is more than the reference value using the DO sensor, the algae removal device is driven to spray the algae removal solution. Raspberry Pi's camera uses OpenCV, and the motor movement is controlled according to the output value of the DO sensor and the result of the camera's green algae recognition. Algae recognition and spraying of algae removal solution were implemented through Arduino and Raspberry Pi, and the feasibility of the proposed portable algae removal device was verified through experiments.

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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• v.7 no.4
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• pp.623-630
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• 2017

This paper surveys the state-of-the-art in korean commercial Internet of Things(IoT) services for deriving the core elements of a curriculum for major courses of IoT using RaspberryPi3. First, we survey the state-of-the-art of IoT researches and commercial services in three korean major telecommunication corporations such as Korean Telecommunications (KT), LGU+ Telecommunication (LGT), and SK Telecommunication(SKT). Second, we consider the components and advantages of the RaspberryPi3 which is popular as a representative educational tool. Concludingly, this paper derives the core elements of curriculum for major courses of IoT using RaspberryPi3 from above both processes. The corresponding elements consist of platforms, hardwares, softwares, and big-data network. Based on the important design elements of the IoT curriculum using Raspberry Pie 3, we taught embedded system course to junior students for one semester. It was successfully completed and more than 90% students were satisfied with its contents and amounts.

• The Journal of the Korea institute of electronic communication sciences
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• v.17 no.6
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• pp.1193-1198
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• 2022

As unmanned processing systems emerged socially due to the rapid development of modern society, a face recognition attendance management system using Raspberry Pi 4 was studied and conceived to automatically analyze and process images and produce meaningful results using OpenCV. Based on Raspberry Pi 4, the software is designed with Python 3 and consists of technologies such as OpenCV, Haarcascade, Kakao API, and Google Drive, which are open sources, and can communicate with users in real time through Kakao API for face registration and face recognition.

• Journal of Industrial Convergence
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• v.20 no.8
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• pp.61-67
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• 2022

The Internet of Things(IoT) is one of the key technologies in the Fourth Industrial Revolution. The IoT is a system that acquires information from various sensors and provides meaningful information to users. The method of obtaining information from sensor is using WIFI, Bluetooth and Server. is not accessible to external users because of different type of networks or local area communication. For this reason, there is a problem that external user cannot receive notification in regard to sensor information. In this paper, we want to establish a cloud message environment using Google's FCM(Firebase Cloud Messaging) and find out through experiments how users can receive notifications even if they are outside.

• Proceedings of the Korean Society of Computer Information Conference
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• 2022.01a
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• pp.1-2
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• 2022

본 논문은 4차 산업혁명의 핵심기술인 인공지능과 IoT를 피지컬 컴퓨팅을 이용해 교육을 할 수 있는 플랫폼을 설계하였다. 플랫폼은 파이썬 비주얼 블록 프로그래밍을 기반으로 사용자의 코딩 언어의 구문적인 어려움을 감소시키며 데이터 분석과 머신러닝을 쉽게 응용할 수 있다. 피지컬 컴퓨팅을 위한 AIoT 타겟 보드로는 라즈베리파이를 활용하였으며 타겟보드의 하드웨어에 대한 선수 지식을 최소화해서 원하는 시스템을 개발할 수 있다. 응용에서는 센서로 수집한 데이터를 분석하고 인공지능 모델 생성을 할 수 있으며 학습된 모델을 액추에이터 제어에 활용하는 등 AIoT 피지컬 컴퓨팅 교육에 여러 장벽을 낮추었다.

• The Journal of the Korea institute of electronic communication sciences
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• v.14 no.1
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• pp.97-110
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• 2019

Recently, the 4th Industrial Revolution has been emerged and various products are developed and commercialized in preparation of the communication failure. Many solutions are underway in Back-Up Network for IDC Servers, but not in the personal or sensor for low-power system use. Therefore we used the OpenWRT Firmware in Raspberry Pi which can be easily obtained in online market, and it created a low-power load balancer. Therefore, we developed the device that uses LTE Antenna based on USB Interface for communication fault notification and important data. The equipment used in this paper is easy to buy in online shop for anyone. Also, it can be applied in other vendors' boards by using USB. We hope that this paper will contribute to the stability of individual sensor networks.

• The Journal of the Korea institute of electronic communication sciences
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• v.11 no.4
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• pp.433-440
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• 2016

In order to construct a system for big data processing, one needs to configure the node by using network equipments to connect multiple computers or establish cloud environments through virtual hosts on a single computer. However, there are many restrictions on constructing the big data analysis system including complex system configuration and cost. These constraints are becoming a major obstacle to professional manpower training for big data areas which is emerging as one of the most important national competitiveness. As a result, for professional manpower training of big data areas, this paper proposes a Raspberry Pi Board based educational big data processing system which is capable of practical training at an affordable price.