• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.23 no.4
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• pp.99-105
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• 2023

In this paper, an intelligent CCTV was designed and experimentally developed by using an IOT device, Raspberry Pi, and artificial intelligence technology. Object Detection technology was used to detect the number of people on the CCTV screen, and Action Detection technology provided by OpenPose was used to detect emergency situations. The proposed system has a structure of CCTV, server and client. CCTV uses Raspberry Pi and USB camera, server uses Linux, and client uses iPhone. Communication between each subsystem was implemented using the MQTT protocol. The system developed as a prototype could transmit images at 2.7 frames per second and detect emergencies from images at 0.2 frames per second.

• Journal of IKEEE
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• v.26 no.1
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• pp.10-18
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• 2022

Accurate SOC estimation is an important indicator of battery operation strategies, and many studies have been conducted. The simulation method which was mainly used in previous studies, is difficult to conduct real-time SOC estimation like real BMS environment. Therefore, this paper aims to implement a real-time battery SOC estimation embedded system and analyze problems that can arise during the verification process. In environment consisting of two Raspberry Pi boards, SOC estimation with the EKF uses data measured by the Simscape battery model. Considering that the operating characteristics of the battery vary depend on the temperature, the results were analyzed at various ambient temperatures. It was confirmed that accurate SOC estimation was performed even when offset fault and packet loss occurred due to communication or sensing problems. This paper proposes a guide for embedded system strategies that enable real-time SOC estimation with errors within 5%.

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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• v.8 no.6
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• pp.909-917
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• 2018

Recently, the Internet of Thing (IoT) technology is expanding explosively in the number of devices and applications in many application areas. In IoT systems, sensors and actuators are connected to the Internet and cooperate to do some applications by exchanging information. In this paper an IoT smart home system is developed to monitor and control home devices easily. Our system consists of sensor devices, IoT gateways, and an IoT server. Sensor devices developed using Rfduino sense the physical world and transmit their data using BLE to the IoT server thru the IoT gateway. We implemented the IoT gateway using Raspberry Pi and the IoT server using ARTIK cloud. We installed our system and made a test in our lab, which showed that our system can be installed and managed easily and extended its functionality in an easy way. By taking advantage of the rule mechanism and action messages of ARTIK cloud, we implemented the control of device parameters easily by sending action messages to the ARTIK cloud.

• Journal of Advanced Navigation Technology
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• v.28 no.4
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• pp.428-435
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• 2024

In this paper, a human activity regeneration (HAR) system based on multiple input multiple output frequency modulation continuous wave (MIMO FMCW) radar was designed and implemented. Using point cloud data from MIMO radar sensors has advantages in terms of privacy, safety, and accuracy. For the implementation of the HAR system, a customized neural network based on PointPillars and depthwise separate convolutional neural network (DS-CNN) was developed. By processing high-resolution point cloud data through a lightweight network, high accuracy and efficiency were achieved. As a result, the accuracy of 98.27% and the computational complexity of 11.27M multiply-accumulates (Macs) were achieved. In addition, the developed neural network model was implemented on Raspberry-Pi embedded system and it was confirmed that point cloud data can be processed at a speed of up to 8 fps.

• 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.

• The Journal of the Korea institute of electronic communication sciences
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• v.15 no.1
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• pp.93-100
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• 2020

In this paper, we implemented a smart mirror that helps users to measure the results before the procedure by reflecting various hairstyles on the head. When the camera is used to capture a face in real time and recognize the face, the stored hair image is uploaded to provide a virtual image. In addition, the high production cost, which is a problem of the existing smart mirrors, was reduced by using Raspberry Pi, Open CV, and half mirror film, and various functions were implemented through touch control. It is also designed to provide information such as weather, calendar and time.

• The Journal of the Korea institute of electronic communication sciences
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• v.16 no.6
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• pp.1271-1278
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• 2021

In this paper, we implemented smart mirrors that virtually select and experience eyeglasses and hair styles on user faces through face recognition and recommend weather-specific clothes to guide various styles. In addition, makeup is possible while watching the video while looking at the screen. Raspberry Pi, acrylic plate and half mirror film were used to reduce the cost of conventional smart mirrors. It also added basic information such as weather, dates, calendars, and news, and increased user convenience by using a touchscreen.

• The Journal of the Korea institute of electronic communication sciences
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• v.16 no.4
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• pp.689-698
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• 2021

In this paper, lane recognition, steering control and speed control algorithms were developed using Bluetooth wireless communication and image processing techniques. Instead of recognizing road traffic signals based on image processing techniques, a methodology for recognizing the permissible road speed by receiving speed codes from electronic traffic signals using Bluetooth wireless communication was developed. In addition, a steering control algorithm based on PWM control that tracks the lanes using the Canny algorithm and Hough transform was developed. A vehicle prototype and a driving test track were developed to prove the accuracy of the developed algorithm. Raspberry Pi and Arduino were applied as main control devices for steering control and speed control, respectively. Also, Python and OpenCV were used as implementation languages. The effectiveness of the proposed methodology was confirmed by demonstrating effectiveness in the lane tracking and driving control evaluation experiments using a vehicle prototypes and a test track.

• Proceedings of the Korean Society of Computer Information Conference
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• 2016.07a
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• pp.133-134
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• 2016

본 논문에서는 라즈베리파이에 LTE를 장착하여 PC 서버와 통신을 하여 라즈베리파이 보드에서 GPS와 이미지에 대한 정보를 전송해 주고 PC 서버에서 정보를 받아 데이터베이스에서 저장이 되도록 개발하였다. 이 기술은 LTE를 통하여 원거리 통신이 가능 하도록 해주며, PC 서버에 Spring Framework 개발 툴을 이용하여 GPS 정보와 이미지를 웹 브라우저에서 볼 수 있도록 구축하였다. 또한 PC 서버의 데이터베이스에서 들어오는 정보를 계속해서 저장을 해 주도록 하여 웹 브라우저에서 지나간 GPS의 정보와 이미지를 볼 수 있도록 하였다. 이 기술을 이용하여 드론에 적용하여 실시간 재난 모니터링 시스템으로 구축할 계획이다.

• Annual Conference of KIPS
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• 2017.04a
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• pp.111-112
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• 2017

IoT(Internet of Thing)기술의 발전으로 다양한 분야에서 라즈베리파이(Raspberry Pi)와 같은 경량시스템으로, 실생활에 유용하게 사용될 수 있는 비전문 시스템에 대한 다양한 형태의 기술이 선보이고 있다. 한 예로, 스마트팜(Smart farm)분야에서는 다양한 온실 형태로 과실류를 재배하고 있으며, 보다 전문적인 챔버(Chamber)형태의 시스템으로는 관엽식물/채소/알뿌리식물/인삼 등 다양한 식물류에서 사용되어 질 수 있다. 이에 본 논문에서는 챔버 시스템 상에 서버와의 연결 없이 정해진 생육 규칙에 따라 자동으로 제어 되는 라즈베리파이 엣지(Edge)에 기반한 챔버 제어 시스템에 대한 연구를 담고 있다.