• Journal of IKEEE
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• v.23 no.3
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• pp.777-784
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• 2019

A pre-fire awareness and automatic notification system are required because it is possible to minimize the damage if the fire situation is precisely detected after a fire occurs in a place where people are unusual or in a mountainous area. In this study, we developed a RaspberryPi-based fire recognition system using Faster-recurrent convolutional neural network (F-RCNN) and single shot multibox detector (SSD) and demonstrated a fire alarm system that works with power line communication. Image recognition was performed with a pie camera of RaspberryPi, and the detected fire image was transmitted to a monitoring PC through an inductive power line communication network. The frame rate per second (fps) for each learning model was 0.05 fps for Faster-RCNN and 1.4 fps for SSD. SSD was 28 times faster than F-RCNN.

• Journal of IKEEE
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• v.24 no.2
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• pp.392-402
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• 2020

This paper proposes a solar tracking system without photo-sensors. The system can be classified into four modules: Solar Tracking, MPPT, ESS, and Real-Time Monitoring. Nine solar panels, as a basic unit, are adopted with grid structures of different heights to reduce wind influence and to enable solar tracking without photo-sensors. The low-cost MCU implements MPPT method which generates PWM switching signal for boost converter. The unit of ESS consists of three-series and four-parallel lithium-ion batteries in order to enable monitoring for abnormalities in temperature and electrical characteristics of battery. Four MCUs used in the system consists of two AVR Atmega128, and two Raspberry PI, and they exchanges operation informations. Experimental results of the proposed system show the solar tracking performance, the possibility of on-site and remote monitoring and the convenience of maintenance based on IoT technology.

• Smart Media Journal
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• v.6 no.3
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• pp.15-20
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• 2017

Recently, the automotive industry has been studied about driver assistance systems for helping drivers to drive their cars easily by integrating them with the IT technology. This study suggests a method of detecting lanes, robust to road condition changes and applicable to lane departure warning and autonomous vehicles mode. The proposed method uses the method of detecting candidate areas by using the Gaussian filter and by determining the Otsu threshold value and edge. Moreover, the proposed method uses lane gradient and width information through the Hough transform to detect lanes. The method uses road lane information detected before to detect dashed lines as well as solid lines, calculates routes in which the lanes will be located in the next frame to draw virtual lanes. The proposed algorithm was identified to be able to detect lanes in both dashed- and solid-line situations, and implement real-time processing where applied to Raspberry Pi 2 which is open source hardware.

• Smart Media Journal
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• v.10 no.1
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• pp.55-62
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• 2021

We applied machine learning of semi-supervised learning, transfer learning, and federated learning as examples of AI use cases that can be applied to the three major industries(Automobile industry, Energy industry, and AI/Healthcare industry) of Gwangju Metro-city, and established an ML strategy for AI services for the major industries. Based on the ML strategy of AI service, practical approaches are suggested, the semi-supervised learning approach is used for automobile image recognition technology, and the transfer learning approach is used for diabetic retinopathy detection in the healthcare field. Finally, the case of the federated learning approach is to be used to predict electricity demand. These approaches were tested based on hardware such as single board computer Raspberry Pi, Jaetson Nano, and Intel i-7, and the validity of practical approaches was verified.

• Journal of the Korea Society of Computer and Information
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• v.27 no.9
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• pp.279-286
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• 2022

The purpose of this study is to present a case of the development and application of a one-time special lecture program that requires the use of computers in frontline elementary and secondary schools. For this purpose, the researcher developed an Arduino-based special lecture program that works as a teaching tool to help with the functions of a student PC with a Raspberry Pi. This special lecture program was applied at three elementary and middle schools near K-University, and then the program was evaluated. The results of this study are as follows. First, the researcher developed a teaching aid for PC functions to be used in special lectures. Second, teaching and learning materials for visiting special lecture education programs using Arduino were developed. Third, in the special lecture, a teaching-learning method was used to guide a small number of students individually. Fourth, the special lecture program resulted in high satisfaction. The results of this study can be a useful reference for teachers who plan one-time special lecture programs requiring computers or for those who want to apply physical computing-related devices in an educational field.

• Proceedings of the Korean Society of Computer Information Conference
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• 2020.07a
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• pp.335-338
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• 2020

주로 맵 빌딩 테스트는 불안정한 환경이 아닌 안정된 환경을 조성한 후에 이루어진다. 본 논문에서는 인위적인 안정된 환경이 아닌 불안정한 환경에서 맵 빌딩을 테스트한다. 맵 빌딩 테스트를 위하여 터틀봇3 버거를 사용한다. 터틀봇3의 라이더 센서를 이용하여 맵 빌딩을 진행한다. 터틀봇3는 라즈베리파이로 제어되며 맵 빌딩과 터틀봇3 제어를 위해서는 ROS를 사용한다. 터틀봇3는 우분투와 ROS가 설치된 컴퓨터와 네트워크 통신을 하며 맵 빌딩을 한다. 불안정한 환경에서 맵빌딩이 동작 및 오동작하는 모습을 확인하였으며, 향후 이를 보완하기 위한 방향을 제시한다.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.23 no.12
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• pp.1742-1745
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• 2019

Hidden flame detection after allegedly extinguishing a fire cannot be emphasized enough. There are a few commercial hidden fire detection equipments which are imported, but the cost is relatively high. In this contribution, we propose a development of a low-cost, high-performance hidden flame detector using open-source hardware/software. We use Raspberry-pi based hardware board equipped with a TFT touch-screen LCD, a 3G modem, and an attachable battery device altogether integrated in a plastic case fabricated with a 3D printer. The proposed hidden flame detector shows the same performance of a commercial product FLIR E5 while consuming less than a half of the cost.

• IEMEK Journal of Embedded Systems and Applications
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• v.14 no.3
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• pp.113-121
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• 2019

Algorithms for geographical routing and location update attract the researchers' interests in wireless ad hoc networks. Even though many various schemes have been proposed, most of them cause scalability problem in small groups of nodes. To defeat this problem, flooding algorithm is widely utilized due to low complexity. However, there is no previous research work to evaluate flooding algorithm through implementation instead of simulation. In this paper, we present implementation of flooding algorithm on Raspberry Pi and performance evaluation results.

• Proceedings of the Korea Information Processing Society Conference
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• 2016.10a
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• pp.71-74
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• 2016

재난지역의 영상 촬영 및 물품 조달 등 인간이 직접 수행하기 어려운 임무를 대신하기 위해 드론이 사용된다. 시중에 판매되고 있는 드론들은 비행과 영상촬영 기능을 모두 제공하지만 firmware 및 응용프로그램 소스코드가 제한적으로 공개되어 있어 일반 개발자가 드론의 firmware를 수정하거나 센서 및 카메라를 직접 제어할 수 없다는 단점이 있다. 하지만 개발자의 목적에 맞는 드론의 비행 시스템을 구축하기 위해서는 시스템 내부의 제어코드를 직접 수정할 필요성이 있다. Pixhawk는 firmware 및 관련 application의 개발에 대한 소스 코드가 공개되어 있고, 일반 개발자들의 접근이 상대적으로 용이하다는 장점이 있다. 본 프로젝트에서는 Pixhawk와 3D Robotics 사에서 제공하는 Drone-Kit Platform을 활용하여 조난 상황에 대한 인명 구조 시스템을 설계하고, 응급상황에 대한 드론 제어 시스템을 구현하였다.

• Proceedings of the Korea Information Processing Society Conference
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• 2017.11a
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• pp.1155-1158
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• 2017

자동차 키의 발전이 커지면서 만드는데 있어 드는 비용이 점차 증가하고 있다. 그럼으로써 자동차 키를 분실 시 따른 개인적인 비용 손실이 증가하고 있다. 자동차 키의 분실을 방지하고자 자동차 키에 BLE 4.0의 동글을 부착하며 BLE 4.0의 RSSI을 활용한 위치 기반 서비스 시스템을 이요하고 자동차 키의 실시간 위치 확인 가능하도록 하며 우리의 눈을 통해 더 정확히 위치를 파악할 수 있도록 소리/진동 알림과 LED를 동글에 부착하여 시스템을 구축하였다.