• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2015.10a
• /
• pp.651-653
• /
• 2015

Common Embedded boards like the Arduino, Raspberry Pi, BeagleBone Black, leverages smart home systems, machine tools and various products in our day to day life. Managing and dealing frequent large scale incidents involving recent reagents and hazardous materials can be dangerous and difficult to detect in advance like in an event of an accidents or fires. In this paper I have done research by utilizing an Embedded (BeagleBone Black) boards sensors and RFID management system to detect a hazardous situation like fire in real time and avoiding it by sending out an alert message to the admin user to minimizing the risk. This system provides immediate information to the administrator of any hazardous situation and prevents any accidents from occurring.

• International Journal of Advanced Culture Technology
• /
• v.5 no.1
• /
• pp.51-57
• /
• 2017

Digital signage is becoming part of daily life across a wide range of visual advertisements segments market used in stations, hotels, retail stores, hotels, etc. The current digital signage system used in market is generally works on limited user interactivity with static contents. In this paper, a new approach is proposed using computer vision based dynamic audience adaptive cost-effective digital signage system. The proposed design uses the Camera attached Raspberry Pi Open source platform to employ the real-time audience interaction using computer vision algorithms to extract facial features of the audience. The real-time facial features are extracted using Haar Cascade algorithm which are used for audience gender specific rendering of dynamic digital signage content. The audience facial characterization using Haar Cascade is evaluated on the FERET database with 95% accuracy for gender classification. The proposed system, developed and evaluated with male and female audiences in real-life environments camera embedded raspberry pi with good level of accuracy.

• The Journal of the Korea institute of electronic communication sciences
• /
• v.13 no.5
• /
• pp.1079-1084
• /
• 2018

The vehicle's black box is not suitable for bicycle black box because they contain sensors that are not suitable for bicycle black box. Therefore, this study implemented a system for viewing a video with a mobile phone as the slope changes. The angle was measured by using the gyro sensor and this angle was saved based on the angle setting on the raspberry pi. It has developed a system that allows users to download saved video files through mobile phone applications via FTP.

• Journal of the Institute of Convergence Signal Processing
• /
• v.20 no.3
• /
• pp.145-150
• /
• 2019

We develop the system realization of whale sound reconstruction by inverse MFCC algorithm with the weighted L2-norm minimization techniques. The output products from this research will contribute to the whale tourism and multimedia content industry by combining whale sound contents with the prototype of 3D printing. First of all, we develop the softwares for generating whale sounds and install them into Raspberry Pi hardware and fasten them inside a 3D printed whale. The languages used in the development of this system are the C++ for whale-sounding classification, MATLAB and Python for whale-sounding playback algorithm, and Rhino 6 for 3D printing.

• The Transactions of The Korean Institute of Electrical Engineers
• /
• v.65 no.7
• /
• pp.1252-1256
• /
• 2016

Internet of Things(IoT)-devices are now expanding inter-connecting networking technologies to invent healthcare monitoring system especially for assessing physiological conditions of the chronically-ill patients those with cardiovascular diseases. Hence, IoT system is expected to be utilized for home healthcare by dedicating the original usage of IoT devices to collect the biomedical data such as electrocardiogram(ECG) and photoplethysmography(PPG) signal. The aim of this work is to implement health monitoring system by integrating IoT devices with Raspberry-pi components to measure and analyze ECG and the multi-channel PPG signals. The acquired data and fiducial features from our system can be transmitted to mobile devices via wireless networking technology to support the concept of tele-monitoring services based on IoT devices.

• Korean Journal of Medicinal Crop Science
• /
• v.17 no.3
• /
• pp.165-172
• /
• 2009

The bramble cultivated widely in South Korea, which is known as Bokbunja-ddal-gi, is regarded as having originated from Korean native Rubus coreanus. This study was carried out to obtain basic phylogenetic information on Korean cultivated bramble (KCB) by comparing the internal transcribed spacer (ITS) regions with those of R. coreanus, blackberry (R. lanciniatus), black (R. occidentalis) and red (R. idaeus) raspberry. Sequences of the ITS 1 suggest that some KCB accessions share a significant similarity with both R. occidentalis and R. coreanus in the ITS 1 region. The ITS 2 sequences of the three KCB accessions clustered more closely to those of two R. occidentalis accessions than to those of R. coreanus. These results suggest that there exist variations in the sequences of ITS among KCB accessions and KCB accessions are more closely related to black raspberry than R. coreanus in the ITS regions.

• The Journal of the Korea institute of electronic communication sciences
• /
• v.14 no.1
• /
• pp.213-218
• /
• 2019

In this paper, we study autonomous navigation system for path guide system by using RFID that is enable to navigate and load in hotel. In case of a mobile robot used in a general autonomous navigation guidance system, a large amount of sensors are added to the system in order to improve the accuracy, resulting in cost problems. Therefore, to reduce the number of sensors, and to increase the accuracy and recognition rate, an autonomous driving guidance system was implemented using one of the inexpensive small micro controller units (MCU) such as Raspberry Pi3.

• Proceedings of the Korean Society of Computer Information Conference
• /
• 2019.07a
• /
• pp.153-155
• /
• 2019

본 논문에서는 다양한 아두이노 무선센서 모듈과 Raspberry Pi, 웹서버를 이용한 IOT 기반 환경정보 수집시스템과 기상청 API를 통한 기상정보, 상점 서비스를 매시업하여 상품추천시스템을 구현하였다. 이 시스템은 사용자가 주변 환경의 데이터를 정확하게 확인하고 그에 맞는 상품을 추천받을 수 있도록 한다. 상품추천시스템에서는 상점 외부에 부착된 환경정보 수집시스템에서 측정한 데이터와 기상청 API 데이터를 DB에 저장하고 DB에 저장된 데이터를 이용하여 상황에 맞는 기후화면디자인과 환경정보 데이터를 html로 구성하여 보여준다. Raspverry Pi에 연결된 모니터를 통해 실시간으로 정보를 보여주며 일정 시간 간격으로 관련 상품 광고를 보여주며 필요한 물건을 추천해준다.

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

• Journal of the Korea Institute of Information Security & Cryptology
• /
• v.31 no.3
• /
• pp.527-532
• /
• 2021

In this paper, we propose an efficient finite field computation method for Rainbow algorithm, which is the only multivariate quadratic-equation based digital signature among the current US NIST PQC standardization Final List algorithms. Recently, Chou et al. proposed a new efficient implementation method for Rainbow on the Cortex-M4 environment. This paper proposes a new multiplication method over the finite field that can reduce the number of XOR operations by more than 13.7% compared to the Chou et al. method. In addition, a multiplicative inversion over that can be performed by a 4x4 matrix inverse instead of the table lookup method is presented. In addition, the performance is measured by porting the software to which the new method was applied onto RaspberryPI 3B+.