• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2018.05a
• /
• pp.679-680
• /
• 2018

IoT(Internet of Things) is no longer just a concept, and It has become common as individual users have tried to implement it directly through small boards and components. This research implemented a system to control a general toy car using Raspberry pi and motor driver. This research will help develop ordinary toy cars to RC cars or learn on their own and drive on their own through further development.

• Proceedings of the Korean Society of Computer Information Conference
• /
• 2018.01a
• /
• pp.5-6
• /
• 2018

Edge Computing의 성능 분석을 위해 SDN 테스트 베드를 구축하는 방안을 제안한다. Edge Computing 환경에서 연구한 알고리즘들을 실증적 성능 테스트하기 위해 테스트베드를 구축하였다. Raspberry-Pi를 이용해 SDN Switch를 구현하였고, Edge단의 노드는 테스트를 위해 노트북을 연결해 인터넷이 되는지 확인하였다. Edge Computing 환경은 수 많은 노드를 연결해 테스트해야 하며 따라서 SDN 환경이 적절하다. 본 논문에서는 SDN에 대해서 알아보고 Raspberry-Pi를 이용한 테스트 베드 구축 방안에 대해 소개하고자 한다.

• International journal of advanced smart convergence
• /
• v.4 no.2
• /
• pp.120-123
• /
• 2015

The use of smart devices worldwide has been increasing day by day and its applications based on IoT have been also extended. But the power control system requires complicated control and processing information from the various sensors in practice. One of the best ways to save the power consumption is to manage electrical equipment individually on the Internet. In this paper, remote power control system for managing the power through the relay switch module via Python server was implemented by using Raspberry Pi. The proposed power control system can be used anywhere over the Internet.

• International Journal of Computer Science & Network Security
• /
• v.21 no.4
• /
• pp.277-283
• /
• 2021

The objective of this project is to conduct an underwater survey. The primary goal is to develop a device that can achieve the desired output under test conditions. For this reason, certain practical considerations must be taken into account, and the implementation is then developed to be carried out to obtain stable performance with the available hardware based on that experiment. The experiment was performed via BlueROV2 (Remotely Operated Vehicle) using RaspberryPi and softwares such as QGC (QGroundControl) and ArduPilot. This paper explains the work, the results with the collected data and how we implemented the work is presented in the end. The intention of this experiment is to connect two PCs using RaspberryPi with MAVLink communication using a Commercial-Off-The-Shelf device.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2021.10a
• /
• pp.637-639
• /
• 2021

As autonomous driving research is actively progressing, lane detection is an essential technology in ADAS (Advanced Driver Assistance System) to locate a vehicle and maintain a route. Lane detection is detected using an image processing algorithm such as Hough transform and RANSAC (Random Sample Consensus). This paper implements a linear shape detection algorithm using OpenCV on Raspberry Pi 3 B+. Thresholds were set through OpenCV Gaussian blur structure and Canny edge detection, and lane recognition was successful through linear detection algorithm.

• Journal of Korea Society of Digital Industry and Information Management
• /
• v.10 no.4
• /
• pp.79-87
• /
• 2014

In this paper, we implemented the HearCAM platform with Raspberry PI B+ model which is an open source platform. Raspberry PI B+ model consists of dual step-down (buck) power supply with polarity protection circuit and hot-swap protection, Broadcom SoC BCM2835 running at 700MHz, 512MB RAM solered on top of the Broadcom chip, and PI camera serial connector. In this paper, we used the Google speech recognition engine for recognizing the voice characteristics, and implemented the pattern matching with OpenCV software, and extended the functionality of speech ability with SVOX TTS(Text-to-speech) as the matching result talking to the microphone of users. And therefore we implemented the functions of the HearCAM for identifying the voice and pattern characteristics of target image scanning with PI camera with gathering the temperature sensor data under IoT environment. we implemented the speech recognition, pattern matching, and temperature sensor data logging with Wi-Fi wireless communication. And then we directly designed and made the shape of HearCAM with 3D printing technology.

• Journal of The Korean Association of Information Education
• /
• v.23 no.5
• /
• pp.461-467
• /
• 2019

As the convergence solutions become more common, the use of Arduino and Raspberry Pi boards has been increasing. These control boards has to be executed under power blackout. In this environment, we take advantage of solar power system to overcome the power out. In this paper, we poposed a effficient power control strategy. Our experimental device is a DSLR shooting device executed based a predesigned interval time. The control module of our experimental device is the compound system of Raspberry Pi and Arduino boards. Arduino board send the force signals to wake up Raspberry Pi. We developed a new control strategy algorithm for the efficient use of solar power energy. In this paper, we mesured the efficiency of solar enery consuming of our system. We programmed a control system to send DSLR shooting signals. In experimentals, we ensured a stable consuming of electricity during 10 days. In the end, it was found that the consumption power of the Raspberry was reduced by about 81% when the Aduino was combined to save power.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.17 no.9
• /
• pp.745-752
• /
• 2016

In the era of the Internet of Things, where all physical objects are connected to the Internet, we suggest a remote control system using a Raspberry Pi single-board computer with ZigBee, which can turn an indoor light-emitting diode (LED) and a multiple-tap on and off, and with a smart phone can control the brightness of the LED as well as an electronic door lock. By connecting an infrared (IR) transmitter module to the Raspberry Pi, we can control home appliances, such as an air conditioner, and we can also monitor indoor images, indoor temperatures, and illumination by using a smart phone app. We developed a method of finding out IR transmission codes required for remote-controllable appliances with an AVR micro-controller. We suggest a method to remotely open and shut an office door by novating the door lock. The brightness level of an LED (between 0 and 10) can be controlled through a PWM signal generated by an ATmega88 microcontroller. A mutiple-tap is controlled using an ATmega32, a photo-coupler, and a TRIAC. The signals for measured temperature and illumination are converted from analog to digital by using the ATtiny44A microcontroller transmitting to a Raspberry Pi through SPI communication. Then, we connect a camera to the CSI head of the Raspberry Pi. We can turn on the smart multiple-tap for a certain period of time, or we can schedule the multi-tap to turn on at a specific time. To reduce standby power, people usually pull out a power code from multiple-taps or turn off a switch. Our method helps people do the same thing with a smart phone, if they are away from home.

• Journal of Korea Society of Digital Industry and Information Management
• /
• v.11 no.3
• /
• pp.1-9
• /
• 2015

In this paper, we implemented the computer vision platform design with MEAN Stack through Raspberry PI 2 model which is an open source platform. we experimented the face recognition, temperature and humidity sensor data logging with WiFi communication under Raspberry Pi 2 model. Especially we directly made the shape of platform with 3D printing design. In this paper, we used the face recognition algorithm with OpenCV software through haarcascade feature extraction machine learning algorithm, and extended the functionality of wireless communication function ability with Bluetooth technology for the purpose of making Android Mobile devices interface. And therefore we implemented the functions of the vision platform for identifying the face recognition characteristics of scanning with PI camera with gathering the temperature and humidity sensor data under IoT environment. and made the vision platform with 3D printing technology. Especially we used MongoDB for developing the performance of vision platform because the MongoDB is more akin to working with objects in a programming language than what we know of as a database. Afterwards, we would enhance the performance of vision platform for clouding functionalities.

• Journal of Multimedia Information System
• /
• v.6 no.4
• /
• pp.239-244
• /
• 2019

With the development of Cyber-Physical Systems(CPS), several technologies such as automation control, automotive and intelligent house systems have been developed. To enable communication among various components of such systems, several wired and wireless communication protocols are used. The Controller Area Network(CAN) is one of such wired communication protocols that is popularly used for communication in automobiles and other machinery in the industry. In this paper, we designed and implemented a response time analysis system for CAN communication. The reliable data transfer among various electronic components in a significant time is crucial for the smooth operation of an electric vehicle. Therefore, this system is designed to conveniently analyze the response time of various electronic components of a CAN enabled system. The priority for transmission of the messages in the CAN bus is determined by the message identifier. As the number of nodes increases the transmission of low priority messages is delayed due to the existence of higher priority messages on the bus. We used Raspberry Pi3 and PiCAN2 board to simulate the data transfer for studying the comparative delay in low priority nodes.