• International journal of advanced smart convergence
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• v.8 no.4
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• pp.194-199
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• 2019

As the performance of the system increases, more parallelized data is being processed than single processing of data. Today's cpu structure has been developed to leverage multicore, and hence data processing methods are being developed to enable parallel processing. In recent years desktop cpu has increased multicore, data is growing exponentially, and there is also a growing need for data processing as artificial intelligence develops. This neural network of artificial intelligence consists of a matrix, making it advantageous for parallel processing. This paper aims to speed up the processing of the system by using raspberrypi to implement the cluster building and parallel processing system against the backdrop of the foregoing discussion. Raspberrypi is a credit card-sized single computer made by the raspberrypi Foundation in England, developed for education in schools and developing countries. It is cheap and easy to get the information you need because many people use it. Distributed processing systems should be supported by programs that connected multiple computers in parallel and operate on a built-in system. RaspberryPi is connected to switchhub, each connected raspberrypi communicates using the internal network, and internally implements parallel processing using the Message Passing Interface (MPI). Parallel processing programs can be programmed in python and can also use C or Fortran. The system was tested for parallel processing as a result of multiplying the two-dimensional arrangement of 10000 size by 0.1. Tests have shown a reduction in computational time and that parallelism can be reduced to the maximum number of cores in the system. The systems in this paper are manufactured on a Linux-based single computer and are thought to require testing on systems in different environments.

• Proceedings of the Korea Information Processing Society Conference
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• 2023.05a
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• pp.192-193
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• 2023

게임 산업의 성장에 맞춰 그에 따른 게임시스템 보안, 무결성 보장의 중요성 또한 커지고 있다. 본 논문에서는 게임 시스템과 TrustZone을 결합시켜 TrustZone의 Normal World와 Secure World 영역과 그 기능을 활용하여 게임 내 주요 데이터의 위·변조를 방지하여 시스템의 무결성을 보다 높은 수준에서 보장하는 방식을 탐구해보고자 한다.

• Proceedings of the Korean Society of Computer Information Conference
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• 2017.07a
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• pp.172-173
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• 2017

어린 자녀들은 성장하며 많은 문제를 직면하고 어려움을 겪으나 부모들은 자녀들의 고민이 무엇인지, 어떤 생각을 하는지 잘 모른다. 어린 자녀가 부모에게 꺼내기 힘든 고민들을 인형을 통하여 녹음후 저장하고 부모는 듣고 자녀의 고민을 더 알 수 있다. 이를 통하여 말하고 이야기를 들어주는 인형은 어린 자녀들이 심리적으로 안정을 얻을 수 있게 해주며 녹음파일을 통하여 부모와 자녀간의 이해를 돕고 화목한 가정을 이룰 수 있을 것이다. 따라서 본 연구에서는 자녀와의 친숙한 인형에 녹음장치를 삽입하고, 어린이가 인형과의 대화를 녹음하고, 이를 실시간 또는 녹음 후 청취함으로서 자녀의 마음을 이해함으로서 육아에 도움을 주도록 하는 시스템을 개발하였다.

• Proceedings of the Korea Information Processing Society Conference
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• 2019.10a
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• pp.276-279
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• 2019

본 논문은 실내 온도, 습도, 조도, 그리고 토양의 습도까지 탐지하여 자동으로 습도와 빛을 조절해주는 스마트 화분을 다룬다. 화분은 일상생활에서 구할 수 있는 화분을 사용했고 다양한 꽃의 생육 정보를 모은 DB를 기반으로 아두이노를 통해서 다양한 센서 값들을 측정하고 모인 센서 값들은 라즈베리파이로 보내진다. 화분에 부착된 다수의 아두이노로부터 온 데이터를 라즈베리파이가 분석하고 판단해서 사용자에게 전달해주고 조치가 필요한 부분은 아두이노에 전송되어 알맞은 처리가 이뤄진다. 이때 다수의 아두이노와 라즈베리파이의 통신은 지그비 통신이며 라즈베리파이와 사용자 간의 통신은 블루투스와 클라우드 서버를 통해 이루어진다.

• Proceedings of the Korean Society of Computer Information Conference
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• 2021.07a
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• pp.495-496
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• 2021

코로나 19로 인하여 다중이용시설에 출입 시 정부 지침에 따라 QR코드 스캔, 출입 명부 작성, 체온 측정 등 방역절차를 지켜야한다. 본 연구에서는 방역 절차를 간편화하고 동합한 방역 시스템을 제안한다. QR코드 스캐너를 통하여 출입자의 신상 정보를 확인하며 체온 측정 모듈을 통하여 출입자의 체온을 측정한다. 추가적으로 워터펌프를 통하여 소독제를 분사하며 서보모터를 통하여 출입문을 열고 닫는다. 또한, 산업 현장에서는 알코올 측정 센서를 통하여 작업자의 알코올 수치를 측정하여 음주로 인한 산업사고도 예방한다.

• Journal of the Korean Institute of Intelligent Systems
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• v.26 no.4
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• pp.295-300
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• 2016

Internet of things which helps communication between human and thing and between things by connecting networks on them is developing. Develops of Internet of things, network technique, and smart machine result interest on home network system. In this paper, we suggested a system with the home network to the dormitory using pressure sensors, infrared sensor, ultrasonic sensor, switch, arduino, raspberrypi, android application. Smart dormitory system based on the internet of things provide information whether public things in dormitory like laundry machine, computer, treadmill is being used now, and package is arrived through android application.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.18 no.12
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• pp.2885-2890
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• 2014

Localization of a sensor network node using machine learning has been recently studied. It is easy for Support vector machines algorithm to implement in high level language enabling parallelism. Raspberrypi is a linux system which can be used as a sensor node. Pi can be used to construct IP based Hadoop clusters. In this paper, we realized Support vector machine using python language and built a sensor network cluster with 5 Pi's. We also established a Hadoop software framework to employ MapReduce mechanism. In our experiment, we implemented the test sensor network with a variety of parameters and examined based on proficiency, resource evaluation, and processing time. The experimentation showed that with more execution power and memory volume, Pi could be appropriate for a member node of the cluster, accomplishing precise classification for sensor localization using machine learning.

• Journal of Digital Contents Society
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• v.18 no.3
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• pp.607-612
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• 2017

The use of RaspberryPi in building an embedded system may be difficult for users in understanding the circuit and the hardware cost. This paper proposes a solution that can test the systems virtually. The solution consists of three elements; (i) editor, (ii) interpreter and (iii) simulator and provides nine full modules and also allows the users to configure/run/test their own circuits like real environment. The task of abstraction for modules through the actual circuit test was carried out on the basis of the data sheet and the specification provided by the manufacturer. If we can improve the level of quality of our solution, it can be useful in terms of cost reduction and easy learning. To achieve this end, the electrical physics engine, the level of interpreter that can be ported to the actual board, and a generalization of the simulation logic are required.

• 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 Advanced Navigation Technology
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• v.24 no.6
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• pp.620-626
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• 2020

This research propose and simulate a solar power generation system monitoring system based on Modbus TCP communication using RaspberryPi, an IOT equipment, as a master and an inverter as a slave. In this model, various sensors are added to the RaspberryPi to add necessary information for monitoring solar power plants, and power generation prediction and monitoring information are transmitted to the smart phone through real-time power generation prediction. In addition, information that is continuously generated by the solar power plant is built on the server as big data, and a deep learning model for predicting power generation is trained and updated. As a result of the study, stable communication was possible based on Modbus TCP with the Raspberry Pi in the inverter, and real-time prediction was possible with the deep learning model learned in the Raspberry Pi. The server was able to train various deep learning models with big data, and it was confirmed that LSTM showed the best error with a learning error of 0.0069, a test error of 0.0075, and an RMSE of 0.0866. This model suggested that it is possible to implement a real-time monitoring system that is simpler, more convenient, and can predict the amount of power generation for inverters of various manufacturers.