• Title/Summary/Keyword: Raspberry Pi3

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Design of Data Center Environmental Monitoring System Based On Lower Hardware Cost

  • Nkenyereye, Lionel;Jang, Jongwook
    • Journal of Multimedia Information System
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    • v.3 no.3
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    • pp.63-68
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    • 2016
  • Environmental downtime produces a significant cost to organizations and makes them unable to do business because what happens in the data center affects everyone. In addition, the amount of electrical energy consumed by data centers increases with the amount of computing power installed. Installation of physical Information Technology and facilities related to environmental concerns, such as monitoring temperature, humidity, power, flood, smoke, air flow, and room entry, is the most proactive way to reduce the unnecessary costs of expensive hardware replacement or unplanned downtime and decrease energy consumed by servers. In this paper, we present remote system for monitoring datacenter implementing using open-source hardware platforms; Arduino, Raspberry Pi, and the Gobetwino. The sensed data displayed through Arduino are transferred using Gobetwino to the nearest host server such as temperature, humidity and distance every time an object hitting another object or a person coming in entrance. The raspberry Pi records the sensed data at the remote location. The objective of collecting temperature and humidity data allows monitoring of the server's health and getting alerts if things start to go wrong. When the temperature hits $50^{\circ}C$, the supervisor at remote headquarters would get a SMS, and then they would take appropriate actions to reduce electrical costs and preserve functionality of servers in data centers.

Study of Autonomous Navigation for Path Guide System Using RFID (RFID를 이용한 자율주행 안내 시스템 연구)

  • Kim, Taek-Su;Kim, Youn-Gon;Jeong, Hyeon-Woo;Kim, Young-Jun;Park, Yong-Wook
    • The Journal of the Korea institute of electronic communication sciences
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    • v.14 no.1
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    • pp.213-218
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    • 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.

Efficient Implementation of Finite Field Operations in NIST PQC Rainbow (NIST PQC Rainbow의 효율적 유한체 연산 구현)

  • Kim, Gwang-Sik;Kim, Young-Sik
    • Journal of the Korea Institute of Information Security & Cryptology
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    • v.31 no.3
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    • pp.527-532
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    • 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+.

Implementation of The Personal Secretary System using Raspberry-Pi (라즈베리파이를 이용한 개인 비서 시스템 구현)

  • Park, Na-Hyun;Park, Ji-Hyun;Yun, So-Hyun;Park, Jeong-Sik;Kim, Tai-Woo
    • Journal of Internet of Things and Convergence
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    • v.3 no.1
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    • pp.1-8
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    • 2017
  • Information and time are very important for a modem life, and researches about the personal secretary system that provides specific information for each individual are being studied. In this research, we developed the personal secretary system called Genie which provides the user with desired informations such as weather, news, and traffic information with time. It is expected that the Genie system will provide information on news, weather, traffic information including bus arrival times, and memos with time so that users can find their own leisure time and live a comfortable life.

Implementation of Indoor Positioning System using Raspberry Pi and RSSI Scanner (라즈베리파이와 RSSI 스캐너를 활용한 실내측위 시스템 구현)

  • Lee, Sung-jin;Choi, Jun-hyeong;Choi, Byeong-yoon
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2021.10a
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    • pp.640-642
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    • 2021
  • In order to collect a lot of data clearly and efficiently, it is essential to know the locations of the current facilities and analyze the movement data. The current location collection technology can collect data using a GPS (Global Positioning System) sensor, but in the case of GPS, it has strong straightness and low diffraction and reflectivity, making it difficult to position indoors. It is impossible to measure the distance between the server and the client because the signal sensitivity cannot be received. This paper implements an indoor positioning system using beacons and scanners in Raspberry Pi 3 B+. It controls Advertise Mode and Connection Mode at the same time using the scanner algorithm.

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Data Collection Management Program for Smart Factory (스마트팩토리를 위한 데이터 수집 관리 프로그램 개발)

  • Kim, Hyeon-Jin;Kim, Jin-Sa
    • Journal of the Korean Institute of Electrical and Electronic Material Engineers
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    • v.35 no.5
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    • pp.509-515
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    • 2022
  • As the 4th industrial revolution based on ICT is progressing in the manufacturing field, interest in building smart factories that can be flexible and customized according to customer demand is increasing. To this end, it is necessary to maximize the efficiency of factory by performing an automated process in real time through a network communication between engineers and equipment to be able to link the established IT system. It is also necessary to collect and store real-time data from heterogeneous facilities and to analyze and visualize a vast amount of data to utilize necessary information. Therefore, in this study, four types of controllers such as PLC, Arduino, Raspberry Pi, and embedded system, which are generally used to build a smart factory that can connect technologies such as artificial intelligence (AI), Internet of Things (IoT), and big data, are configured. This study was conducted for the development of a program that can collect and store data in real time to visualize and manage information. For communication verification by controller, data communication was implemented and verified with the data log in the program, and 3D monitoring was implemented and verified to check the process status such as planned quantity for each controller, actual quantity, production progress, operation rate, and defect rate.

Implementation of Enhanced Vision for an Autonomous Map-based Robot Navigation

  • Roland, Cubahiro;Choi, Donggyu;Kim, Minyoung;Jang, Jongwook
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2021.10a
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    • pp.41-43
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    • 2021
  • Robot Operating System (ROS) has been a prominent and successful framework used in robotics business and academia.. However, the framework has long been focused and limited to navigation of robots and manipulation of objects in the environment. This focus leaves out other important field such as speech recognition, vision abilities, etc. Our goal is to take advantage of ROS capacity to integrate additional libraries of programming functions aimed at real-time computer vision with a depth-image camera. In this paper we will focus on the implementation of an upgraded vision with the help of a depth camera which provides a high quality data for a much enhanced and accurate understanding of the environment. The varied data from the cameras are then incorporated in ROS communication structure for any potential use. For this particular case, the system will use OpenCV libraries to manipulate the data from the camera and provide a face-detection capabilities to the robot, while navigating an indoor environment. The whole system has been implemented and tested on the latest technologies of Turtlebot3 and Raspberry Pi4.

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How to fix errors in ROS installation and control for TurtleBot 3 (터틀봇3를 위한 ROS 설치 및 제어의 오류 해결 방법)

  • Park, Tae-Whan;Lee, Kang-Hee
    • Proceedings of the Korean Society of Computer Information Conference
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    • 2020.07a
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    • pp.331-334
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    • 2020
  • 터틀봇3(Turtlebot3)을 제어하기 위하여 피시와 터틀봇3 각각에 ROS(Robot Operating System)을 설치하고 제어한다. 터틀봇3는 라즈베리파이 3 보드로 제어되는 오픈소스 로봇이다. 전세계에서 유명한 교육 및 연구용 로봇이지만 설치와 제어 과정에서 여러 오류를 경험하는 사용자들이 있다. 본 논문은 터틀봇3를 처음 사용하는 사용자들을 위하여 설치과정과 설치과정에서 발생하는 오류들에 대하여 다룬다.

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Bluetooth Smart Ready implementation and RSSI Error Correction using Raspberry (라즈베리파이를 활용한 블루투스 Smart Ready 구현 및 RSSI 오차 보정)

  • Lee, Sung Jin;Moon, Sang Ho
    • Journal of Korea Multimedia Society
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    • v.25 no.2
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    • pp.280-286
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    • 2022
  • In order to efficiently collect data, it is essential to locate the facilities and analyze the movement data. The current technology for location collection can collect data using a GPS sensor, but GPS has a strong straightness and low diffraction and reflectance, making it difficult for indoor positioning. In the case of indoor positioning, the location is determined by using wireless network technologies such as Wifi, but there is a problem with low accuracy as the error range reaches 20 to 30 m. In this paper, using BLE 4.2 built in Raspberry Pi, we implement Bluetooth Smart Ready. In detail, a beacon was produced for Advertise, and an experiment was conducted to support the serial port for data transmission/reception. In addition, advertise mode and connection mode were implemented at the same time, and a 3-count gradual algorithm and a quadrangular positioning algorithm were implemented for Bluetooth RSSI error correction. As a result of the experiment, the average error was improved compared to the first correction, and the error rate was also improved compared to before the correction, confirming that the error rate for position measurement was significantly improved.

Design and Implementation of IoT based Low cost, Effective Learning Mechanism for Empowering STEM Education in India

  • Simmi Chawla;Parul Tomar;Sapna Gambhir
    • International Journal of Computer Science & Network Security
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    • v.24 no.4
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    • pp.163-169
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    • 2024
  • India is a developing nation and has come with comprehensive way in modernizing its reducing poverty, economy and rising living standards for an outsized fragment of its residents. The STEM (Science, Technology, Engineering, and Mathematics) education plays an important role in it. STEM is an educational curriculum that emphasis on the subjects of "science, technology, engineering, and mathematics". In traditional education scenario, these subjects are taught independently, but according to the educational philosophy of STEM that teaches these subjects together in project-based lessons. STEM helps the students in his holistic development. Youth unemployment is the biggest concern due to lack of adequate skills. There is a huge skill gap behind jobless engineers and the question arises how we can prepare engineers for a better tomorrow? Now a day's Industry 4.0 is a new fourth industrial revolution which is an intelligent networking of machines and processes for industry through ICT. It is based upon the usage of cyber-physical systems and Internet of Things (IoT). Industrial revolution does not influence only production but also educational system as well. IoT in academics is a new revolution to the Internet technology, which introduced "Smartness" in the entire IT infrastructure. To improve socio-economic status of the India students must equipped with 21st century digital skills and Universities, colleges must provide individual learning kits to their students which can help them in enhancing their productivity and learning outcomes. The major goal of this paper is to present a low cost, effective learning mechanism for STEM implementation using Raspberry Pi 3+ model (Single board computer) and Node Red open source visual programming tool which is developed by IBM for wiring hardware devices together. These tools are broadly used to provide hands on experience on IoT fundamentals during teaching and learning. This paper elaborates the appropriateness and the practicality of these concepts via an example by implementing a user interface (UI) and Dashboard in Node-RED where dashboard palette is used for demonstration with switch, slider, gauge and Raspberry pi palette is used to connect with GPIO pins present on Raspberry pi board. An LED light is connected with a GPIO pin as an output pin. In this experiment, it is shown that the Node-Red dashboard is accessing on Raspberry pi and via Smartphone as well. In the final step results are shown in an elaborate manner. Conversely, inadequate Programming skills in students are the biggest challenge because without good programming skills there would be no pioneers in engineering, robotics and other areas. Coding plays an important role to increase the level of knowledge on a wide scale and to encourage the interest of students in coding. Today Python language which is Open source and most demanding languages in the industry in order to know data science and algorithms, understanding computer science would not be possible without science, technology, engineering and math. In this paper a small experiment is also done with an LED light via writing source code in python. These tiny experiments are really helpful to encourage the students and give play way to learn these advance technologies. The cost estimation is presented in tabular form for per learning kit provided to the students for Hands on experiments. Some Popular In addition, some Open source tools for experimenting with IoT Technology are described. Students can enrich their knowledge by doing lots of experiments with these freely available software's and this low cost hardware in labs or learning kits provided to them.