scholarly journals Benchmarking Raspberry Pi 2 Beowulf Cluster

2018 ◽  
Vol 179 (32) ◽  
pp. 21-27 ◽  
Author(s):  
Dimitrios Papakyriakou ◽  
Dimitra Kottou ◽  
Ioannis Kostouros
Keyword(s):  
Raspberry Pi ◽  
Beowulf Cluster

Scaling XML Using a Beowulf Cluster

2018 ◽  
Author(s):  
John J. Chelsom ◽  
Jay H. Chelsom
Keyword(s):  
Open Source ◽  
Low Cost ◽  
Data Access ◽  
Raspberry Pi ◽  
Optimal Size ◽  
Database Access ◽  
Xml Databases ◽  
Beowulf Cluster ◽  
Cost Efficient ◽  
And Performance

We describe a series of experiments which test the performance and scalability of an XML records system deployed on a Beowulf cluster of open source XML databases. Using the open source cityEHR health records system as an example, we first ran experiments to determine the feasibility and optimal size of database instances running on Raspberry Pi and low-cost Intel computers. We describe the implementation of a Data Access Layer for create, read, query and delete operations, using XForms submissions, which encapsulates all database access. We then present the results of testing the scalability and performance of this implementation on clusters of one to sixteen physical database nodes. We conclude that Beowulf clustering provides an effective and cost-efficient mechanism for scaling XML records systems.

PROTOTYPE ALAT PEMANTAU SALURAN AIR BAWAH TANAH DENGAN MENGGUNAKAN WEBCAM C170 BERBASIS RASPBERRY PI

2015 ◽  
Vol 1 (1) ◽  
pp. 37-45
Author(s):  
Irwansyah Irwansyah ◽  
Hendra Kusumah ◽  
Muhammad Syarif
Keyword(s):  
Real Time ◽  
Monitoring System ◽  
Public Awareness ◽  
Underground Water ◽  
Raspberry Pi ◽  
Laptop Computer ◽  
Web Browser ◽  
Disaster Monitoring ◽  
The Times ◽  
Human Desire

Along with the times, recently there have been found tool to facilitate human’s work. Electronics is one of technology to facilitate human’s work. One of human desire is being safe, so that people think to make a tool which can monitor the surrounding condition without being monitored with people’s own eyes. Public awareness of the underground water channels currently felt still very little so frequent floods. To avoid the flood disaster monitoring needs to be done to underground water channels.This tool is controlled via a web browser. for the components used in this monitoring system is the Raspberry Pi technology where the system can take pictures in real time with the help of Logitech C170 webcam camera. web browser and Raspberry Pi make everyone can control the devices around with using smartphone, laptop, computer and ipad. This research is expected to be able to help the users in knowing the blockage on water flow and monitored around in realtime.

Implementasi Voip Server Berbasis IPV6 Dengan Raspberry PI

2019 ◽  
Vol 9 (01) ◽  
pp. 47-54
Author(s):  
Rabbai San Arif ◽  
Yuli Fitrisia ◽  
Agus Urip Ari Wibowo
Keyword(s):  
Internet Protocol ◽  
Wireless Transmission ◽  
Raspberry Pi ◽  
Test Results ◽  
Average Delay ◽  
Ipv6 Network ◽  
Ip Network ◽  
Selection Of ◽  
Better Than

Voice over Internet Protocol (VoIP) is a telecommunications technology that is able to pass the communication service in Internet Protocol networks so as to allow communicating between users in an IP network. However VoIP technology still has weakness in the Quality of Service (QoS). VOPI weaknesses is affected by the selection of the physical servers used. In this research, VoIP is configured on Linux operating system with Asterisk as VoIP application server and integrated on a Raspberry Pi by using wired and wireless network as the transmission medium. Because of depletion of IPv4 capacity that can be used on the network, it needs to be applied to VoIP system using the IPv6 network protocol with supports devices. The test results by using a wired transmission medium that has obtained are the average delay is 117.851 ms, jitter is 5.796 ms, packet loss is 0.38%, throughput is 962.861 kbps, 8.33% of CPU usage and 59.33% of memory usage. The analysis shows that the wired transmission media is better than the wireless transmission media and wireless-wired.

Conception and implementation of a course for professional training and education in the field of IoT and smart home security

2020 ◽  
Vol 2020 (3) ◽  
pp. 277-1-277-8
Author(s):  
Michael Pilgermann ◽  
Thomas Bocklisch ◽  
Reiner Creutzburg
Keyword(s):  
Smart Home ◽  
Professional Training ◽  
Raspberry Pi ◽  
Science Students ◽  
Training And Education ◽  
Home Security ◽  
Master Level ◽  
University Course ◽  
Home Technology ◽  
Smart Home Technology

The aim of this paper is to describe the new concept of a Master level university course for computer science students to address the issues of IoT and Smart Home Security. This concept is well suited for professional training for interested customers and allows the creation of practical exercises. The modular structure of the course contains lectures and exercises on the following topics: 1. Introduction - IoT and Smart Home Technology and Impact 2. Homematic Technology and Smart Home Applications 3. Loxone Technology and Smart Home Applications 4. Raspberry Pi and Smart Home Applications 5. Security of IoT and Smart Home Systems and contains laboratory exercises of diverse complexities.

An Adaptive Binarization Method for Cost-efficient Document Image System in Wavelet Domain

2020 ◽  
Vol 64 (3) ◽  
pp. 30401-1-30401-14 ◽  
Author(s):  
Chih-Hsien Hsia ◽  
Ting-Yu Lin ◽  
Jen-Shiun Chiang
Keyword(s):  
Wavelet Transform ◽  
Discrete Wavelet Transform ◽  
Document Image ◽  
Background Information ◽  
Raspberry Pi ◽  
Discrete Wavelet ◽  
Image System ◽  
Low Frequencies ◽  
Cost Efficient ◽  
Binarization Method

Abstract In recent years, the preservation of handwritten historical documents and scripts archived by digitized images has been gradually emphasized. However, the selection of different thicknesses of the paper for printing or writing is likely to make the content of the back page seep into the front page. In order to solve this, a cost-efficient document image system is proposed. In this system, the authors use Adaptive Directional Lifting-Based Discrete Wavelet Transform to transform image data from spatial domain to frequency domain and perform on high and low frequencies, respectively. For low frequencies, the authors use local threshold to remove most background information. For high frequencies, they use modified Least Mean Square training algorithm to produce a unique weighted mask and perform convolution on original frequency, respectively. Afterward, Inverse Adaptive Directional Lifting-Based Discrete Wavelet Transform is performed to reconstruct the four subband images to a resulting image with original size. Finally, a global binarization method, Otsu’s method, is applied to transform a gray scale image to a binary image as the output result. The results show that the difference in operation time of this work between a personal computer (PC) and Raspberry Pi is little. Therefore, the proposed cost-efficient document image system which performed on Raspberry Pi embedded platform has the same performance and obtains the same results as those performed on a PC.

A driver drowsiness and distraction warning system based on raspberry Pi 3 Kit

2019 ◽  
Vol 70 (3) ◽  
pp. 184-192
Author(s):  
Toan Dao Thanh ◽  
Vo Thien Linh
Keyword(s):  
Processing System ◽  
Warning System ◽  
Raspberry Pi ◽  
Data Set ◽  
Lower Lip ◽  
Driver Drowsiness ◽  
Image Sensing ◽  
The Face ◽  
The Common ◽  
University Laboratory

In this article, a system to detect driver drowsiness and distraction based on image sensing technique is created. With a camera used to observe the face of driver, the image processing system embedded in the Raspberry Pi 3 Kit will generate a warning sound when the driver shows drowsiness based on the eye-closed state or a yawn. To detect the closed eye state, we use the ratio of the distance between the eyelids and the ratio of the distance between the upper lip and the lower lip when yawning. A trained data set to extract 68 facial features and “frontal face detectors” in Dlib are utilized to determine the eyes and mouth positions needed to carry out identification. Experimental data from the tests of the system on Vietnamese volunteers in our University laboratory show that the system can detect at realtime the common driver states of “Normal”, “Close eyes”, “Yawn” or “Distraction”

Smart and Interactive Home Using Raspberry Pi

2018 ◽  
Vol 6 (3) ◽  
pp. 241-245
Author(s):  
V. Mehta ◽  
◽  
B. Walia ◽  
V. Rathod ◽  
M. Kothari ◽  
...  
Keyword(s):  
Raspberry Pi

Age and Gender Detection System using Raspberry Pi

2019 ◽  
Vol 7 (6) ◽  
pp. 14-18
Author(s):  
Sumangala Biradar ◽  
Beena Torgal ◽  
Namrata Hosamani ◽  
Renuka Bidarakundi ◽  
Shruti Mudhol
Keyword(s):  
Detection System ◽  
Raspberry Pi ◽  
Age And Gender ◽  
And Gender ◽  
Gender Detection
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