scholarly journals Low-Cost Fault Tolerant Methodology for Real Time MPSoC Based Embedded System

2014 ◽  
Vol 2014 ◽  
pp. 1-8 ◽  
Author(s):  
Mohsin Amin ◽  
Muhammad Shakir ◽  
Aqib Javed ◽  
Muhammad Hassan ◽  
Syed Ali Raza
Keyword(s):  
Embedded System ◽  
Real Time ◽  
Design Methodology ◽  
Fault Tolerant ◽  
Low Cost ◽  
Design Constraints ◽  
Hardware Overhead ◽  
And Performance ◽  
The Given

We are proposing a design methodology for a fault tolerant homogeneous MPSoC having additional design objectives that include low hardware overhead and performance. We have implemented three different FT methodologies on MPSoCs and compared them against the defined constraints. The comparison of these FT methodologies is carried out by modelling their architectures in VHDL-RTL, on Spartan 3 FPGA. The results obtained through simulations helped us to identify the most relevant scheme in terms of the given design constraints.

scholarly journals Low-Cost Embedded System Using Convolutional Neural Networks-Based Spatiotemporal Feature Map for Real-Time Human Action Recognition

2021 ◽  
Vol 11 (11) ◽  
pp. 4940
Author(s):  
Jinsoo Kim ◽  
Jeongho Cho
Keyword(s):  
Embedded System ◽  
Real Time ◽  
Action Recognition ◽  
Processing Speed ◽  
Recognition Accuracy ◽  
Low Cost ◽  
Human Action Recognition ◽  
Human Action ◽  
Video Data ◽  
Feature Maps

The field of research related to video data has difficulty in extracting not only spatial but also temporal features and human action recognition (HAR) is a representative field of research that applies convolutional neural network (CNN) to video data. The performance for action recognition has improved, but owing to the complexity of the model, some still limitations to operation in real-time persist. Therefore, a lightweight CNN-based single-stream HAR model that can operate in real-time is proposed. The proposed model extracts spatial feature maps by applying CNN to the images that develop the video and uses the frame change rate of sequential images as time information. Spatial feature maps are weighted-averaged by frame change, transformed into spatiotemporal features, and input into multilayer perceptrons, which have a relatively lower complexity than other HAR models; thus, our method has high utility in a single embedded system connected to CCTV. The results of evaluating action recognition accuracy and data processing speed through challenging action recognition benchmark UCF-101 showed higher action recognition accuracy than the HAR model using long short-term memory with a small amount of video frames and confirmed the real-time operational possibility through fast data processing speed. In addition, the performance of the proposed weighted mean-based HAR model was verified by testing it in Jetson NANO to confirm the possibility of using it in low-cost GPU-based embedded systems.

A Low Cost Fault-Tolerant Multiprocessor System for Real-Time Control

1986 ◽  
Vol 19 (13) ◽  
pp. 113-117
Author(s):  
J.J. Serrano ◽  
C. Cebrián ◽  
J. Vila ◽  
R. Ors
Keyword(s):  
Real Time ◽  
Fault Tolerant ◽  
Low Cost ◽  
Multiprocessor System ◽  
Real Time Control ◽  
Time Control

scholarly journals Visual Attitude Estimation for Low-Cost Personal Remote Sensing Systems

2011 ◽  
Author(s):  
Tobias Fromm ◽  
Long Di ◽  
YangQuan Chen ◽  
Holger Voos
Keyword(s):  
Remote Sensing ◽  
Unmanned Aerial Vehicles ◽  
Fault Tolerant ◽  
Low Cost ◽  
Sufficient Accuracy ◽  
Sensing Systems ◽  
Personal Remote Sensing ◽  
Remote Sensing Systems ◽  
And Performance ◽  
The Moment

Remote Sensing using unmanned aerial vehicles (UAV) is gathering a lot of attention at the moment by researchers and developers, especially in terms of low-cost aircrafts which still maintain sufficient accuracy and performance. This paper introduces a low-cost approach to increase airworthiness by using a forward-looking camera to estimate the attitude of a UAV. It not only focuses on using machine learning to classify ground and sky, but also uses image processing and software engineering methods to make it fault-tolerant and really applicable on a miniature UAV. Additionally, it is able to interface with an autopilot framework to being used productively on flight missions.

OBD-II and raspberry Pi technology to diagnose car’s machine current condition: study literature

2017 ◽  
Vol 34 (10) ◽  
pp. 15-21 ◽  
Author(s):  
Sonya Rapinta Manalu ◽  
Jurike Moniaga ◽  
Dionisius Andrian Hadipurnawan ◽  
Firda Sahidi
Keyword(s):  
Real Time ◽  
Mobile Technology ◽  
Design Methodology ◽  
Low Cost ◽  
Raspberry Pi ◽  
Data Link ◽  
Content Type ◽  
History Of ◽  
To Receive ◽  
Technology Comparison

Purpose Low-cost microcomputers such as the Raspberry Pi are common in library makerspaces. This paper aims to create an OBD-II technology to diagnose a vehicle’s condition. Design/methodology/approach An OBD-II scanner plugged into the OBD-II port or usually called the data link connector (DLC), sends diagnostics to the Raspberry Pi. Findings Compared with other microcontrollers such as Arduino, the Raspberry Pi was chosen because it sustains the application to receive real-time diagnostics, process the diagnostics and send commands to automobiles at the same time, rather than Arduino that must wait for another process finished to run another process. Originality/value This paper also represents the history of mobile technology and OBD-II technology, comparison between Arduino and Raspberry Pi and Node.

scholarly journals Artificial vision system for object classification in real time using Raspberry Pi and a Web camera

2021 ◽  
pp. 20-25
Author(s):  
Tomás Serrano-Ramírez ◽  
Ninfa del Carmen Lozano-Rincón ◽  
Arturo Mandujano-Nava ◽  
Yosafat Jetsemaní Sámano-Flores
Keyword(s):  
Embedded System ◽  
Real Time ◽  
Vision System ◽  
Low Cost ◽  
Artificial Vision ◽  
Maintenance Cost ◽  
Raspberry Pi ◽  
Smart Cameras ◽  
Suggested Technique ◽  
Web Camera

Computer vision systems are an essential part in industrial automation tasks such as: identification, selection, measurement, defect detection and quality control in parts and components. There are smart cameras used to perform tasks, however, their high acquisition and maintenance cost is restrictive. In this work, a novel low-cost artificial vision system is proposed for classifying objects in real time, using the Raspberry Pi 3B + embedded system, a Web camera and the Open CV artificial vision library. The suggested technique comprises the training of a supervised classification system of the Haar Cascade type, with image banks of the object to be recognized, subsequently generating a predictive model which is put to the test with real-time detection, as well as the calculation for the prediction error. This seeks to build a powerful vision system, affordable and also developed using free software.

scholarly journals LOW COST EMBEDDED STEREO SYSTEM FOR UNDERWATER SURVEYS

2017 ◽  
Vol XLII-2/W8 ◽  
pp. 179-186
Author(s):  
M. M. Nawaf ◽  
J.-M. Boï ◽  
D. Merad ◽  
J.-P. Royer ◽  
P. Drap
Keyword(s):  
Embedded System ◽  
Real Time ◽  
Low Cost ◽  
Visual Odometry ◽  
Movement Speed ◽  
Underwater Imaging ◽  
Lighting Conditions ◽  
Computational Resources ◽  
Processing Techniques

This paper provides details of both hardware and software conception and realization of a hand-held stereo embedded system for underwater imaging. The designed system can run most image processing techniques smoothly in real-time. The developed functions provide direct visual feedback on the quality of the taken images which helps taking appropriate actions accordingly in terms of movement speed and lighting conditions. The proposed functionalities can be easily customized or upgraded whereas new functions can be easily added thanks to the available supported libraries. Furthermore, by connecting the designed system to a more powerful computer, a real-time visual odometry can run on the captured images to have live navigation and site coverage map. We use a visual odometry method adapted to low computational resources systems and long autonomy. The system is tested in a real context and showed its robustness and promising further perspectives.

scholarly journals Monitoring and controlling the speed and direction of a DC motor through FPGA and comparison of FPGA for speed and performance optimization

2021 ◽  
Vol 11 (5) ◽  
pp. 3903
Author(s):  
Huda M. Abdul Abbas ◽  
Raad Farhood Chisab ◽  
Mohannad Jabbar Mnati
Keyword(s):  
Real Time ◽  
Performance Optimization ◽  
Pulse Width Modulation ◽  
Electronic Device ◽  
Low Cost ◽  
Dc Motor ◽  
Know How ◽  
Field Programmable ◽  
Programmable Gate Arrays ◽  
And Performance

<span lang="EN-US">We are living in the 21<sup>st</sup> century, an era of acquiring necessity in one click. As we, all know that technology is continuously reviving to stay ahead of advancements taking place in this world of making things easier for mankind. Technology has been putting his part in introducing different projects as we have used the field programmable gate arrays (FPGAs) development board of low cost and programmable logic done by the new evolvable cyclone software is optimized for specific energy based on Altera Cyclone II (EP2C5T144) through which we can control the speed of any electronic device or any Motor Control IP product targeted for the fan and pump. Altera Cyclone FPGAs’ is a board through which we can monitor the speed and direction of the DC motor. As we know how to make understand, dynamic analog input using an A-to-D convertor and we know how to create pulse width modulation (PWM) output with FPGA. Therefore, by combining these two functions we can create an FPGA DC motor controller. Our paper is divided into three parts: First, all of us will attempt to imitate the issue and can try to look for its answer. Secondly, we will try to verify the solution for real-time. In addition, in the last step, we will verify the solution on the real-time measurements.</span>

scholarly journals Network-Oriented Real-Time Embedded System Considering Synchronous Joint Space Motion for an Omnidirectional Mobile Robot

Electronics ◽  
2019 ◽  
Vol 8 (3) ◽  
pp. 317 ◽  
Author(s):  
Raimarius Delgado ◽  
Byoung Choi
Keyword(s):  
Mobile Robot ◽  
Embedded System ◽  
Real Time ◽  
Low Cost ◽  
Joint Space ◽  
Geometric Constraints ◽  
Real Time Control ◽  
Synchronization Mechanism ◽  
Omnidirectional Mobile Robot ◽  
Time Control

This paper proposes a real-time embedded system for joint space control of omnidirectional mobile robots. Actuators driving an omnidirectional mobile robot are connected in a line topology which requires synchronization to move simultaneously in translation and rotation. We employ EtherCAT, a real-time Ethernet network, to control servo controllers for the mobile robot. The first part of this study focuses on the design of a low-cost embedded system utilizing an open-source EtherCAT master. Although satisfying real-time constraints is critical, a desired trajectory on the center of the mobile robot should be decomposed into the joint space to drive the servo controllers. For the center of the robot, a convolution-based path planner and a corresponding joint space control algorithm are presented considering its physical limits. To avoid obstacles that introduce geometric constraints on the curved path, a trajectory generation algorithm considering high curvature turning points is adapted for an omnidirectional mobile robot. Tracking a high curvature path increases mathematical complexity, which requires precise synchronization between the actuators of the mobile robot. An improvement of the distributed clock—the synchronization mechanism of EtherCAT for slaves—is presented and applied to the joint controllers of the mobile robot. The local time of the EtherCAT master is dynamically adjusted according to the drift of the reference slave, which minimizes the synchronization error between each joint. Experiments are conducted on our own developed four-wheeled omnidirectional mobile robot. The experiment results confirm that the proposed system is very effective in real-time control applications for precise motion control of the robot even for tracking high curvature paths.

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