Smart Embedded Systems and Applications

✍ Scribed by Saad Motahhir (editor)

• Publisher: River Publishers
• Year: 2023
• Tongue: English
• Leaves: 346
• Edition: 1
• Category: Library

✦ Synopsis

This book covers a wide range of challenges, technologies and state-of-the-art for the design, development and realization of smart and complex embedded systems and their applications; i.e., software and hardware development, with the use of digital technologies, and quality assurance for critical applications.

This book starts with automotive safety systems which is one of the major functional domains. It discusses the importance of software in automotive systems followed by an insight into Automotive Software Standards, ISO26262, and Autosar. The book further discusses the use of Processor in the loop test for an adaptive trajectory tracking control for quadrotor UAVs. It also illustrates the role of embedded systems in medical engineering. Various innovative applications involving the concept of image processing and Internet of Things are also presented in this book. The SoC Power Estimation is also investigated. Finally, a Review of the Hardware/Software Partitioning Algorithms with some future works have been presented. this book is intended for academicians, researchers, and industrialists.

✦ Table of Contents

Cover
Half-Title
Smart Embedded Systems andApplications
RIVER PUBLISHERS SERIES IN ELECTRONIC MATERIALS, CIRCUITS AND DEVICES
Title
Copyrights
Dedicate
Contents
Preface
Acknowledgments
List of Reviewers
List of Figures
List of Tables
List of Notations and Abbreviations
SECTION 1 Smart Embedded Systems for the Automotive Industry
1Functional Safety Audit/Assessment for Automotive Engineering
Abstract
1.1 Introduction and Objectives
1.2 ISO 26262 and ASIL Overview
1.3 Functional Safety Audit/Assessment Program
1.3.1 Internal functional safety audit procedure
1.3.1.1 Definition and safety compliance procedures phases
1.3.1.2 Objective and scope of internal FS audit
1.3.1.3 Internal functional safety audit procedure:
1.3.1.4 Non-Conformance
1.3.2 Internal functional safety assessment procedure
1.3.2.1 Objective and scope of internal FS assessment
1.3.2.2 Project FSA procedure:
1.3.3 External or supplier functional safety audit and functional safety assessment
1.4 Functional Safety Audit / Assessment Planning
1.5 Functional Safety Audit / Assessment Preparation
1.6 Functional Safety Audit / Assessment Performance
1.7 Functional Safety Audit / Assessment Report and Follow-up
1.8 Conclusion
References
2Comparison between AUTOSAR Platforms with Functional Safety for Automotive Software Architectures
Abstract
2.1 Introduction
2.2 Overview of the Future E/E Architectures
2.2.1 Combination of different software platforms
2.2.2 Service oriented communication
2.3 The AUTOSAR Adaptive Platform
2.4 AUTOSAR Foundation
2.5 Classic AUTOSAR Vs Adaptive AUTOSAR
2.6 Communication Between AUTOSAR Platforms
2.7 Safety Preliminaries for E/E Architectures
2.7.1 Functional safety overview
2.7.2 ASIL determination
2.8 Conclusion
References
3Hardware-in-the-Loop System for Electronic Control Unit Software and Calibration Development
Abstract
3.1 Introduction
3.2 Automotive Embedded Systems Overview
3.2.1 Automotive systems
3.2.2 Electronic control units
3.2.3 Hardware-in-the-loop systems
3.3 HIL for Engine Calibration: A Case Study
3.3.1 System setup
3.3.2 Signal manipulation
3.3.3 Engine model
3.3.4 Overall system
3.4 Experimental Evaluation and Measurements
3.4.1 Experimental setup
3.4.2 Experiment measurements
3.4.3 Engine model accuracy results
3.4.4 Cam-Crank signal generator results
3.4.5 Open-loop performance
3.4.6 Closed-loop performance
3.5 Conclusion
3.6 Acknowledgements
References
SECTION 2 Utilizing Embedded Systems for UAVs
4 Processor in the Loop Experiments of an Adaptive Trajectory Tracking Control for Quadrotor UAVs
Abstract
4.1 Introduction
4.2 Quadrotor Modeling
4.3 Controller Design
4.4 Processor-in-the-Loop Experiments
4.5 Conclusion
References
SECTION 3 Smart Embedded Systems in Biomedicine
5A Detailed Review on Embedded Based Heartbeat Monitoring Systems
Abstract
5.1 Introduction
5.2 Measuring Methods
5.3 Categorisation of Algorithms for Heartbeat Detection
5.3.1 Categorisation of heartbeat displacement models
5.3.2 Demodulation techniques
5.4 Various Embedded Applications in the Medical Field
5.4.1 Software related to embedded systems
5.5 Embedded System Hardware for Heartbeat Monitoring
5.6 Conclusion
References
6Embedded Systems in Biomedical Engineering: Case of ECG Signal Processing Using Multicores CPU and FPGA Architectures
Abstract
6.1 Introduction
6.2 Embedded System Architectures
6.2.1 Embedded systems overview
6.2.2 Embedded systems architectures
6.2.2.1 Standalone architectures
6.2.2.2 Heterogeneous architectures
6.3 Embedded Systems Applications in Biomedical Engineering: Case of the Pre-treatment of ECG Signal
6.3.1 The proposed techniques for embedded systems implementations
6.3.1.1 ADTF technique
6.3.1.2 DWT Technique
6.3.1.3 Hybrid DWT-ADTF technique
6.3.2 Implementation of the ADTF technique usingmulti-CPU architectures
6.3.3 HLS implementation of ADTF techniqueusing FPGA architecture
6.3.4 VHDL implementation of ADTF techniqueusing FPGA architecture
6.3.5 VHDL implementation of hybrid DWT-ADTF technique using FPGA architecture
6.4 Conclusions
References
7Acquisition and Processing of SurfaceEMG Signal with an Embedded Compact RIO-based System
Abstract
7.1 Introduction
7.2 EMG Signal Conditioning Circuit
7.2.1 Instrumentation amplifier
7.2.2 Band pass filter
7.2.3 Analog-to-digital converter
7.3 EMG Signal Processing
7.3.1 Flowchart description
7.4 Implementation Results
7.4.1 Implementation on compact RIO-9035 controller
7.4.2 EMG instrumentation based on NI-ELVIS II+
7.4.3 Real-time evaluation
7.5 Conclusion
7.6 Funding
7.7 ORCID ID
References
SECTION 4 The Application of Embedded System in Image Processing
8Quick and Efficient Hardware-Software Design Space Exploration UsingVivado-HLS: A Case Study of Adaptive Algorithm for Image Denoising
Abstract
8.1 Introduction
8.2 High-level Synthesis
8.3 Adaptive Algorithm
8.3.1 LMS algorithm
8.3.2 NLMS algorithm
8.4 Implementation and Results
8.4.1 Phase I
8.4.2 Phase II
8.4.3 Phase III
8.5 Conclusion and Future Scope
References
9Fast FPGA Implementation of A Moving Object Detection System
Abstract
9.1 Introduction
9.2 Detect Moving Objects Algorithm
9.3 Implementation and Experiment Results
9.3.1 Software simulation and evaluation
9.3.2 Embedded objects detection system
9.4 Conclusion
References
10Face Recognition based on CNN, Hog and Haar Cascade Methods using RaspberryPi v4 Model B
Abstract
10.1 Introduction
10.2 Implementation Methods
10.2.1 Method 1. Haar cascade
10.2.2 Method 2. Histogram of Oriented Gradients (HOG)
10.2.3 Method 3. Convolutional Neural Networks (CNN)
10.2.3.1 Convolution layer
10.2.3.2 Pooling layer
10.2.3.3 Fully connected layer
10.3 Deployment Environments and Results
10.3.1 Hardware environment
10.3.1.1 Raspberry Pi4
10.3.1.2 Camera Pi V2
10.3.2 Software environment
10.3.2.1 Python
10.3.3 Application process/steps
10.3.3.1 Dataset creation
10.3.3.2 Training part
10.3.3.3 Recognition part
10.3.4 Implementation results and comparison
10.4 Conclusion
References
SECTION 5 Internet of Things BasedEmbedded System
11Survey Review on Artificial Intelligence and Embedded Systems for Agriculture Safety: A proposed IoT Agro-meteorology System for Local Farmers in Morocco
Abstract
11.1 Introduction
11.2 AI-enabled Embedded Systems for Agriculture
11.2.1 Precision in water management
11.2.2 Integrated food safety
11.2.3 Crop productivity and fertility
11.2.4 Automation: Unmanned aerial vehicles (UAVs) and robots
11.2.5 Weather predictive analysis
11.3 Proposed Solution for Familial Agriculture andSmall Farmers
11.3.1 Description of the study area
11.3.2 Model architecture
11.3.3 Wireless sensors networks for agricultural Forecasting
11.3.4 Communication modules
11.4 Discussions: Questions and Challenges Raised by the use of AI and IoT in Agriculture
11.4.1 The question of trust
11.4.2 The question of applying AI stochastic algorithms
11.4.3 The question of data
11.4.4 The question of interpretability
11.5 Conclusion and Future Works
Appendix A
Appendix B
Appendix C
Appendix D
References
12IoT-Based Intelligent Handicraft System Using NFC Technology
Abstract
12.1 Introduction
12.2 Preliminary and Related Work
12.3 System Design
12.3.1 Data acquisition
12.3.2 Data analysis
12.4 System Implementation
12.4.1 System workflow
12.4.2 Database design
12.4.3 Mobile application prototype
12.5 Conclusion
12.6 Acknowledgments
References
SECTION 6 System on Chip and Co-design
13SoC Power Estimation: A Short Review
Abstract
13.1 Introduction
13.2 Background
13.2.1 Levels of parallelism
13.2.2 Advances in processor microarchitecture
13.2.2.1 Single cycle processor
13.2.2.2 Multi cycle processor
13.2.2.3 Pipelining
13.2.2.4 Superscalar processor
13.2.2.5 Vector processor
13.2.2.6 Multicore processors
13.2.3 Abstraction levels classification
13.2.3.1 Layout
13.2.3.2 Gate level
13.2.3.3 Register transfer level
13.2.3.4 Cycle accurate level
13.2.3.5 Transactional level modeling
13.2.3.6 Algorithmic level
13.3 Physical Power Models
13.3.1 Leakage power
13.3.2 Dynamic power
13.3.3 Short-circuit power
13.4 Power Estimation Techniques
13.4.1 WATTCH
13.4.2 AVALACHE
13.4.3 PowerVIP
13.4.4 Hybrid System Level power consumptionestimation (HSL)
13.4.5 Early Design Power Estimation (EDPE)
13.4.6 Recent power and temperature modelling method
13.5 Discussion
13.6 Proposed Technique
13.7 Conclusion
References
14Hardware/Software Partitioning Algorithms: A Literature Review and New Perspectives
Abstract
14.1 Introduction
14.2 Overview of Partitioning Problem
14.3 Exact Algorithms
14.3.1 Integer linear programming
14.3.2 Dynamic programming
14.3.3 Branch and bound
14.4 Classical Heuristic Approaches
14.4.1 Genetic Algorithm
14.4.2 Simulated annealing algorithm
14.4.3 Tabu search algorithm
14.4.4 Greedy algorithm
14.4.5 Hill climbing algorithm
14.4.6 Kernighan-Lin algorithm
14.5 Modern Heuristic Approaches
14.5.1 Particle swarm optimization
14.5.2 Ant colony optimization
14.5.3 Artificial immune systems
14.5.4 Pareto optimal
4.5.5 Path-based algorithms
4.5.6 Fuzzy logic
14.5.7 Other heuristic algorithms
14.6 New Perspectives
14.6.1 First category algorithms
14.6.2 Second category algorithms
14.6.3 Third category algorithms
14.7 Conclusion
References
Index
About the Editor
BackCover