Integrated Systems : Embedded, Signal Processing, and Communication.

Format:

Book

Author/Creator:

Gudipalli, Abhishek.

Language:

English

Subjects (All):

Embedded computer systems.

Physical Description:

1 online resource (612 pages)

Edition:

1st ed.

Place of Publication:

Newark : John Wiley & Sons, Incorporated, 2026.

Summary:

Future-proof your technical expertise with this essential book, offering a comprehensive guide to the latest innovations, trends, and solutions at the critical intersection of embedded systems, signal processing, and communication systems.Embedded systems play a pivotal role in our modern lives.

Contents:

Cover

Series Page

Title Page

Copyright Page

Contents

Preface

Chapter 1 Integration of Industrial Robots to Enhance Warehouse Efficiency in an Industry 4.0 Environment Using Digital Twin Technology

Abbreviations

1.1 Introduction

1.2 Industry Internet of Things and Robot Applications in Warehouse

1.3 Programming Using CODESYS V3.5 SP19

1.4 Creation of Warehouse in Factory IO

1.5 Sequential Function Chart Programming Using CODESYS V3.5

1.6 Conclusions

Bibliography

Chapter 2 QR Code-Enabled Anytime Pill Dispenser

2.1 Introduction

2.2 Literature Review

2.3 Methodology

2.3.1 Hardware Requirements

2.3.2 Workflow

2.4 Results and Discussions

2.4.1 System Initialization

2.4.2 QR Code Scanning

2.5 Conclusion

References

Chapter 3 Analysis on Insulation Properties of Carbon Quantum Dots-SiO2 Oil Fillers in Mineral Oil

3.1 Introduction

3.2 Experimental Arrangement and Preparation Method

3.2.1 Preparation of Nanofluid

3.2.2 AC Breakdown Voltage Test

3.2.3 Tan Delta and Volume Resistivity Test

3.3 Results and Discussion

3.4 Conclusion

Chapter 4 Comparative Analysis of Partial Discharge Characteristics in Different Electrode Configurations of Biodegradable Nanofluid

4.1 Introduction

4.2 Sample and Procedure for Test

4.2.1 Mixture of Test Solution and Nanofluids

4.2.2 Test Arrangements and Procedures

4.3 Test Results and Analysis

4.3.1 Partial Discharge Magnitude and Its Inception

4.4 Conclusion

Chapter 5 Cost-Effective Real-Time Facial Recognition and Database Integration Using Firebase

5.1 Introduction

5.2 Literature Review

5.2.1 Overview of Facial Recognition Techniques

5.2.2 Existing Systems and Technologies

5.2.3 Applications of Facial Recognition in Various Fields.

5.2.3.1 Education Attendance Monitoring

5.2.3.2 Exam Proctoring

5.2.3.3 Financial Services and Banking Secure Transactions

5.2.3.4 Fraud Prevention

5.2.3.5 Healthcare Patient Identification

5.2.3.6 Emotion Detection

5.2.3.7 Safety and Monitoring

5.2.3.8 Access Control

5.2.3.9 Border Control

5.3 Methodology

5.4 Implementation

5.4.1 Real-Time Facial Recognition System

5.4.2 Face Encoding Generation Script

5.4.3 Database Initialization Script

5.5 Conclusion

Chapter 6 Remote Light Monitoring for Energy Efficiency

6.1 Introduction

6.2 Methodology

6.3 Design Approach

6.4 Results

6.4.1 Cost Analysis

6.5 Conclusion

Chapter 7 Buffer for Critical Path VLSI Circuits

7.1 Introduction

7.2 Conventional Buffer

7.3 Schematic Design of the Proposed Buffer

7.4 Results and Discussions

7.4.1 Scaling of Voltage and Load

7.4.1.1 Delay Due to Scaling of Voltage and Load

7.4.1.2 Power Dissipation for Scaling of Voltage and Load

7.4.2 Scaling the Technology Node

7.5 Conclusion

Chapter 8 Fuzzy Logic-Based Navigation Control for Khepera Robot

8.1 Introduction

8.1.1 Scope and Limitations

8.2 Research Methodology

8.2.1 Environment Modeling

8.2.2 Robot Modeling

8.2.3 Fuzzy Logic Controller Design

8.2.4 Simulation-Based

8.3 Results and Discussions

8.3.1 Fuzzy System Inputs and Outputs

8.3.2 Khepera's Trajectory

8.3.3 Khepera's Performances with Fuzzy and without Fuzzy Controller

8.4 Conclusions

Chapter 9 Detection and Recurrence of Breast Cancer Through Image Processing and Attention Awareness: A Comparative Analysis of Algorithms

9.1 Introduction

9.2 Literature Review

9.3 System Implementation

9.4 Results and Discussion

9.5 Conclusion

References.

Chapter 10 Transformative Innovations in Tomato Plant Disease Detection: A Comprehensive Examination of Advanced Sensing Technologies and Algorithmic Precision

10.1 Introduction

10.2 Problem Statement

10.3 Related Works

10.4 Materials and Methods

10.4.1 Architecture

10.4.2 Algorithm

10.4.3 Mathematics

10.4.3.1 Intersection Over Union

10.4.3.2 Average Precision

10.4.4 Implementation

10.4.5 Dataset

10.5 Experiments and Results

10.5.1 Test Bench

10.5.2 Test Case

10.5.3 Benchmarking

10.5.4 Results

10.6 Conclusion

Chapter 11 Triples, Helmet, Number Plate Design On Real-Time Information System

Introduction

Proposed System

Models Implemented

Advanced Picture Handling Includes a Few Major Advances

Picture Compression

Image Compression Types

Compression Ratio

Image Lossy Compression

Lossless Image Input

Experimental Results

Limitations

Future Works

Conclusion

Chapter 12 Brain Tumor Segmentation Using U-Net, U-Net with Attention, and ResNeXt50

12.1 Introduction

12.2 Dataset Description

12.2.1 MRI Images

12.2.2 Manual FLAIR Abnormality Segmentation Masks

12.2.3 Patient Information

12.2.4 Purpose

12.2.5 Availability

12.3 Methodology

12.3.1 Data Preprocessing

12.3.2 Data Augmentation and Transformations

12.3.3 Algorithm Selection

12.4 Segmentation Quality Metrics and Loss Functions

12.4.1 Segmentation Quality Metric

12.4.2 Segmentation Loss Function

12.5 Training Procedure

12.5.1 Model Training and Optimization

12.5.2 Test Performance Evaluation

12.6 Test Results and Visualization

12.7 Performance Evaluation of Segmentation Models

12.8 Discussion

12.8.1 Model Performance Comparison

12.8.2 Architectural Advantages.

12.8.3 Training Strategy and Data Augmentation

12.9 Future Scope

12.10 Conclusion

Acknowledgment

Chapter 13 Skin Disease Classification for Healthcare Using a Federated Learning-Based Ensemble Learning

13.1 Introduction

13.2 Literature Review

13.3 Dataset and Methodology

13.4 Results and Discussion

13.5 Conclusion

Chapter 14 Fingerprint Recognition Using Image Processing and Neural Networks

14.1 Introduction

14.2 Related Works

14.3 Proposed Methodology

14.4 Results and Discussion

14.5 Methodology Comparison

14.6 Conclusion and Future Work

Chapter 15 Machine Learning Algorithms to Predict and Detect Malicious Network Traffic and Cyberattacks

Literature Review

Proposed Methodologies

Algorithms Used

Decision Tree Algorithm

XGBoost Algorithm

Performance Metrics

Confusion Matrix

Results and Output

Chapter 16 Machine Learning-Based Term Retrieval Method for Text Extraction from Emojipedia

16.1 Introduction

16.2 Related Works

16.3 Proposed Methodology

16.3.1 Preprocessing

16.3.2 Feature Extraction

16.3.3 Automated Term-Based Retrieval Method

16.3.4 Stemming

16.3.5 Stop Words

16.3.6 Feature Extraction-Term Frequency-IDF

16.4 Result and Discussion

16.5 Conclusion

Chapter 17 Experimentations on Eulerian Video Magnification

17.1 Introduction

17.2 Related Works

17.3 Methodology

17.3.1 Video Acquisition

17.3.2 Spatial Decomposition

17.3.3 Time Domain Filtering

17.3.4 Amplification Filtering

17.3.5 Synthesized Images

17.4 Experiments

17.4.1 Video Acquisition

17.4.1.1 Methods

17.5 Results

17.5.1 Horizontal Vibration Video

17.5.2 Vertical Vibration Video

17.6 Discussion

17.6.1 Significance of Findings.

17.6.2 Challenges Encountered

17.6.3 Noise Amplification

17.6.4 Artifact Introduction

17.6.5 Computational Efficiency

17.6.6 Potential Applications

17.6.6.1 Medical Diagnostics

17.6.6.2 Structural Health Monitoring

17.6.6.3 Video Forensics

17.6.6.4 Materials Science

17.6.7 Future Research Directions

17.6.7.1 Advanced Noise Reduction Techniques

17.6.7.2 Artifact Minimization

17.6.7.3 Real-Time Processing

17.6.7.4 Application-Specific Customization

17.6.7.5 Extended Validation

17.7 Conclusion

Data Availability

Chapter 18 Predictive Modeling for Early Detection of Mental Health Crisis Among Employees

18.1 Introduction

18.2 Related Works

18.3 Methodology and Model Development

18.3.1 Mental Health Prediction Models

18.3.2 Logistic Regression

18.3.3 K-Nearest Neighbors

18.3.4 Decision Tree Classifier

18.3.5 Random Forest

18.3.6 Bagging (Bootstrap Aggregating)

18.3.7 Boosting

18.3.8 Stacking

18.3.9 Data Collection and Preprocessing Methods

18.4 Evaluation Methodologies

18.4.1 Comparison with Baseline Methods

18.4.2 Model Performance

18.4.3 Challenges and Solutions

18.4.4 Limited Access to Large and High-Quality Datasets

18.4.5 Feature Selection

18.4.6 Class Imbalance

18.4.7 Model Overfitting

18.5 Conclusion

Chapter 19 Enhancement of Spatial Resolution with Deep CNN-Based Fusion of Panchromatic-Multispectral Images

19.1 Introduction

19.2 Literature Survey

19.3 Methodology

19.3.1 Input Layers

19.3.2 Multi-Filter Layer (Edge Filters)

19.3.3 Upsampling and Concatenation (C)

19.3.4 Convolutional Layers

19.3.5 Residual Skip Connection

19.3.6 Output Layer

19.4 Experimental Results and Analysis

19.4.1 Datasets

19.4.2 Quantitative Metrics

19.4.3 Metrics and Graphs

19.5 Conclusion.

References.

Notes:

Description based on publisher supplied metadata and other sources.

ISBN:

1-394-31176-1

1-394-31175-3

9781394311750

OCLC:

1551365266