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Submit a ProposalIntegrated Systems
One Line Description
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.
Audience
Engineers, developers, academics, and researchers seeking a comprehensive understanding of integrated systems.
Engineers, developers, academics, and researchers seeking a comprehensive understanding of integrated systems.
Description
Embedded systems play a pivotal role in our modern lives. These specialized devices are discreetly embedded within larger systems, performing specific tasks autonomously. From smartphones and wearables to industrial machinery and automotive control units, embedded systems are ubiquitous. Signal processing enables the extraction of meaningful information from raw data, making it essential for applications such as image and speech recognition, medical diagnostics, and wireless communication. This book focuses on the latest innovations, trends, and challenges encountered in the areas of embedded systems, signal processing, and communication systems. It highlights potential solutions and provides insights into emerging areas, such as signal processing algorithms and communication protocols, making it an invaluable resource for anyone working with integrated systems.
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Embedded systems play a pivotal role in our modern lives. These specialized devices are discreetly embedded within larger systems, performing specific tasks autonomously. From smartphones and wearables to industrial machinery and automotive control units, embedded systems are ubiquitous. Signal processing enables the extraction of meaningful information from raw data, making it essential for applications such as image and speech recognition, medical diagnostics, and wireless communication. This book focuses on the latest innovations, trends, and challenges encountered in the areas of embedded systems, signal processing, and communication systems. It highlights potential solutions and provides insights into emerging areas, such as signal processing algorithms and communication protocols, making it an invaluable resource for anyone working with integrated systems.
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Author / Editor Details
Abhishek Gudipalli, PhD is a Professor in the Instrumentation Department in the School of Electrical Engineering at the Vellore Institute of Technology with more than 15 years of experience. He has published more than 40 journal papers and 15 conference papers. His research interests include image processing, machine learning, IoT, and electric vehicles.
Abhishek Gudipalli, PhD is a Professor in the Instrumentation Department in the School of Electrical Engineering at the Vellore Institute of Technology with more than 15 years of experience. He has published more than 40 journal papers and 15 conference papers. His research interests include image processing, machine learning, IoT, and electric vehicles.
B. Jaganatha Pandian, PhD is a Professor and the Head of the Control and Automation Department in the School of Electrical Engineering at the Vellore Institute of Technology with more than 20 years of teaching experience. He has published more than 20 journal papers and 15 conference papers. His research interests include machine learning, process control, and intelligent systems.
N. Amutha Prabha, PhD is a Professor in the School of Electrical Engineering in the Department of Instrumentation at the Vellore Institute of Technology with more than 25 years of experience. She has published more than 50 papers in national and international journals and conferences. Her research includes wireless LAN networks and discrete time linear systems.
V. Indra Gandhi, PhD is an Associate Professor in the School of Electrical Engineering at the Vellore Institute of Technology with more than 12 years of research and teaching experience. She has authored more than 100 research articles in leading peer-reviewed international journals and filed three patents. Her research focuses on power generation, inverters, and photovoltaics.
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Table of Contents
Preface
1. Integration of Industrial Robots to Enhance Warehouse Efficiency in an Industry 4.0 Environment Using Digital Twin Technology
Manikandan Pounraj, James Periyanayagam L., Jennifer Pearline Lobo and Ashwitha P.
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
2. QR Code-Enabled Anytime Pill Dispenser
Tamizharasi A. R. S., Rekha Mahalakshmi N., Nivetha K., Mutyam Gayathri Priya, Ashwini K. and R. Resmi
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
3. Analysis on Insulation Properties of Carbon Quantum Dots–SiO2 Oil Fillers in Mineral Oil
Madhumathi R. M. and Chandrasekar Subramaniam
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
Bibliography
4. Comparative Analysis of Partial Discharge Characteristics in Different Electrode Configurations of Biodegradable Nanofluid
Sangamithirai V. S. and S. Chandrasekar
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
References
5. Cost-Effective Real-Time Facial Recognition and Database Integration Using Firebase
Ragavan K, Kasamsetty Sai Dhanush, Kamisetty Naga Umesh, Perumalla Yuva Sai and Aeeja Haneesha Reddy
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
References
6. Remote Light Monitoring for Energy Efficiency
Gerardine Immaculate Mary, S. Chandramaouli, Anitha Julian and Rohan George Joshua
6.1 Introduction
6.2 Methodology
6.3 Design Approach
6.4 Results
6.4.1 Cost Analysis
6.5 Conclusion
References
7. Buffer for Critical Path VLSI Circuits
Karthikeyan A., Danush Ranganath G.V. and Rajalakshmi S.
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
References
8. Fuzzy Logic-Based Navigation Control for Khepera Robot
Bryan Tan Shun Xing, Nohaidda Sariff , Swee King Phang and B. Jaganatha Pandian
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
References
9. Detection and Recurrence of Breast Cancer Through Image Processing and Attention Awareness: A Comparative Analysis of Algorithms
Rajini G. K., Jasmin Pemeena Priyadarsini, Alan George, Thomas Tom and Arshaque Abdusalam
9.1 Introduction
9.2 Literature Review
9.3 System Implementation
9.4 Results and Discussion
9.5 Conclusion
References
10. Transformative Innovations in Tomato Plant Disease Detection: A Comprehensive Examination of Advanced Sensing Technologies and Algorithmic Precision
Rajesh Kannan Megalingam, Ananya S. Mallia and Sriram Ghali
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
References
11. Triples, Helmet, Number Plate Design On Real-Time Information System
J. Thomas Perera M.E. and R. Hemalatha M.E.
Introduction
Abbreviations
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
References
12. Brain Tumor Segmentation Using U-Net, U-Net with Attention, and ResNeXt50
Preetha R., Jasmine Pemeena Priyadarsini M., Subash Anumula, Sai Sathvik Reddy M., Praneeth Samana, Nisha J. S., A Jabeena, Ernest Bravin Clinton S. and Ganesan Subramanian
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
References
13. Skin Disease Classification for Healthcare Using a Federated Learning Based Ensemble Learning
N. V. Neeraja and J. Kamalakannan
13.1 Introduction
13.2 Literature Review
13.3 Dataset and Methodology
13.4 Results And Discussion
13.5 Conclusion
References
14. Fingerprint Recognition Using Image Processing and Neural Networks
Jasmin Pemeena Priyadarsini M., Addanki Keerthan, Bandi Sree Charan Teja Reddy, Pradeep Kumar Das, S. Sowmiya, A. Jabeena, Rizee P. J., Elavarasi A. and Ganesan Subramanian
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
Bibliography
15. Machine Learning Algorithms to Predict and Detect Malicious Network Traffic and Cyberattacks
M. Rajeshwari, Anbarasa Kumar Anbarasan, P. Ramakrishnan, T. Abirami and Mohammed Bilal K.
Introduction
Literature Review
Proposed Methodologies
Algorithms Used
Decision Tree Algorithm
XGBoost Algorithm
Performance Metrics
Confusion Matrix
Results and Output
Conclusion
References
16. Machine Learning-Based Term Retrieval Method for Text Extraction from Emojipedia
M. Divya and S. Sukumaran
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
Bibliography
17. Experimentations on Eulerian Video Magnification
Keshav Goyal, Shashaank Nair, Nilay Jain, Gerardine Immaculate Mary, Anitha Julian and Mayur Rele
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
References
18. Predictive Modeling for Early Detection of Mental Health Crisis Among Employees
Anitha Julian, Anto Lourdu Xavier Raj Arockia Selvarathinam and Gerardine Immaculate Mary
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
References
19. Enhancement of Spatial Resolution with Deep CNN-Based Fusion of Panchromatic-Multispectral Images
Sujatha Canavoy Narahari, Sivaneasan Bala Krishnan, Prasun Chakrabarti and Abhishek Gudipalli
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
20. Analysis of Vibrations Using von Kármán and Green’s Geometric Nonlinearities
B. Ravi, Sujatha Canavoy Narahari, Abhishek Gudipalli and Wai Leong Pang
20.1 Introduction: Geometric Nonlinearity
20.1.1 Green’s Strain–Displacement Equations
20.2 Literature Survey
20.3 Methodology: Basic Formulas for Slender Columns
20.4 Results and Discussion
20.5 Conclusions and Future Scope
Bibliography
21. Dynamic Prosthetic Control through Real-Time EMG Monitoring
Sinthia P., Karthick M. and Muzzamil Sulthan K. S.
21.1 Introduction
21.2 Related Works
21.3 Methodology
21.3.1 Signal Acquisition
21.3.2 Signal Processing
21.3.3 Cases of Algorithms for EMG Analysis
21.3.4 Personalized Calibration
21.3.5 Feedback and Real-Time Monitoring
21.4 Proposed System Architecture
21.5 Results and Discussion
21.6 IoT Module
References
22. Automatic Piano Key Recognition for Beginners
Jackie Wen Yu Chong, Wei Jen Chew and G. Abhishek
22.1 Introduction
22.2 Research Methodology
22.2.1 Project Overview
22.2.2 Camera Calibration
22.2.3 Key Detection Algorithm
22.3 Results and Discussion
22.3.1 Edge Detection
22.3.2 Extraction of Black and White Keys
22.3.3 Labeling of Keys
22.4 Conclusion
References
23. Brain Tumor Severity Detection Using CNN
Deepika Rani Sona, Rashmi Ranjan Das, Deepikaa Balaji and Nitikaa Samundeeswari
23.1 Introduction
23.2 Methodology
23.2.1 Mathematical Theory
23.2.1.1 Merging Layer
23.2.1.2 Condensed Layer
23.2.1.3 Activation Function
23.2.1.4 ReLU Function
23.2.1.5 Sigmoid Function
23.2.2 System Model
23.2.2.1 Compiling Datasets
23.2.2.2 Data Cleaning and Preprocessing
23.2.2.3 Image Normalization
23.2.2.4 Data Augmentation
23.2.2.5 Model Generation
23.2.2.6 Training and Validation
23.2.2.7 Prediction and Visualization
23.3 Results and Discussions
23.3.1 Datasets
23.3.2 Model Performance
23.3.3 Confusion Matrix
23.3.4 Classification Report
23.3.5 Comparison with Existing Models
23.3.6 Open Challenges in a Similar Domain for Future Researchers
23.4 Conclusion
References
24. Edge-Based Cough and Snore Sleep Monitoring
Mekala Manikanta, Kakarla Akash Gangireddy, Swaroop Dintakurthi, Santhosh Kumar Reddy, Rashmi Ranjan Das, Deepika Rani Sona and Leela Praneeth Puli
24.1 Introduction
24.2 Literature Survey
24.2.1 Problem Formulation and Research Contributions
24.3 Methodology
24.3.1 Algorithm for the Proposed Keras Scheme
24.3.2 MFCC Feature Extraction in Preprocessing
24.3.2.1 Preemphasis
24.3.2.2 Framing
24.3.2.3 Windowing
24.3.2.4 Fast Fourier Transform
24.3.2.5 Mel Filterbank
24.3.2.6 Logarithm
24.3.2.7 Discrete Cosine Transform
24.3.3 Keras Library
24.3.3.1 Conv1D Layer
24.3.3.2 MaxPooling1D Layer
24.3.3.3 Flatten Layer
24.3.3.4 Dropout Layer
24.4 Results and Discussions
24.5 Conclusion
References
25. Design of 1.8 to 2.4 GHz LC Voltage Controlled Oscillator for Bluetooth Transceivers
Kusuma Neerugatti, Venugopal P. and Satheesh Kumar S.
25.1 Introduction
25.2 Literature Review
25.3 Proposed LC-Voltage Controlled Oscillator Design
25.3.1 Analytical Model of the Proposed LC-Voltage Controlled Oscillator
25.4 Simulation Results Discussion
25.4.1 Measuring of S-Parameters
25.4.2 Measuring of Frequency
25.4.3 Measuring of Phase Noise
25.4.4 Measuring of Power
25.4.5 Measuring of Figure of Merit
25.4.6 Monte Carlo and PVT Analysis
25.5 Conclusion
References
26. LEACH-Enhanced LoRa-Based Forest Fire Detection System
Priyanshu, Latha P., Sumitra V., Sivakumar R. and Jeevitha K.
26.1 Introduction
26.2 Objective
26.3 Literature Survey
26.4 Existing Work
26.5 Proposed Work
26.6 Methodology
26.6.1 Hardware Part
26.6.1.1 End Nodes
26.6.1.2 Outskirts Nodes
26.6.2 Software Part
26.7 Results
26.8 Conclusion
References
27. Flexible Broadband Electronic Textile Antenna for Wireless Body Area Network Fifth-Generation Communication
Siddharth Shaji, Paresh Sagar, Kalyanbrata Ghosh, Rahul Manohar and Arpan Shah
27.1 Introduction
27.2 Design of E-Textile Antenna for WBAN
27.3 Future Research Directions
27.4 Conclusion
References
28. Deep Neural Architectures for Proactive Collision Avoidance in Automated Vehicular Networks
Metta Vidhaya Datta Reddy, Mithul Raaj A. T., M. Vinodhini, Sujatha Rajkumar, Hamid Abdi, Anuja A. and Niranjan Kumar S.
28.1 Introduction
28.2 Related Works
28.3 Dataset for Semantic Segmentation of Vehicular Object Recognition
28.3.1 Extended U-Net Architecture for Real-Time Semantic Segmentation
28.3.2 Unveiling the E-Net Architecture for Pixel-Wise Semantic Segmentation
28.4 Performance Evaluation of Collision Avoidance in Vehicular Architectures
28.5 Results and Discussion
28.6 Conclusion and Future Scope
Bibliography
29. Real-Time Sleep Apnea Monitoring System Using IoT: A Bluetooth-Enabled Device for Continuous Sleep Tracking and Mobile Alerts
Sinthia P., Sarana Raj S., Amuthan P. and Ganesh M.
29.1 Introduction
29.2 Related Works
29.3 Aim and Objective
29.3.1 Components
29.3.2 Device Design
29.3.3 Mobile Application
29.3.4 System Development
29.3.5 Testing and Validation
29.4 Methodology
29.4.1 Architecture and Design of Systems
29.4.2 Gathering and Preparing Data
29.4.3 Development of Algorithms
29.4.4 Integration of Systems
29.4.5 Platform Based in the Cloud
29.4.6 Validation and Testing
29.5 Modules
29.5.1 Sensor Interfacing
29.5.2 Preparing Power Supply Unit
29.5.3 Microcontroller Programming
29.5.4 Reading Analog Data
29.5.5 Test and Debug
29.6 Results and Conclusion
29.7 Conclusion 4
References
30. Efficient Buffer Utilization Mechanism for 3D Network on Chip
Ravi S., Puli Manoj Kumar Reddy, Marimuthu R. and Harish M. Kittur
30.1 Introduction
30.2 Literature Review
30.3 Generic Router
30.4 Proposed Router
30.4.1 The Memory Bowl
30.4.2 Free Address Generator
30.4.3 Network Interface
30.5 Topology and Routing
30.6 Synthesis Results
30.7 Conclusions
References
31. Machine Learning Approaches for Predicting QoS in 5G Networks
Pooja Nandhini N., Abinaya P., Satyanarayan G. D., Revathi S., Anuprabha S. S. and M. J. Rhesa
31.1 Introduction
31.2 Methodology
31.2.1 Data Analysis
31.2.2 Data Processing
31.2.3 Regression Models
31.2.4 Evaluation Metrics
31.3 Results
31.4 Conclusion
References
32. A Communication Switch to Facilitate Communication During Natural Disasters and Crises
Ujjawal Tiwari, Siddharth Shaji, Arnab Saha, Saptarsi Banik, Dhruv Joshi and Venkata Ramana Kasi
32.1 Introduction
32.2 Technical Details
32.3 Methodology
32.4 Experimental Analysis and Results
32.5 Conclusion
References
33. Optimized Automatic Door Opening Using Millimeter-Wave Radar
Yandarapu Jaya Kushal, Gundu Sai Rithwik, M. Manoj Kumar and J. Valarmathi
33.1 Introduction
33.2 Introduction to the Millimeter-Wave Radar
33.2.1 Radar Setup
33.3 Proposed Methodology
33.3.1 Optimization in Automatic Door Opening
33.3.1.1 Filtering
33.3.1.2 Data Reduction
33.3.1.3 Data Smoothing
33.3.2 Proposed Trend-Following Algorithm
33.4 Results and Analysis
33.4.1 Inferences
33.5 Conclusion
References
34. Sensor Data Fusion Through CAN Bus for Autonomous Vehicles
Gerardine Immaculate Mary, Pranav Joshi, Nikhil Warungase, Anitha Julian and Anto Lourdu Xavier Raj Arockia Selvarathinam
34.1 Introduction
34.2 Related Works
34.3 Proposed Work Design
34.4 Proposed Work Description
34.4.1 Hardware Descriptions
34.4.2 Kalman Filtering
34.4.3 CAN to the Raspberry Pi
34.5 Conclusion and Future Work
References
35. Design and Implementation of an RF to DC Conversion Circuit for RF Energy Harvesting Applications for Wi-Fi 6 and Wi-Fi 6E Frequency Bands
Mellvin Dhivian A/L Lourdasamy, Manee Sangaran Diagarajan, Chockalingam Aravind Vaithilingam and N. Amutha Prabha
35.1 Introduction
35.2 Research Methodology
35.2.1 Overview
35.2.2 2.4-GHz Circuit Configuration
35.2.3 Type of Diode Chosen for the 2.4-GHz Circuit
35.2.4 5-GHz and 6-GHz Circuit Configuration
35.3 Results and Discussion
35.3.1 Circuit Operating at 2.4 GHz
35.3.2 Simulating at 2.4 GHz
35.3.3 Optimized 2.4-GHz Circuit Parameters
35.3.4 Circuit Operating at 5 GHz and 6 GHz
35.3.5 Simulating at 5 GHz
35.3.6 Simulating at 6 GHz
35.3.7 Optimized Dual-Band 5-GHz and 6-GHz Circuit Parameters
35.4 Conclusions
References
36. Hybrid Optimization and Machine Learning Approaches for Enhanced 5G Network Slicing with Improved QoS and QoE
D. Danteshwari, A. Vijayalakshmi, A. Packialatha, Ebenezer Abishek B. and R. Kumudham
36.1 Introduction
36.2 Related Works
36.3 System Architecture
36.4 Methodology
36.4.1 Data Collection
36.4.2 Deep Feature Extraction Using Whale-U-Net
36.4.3 Feature Optimization with BS-QNO
36.4.4 Network Slicing Classification
36.5 Proposed System
36.5.1 Benchmark Classifiers for Level-1 Classification
36.5.1.1 Decision Tree
36.5.1.2 Support Vector Machine
36.5.1.3 Recurrent Neural Network
36.5.1.4 Long Short-Term Memory
36.5.1.5 Hybrid DRRL Classifier for Slice Classification
36.6 Results and Discussion
36.6.1 Description of the Dataset
36.6.2 Comparative Analysis
36.6.3 Quality Measures and Error Measures Comparison
36.6.4 Comparison with Existing Deep Learning Techniques
36.7 Conclusion
References
About the Editors
Index
Back to Top
Preface
1. Integration of Industrial Robots to Enhance Warehouse Efficiency in an Industry 4.0 Environment Using Digital Twin Technology
Manikandan Pounraj, James Periyanayagam L., Jennifer Pearline Lobo and Ashwitha P.
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
2. QR Code-Enabled Anytime Pill Dispenser
Tamizharasi A. R. S., Rekha Mahalakshmi N., Nivetha K., Mutyam Gayathri Priya, Ashwini K. and R. Resmi
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
3. Analysis on Insulation Properties of Carbon Quantum Dots–SiO2 Oil Fillers in Mineral Oil
Madhumathi R. M. and Chandrasekar Subramaniam
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
Bibliography
4. Comparative Analysis of Partial Discharge Characteristics in Different Electrode Configurations of Biodegradable Nanofluid
Sangamithirai V. S. and S. Chandrasekar
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
References
5. Cost-Effective Real-Time Facial Recognition and Database Integration Using Firebase
Ragavan K, Kasamsetty Sai Dhanush, Kamisetty Naga Umesh, Perumalla Yuva Sai and Aeeja Haneesha Reddy
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
References
6. Remote Light Monitoring for Energy Efficiency
Gerardine Immaculate Mary, S. Chandramaouli, Anitha Julian and Rohan George Joshua
6.1 Introduction
6.2 Methodology
6.3 Design Approach
6.4 Results
6.4.1 Cost Analysis
6.5 Conclusion
References
7. Buffer for Critical Path VLSI Circuits
Karthikeyan A., Danush Ranganath G.V. and Rajalakshmi S.
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
References
8. Fuzzy Logic-Based Navigation Control for Khepera Robot
Bryan Tan Shun Xing, Nohaidda Sariff , Swee King Phang and B. Jaganatha Pandian
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
References
9. Detection and Recurrence of Breast Cancer Through Image Processing and Attention Awareness: A Comparative Analysis of Algorithms
Rajini G. K., Jasmin Pemeena Priyadarsini, Alan George, Thomas Tom and Arshaque Abdusalam
9.1 Introduction
9.2 Literature Review
9.3 System Implementation
9.4 Results and Discussion
9.5 Conclusion
References
10. Transformative Innovations in Tomato Plant Disease Detection: A Comprehensive Examination of Advanced Sensing Technologies and Algorithmic Precision
Rajesh Kannan Megalingam, Ananya S. Mallia and Sriram Ghali
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
References
11. Triples, Helmet, Number Plate Design On Real-Time Information System
J. Thomas Perera M.E. and R. Hemalatha M.E.
Introduction
Abbreviations
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
References
12. Brain Tumor Segmentation Using U-Net, U-Net with Attention, and ResNeXt50
Preetha R., Jasmine Pemeena Priyadarsini M., Subash Anumula, Sai Sathvik Reddy M., Praneeth Samana, Nisha J. S., A Jabeena, Ernest Bravin Clinton S. and Ganesan Subramanian
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
References
13. Skin Disease Classification for Healthcare Using a Federated Learning Based Ensemble Learning
N. V. Neeraja and J. Kamalakannan
13.1 Introduction
13.2 Literature Review
13.3 Dataset and Methodology
13.4 Results And Discussion
13.5 Conclusion
References
14. Fingerprint Recognition Using Image Processing and Neural Networks
Jasmin Pemeena Priyadarsini M., Addanki Keerthan, Bandi Sree Charan Teja Reddy, Pradeep Kumar Das, S. Sowmiya, A. Jabeena, Rizee P. J., Elavarasi A. and Ganesan Subramanian
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
Bibliography
15. Machine Learning Algorithms to Predict and Detect Malicious Network Traffic and Cyberattacks
M. Rajeshwari, Anbarasa Kumar Anbarasan, P. Ramakrishnan, T. Abirami and Mohammed Bilal K.
Introduction
Literature Review
Proposed Methodologies
Algorithms Used
Decision Tree Algorithm
XGBoost Algorithm
Performance Metrics
Confusion Matrix
Results and Output
Conclusion
References
16. Machine Learning-Based Term Retrieval Method for Text Extraction from Emojipedia
M. Divya and S. Sukumaran
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
Bibliography
17. Experimentations on Eulerian Video Magnification
Keshav Goyal, Shashaank Nair, Nilay Jain, Gerardine Immaculate Mary, Anitha Julian and Mayur Rele
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
References
18. Predictive Modeling for Early Detection of Mental Health Crisis Among Employees
Anitha Julian, Anto Lourdu Xavier Raj Arockia Selvarathinam and Gerardine Immaculate Mary
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
References
19. Enhancement of Spatial Resolution with Deep CNN-Based Fusion of Panchromatic-Multispectral Images
Sujatha Canavoy Narahari, Sivaneasan Bala Krishnan, Prasun Chakrabarti and Abhishek Gudipalli
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
20. Analysis of Vibrations Using von Kármán and Green’s Geometric Nonlinearities
B. Ravi, Sujatha Canavoy Narahari, Abhishek Gudipalli and Wai Leong Pang
20.1 Introduction: Geometric Nonlinearity
20.1.1 Green’s Strain–Displacement Equations
20.2 Literature Survey
20.3 Methodology: Basic Formulas for Slender Columns
20.4 Results and Discussion
20.5 Conclusions and Future Scope
Bibliography
21. Dynamic Prosthetic Control through Real-Time EMG Monitoring
Sinthia P., Karthick M. and Muzzamil Sulthan K. S.
21.1 Introduction
21.2 Related Works
21.3 Methodology
21.3.1 Signal Acquisition
21.3.2 Signal Processing
21.3.3 Cases of Algorithms for EMG Analysis
21.3.4 Personalized Calibration
21.3.5 Feedback and Real-Time Monitoring
21.4 Proposed System Architecture
21.5 Results and Discussion
21.6 IoT Module
References
22. Automatic Piano Key Recognition for Beginners
Jackie Wen Yu Chong, Wei Jen Chew and G. Abhishek
22.1 Introduction
22.2 Research Methodology
22.2.1 Project Overview
22.2.2 Camera Calibration
22.2.3 Key Detection Algorithm
22.3 Results and Discussion
22.3.1 Edge Detection
22.3.2 Extraction of Black and White Keys
22.3.3 Labeling of Keys
22.4 Conclusion
References
23. Brain Tumor Severity Detection Using CNN
Deepika Rani Sona, Rashmi Ranjan Das, Deepikaa Balaji and Nitikaa Samundeeswari
23.1 Introduction
23.2 Methodology
23.2.1 Mathematical Theory
23.2.1.1 Merging Layer
23.2.1.2 Condensed Layer
23.2.1.3 Activation Function
23.2.1.4 ReLU Function
23.2.1.5 Sigmoid Function
23.2.2 System Model
23.2.2.1 Compiling Datasets
23.2.2.2 Data Cleaning and Preprocessing
23.2.2.3 Image Normalization
23.2.2.4 Data Augmentation
23.2.2.5 Model Generation
23.2.2.6 Training and Validation
23.2.2.7 Prediction and Visualization
23.3 Results and Discussions
23.3.1 Datasets
23.3.2 Model Performance
23.3.3 Confusion Matrix
23.3.4 Classification Report
23.3.5 Comparison with Existing Models
23.3.6 Open Challenges in a Similar Domain for Future Researchers
23.4 Conclusion
References
24. Edge-Based Cough and Snore Sleep Monitoring
Mekala Manikanta, Kakarla Akash Gangireddy, Swaroop Dintakurthi, Santhosh Kumar Reddy, Rashmi Ranjan Das, Deepika Rani Sona and Leela Praneeth Puli
24.1 Introduction
24.2 Literature Survey
24.2.1 Problem Formulation and Research Contributions
24.3 Methodology
24.3.1 Algorithm for the Proposed Keras Scheme
24.3.2 MFCC Feature Extraction in Preprocessing
24.3.2.1 Preemphasis
24.3.2.2 Framing
24.3.2.3 Windowing
24.3.2.4 Fast Fourier Transform
24.3.2.5 Mel Filterbank
24.3.2.6 Logarithm
24.3.2.7 Discrete Cosine Transform
24.3.3 Keras Library
24.3.3.1 Conv1D Layer
24.3.3.2 MaxPooling1D Layer
24.3.3.3 Flatten Layer
24.3.3.4 Dropout Layer
24.4 Results and Discussions
24.5 Conclusion
References
25. Design of 1.8 to 2.4 GHz LC Voltage Controlled Oscillator for Bluetooth Transceivers
Kusuma Neerugatti, Venugopal P. and Satheesh Kumar S.
25.1 Introduction
25.2 Literature Review
25.3 Proposed LC-Voltage Controlled Oscillator Design
25.3.1 Analytical Model of the Proposed LC-Voltage Controlled Oscillator
25.4 Simulation Results Discussion
25.4.1 Measuring of S-Parameters
25.4.2 Measuring of Frequency
25.4.3 Measuring of Phase Noise
25.4.4 Measuring of Power
25.4.5 Measuring of Figure of Merit
25.4.6 Monte Carlo and PVT Analysis
25.5 Conclusion
References
26. LEACH-Enhanced LoRa-Based Forest Fire Detection System
Priyanshu, Latha P., Sumitra V., Sivakumar R. and Jeevitha K.
26.1 Introduction
26.2 Objective
26.3 Literature Survey
26.4 Existing Work
26.5 Proposed Work
26.6 Methodology
26.6.1 Hardware Part
26.6.1.1 End Nodes
26.6.1.2 Outskirts Nodes
26.6.2 Software Part
26.7 Results
26.8 Conclusion
References
27. Flexible Broadband Electronic Textile Antenna for Wireless Body Area Network Fifth-Generation Communication
Siddharth Shaji, Paresh Sagar, Kalyanbrata Ghosh, Rahul Manohar and Arpan Shah
27.1 Introduction
27.2 Design of E-Textile Antenna for WBAN
27.3 Future Research Directions
27.4 Conclusion
References
28. Deep Neural Architectures for Proactive Collision Avoidance in Automated Vehicular Networks
Metta Vidhaya Datta Reddy, Mithul Raaj A. T., M. Vinodhini, Sujatha Rajkumar, Hamid Abdi, Anuja A. and Niranjan Kumar S.
28.1 Introduction
28.2 Related Works
28.3 Dataset for Semantic Segmentation of Vehicular Object Recognition
28.3.1 Extended U-Net Architecture for Real-Time Semantic Segmentation
28.3.2 Unveiling the E-Net Architecture for Pixel-Wise Semantic Segmentation
28.4 Performance Evaluation of Collision Avoidance in Vehicular Architectures
28.5 Results and Discussion
28.6 Conclusion and Future Scope
Bibliography
29. Real-Time Sleep Apnea Monitoring System Using IoT: A Bluetooth-Enabled Device for Continuous Sleep Tracking and Mobile Alerts
Sinthia P., Sarana Raj S., Amuthan P. and Ganesh M.
29.1 Introduction
29.2 Related Works
29.3 Aim and Objective
29.3.1 Components
29.3.2 Device Design
29.3.3 Mobile Application
29.3.4 System Development
29.3.5 Testing and Validation
29.4 Methodology
29.4.1 Architecture and Design of Systems
29.4.2 Gathering and Preparing Data
29.4.3 Development of Algorithms
29.4.4 Integration of Systems
29.4.5 Platform Based in the Cloud
29.4.6 Validation and Testing
29.5 Modules
29.5.1 Sensor Interfacing
29.5.2 Preparing Power Supply Unit
29.5.3 Microcontroller Programming
29.5.4 Reading Analog Data
29.5.5 Test and Debug
29.6 Results and Conclusion
29.7 Conclusion 4
References
30. Efficient Buffer Utilization Mechanism for 3D Network on Chip
Ravi S., Puli Manoj Kumar Reddy, Marimuthu R. and Harish M. Kittur
30.1 Introduction
30.2 Literature Review
30.3 Generic Router
30.4 Proposed Router
30.4.1 The Memory Bowl
30.4.2 Free Address Generator
30.4.3 Network Interface
30.5 Topology and Routing
30.6 Synthesis Results
30.7 Conclusions
References
31. Machine Learning Approaches for Predicting QoS in 5G Networks
Pooja Nandhini N., Abinaya P., Satyanarayan G. D., Revathi S., Anuprabha S. S. and M. J. Rhesa
31.1 Introduction
31.2 Methodology
31.2.1 Data Analysis
31.2.2 Data Processing
31.2.3 Regression Models
31.2.4 Evaluation Metrics
31.3 Results
31.4 Conclusion
References
32. A Communication Switch to Facilitate Communication During Natural Disasters and Crises
Ujjawal Tiwari, Siddharth Shaji, Arnab Saha, Saptarsi Banik, Dhruv Joshi and Venkata Ramana Kasi
32.1 Introduction
32.2 Technical Details
32.3 Methodology
32.4 Experimental Analysis and Results
32.5 Conclusion
References
33. Optimized Automatic Door Opening Using Millimeter-Wave Radar
Yandarapu Jaya Kushal, Gundu Sai Rithwik, M. Manoj Kumar and J. Valarmathi
33.1 Introduction
33.2 Introduction to the Millimeter-Wave Radar
33.2.1 Radar Setup
33.3 Proposed Methodology
33.3.1 Optimization in Automatic Door Opening
33.3.1.1 Filtering
33.3.1.2 Data Reduction
33.3.1.3 Data Smoothing
33.3.2 Proposed Trend-Following Algorithm
33.4 Results and Analysis
33.4.1 Inferences
33.5 Conclusion
References
34. Sensor Data Fusion Through CAN Bus for Autonomous Vehicles
Gerardine Immaculate Mary, Pranav Joshi, Nikhil Warungase, Anitha Julian and Anto Lourdu Xavier Raj Arockia Selvarathinam
34.1 Introduction
34.2 Related Works
34.3 Proposed Work Design
34.4 Proposed Work Description
34.4.1 Hardware Descriptions
34.4.2 Kalman Filtering
34.4.3 CAN to the Raspberry Pi
34.5 Conclusion and Future Work
References
35. Design and Implementation of an RF to DC Conversion Circuit for RF Energy Harvesting Applications for Wi-Fi 6 and Wi-Fi 6E Frequency Bands
Mellvin Dhivian A/L Lourdasamy, Manee Sangaran Diagarajan, Chockalingam Aravind Vaithilingam and N. Amutha Prabha
35.1 Introduction
35.2 Research Methodology
35.2.1 Overview
35.2.2 2.4-GHz Circuit Configuration
35.2.3 Type of Diode Chosen for the 2.4-GHz Circuit
35.2.4 5-GHz and 6-GHz Circuit Configuration
35.3 Results and Discussion
35.3.1 Circuit Operating at 2.4 GHz
35.3.2 Simulating at 2.4 GHz
35.3.3 Optimized 2.4-GHz Circuit Parameters
35.3.4 Circuit Operating at 5 GHz and 6 GHz
35.3.5 Simulating at 5 GHz
35.3.6 Simulating at 6 GHz
35.3.7 Optimized Dual-Band 5-GHz and 6-GHz Circuit Parameters
35.4 Conclusions
References
36. Hybrid Optimization and Machine Learning Approaches for Enhanced 5G Network Slicing with Improved QoS and QoE
D. Danteshwari, A. Vijayalakshmi, A. Packialatha, Ebenezer Abishek B. and R. Kumudham
36.1 Introduction
36.2 Related Works
36.3 System Architecture
36.4 Methodology
36.4.1 Data Collection
36.4.2 Deep Feature Extraction Using Whale-U-Net
36.4.3 Feature Optimization with BS-QNO
36.4.4 Network Slicing Classification
36.5 Proposed System
36.5.1 Benchmark Classifiers for Level-1 Classification
36.5.1.1 Decision Tree
36.5.1.2 Support Vector Machine
36.5.1.3 Recurrent Neural Network
36.5.1.4 Long Short-Term Memory
36.5.1.5 Hybrid DRRL Classifier for Slice Classification
36.6 Results and Discussion
36.6.1 Description of the Dataset
36.6.2 Comparative Analysis
36.6.3 Quality Measures and Error Measures Comparison
36.6.4 Comparison with Existing Deep Learning Techniques
36.7 Conclusion
References
About the Editors
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