The Future of Artificial Intelligence and Robotics: Proceedings of 5th International Conference on Deep Learning, Artificial Intelligence and ... (Lecture Notes in Networks and Systems, 1001)

This book includes the results from the 5th International Conference on Deep Learning, Artificial Intelligence and Robotics (ICDLAIR), held in National Institute of Technology, Kurukshetra, on December 07–09, 2023, which brought together visionaries, researchers, and industry leaders at the forefront of technological innovation. In the rapidly evolving landscape of technology, deep learning, artificial intelligence, and robotics stand as a beacon of innovation and intellectual exchange. Among the myriad of groundbreaking contributions, a notable gem emerges―a forthcoming book that promises to encapsulate the essence of the 5th International Conference on Deep Learning, Artificial Intelligence and Robotics, (ICDLAIR) 2023 proceedings. Titled " Progress in AI-Driven Business Decisions & Robotic Process Automation," this publication is poised to become a cornerstone for enthusiasts, researchers, and professionals seeking a comprehensive understanding of the latest advancements in deep learning, artificial intelligence, and robotics. Focused on the theme "Progress in AI-Driven Business Decisions & Robotic Process Automation," the conference showcased groundbreaking developments in the field, exploring the intersection of deep learning, artificial intelligence (AI), and robotics. Contents A Comparative Study of Machine Learning Algorithms for Predicting Cardiovascular Disease 1 Introduction 2 Related Works 2.1 Supervised Machine Learning-Based Approaches 2.2 Unsupervised Machine Learning-Based Approaches 2.3 Hybrid Machine Learning-Based Approaches 3 Methodology and Study Design 4 Experiments and Discussions 4.1 Experiments: Setup and Datasets 4.2 Discussions: Performance Evaluation 5 Conclusion References Deep W-Net: DNN for Spatial Saliency Prediction in Video Frames 1 Introduction 2 Related Work 2.1 Recent Work 3 Proposed Model 3.1 Proposed Architecture 3.2 Encoder Block 3.3 Decoder Block 3.4 Training Process 4 Experimental Results 4.1 Evaluation Methodology 4.2 Comparative Research Employing Techniques that Are Already Proposed 5 Conclusion References Optimal Pose Estimation with Particle Filters Using Unpowered Wheels 1 Introduction 2 Literature Review 3 Problem Statement 4 Error Analysis in Conventional Approaches 4.1 GPS Based Path Tracking Analysis 4.2 Wheel Odometry Data-Based Path Tracking Analysis 5 Improved Path Tracking Technique 6 Conclusion References A Short Survey on Comparative Study of Modern Cryptography Approach 1 Introduction 1.1 Cryptography Goals 1.2 Cryptography Algorithm 1.3 Applications of Cryptography 1.4 Aims and Objectives of the Study 1.5 Structure of the Paper 2 Background 2.1 History of Cryptography 2.2 Short Overview of Classic to Modern Cryptography Path 2.3 Basic Terminology of Cryptography 2.4 Cryptography Attacks 2.5 Related Work 3 Comparative Study of Modern Cryptography 3.1 Symmetric Encryption 3.2 Asymmetric Encryption 3.3 Hashing 4 Conclusion References Advances in Computer-Aided Detection and Diagnosis of Retinal Diseases: A Comprehensive Survey of Fundal Image Analysis 1 Introduction 2 Literature Review 2.1 Data Acquisition 2.2 Data Pre-processing and Feature Selection 2.3 Techniques Used 3 Critical Evaluation 4 Conclusion References Driver Safety and Drowsiness Detection in Internet of Vehicles with Federated Learning 1 Introduction 2 Related Work 3 Proposed Method 4 Results and Discussion 4.1 Tools Used and Dataset 4.2 Vehicle Network Simulation 5 Conclusion and Future Work References Privacy Preserving Fingerprint Classification Using Federated Learning 1 Introduction 2 Related Work 3 Proposed Solution 4 Results and Discussion 4.1 Network Architecture 4.2 Training Setup 4.3 Authentication Results 5 Conclusion and Future Direction References Comparative Study of Ensemble Learning Models for Smart Meter Load 1 Introduction 2 Literature Review 3 Ensemble Learning Based Forecasting Model 4 Results and Discussion 4.1 Experimental Setup and Dataset 4.2 Performance Analysis 5 Conclusion References Social-Media Video Summarization Using Convolutional Neural Network and Kohnen's Self Organizing Map 1 Introduction 2 Related Work 3 Proposed Model 3.1 Pre-processing 3.2 Feature Extraction 3.3 SOM Clustering 3.4 Keyframe Selection 4 Experimental Results and Discussion 4.1 Experimental Settings 4.2 Dataset 4.3 Evaluation Metrics 4.4 Results Analysis 5 Conclusion References Machine Learning and Deep Leaning in Predicting Coronary Heart Disease 1 Introduction 2 Research Methodology 2.1 Collection and Properties of Dataset 2.2 Data Pre-processing 3 Experiment and Output 4 Conclusion 5 Future Works References Augmented Super Resolution GAN (ASRGAN) for Image Enhancement Through Reinforced Discriminator 1 Introduction 2 Super Resolution 3 Proposed Method 4 Results and Findings 5 Conclusion References Convolutional Block Attention Assisted Dense Stacked Bi-LSTM for the Generation of RDF Statements 1 Introduction 2 Related Works 3 Proposed Methodology 3.1 Pre-processing 3.2 Feature Extraction Using the BERT-LSTM Model 3.3 Feature Clustering Using Adaptive Density K-means Clustering 3.4 RDF Classification Using Convolutional Block Attention Assisted Dense Stacked Bi-LSTM Model 4 Results and Discussion 4.1 Dataset Description 4.2 Performance Measures 4.3 Performance Analysis 4.4 Discussion 5 Conclusion References Real-Time Permanent Change Proposals for Abandoned Object Detection 1 Introduction 2 Related Work 3 Methodology 4 Experiment Results 4.1 Accuracy Results 4.2 Accuracy Comparison 4.3 Runtime Speed Analysis 5 Conclusion 6 Future Work References An Excursion to Ontology-Based Non-functional Requirements Specification 1 Introduction 2 Non-functional Requirements 3 Quality Models 4 Ontology 5 NFRs Specification 5.1 NFRs: A Hard or Soft Goal? 5.2 NFRs Extraction: Interview-Based Approach to Ontology-Based Approach 5.3 Comparative Analysis and Issues 6 Conclusions References A Review of Traditional and Neural Network Methods for Protecting Privacy in Big Data Analytics 1 Introduction 2 Anonymization Techniques 3 Data Distribution Technique 3.1 Horizontal Distribution 3.2 Vertical Distribution 4 Randomization Technique 5 Privacy Preserving Neural Networks 5.1 Cloud-Based Neural Networks 5.2 Clustering Based Algorithms 6 Privacy Preservation Using Fuzzy Neural Network 7 Conclusion References A Long Short-Term Memory Learning Based Malicious Node Detection for Clustering in Wireless Sensor Networks 1 Introduction 2 Related Work 3 Proposed System Architecture 3.1 Parameter Tuning, and Evaluation Metrics 4 Results and Discussions 5 Conclusion References Experimental Analysis for Sensor Reduction to Depict Real-Time Applications Through Regression Techniques 1 Introduction 2 Related Work 3 Proposed Methodology 3.1 Regression Technique 3.2 Mathematical Model 4 Experiments and Results 5 Conclusion References Multi-resolution Neural Network for Road Scene Segmentation 1 Introduction 2 Related Works 3 Proposed Work 3.1 Proposed Neural Network 3.2 Dataset 3.3 Benchmarking 4 Results and Discussion 4.1 Discussion 5 Conclusion References A CNN-Based Road Accident Detection and Comparison of Classification Techniques 1 Introduction 1.1 Motivation 1.2 Objective 1.3 Contribution 1.4 Paper Organization 2 Related Works 2.1 Machine Learning Methods 3 Proposed Work 3.1 Feature Extraction by CNN 3.2 Architecture Used 4 Results and Analysis 5 Conclusion and Future Work References Football Match Result Prediction Using Twitter Statistical/Historical Data 1 Introduction 1.1 Motivation 1.2 Objective 1.3 Contribution 2 Literature Survey 3 Methodology 3.1 Datasets 3.2 Training and Testing Splitting 3.3 Models Used 3.4 Evaluation Matrices 4 Results and Discussion 4.1 Random Forest Classifier 4.2 SVM Classifier 4.3 Naive Bayes Classifier 4.4 KNN Classifier 4.5 Comparison of all Models Used 4.6 Comparison with Existing Models 5 Conclusion and Future Work References Safeguarding Ecosystems and Efficiency in Peer-to-Peer File Sharing Systems: An IoT-Inspired Approach to Pollution Mitigation 1 Introduction 2 Related Work 3 Methodology 4 Experiments and Results 4.1 Analysis 4.2 Impact 5 Conclusion References A Heuristic for Minimizing Resource Requirement for Quantum Graph Neural Networks 1 Introduction 2 Related Work 3 Preliminaries 3.1 GNNs for Graph Classification 3.2 Quantum Circuits 3.3 Hybrid-QGNNs for Graph Classification 3.4 Clustering Algorithms 4 Methodology 4.1 Parameter Training 4.2 Classification 5 Experiments and Results 6 Conclusion References Light-Gated Recurrent Unit Based Acoustic Modeling for Improved Hindi ASR 1 Introduction 2 DNN-Li-GRU Hybrid Architecture 3 Corpus Details and Experimental Setup 3.1 Corpus Details 3.2 Experimental Setup 4 Experiments 4.1 Experiment with Different Acoustic Features 4.2 Role of Batch-Normalization 4.3 Impact of Diffent Techniques 4.4 Computational Efficiency of Different Models 4.5 Hybrid Acoustic Modeling 5 Conclusion References Detecting Phishing URLs Using Machine Learning: A Review 1 Introduction 2 Literature Review 3 Issues and Challenges 3.1 Datasets and Insufficient Training Data 3.2 Dynamic and Changing Nature of Phishing Techniques 3.3 Feature Extraction Challenges 3.4 Class Imbalance 4 Future Research Directions 4.1 Improved Feature Extraction and Selection 4.2 Better Training Data 4.3 Hybrid Approaches 4.4 Integration with User Education 5 Conclusion References Comparative Analysis of Pneumonia Detection from Chest X-ray Using Deep Learning 1 Introduction 1.1 Transfer Learning 1.2 Ensemble Learning 2 Available Datasets 3 Issues with Datasets 4 Comparative Analysis of Pneumonia Detection Approaches 5 Role of Pre-processing in Deep Learning 6 Discussion and Comparative Analysis 7 Conclusion References Forging Futures: Empowering Decentralised AI Marketplaces Through Blockchain Innovation 1 Introduction: Decentralized Artificial Intelligence Marketplace Bridging Innovation and Trust 2 What is Decentralized AI Marketplace? 2.1 The Decentralised Artificial Intelligence Market Seeks to Address These Issues by 3 Blockchain and Smart Contracts 3.1 Immutable Record Keeping 3.2 Smart Contract Automation 4 Data Monetization and Ownership 4.1 Data Sovereignty and Control 4.2 Tokenized Data Exchange 4.3 Fair Compensation 5 Federated Learning and Privacy in a Decentralized AI Marketplace 5.1 Federated Learning: A Decentralized Approach to Learning 6 Dynamic Pricing and Allocation of Resources in a Decentralised Artificial Intelligence Marketplace 6.1 Dynamic Pricing Mechanisms 6.2 User-Centric Pricing 6.3 Obstacles and Considerations 7 Decentralized Governance Models AI 7.1 Decentralized Autonomous Organizations (DAOs) 7.2 Consensus Mechanisms for Governance 7.3 Compliance and Governance in the Field of Regulation 8 Cross-Chain Interoperability 8.1 Key Aspects 9 Challenges and Solutions in Decentralized AI Marketplaces 9.1 Scalability 9.2 Quality Assurance 9.3 Data Privacy and Ownership 10 Case Study - Ocean Protocol 10.1 Data Assets Representation 10.2 Smart Contracts 10.3 Compute-To-Data (C2D) 10.4 Data Monetisation 10.5 Decentralised Governance Mechanisms 11 Conclusion References Citrus Leaf Disease Prediction: Deep Feature Fusion Perspective 1 Introduction 1.1 Contributions 1.2 Organisations 2 Related Work 3 Material and Methodology 3.1 About Dataset 3.2 Methodology 4 Result and Discussion 5 Conclusion References Badminton Shot Recognition with LSTM Network 1 Introduction 2 Related Work 3 Proposed Methodology 3.1 Dataset Collection 3.2 Video Augmentation and Labelling 3.3 Key-Point Detection 3.4 Classification Model 4 Experiments and Results 5 Conclusion References An Ensemble Learning Model for Automatic Detection of Cyberbullying on Instagram Platform 1 Introduction 2 Related Works 3 Proposed System 3.1 Pre-processing of Data 3.2 Detection Model Using Supervised Machine Learning Algorithm 4 Experimental Results 4.1 Description of Dataset 4.2 Performance Evaluation Metrics 5 Conclusion and Future Enhancement References Enhancing Plant Pathology Detection and Stratification with a Tailored Mask R-CNN Framework 1 Introduction 2 Literature Survey 3 Proposed Methodology 4 Results and Discussions 4.1 Dataset Description 4.2 Quantitative Metrics 4.3 Performance Evaluation Metrics 4.4 Performance Evaluation 4.5 Computation Time 5 Conclusion References Deep Neural Network Regression Based Device Free Localization Technique in Changing Indoor Environment 1 Introduction 2 Proposed Link Distance Deep Neural Network (LD-DNN) Regression Based DFL Technique 2.1 A System Architecture of Proposed LD-DNNR Model in Real Time Scenario 3 Deep Neural Network Regression Model 3.1 MLP Based Deep Neural Network Regression 4 Results and Discussion 4.1 Experimental Setup 4.2 Performance Metrics 4.3 Performance Comparison of the Proposed LD-DNNR Based DFL Technique with Benchmark Models 4.4 Performance of Proposed LD-DNNR Based DFL Technique in Changing Indoor Environment 5 Conclusion References An Ensemble-Based Approach for Cyber Attack Detection in Financial Systems 1 Introduction 2 Background Study 2.1 Digital Transaction and Payment Methods 2.2 Online Transaction System 2.3 Digital Payment Fraud 3 Methodology 3.1 Operational Flow 4 Result and Analysis 4.1 Formulation 5 Conclusion References LoHCEO (Low Overhead and High Congestion Reduction in Epidemic Mode for Opportunistic Networks) 1 Introduction 2 Contextual and Associated Work 2.1 Epsoc: Social-Based Epidemic-Based Routing Protocol in Opportunistic Mobile Social Network 2.2 Enhanced Epidemic Routing Protocol in Delay Tolerant Networks 2.3 Analysis of Epidemic, PROPHET and Spray and Wait Routing Protocols in the Mobile Opportunistic Networks 2.4 Congestion Control for Epidemic Routing in Opportunistic Networks 2.5 Buffer Adaptive Epidemic Protocols for DTN 2.6 Prioritized Epidemic Routing for Opportunistic Networks 3 Proposed Work 3.1 Apprehension of Network Configuration 4 Result Discussion 4.1 Packet Transfer Ratio (PDR) 4.2 Packet Overhead Ratio 4.3 Packet Transmission Delay 5 Conclusion and Future Work References MetaMis: A Study of Identifying Missed Labels or Mislabels of Chest Radiographic Images Using Meta Learning 1 Introduction 1.1 Missed diagnosis 2 Related Work 3 Methods 3.1 Chest Radiographies 3.2 AI and Meta Learning Algorithms 3.3 Statistical analysis 4 Statistical Analysis 5 Discussion 6 Conclusion References An Automatic Process of Online Handwriting Recognition and Its Challenges 1 Introduction 2 Online Handwriting Recognition Systems 3 Challenges in Case of Online Handwriting Recognition 4 Challenges Based on Writer’s Category and Vocabulary Type 5 Conclusion References IoT-Enabled Smart Restaurant Management System 1 Introduction 2 Existing Literature 2.1 Restaurant Management Systems 2.2 Fire Prevention Systems 3 Proposed System 3.1 Fire Safety 3.2 Food Ordering 3.3 Face Recognition System 4 Performance Analysis 4.1 Design for Hardware Fault Tolerance 4.2 Design for Network Fault Tolerance 4.3 Design for Performance 4.4 Design for Maintenance 4.5 Unit Testing 5 Conclusion References Design Framework for Building Smart Shopping Stores Using IoT 1 Introduction 2 Existing Literature 3 Proposed Framework 3.1 Smart Shopping Cart 3.2 Automated Billing Counter 3.3 Inventory Management 3.4 Sensor-Enabled Exit Gate 4 Results Analysis and Discussion 5 Conclusion References A Multi-objective Virtual Machine Placement Optimization in Sustainable Cloud Environment 1 Introduction 2 Related Work 3 Proposed Model 3.1 Resource Utilization 3.2 Energy Consumption 3.3 Carbon Footprint 4 NSGA II Based VM Allocations 4.1 Time Complexity Analysis 5 Performance Evaluation 5.1 Experimental Set-Up 5.2 Results 5.3 Comparative Analysis in Dynamic VMP 6 Conclusion References Fake News Detection Using Heterogeneous Information from Multimedia Content 1 Introduction 2 Related Work 3 Methodology 3.1 Visual Model for Feature Map Extraction 3.2 Lingual Model For Embedding Extraction 3.3 Fusion of Visual and Lingual Features 4 Dataset and Experiments 4.1 Dataset 4.2 Experimental Results and Analysis 5 Conclusion and Future Work References Comparative Analysis of CNN and Transformers on Malicious Intent Detection in HTTP 1 Introduction 2 Literature Review 3 The Proposed Work 3.1 Overall Workflow and Process 3.2 Dataset Details 3.3 Data Preprocessing 3.4 Generate Embeddings 3.5 Visualisation 3.6 Deep Learning Models 4 Results and Discussion 4.1 More Findings 5 Conclusion References Comparison of Sensor-MAC (S-MAC), Timeout-MAC (T-MAC), Berkeley-MAC (B-MAC), and Modified ML-MAC (M2L-MAC) for Wireless Sensor Networks 1 Introduction 1.1 Motivation 1.2 Contributions 1.3 Organization of Paper 2 Literature Survey 3 Proposed Methodology 4 Simulation Results 4.1 Evaluation of Network Longevity 4.2 State of the Art Techniques 5 Conclusions References Automatic Code Scraping Based Test Case Generation 1 Introduction 1.1 Motivation 1.2 Organization of the Paper 2 Related Work 3 Problem Statement 4 Proposed Work 4.1 Abstract Syntax Tree (AST) Generation 4.2 AST Traversal 4.3 Test Case Generation 4.4 Test Case Prioritization 4.5 Cyclomatic Complexity for Coverage Analysis 4.6 Decision Points Detection 5 Result Analysis 6 Conclusion References Prediction of AQI for Urban Metropolis Using MLSTM-GRU Model 1 Introduction 1.1 Organization of the Paper 2 Related Work 3 Proposed Work 3.1 Collection and Description of Dataset 3.2 Preprocessing and Visualization of Data 3.3 Feature Selection 3.4 Modified LSTM-GRU (MLSTM-GRU) Model 4 Result and Discussion 4.1 Performance Evaluation Metrics 4.2 Experimental Result and Comparative Analysis 5 Conclusion and Future Scope References Land Use Land Cover Classification Using Multi-spectral Satellite Imagery 1 Introduction 2 Related Work 3 Datasets 4 Proposed Work 4.1 Design Methodology 4.2 System Architecture Diagram 4.3 Description of Algorithms 5 Result Analysis 6 Conclusion References An Ensemble Learning Based Career Prediction Model 1 Introduction 1.1 Contribution 1.2 Organisation 2 Proposed Model 2.1 Data Collection 2.2 Data Pre-processing 2.3 Ensemble Classification and Classifiers 3 Operational Summary 4 Results and Discussion 4.1 Experimental Setup and Data Set 4.2 Performance Analysis 5 Conclusion References Feature Extraction Analysis in a Speaker Identification System 1 Introduction 1.1 About the Paper 1.2 Motivation 1.3 Novelty and Contributions 2 Literature Survey 3 Proposed Methodology 3.1 MFCC 3.2 BFCC 3.3 GFCC 3.4 LPC 3.5 GMM 4 Experimental Setup 4.1 Dataset Used 4.2 Training Model 5 Results and Outcomes 6 Discussions and Future Aspects 7 Conclusion References Breast Cancer Prognosis Based on Machine Learning Model 1 Introduction 2 Literature Exploration 3 Materials and Methods 3.1 Preprocessing of Image 3.2 Feature Extraction 3.3 Naïve Bayes 3.4 Decision Tree (DT) 3.5 Logistic Regression (LR) 3.6 Random Forest (RF) 3.7 K-Nearest Neighbour (KNN) 3.8 Support Vector Machine (SVM) 4 Result and Discussion 5 Conclusion References PRESENT Block Cipher Defined over Galois-Field (28) 1 Introduction 2 Related Work 3 Proposed Method 3.1 S-Box Layer 3.2 Permutation Layer 3.3 Key Schedule 4 Statistical Testing 5 Performance Analysis 5.1 Security 5.2 Resource Requirement 6 Conclusion References Mammograms Image Quality Enhancement Using Center Adaptive Median Filter (CEAMF) for Noise and Artifact Removal 1 Introduction 1.1 Motivation and Research Gaps 2 Related Work 3 Proposed Work 3.1 Image Dataset 3.2 Methodology 3.3 Performance Metrics 4 Results Analysis 5 Conclusion References Fertilizer Recommendation with Stress Monitoring in Agriculture 1 Introduction 2 Literature Survey 3 Proposed Methodology 3.1 Statistical Analysis 3.2 Fertilizer Recommendation 4 Experimental Results 4.1 Dataset 4.2 Evaluation Metrics 4.3 Discussion on Results 5 Conclusion and Future Scope References Surface Water Mapping and Analysis in SANGAMAM of River Godavari and Krishna Rivers Using Google Earth Engine 1 Introduction 2 Literature Review 3 Methodology 3.1 Description 3.2 Architecture Diagram 3.3 Description 3.4 Description of Algorithms 4 Experimental Results 5 Conclusion References Spyware Alert System and Image Steganography for Military Application 1 Introduction 2 Literature Review 3 Proposed Method 3.1 Architecture Diagram 3.2 Description of Algorithms 3.3 Spyware Detection through Alert Message using Regular Expression 4 Results and Observations 4.1 Result and Analysis of Image Steganography 5 Conclusion References: Abstract. A Review on YOLO Algorithms for Social Distancing 1 Introduction 1.1 Motivation 2 Related Works 3 Research Model for Social Distancing 4 Problems, If Not Maintaining Social Distance 5 Object Detection and Tracking Model 5.1 Object Detection 5.2 Object Tracking 6 Deep Learning Based Object Detection 6.1 You Only Look Once (YOLO V6) 6.2 You Only Look Once (YOLO V7) 7 Results and Comparisons 8 Conclusion References A Hybrid Approach for Detecting Software Refactoring Sequencing 1 Introduction 1.1 Refactoring Sequencing 1.2 Hybridization of Algorithms 2 Research Methodology 3 Conclusions References ADNet: An Attention Embedded DenseNet121 Model for Weed Classification 1 Introduction 2 Related Work 3 Proposed Methodology 3.1 Dataset 3.2 Data Preprocessing 3.3 Architecture of the Proposed ADNet Model 4 Experiment Results 4.1 Experiment Setup 4.2 Dataset Preparation 4.3 Performance Analysis of Proposed CNN Models 4.4 Performance Comparison with Existing Research Work 5 Conclusion References NRASV: Noise Robust ASV System for Audio Replay Attack Detection 1 Introduction 1.1 Related Work 2 Proposed Approach 2.1 Feature Extraction 2.2 Classification 3 Experiments and Result Analysis 3.1 Performance of Proposed Model Under Clean Environment 3.2 Performance of Proposed Model Under Noisy Environment 4 Discussion and Comparative Analysis 5 Conclusion References Machine Learning for the Proactive Identification of Polycystic Ovary Syndrome (PCOS): Empowering Women’s Health 1 Introduction 2 Literature Review 3 Methodology 3.1 Data Set 3.2 Data Analysis and Visualization 3.3 Data Preprocessing 3.4 Selection and Training the Model 3.5 Hyperparameter Tuning 4 Result and Discussion 5 Conclusion References RADU-Net: A Fully Convolutional Neural Network for Efficient Skin Lesion Segmentation 1 Introduction 2 Related Work 3 Proposed Method 3.1 Convolutional Block 3.2 The Encoder Path 3.3 The Connecting Bridge 3.4 The Decoder Path 3.5 Residual Connection 3.6 Attention Gates 4 Experimental Analysis 4.1 Dataset 4.2 Data Preparation and Augmentation 4.3 Experimental Setup 4.4 Evaluation Metrics 5 Results and Discussion 5.1 Ablation Study 5.2 Quantitative Performance Analysis 5.3 Qualitative Performance Analysis 6 Conclusion References Smart Healthcare AI-Infused Saline Monitoring System with IoT- Empirical Study 1 Introduction 2 Literature Review 3 Comparative Study Based on Literature Review 4 Conclusion References Music Recommendation System Using Psychological Scale 1 Introduction 1.1 Our Contributions 2 Related Work 3 Proposed Work 3.1 Data Collection 3.2 TIPI Scale 3.3 Dataset Description 3.4 Data Preprocessing 3.5 Recommendation Generation 4 Result Analysis 5 Conclusion References Bidirectional Long-Short Term Memory Based Approach for Sampling in Dual Arm Locomotion 1 Introduction 2 Related Work 3 Proposed Work 3.1 Dataset Generation 3.2 Finding Solution to the Dataset Using RRT* 3.3 Training of the Bi-directional Long Short Term Memory Projector 3.4 Goal Biased Sampling 3.5 Bi-LSTM Projector Architecture 3.6 Path Length and Time Required 3.7 Setup 4 Results Analysis 5 Conclusion References Decoding Emotions: Unveiling Sentiments and Sarcasm Through Text Analysis 1 Introduction 1.1 Background and Motivation 1.2 Problem Definition 1.3 Problem Objectives 2 Literature Survey 2.1 Sentiment Analysis 2.2 Sarcasm Detection 3 Material and Proposed Methods 3.1 Dataset Overview 3.2 Proposed Methods Used for Sentiment Analysis and Sarcasm Detection 3.3 Overall Workflow of Proposed Methodology and Implementation 4 Results and Discussion 4.1 Sentiment Analysis 4.2 Sarcasm Detection 5 Conclusion and Future Scope References Rice Disease Identification Using Vision Transformer (ViT) Based Network 1 Introduction 2 Related Works 3 Rice Disease Dataset 4 Proposed Network Architecture 5 Results and Discussion 6 Conclusion References Image Based Rice Weed Identification Using Deep Learning and Attention Mechanisms 1 Introduction 2 Methodology 2.1 Dataset 2.2 Data Pre-processing 2.3 Model Architecture 2.4 Hyperparameters 2.5 Experimental Implementation 3 Results and Discussion 3.1 Evaluation Metrics 4 Conclusion References Intrusion Detection System Using Deep Learning Techniques for Internet of Medical Things (IoMT) 1 Introduction 2 Related Work 3 Dataset Description 4 Experimental Setup 5 Research Methodology 5.1 Preprocessing 5.2 Research Model 5.3 Performance Metrics 6 Results and Analysis 7 Conclusion and Future Scope References Detection and Grading of Diabetic Retinopathy from Fundus Images by Applying Transfer Learning 1 Introduction 2 Motivation 3 Literature Survey 4 Proposed Work 4.1 Dataset Description 4.2 Preprocessing 4.3 Data Augmentation 4.4 Implementation 5 Results and Analysis 5.1 Results and Comparison 5.2 Performance Comparison 6 Conclusion and Future Plan References Indian Sign Language Bilateral Translator 1 Introduction 2 Related Work 3 Proposed Work 3.1 English Text to Indian Sign Language Translation 3.2 Indian Sign Language to English Text 4 Result 4.1 English Text to Indian Sign Language Translation 4.2 Indian Sign Language to English Text 5 Conclusion and Future Scope References A Review on Security Challenges: Cryptography and Blockchain for Internet of Things 1 Introduction 2 Security Challenges in IoT 3 Cryptography in IoT Security 3.1 Data Encryption 3.2 Authentication and Key Management 4 Blockchain Technology for IoT Security 5 Integration of Cryptography and Blockchain 6 Future Directions and Challenges 6.1 Emerging Trends 6.2 Ongoing Challenges 7 Conclusion References Current Approaches and Challenges in Medical Image Analysis and Visually Explainable Artificial Intelligence as Future Opportunities 1 Introduction 2 Popular Visual Sources of Medical Diagnosis 3 Deep Learning and Machine Learning Approaches in the Medical Domain 4 Challenges of Deep Learning and Machine Learning 5 XAI Model 6 Conclusion References Early Detection and Classification of Zero-Day Attacks in Network Traffic Using Convolutional Neural Network 1 Introduction 2 Related Work 3 Proposed Approach 3.1 Pre-processing 3.2 Dataset Splitting, Balancing, and Hyper-parameter Tuning 3.3 Model Training, Validation, and Testing 4 Experimental Analaysis 4.1 Experimental Setup 4.2 Evaluation Metrics 4.3 Experimental Results 5 Conclusion References Author Index