Recent Trends in Artificial Intelligence and IoT: First International Conference, ICAII 2022, Jamshedpur, India, April 4-5, 2023, Revised Selected ... in Computer and Information Science)

This book constitutes selected papers presented at the First International Conference on Artificial Intelligence and Internet of Things, ICAII 2022, held in Jamshedpur, India. ICAII 2022 has been postponed to April 2023. The 23 papers were thoroughly reviewed and selected from the 86 submissions. They are arranged in topical sections on ​ artificial Intelligence, and Internet of Things. Preface Organization Contents Artificial Intelligence Student Performance Monitoring System Using Artificial Intelligence Models 1 Introduction 2 Collaboration Through Decision-Making 3 Artificial Intelligence 3.1 Impact of AI on Education 3.2 Machine Learning 3.3 Decision-Making 4 Proposed Model of 4 -Tier DSS Using AI 4.1 Decision-Making Systems 5 Methodology 5.1 Decision-Making with Data Mining 5.2 Typical Attributes 6 Result and Discussion 6.1 Accuracy of Prediction 6.2 DSS in E-Learning 6.3 Decision-Making in Education 7 Conclusion References On Assaying the T-score Value for the Detection and Classification of Osteoporosis Using AI Learning Techniques 1 Introduction 2 Background 3 Analysis 4 Discussion 5 Conclusion References Evaluation of Healthcare Data in Machine Learning Model Used in Fraud Detection 1 Introduction 2 Literature Review 3 Evaluation Method 3.1 Accuracy 3.2 Precision or Positive Predicted Value 3.3 Negative Predicted Value 3.4 Sensitivity or Recall or TPR 3.5 Specificity or True Negative Rate 3.6 False Positive Rate 3.7 False Negative Rate 3.8 FDR 3.9 F 1 Score or Beta 3.10 GLC 3.11 F2 Score or Beta 2 3.12 ROC (Receiver Operating Characteristic) Curve 3.13 AUC 3.14 Average Precision or PR AUC Score 3.15 Brier Score 4 Evaluation Measure 5 Conclusion References A New Approach to Heart Disease Prediction Using Clustering and Classification Algorithms 1 Introduction 2 Literature Review 3 Clustering Algorithms 4 Classification Algorithms 5 Problem Statement 6 Methodology 6.1 K-Nearest Neighbors (KNN) and K-Means Algorithm 6.2 Logistic Regression (LR) 7 Results and Discussions 8 Conclusion References Skin Lesion Classification: Scrutiny of Learning-Based Methods 1 Introduction 2 Skin Lesion Imaging Techniques 2.1 Optical Coherence Tomography (OCT) 2.2 Reflectance Confocal Microscopy (RCM) 2.3 Dermoscopy 2.4 Ultrasound 3 Benchmark Dataset 3.1 Hospital Pedro Hispano (PH2) 3.2 International Skin Imaging Collaboration (ISIC) Archive 4 Deep Learning-Based Skin Lesion Detection Systems 5 Challenges and Future Recommendations 6 Conclusion References Lung Disease Classification Using CNN-Based Trained Models from CXR Image 1 Introduction 2 Related work 3 Methodology 3.1 System Architecture 3.2 AlexNet 3.3 SqueezeNet 3.4 Feature Selection 4 Dataset 5 Preprocessing 6 Proposed Work 7 Result and Discussion 8 Evaluation 9 Conclusion References A Novel Framework for Satellite Image Denoising and Super Resolution Using CNN-GAN 1 Introduction 2 Related Work 2.1 SAR Image Multiplicative Noise Degradation Model 2.2 CNNs for SAR Image Despeckling 2.3 Residual Learning 3 Proposed Model 3.1 Generator Network Architecture 3.2 Discriminator Network Architecture 3.3 Loss Function 4 Experiment and Results 4.1 Training Parameters and Details 5 Conclusion References Deep Learning Based Enhanced Text Recognition System 1 Introduction 2 Literature Review 3 Proposed Work 4 Result and Discussion 4.1 Performance Evaluation 5 Conclusion and Future Scope References Meta-transfer Learning for Contextual Emotion Detection in Face Affirmation 1 Introduction 2 Literature Review 2.1 Proposed Model 2.2 Convolutional Neural Network 2.3 MobileNet-V2 Architecture 2.4 Transfer Learning Approach 2.5 CNN with MobileNet-V2 Architecture Using a Transfer Learning Approach 3 Result and Discussion 4 Conclusion 5 Future Work References Hand-Written Devanagri Character Recognition Using Convolutional Neural Network in Python with Tensorflow 1 Introduction 2 Literature Review 3 Modeling of Convolutional Neural Network to Classify Handwritten Devanagri Characters 3.1 Importing Libraries 3.2 Data Loading and Overview 3.3 Splitting the Data Into Training and Testing Sets 3.4 Showing All the Output Classes 3.5 Converting DataFrame Having Pixel Values into Numpy Arrays 3.6 Visualizing Some Training Images Along with their Labels 3.7 Configuring TPU if Available 3.8 Building a CNN Model 3.9 Training the Model 3.10 Model Evaluation and Accuracy 3.11 Visualizing Predictions on Testing Set 4 Conclusion and Future Work References The Design and Development of Computerized Geogebra Mathematical Model for Painting Color Learning System 1 Introduction 2 Related Works 2.1 Calculus and Program 3 Methods and Materials 3.1 Introduction to the Experiment 4 Results and Discussion 4.1 Composition of System 4.2 Dynamic Polynomial 4.3 Color Match Recommendation Based on the Existing Data 4.4 Function Architecture of the System 4.5 Secant and Tangent 4.6 Language Communication 4.7 Computational Thinking Ability 4.8 Discussion and Analysis 5 Conclusion References Bisimulations for Fuzzy Geometric Models 1 Introduction 2 Preliminaries 3 Coalgebraic Logic 4 Bisimulations for Fuzzy Geometric Models 5 Conclusion References Research Study: Data Preprocessing Using Machine Learning for Prediction of Booking Cancellations 1 Introduction 2 Aims and Objectives 3 Related Works 4 Methods 5 Findings and Analysis. 5.1 Implementing Python Language for predicting the Reservation Cancellation 5.2 Importance of Machine Learning Technology in solving Real World Problems 5.3 Challenges in implementing Machine Learning Technology 5.4 Strategies for improving the implementation of ML in Business 6 Conclusion References Advanced MRI Segmentation Algorithm for the Detection of Brain Tumor Using U-Net Architecture with Transfer Learning EfficientNet-B7 1 Introduction 2 Literature Review 3 Proposed System 3.1 Semantic-Wise Fully CNN Architecture 3.2 U-Net Architecture 3.3 Transfer Learning 3.4 Traditional ML Algorithms 3.5 Data Set 3.6 Data Preprocessing 3.7 Training and Implementation Details 3.8 Performance Metrics 4 Results and Discussion 5 Conclusion and Future Work References Audio Analysis for Early Diagnosis of Alzheimer's Disease: A Study on Fisher's Linear Discriminant and Mel-Frequency Cepstral Coefficients 1 Introduction 2 Related Work 3 Proposed Methodology 4 Experimental Work and Performance Measure 5 Conclusions References Automation in Agriculture Using Deep Machine Learning: A Survey 1 Introduction 2 An Introduction on Machine Learning and Deep Learning 3 Machine Learning-Based Application in Agriculture 3.1 Disease Detection 3.2 Weed Detection 3.3 Yield Production 3.4 Crop Management 3.5 Water Management 3.6 Soil Management 3.7 Seed Sorting 4 Conclusion References Internet of Things A Survey on Security Threats in VANET and Its Solutions 1 Introduction 2 VANETs Characteristics 3 Security Attacks 3.1 Denial of Service (DoS) Attack 3.2 Malware Attack: OBU and RSU Are Prone to Malware Attack 3.3 Broadcast Tampering Attack 3.4 Black Hole and Grey Hole Attack 3.5 Jamming Attack 3.6 Greedy Behavior Attack 3.7 Spamming Attack 3.8 Eavesdropping Attack 3.9 Traffic Analysis Attack 3.10 Sybil Attack 3.11 Tunneling Attack 3.12 GPS Spoofing 3.13 Free-Riding Attack 3.14 Message Fabrication Attack 3.15 Masquerading Attack 4 Conclusion References An Analysis of Advanced Computations and Semantic Reasoning to Create an Intelligence System Using WSN 1 Introduction 2 Related Works 3 Methodology 3.1 Data Source 3.2 AI Based Clustering Model 4 Result Analysis 5 Conclusion References IoT & Smart City Viability: An Empirical Study 1 Introduction 2 Examining Existing research to Develop Hypothesis 3 Success Model for Modern Information Systems 3.1 Deemed Information Quality (DIQ) 3.2 Deemed System Quality (DSQ) 3.3 Deemed user satisfaction (DUS) 3.4 Use Cases for the Internet of Things (AUI) 4 Research Methodology 4.1 Creation of Indicators, Items, and Statements 4.2 Methods for Selecting a Representative Sample of Respondents 4.3 Observed Variable Reliability Analysis 4.4 Framework for Measuring (Loading Factor, CR, AVE, and MSV) 4.5 Indicators of Discriminant Validity 5 Discussion 6 Concluding Remarks References Design of a Contextual IoT Framework for the Improved User Experience and Services 1 Introduction 1.1 Motivation of This Work 1.2 Research Contributions 2 Related Work 3 Architecture of Proposed System 4 Proposed Technique 4.1 Usecase 1 - Geo-Fencing Triggered Device Management 4.2 Usecase 2 - Controlling Smart Lights and Geyser Based on Sleep Pattern 4.3 Usecase 3 - Controlling Smart Air Purifier Based on Weather and Air Quality Pattern 4.4 Usecase 4 - Weather Monitored Application for Controlling Smart Devices 4.5 Usecase 5 - Ambient Brightness Application to Monitor Smart Lights 5 Practical Implementation 6 Conclusion References Internet of Things Enabled Framework for Sustainable Mobility and Clean Environment in Smart Cities 1 Introduction 2 Role of IoT in Smart Cities 2.1 Typical Smart City-IoT Infrastructure 3 Environmental Aspect of Smart Cities 3.1 Sustainable Mobility 3.2 Connected and Autonomous Vehicles 3.3 Intersection of Electric and Autonomous Vehicles 4 Proposed Framework 4.1 IoT: The Core Enabler 5 Conclusion References Human Motion Detection Using Ultra-Wide Band Radar 1 Introduction 2 Data Generation and Preprocessing 3 Detail of Experiment Setup 4 Methodology 4.1 STA/LTA Technique 4.2 Detection using CFAR 4.3 Mean Window Comparison 4.4 Wavelet Transform 5 Discussions 6 Conclusion References Realization of MUX, DEMUX and ADD – DROP of Wavelength Using Bragg Grating and Optical Circulator 1 Introduction 2 Coupled Mode Theory of Fiber Bragg Grating (FBG) 3 Experimental 4 Result and Discussion References Author Index