AI and Machine Learning Paradigms for Health Monitoring System: Intelligent Data Analytics

Description

This book embodies principles and applications of advanced soft computing approaches in engineering, healthcare and allied domains directed toward the researchers aspiring to learn and apply intelligent data analytics techniques. The first part covers AI, machine learning and data analytics tools and techniques and their applications to the class of several hospital and health real-life problems. In the later part, the applications of AI, ML and data analytics shall be covered over the wide variety of applications in hospital, health, engineering and/or applied sciences such as the clinical services, medical image analysis, management support, quality analysis, bioinformatics, device analysis and operations. The book presents knowledge of experts in the form of chapters with the objective to introduce the theme of intelligent data analytics and discusses associated theoretical applications. At last, it presents simulation codes for the problems included in the book for better understanding for beginners. Preface Contents Editors and Contributors About the Editors Contributors Brief Introduction of AI and Machine Learning (AIML) and Its Applications Optimization Solutions for Demand Side Management and Monitoring 1 Introduction 2 From Conventional Energy Management to Demand Side Management 2.1 Supply Side Management SSM 2.2 Demand Side Management 3 Literature Review 4 Demand Side Management Programs and Techniques 4.1 Energy Efficiency (EE) 4.2 Demand Response (DR) 4.3 Strategic Load Growth 4.4 Energy Conservation (ENCON) 5 Optimal Residential Demand Side Management Considering Renewable Energy Resources 6 Architecture of Residential Demand Side Management 6.1 Energy Consumption Model 6.2 Categories of Load 7 Problem Formulation for the Exact Solution Methods 8 Objective Function and Constraints 8.1 Objective Functions 8.2 Constraints 9 Different Models 9.1 Genetic Algorithm 9.2 Differential Evolution Algorithm 9.3 Particle Swarm Optimization (PSO) Algorithm 9.4 Ant Colony Algorithms ACA 10 Impact of DSM on Power Systems 11 Obstacles in Implementing DSM Programs 12 Conclusion References An Insight into Tool and Software Used in AI, Machine Learning and Data Analytics 1 Introduction 1.1 Machine Learning 1.2 Artificial Intelligence ch2mitchell2013artificial 1.3 Data Analytics 2 Impact of Machine Learning, Artificial Intelligence, and Data Analytics ch2dimiduk2018perspectives 3 Current Trends in Machine Learning, AI, and Data Analytics ch2saiyeda2017cloud 4 Our Contribution 5 Objective 6 Software and Tools of Machine Learning, Artificial Intelligence, and Data Analytics 6.1 Data Analytics Tools ch2sapountzi2018social 6.2 Machine Learning Tools ch2yuan2020survey 6.3 Artificial Intelligence Tools ch2coelho2017exploratory 7 Application Domain of Machine Learning, Artificial Intelligence, and Data Analytics 8 Case Study Data Analytics Using Python 8.1 Types of Anomalies 8.2 Techniques Used for Anomaly Detection 9 Conclusion and Future Work References Security Enhancement and Monitoring for Data Sensing Networks Using a Novel Asymmetric Mirror-Key Data Encryption Method 1 Introduction 1.1 Big Data 1.2 Big Data Security 2 Data Security Concerns 2.1 Insecure Computation 2.2 Input Validation and Filtering 2.3 Insecure Data Storage 3 Cryptography 3.1 The Basic Terms Used in Cryptography 4 Classification of Cryptography Algorithms 4.1 Symmetric Cryptography 4.2 Asymmetric Cryptography (Public Key Cryptography) 5 Literature Review 6 The Proposed Encryption Method 6.1 Sender Side 6.2 Receiver Side 7 Analysis 8 Conclusion References Introduction to Cuckoo Search and Its Paradigms: A Bibliographic Survey and Recommendations 1 Overview and Analysis 1.1 Optimization and Cuckoo Search Concept 1.2 Cuckoo Breeding and Search Concept 1.3 Lévy Flights Strategy 2 Cuckoo Search Algorithm and Implementation 2.1 Cuckoo Search Algorithm 2.2 Implementation of Algorithm 3 Cuckoo Search Algorithm Variants, Hybrids and Applications 3.1 Variants Algorithm 3.2 Hybrids of Algorithm 3.3 Applications 4 Analysis of Algorithm 5 Conclusion References Routing Protocols for Internet of Vehicles: A Review 1 Introduction 2 Characteristics 3 Challenges 4 Routing Protocols 4.1 Information-Based Routing Protocol 4.2 Topology-Based Routing Protocol 4.3 Position-Based Routing Protocol 4.4 Delay Routing Protocols 4.5 Target Network Routing Protocols 4.6 Path-Based Routing 5 Conclusion References Introduction to Particle Swarm Optimization and Its Paradigms: A Bibliographic Survey 1 Introduction 1.1 PSO Inspiration, Concept, and Major Developments 2 PSO Algorithm 2.1 PSO Algorithm Structure 2.2 Pseudocode 3 PSO Variants, Hybrids, and Modifications 3.1 Barebones PSO 3.2 Binary PSO 4 PSO Applications 5 Concluding Remarks References AIML Applications for Monitoring System in Health and Management Classification and Monitoring of Injuries Around Knee Using Radiograph-Based Deep Learning Algorithm 1 Introduction 1.1 Novelty of the Work 2 Description of Fractures Around the Knee 3 Background and Design of Deep Learning Algorithm 3.1 Background of Deep Learning 3.2 Design of the Proposed CNN 4 Image Preprocessing and Datasets 5 Overall Process of DLA Based Classification 6 Results and Discussions 7 Conclusions References Artificial Intelligence: Its Role in Diagnosis and Monitoring Against COVID-19 1 Introduction 2 Artificial Intelligence in COVID-19 2.1 Medical Imaging 2.2 Textual Analysis and Virtual Assistants 2.3 Drug Discovery 2.4 Modeling COVID-19 Outbreak 2.5 Data and Privacy 3 Conclusion References Predicting Future, Past, and Misinterpreted COVID-19 Cases Using Bidirectional LSTM Model for Proper Health Monitoring: Advances in Data Analytics 1 Introduction 2 Forecasting Models 2.1 Differential Equation Model 2.2 Statistical Time-Series Prediction Models 2.3 ARIMA (Auto Regression Integrated Moving Average) 2.4 RNN (Recurrent Neural Networks) 2.5 LSTM (Long Short-Term Memory) 2.6 Bidirectional LSTM (Long Short-Term Memory) and RNN 3 Architecture and Training 3.1 Data 4 Results and Discussion 5 Conclusion References Data-Driven Analysis to Identify the Role of Relational Benefit in Developing Customer Loyalty and Management: A Case Study 1 Introduction 2 Literature Review 2.1 Confidence Benefits 2.2 Customer Loyalty 2.3 Theoretical Framework 3 Research Methodology 4 Conclusion and Recommendation References Interpretation of EEG Signals During Wrist Movement Using Multi-resolution Wavelet Features for BCI Application 1 Introduction 2 Signal Acquisition 2.1 BCI Competition 3 Wavelet Transform 4 Feature Extraction 4.1 Inter-quartile Range 4.2 Energy 4.3 Normalized Coefficient of Variation (NCV) 4.4 Normalized Coefficient of Variation-2 (NCV2) 4.5 Normalized Covariance (COVFF) 4.6 Covariance (Cov) 5 Feature Selection 6 Classification 7 Results 8 Discussion and Conclusion References Validation of Road Traffic Noise Prediction Model CoRTN for Indian Road and Traffic Conditions 1 Introduction 2 Material and Methods 2.1 Assumption for Model Validation 2.2 Input Data Used for Validation 3 Result and Discussion 4 Conclusion References AIML Applications for Monitoring System in Engineering and Automation Deep Learning and Statistical-Based Daily Stock Price Forecasting and Monitoring 1 Introduction 2 Methodology 2.1 Time Series Analysis of Financial Data 2.2 Statistical Methods for TS Analysis 2.3 Datasets 2.4 LSTM Hyperparameter Selection 2.5 Network Structure 3 Experimental Results 3.1 Time Series Decomposition 3.2 Average or Mean Method 3.3 Autoregression Method 3.4 ARIMA Model 3.5 LSTM Model 3.6 Comparison of Different Models 4 Conclusion References Intelligent Modelling of Renewable Energy Resources-Based Hybrid Energy System for Sustainable Power Generation and Monitoring 1 Introduction 2 Site Selection and Data Availability 3 Modelling of Renewable Energy Components 3.1 SPV 3.2 Wind Energy System 3.3 Biomass Generator 3.4 Biogas Generator 3.5 Battery 3.6 Grid 4 Optimization Framework 4.1 Objective Function 4.2 Design Constraints 5 GWO 6 HS 6.1 Formulation of Problem 6.2 HS Parameter Initialization 6.3 New Harmony Development 6.4 Updation 6.5 Check Stopping Criteria 7 PSO 7.1 Initialization of the Problem with PSO Parameters 7.2 Initialization of Particles 7.3 Fitness Function Evaluation 7.4 Updation 7.5 Stopping Criteria 8 Simulation Result and Discussion 9 Conclusion References Economic Load Dispatch Monitoring and Optimization for Emission Control Using Flower Pollination Algorithm: A Case Study 1 Introduction 2 Problem Formulation 2.1 Single Objective 2.2 Multi-objective Problems 2.3 Decision-Making 2.4 Constraints 3 Flower Pollination Description 4 Test Systems and Results 4.1 Case Study 1: Optimization of Fuel Cost with Valve-Point Loading Effect Considering Losses 4.2 Case Study 2: Fuel Cost Optimization with Prohibited Zone and Ramp Limits 4.3 Case Study 2: Optimization of Cost Function with Prohibited Zone and Ramp Limits 4.4 Case Study 4: Multi-objective Fuel Cost and Emission Optimization Without Losses 4.5 Case Study 4: Multi-objective Fuel Cost and Emission Optimization with Losses 5 Conclusion and Future Scope References Planning and Monitoring of EV Fast-Charging Stations Including DG in Distribution System Using Particle Swarm Optimization 1 Introduction 2 Recent Scenario and Motivation 3 Station Development 3.1 EV Station 3.2 DG Station 4 Defining Problem and Methodology 4.1 Without DGs 4.2 With DGs 4.3 System Parameters 5 Particle Swarm Optimization (PSO) 5.1 PSO Algorithm for EV FCS Allocation Optimization 5.2 PSO Algorithm for DG Size Optimization 6 Case Study 6.1 Assumption for Case Study 6.2 Electrical Distribution System 7 Results and Discussions 7.1 Case-1: With EV Station only 7.2 Case-2: EV Station with DGs 8 Conclusion References IoT-Based LPG Leakage Detection System with Prevention Compensation 1 Introduction 2 System Designing 2.1 Electronic Part of the System 2.2 Mechanical Part of the System 3 Functional Block Diagram of the Developed System 4 System Operation 5 Schematic Connections in the System 6 The Arduino IDE Sketch 7 Data Flow Diagram of the Proposed System 8 Tests and the Results 9 Future Scope of the Project References Short-Term Scheduling of Hydrothermal Based on Teaching–Learning Optimization 1 Introduction 2 Optimization Technique 3 Problem Description 3.1 Economic Dispatch 3.2 Emission Dispatch 4 Execution of the Proposed Method for STHTS 4.1 Formation of Individuals 4.2 Initialization Individuals 5 Thermal and Hydrocharacteristics 6 Results and Discussion 7 Conclusion References Simulation and Analysis of Rectifier-Based Four-Level Grid-Connected Inverter Using Genetic Algorithm 1 Introduction 2 Photovoltaic Cell and Its Mathematical Modeling 3 Proposed Scheme 3.1 Inverted Mode of Operation of the Single-Phase Bridge Rectifier 3.2 Proposed Model 3.3 Control Strategy and Mathematical Analysis of Four-Level Inverter 3.4 Modes of Operation 4 Simulation Result 5 Conclusion References Vector Control of Dual 3-ϕ Induction Machine-Based Flywheel Energy Storage System Using Fuzzy Logic Controllers 1 Introduction 2 Proposed System Description 2.1 Dual 3-ϕ IM or Asymmetrical 6-ϕ IM 2.2 Mathematical Modelling of Dual 3-ϕ IM 2.3 Fuzzy Logic-Based Vector Control Algorithm for IMs 3 Simulation Case Study 4 Conclusion References Hotspot Detection in Distribution Transformers Using Thermal Imaging and MATLAB 1 Introduction 2 Methodology 3 Algorithm and Implementation 4 Analysis and Result 5 Conclusion References An Innovative Fuzzy Modelling Technique for Photovoltaic Power Generation Farm’s Failure Modes and Effects Analysis 1 Introduction 2 Proposed Approach for PV Generation Farm’s FMEA 3 FMs in a Typical Solar Power Generation Farm 4 Fuzzy FMEA Model Formulation 5 Fuzzy Model Implementation 6 Conclusion Appendix References Analysis and Application of Nine-Level Boost Inverter for Distributed Solar PV System 1 Introduction 2 Nine-Level Boost Inverter Topology 3 Integrated Photovoltaic Distributed System 3.1 System Description 3.2 Control Strategy and PWM Generation 4 Simulation Results 5 Conclusions References Performance Evaluation of a 500 kWp Rooftop Grid-Interactive SPV System at Integral University, Lucknow: A Feasible Study Under Adverse Weather Condition 1 Introduction 2 Overview of the Rooftop Grid-Interactive SPV Plant 2.1 Geographical Description of the Site 2.2 Overall Plant Description 3 Methodology and Data Monitoring 4 Results and Discussions 4.1 Energy Generation at Different Temperature and Insolation 4.2 Simulation Using Solar GIS-PV Planner 4.3 Simulation Using PVSYST 5 Performance Comparison 6 Conclusion References Fuzzy Logic-Based Cycloconverter for Cement Mill Drives 1 Introduction 2 Three-Phase to Three-Phase Cycloconverter in Cement Mill Drives 3 Control Strategy of Three-Phase to Three-Phase Cycloconverter for Cement Mill Drives 4 Results and Discussions 5 Conclusion References Comparative Control Study of CSTR Using Different Methodologies: MRAC, IMC-PID, PSO-PID, and Hybrid BBO-FF-PID 1 Introduction 2 Model Reference Adaptive Control (MRAC) 2.1 MIT Rule 2.2 Lyapunov Rule 3 IMC-PID Controller 4 Particle Swarm Optimization (PSO) 5 Biogeography-Based Optimization (BBO) 6 Firefly Optimization (FFO) 7 Hybrid BBO-FF Algorithm 8 Continuously Stirred Tank Reactor (CSTR) 9 Simulation Results and Discussion 10 Conclusion References Performance Analysis of Nine-Level Packed E Cell Inverter for Different Carrier Wave PWM Techniques 1 Introduction 2 Packed E Cell Topology 3 Carrier Wave Used in Modulation Techniques 3.1 Triangular Carrier Wave-Pulse Width Modulation 3.2 Sinusoidal Carrier Wave-Pulse Width Modulation 3.3 Half Parabolic Carrier Wave-Pulse Width Modulation 4 Results and Discussion 5 Conclusions References PSO-Based Selective Harmonics Elimination Method for Improving THD in Three-Phase Multi-level Inverter 1 Introduction 2 Classification of Multi-level Inverter (MLI) 3 Proposed MLI Topology 4 Selective Harmonic Elimination 5 Simulation Results 6 Conclusion References Optimized Controller Design for Fast Steering Mirror-Based Laser Beam Steering Applications 1 Introduction 2 Dynamic Modeling of FSM 3 Optimized Controller Configuration Design 3.1 PID Controller 3.2 Genetic Algorithm (GA) 3.3 Particle Swarm Optimization (PSO) 4 Result and Discussion 5 Conclusion References Comparison of Metaheuristic and Conventional Algorithms for Maximum Power Point Tracking of Solar PV Array 1 Introduction 2 Partially Shaded Solar PV Array 3 Metaheuristic Algorithms for Maximum Power Point Tracking 4 Results 4.1 Shading Pattern I 4.2 Shading Pattern II 5 Conclusion References Artificial Neural Network-Based Maximum Power Point Tracking Method with the Improved Effectiveness of Standalone Photovoltaic System 1 Introduction 2 PV Module Modeling 3 Artificial Neural Network 4 Proposed MPPT Method 5 Simulation Results 6 Conclusion References Analysis on Various Optimization Technique Used for Load Frequency Control 1 Introduction 1.1 Aims of LFC 2 Control Strategies 2.1 Classical Control Techniques 2.2 Soft Computing Technique 3 Comparative Analysis of Different Control Systems 4 Conclusions References Optimal Design of Permanent Magnet Brushless DC (PMBLDC) Motor Using PSO Algorithm 1 Introduction 2 Problem Formulation 2.1 Electromagnetic Torque 2.2 EMF and Voltage 2.3 Constraint on Rotational Velocity 2.4 Cost of Materials 2.5 Power Loss 2.6 Defining Objective Function and Constraint 3 Design of PMBLDC Motor 3.1 Machine Properties 3.2 Stator Properties 3.3 Rotor Properties 4 Results and Discussion 4.1 Design Sheet 4.2 Different Plots 5 Conclusion References A Novel Lossless Image Cryptosystem for Binary Images Using Feed-Forward Back-Propagation Neural Networks 1 Introduction 2 Literature Survey and Analysis 3 Proposed Approach: Individual Pixel-Based Lossless Image Cryptosystem 3.1 Binary Image Encryption 3.2 Binary Image Decryption 3.3 Training the Neural Network 4 Results and Discussion 4.1 Binary Image Encryption 4.2 Binary Image Decryption 5 Conclusion References