دانلود کتاب Internet of Things and Data Mining for Modern Engineering and Healthcare Applications (Chapman & Hall/CRC Internet of Things)

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Cover Half Title Series Page Title Page Copyright Page Table of Contents Preface Editor biographies Contributors Chapter 1 The Role of IoT in Healthcare Services: An Extensive Review 1.1 Introduction 1.2 The Origin and Development of IoT in Healthcare 1.3 IoT in Healthcare 1.4 Enabling Identification Technology of IoT 1.5 Location and Communication Technologies 1.5.1 Location Technologies 1.5.2 Short- (Near-) Distance Communication Technologies 1.6 Sensor Technology 1.7 Service-Oriented Architecture 1.8 Healthcare Systems and Devices 1.9 Smart Healthcare System 1.10 Advanced Medical Equipment 1.10.1 Withings Equipment 1.10.2 Other Usable Devices 1.11 Application of Methodologies and Strategies 1.11.1 Resource Management 1.11.2 Tracking 1.11.3 Sensing 1.11.4 Authentication and Identification 1.11.5 Data Management 1.11.6 Management of Big Information 1.12 Methods for Building and Designing Telerehabilitation and Telehealth Subsystem 1.13 Challenges/Shortcomings of IoT Applicability in Healthcare 1.14 Conclusion and Future Development Abbreviations References Chapter 2 Smart Healthcare and IoT Technologies: Academic and Service Provider Review 2.1 Introduction 2.2 Methodology 2.2.1 Web of Science – Analytics 2.2.2 Academic Background 2.3 Cases 2.3.1 Case 1: Watson Health 2.3.2 Case 2: Verily 2.3.3 Case 3: Intel Healthcare and Life Sciences 2.3.4 Case 4: Lumiata 2.4 Discussion 2.5 Conclusion References Chapter 3 Recognizing Human Activities of Daily Living Using Mobile Sensors for Health monitoring 3.1 Introduction 3.2 Literature Analysis 3.3 Proposed Model 3.4 Experimental Results and Analysis 3.4.1 Dataset Description 3.4.2 Evaluation Metrices 3.4.3 Results 3.4.4 Loss Plots 3.4.5 Comparison with Existing Models 3.5 Conclusion References Chapter 4 Internet of Things with Machine Learning-Based Smart Cardiovascular Disease Classifier for Healthcare in Secure Platform 4.1 Introduction 4.1.1 Introduction to Cardiovascular Disease 4.1.2 Introduction to Machine Learning Method for Cardiovascular Disease Classification 4.1.3 Introduction to Internet of Things in Healthcare 4.1.4 Introduction of Blockchain 4.1.5 Structure of the Blockchain Technology 4.1.6 Taxonomy of Blockchain 4.1.7 Blockchain Elements 4.2 Literature Survey 4.3 Proposed Work 4.3.1 Flowchart of the Proposed Work 4.3.2 Dataset Collection 4.3.3 Data Description 4.3.4 Filtering 4.3.5 Artefact Removal 4.3.6 Feature Extraction and Selection 4.3.7 Classification 4.3.8 Applications and Highlights of the Proposed System 4.4 Conclusion and Future Work References Chapter 5 IoT-Centered Household Security and Person’s Healthcare System Predominantly Aimed at Epidemic Circumstances 5.1 Introduction: Background and Driving Forces 5.2 Proposed System Setup for Home Automation and Health Security System 5.3 Technical Details of Devices and Connections 5.4 IoT Gadgets for Home Security 5.5 Brain of the Setup 5.5.1 Arduino Microcontroller 5.5.2 Node MCU ESP8266 5.6 Outdoor Health Safety Aspects and Security Monitoring 5.6.1 Health Parameter Measurement Sensors 5.6.1.1 Body Temperature Sensor [MAX30205] 5.6.1.2 MAX30100 Sensor 5.6.2 Flex Sensor 5.6.3 OV7670 Camera Module for Face Authentication 5.6.4 Intuitive Hand Disinfectant Machine 5.7 Indoor Health Safety Aspects and Household Monitoring 5.7.1 Gas Sensor (MQ-X) 5.7.2 MQ2 Sensor 5.7.2.1 Google Firebase and Flutter 5.7.2.2 Application Setup 5.7.3 Optical Smoke Detectors 5.7.4 Piezoelectric Sensor 5.7.5 Temperature Sensors for Room Temperature Monitoring 5.8 Featuring Role of IoT and AI – Machine Learning 5.8.1 Logistic Regression Algorithm 5.8.2 Steps Followed in Logistic Regression Algorithm 5.9 Discussions and Pros and Cons of Our Work 5.10 Conclusion References Chapter 6 Artificial Intelligence-Based Categorization of Healthcare Text 6.1 Introduction 6.2 Text Classification 6.2.1 Text Classification Framework 6.3 Text Processing Techniques 6.3.1 Data Correction 6.3.2 Preprocessing Text Data 6.3.2.1 Tokenization 6.3.2.2 Lowercase Conversion 6.3.2.3 Stop Word Removal 6.3.2.4 Stemming 6.3.2.5 Lemmatizing 6.3.3 Feature Extraction 6.3.3.1 Bag-of-Words Approach 6.3.3.2 Word Embeddings 6.3.4 Feature Selection Methods 6.3.4.1 Chi-Square 6.3.4.2 Correlation Coefficient 6.3.4.3 Information Gain 6.3.5 N-Gram-Based Language Models 6.3.6 Sampling Methods 6.3.6.1 N-Fold Cross-Validation 6.3.7 Statistical Tests 6.3.7.1 T-Test 6.3.7.2 Kappa Coefficient 6.3.8 Document Similarity 6.3.8.1 Cosine Similarity 6.3.8.2 Okapi BM25 6.4 Classification Algorithms 6.4.1 Machine Learning-Based Classifiers 6.4.1.1 Supervised Machine Learning-Based Classifiers 6.4.1.2 Unsupervised Machine Learning Classifiers 6.4.1.3 Semi-supervised Learning 6.4.1.4 Ensemble Learning-Based Classifiers 6.4.2 Deep Learning-Based Classifiers 6.4.2.1 Deep Neural Networks 6.4.2.2 Convolutional Neural Network 6.4.2.3 Recurrent Neural Network 6.4.3 Pre-trained Language Models 6.4.3.1 Embeddings from Language Models 6.4.3.2 Efficiently Learning an Encoder that Classifies Token Replacements Accurately 6.4.3.3 Bidirectional Encoder Representations from Transformers 6.5 Evaluation Metrics 6.5.1 Accuracy 6.5.2 Precision 6.5.3 Recall 6.5.4 F-Measure 6.5.4.1 Receiving Operational Characteristics 6.5.4.2 Area Under ROC Curve 6.6 Conclusion Reference list Chapter 7 Multilayer Perceptron Mode and IoT to Assess the Economic Impact and Human Health in Rural Areas – Alcoholism 7.1 Introduction 7.2 Data Analysis of Health Impact 7.3 Determination of Irregularities 7.4 Vital Role of IoT Systems in Identification of Alcohol Relevant Health Irregularities and Management 7.5 Alcohol Addiction and Use of IoT 7.6 Multilayered Perceptron (MLP) for the Prevalence of Alcoholism 7.7 Conclusion References Chapter 8 Downlink Fronthaul Connectivity for IoT Devices in Rural Areas with Scheduling Approach 8.1 Introduction 8.1.1 Related Works 8.1.2 Contribution 8.1.3 Organization of the Chapter 8.2 System Model 8.2.1 Downlink Signal Transmission 8.2.2 Success Probability 8.2.3 Data Rate 8.2.4 Area Spectral Efficiency 8.2.5 Scheduling and Delay 8.2.5.1 Random Scheduling 8.2.5.2 First-In First-Out Scheduling 8.2.5.3 Round-Robin Scheduling 8.2.6 Delay Success Probability 8.3 Results and Discussions 8.4 Conclusion References Chapter 9 IoT-Enabled Customizable System for Traffic Management with Real-Time Vehicle Emission Measurement Functionality 9.1 Introduction 9.2 Proposed System 9.2.1 Overview of the Proposed System 9.2.2 Aim of the Proposed System 9.2.3 Block Diagram of the Prototype 9.2.4 Proposed System Architecture 9.2.5 Working Principle of the Proposed System (Figure 9.4)​ 9.3 Components and Techniques Used to Design the Proposed System 9.3.1 Prototype Development of the System 9.3.1.1 Real-Time Clock Module 9.3.1.2 Infrared Sensor Module 9.3.1.3 Liquid Crystal Display Module 9.3.1.4 Rack and Pinion Mechanism 9.3.1.5 Gas Sensor 9.3.1.6 Microcontroller Unit 9.3.1.7 NodeMCU 9.3.1.8 Programming Tools/Software 9.4 Prototype Designing Steps 9.5 Results and Discussions 9.6 Conclusion References Chapter 10 Development of Fuel Cell-Based Energy Systems for 3-ph Power Development and Internet of Things Devices 10.1 Introduction 10.2 Presented Work 10.3 Acquaintance with Fuel Cells 10.3.1 Unit Cell 10.3.2 Fuel Cell Stacking 10.3.3 Balance of Plant 10.3.3.1 Fuel Source Constants 10.4 Pyrolysis 10.4.1 Stage 1 10.4.2 Stage 2 10.5 Three-Pphase Full Bridge 10.6 Conclusion References Chapter 11 Fuzzy Logic-Based IoT Technique for Direct Torque Control of Induction Motor Drive 11.1 Introduction 11.2 Basic DTC Principle 11.2.1 Three-Phase Voltage Source Inverter 11.2.2 Direct Flux Control 11.2.3 Direct Torque Control 11.2.4 Selection of Switching Table 11.3 Principle of Fuzzy Direct Torque Control 11.4 Simulated Output and Discussions 11.5 Conclusion References Chapter 12 Body Wearable Antennas and Integration of Internet of Things in Vehicular Wireless Communication Systems 12.1 Introduction 12.2 Antenna Design Methodology 12.3 Results and Discussion 12.4 Parametric Analysis 12.4.1 Variation in the Widths of Two Arms of the Fork (D1 and D2) 12.4.2 Effect of Using Varied Types of Substrates 12.4.3 Effect of the Thickness of the Substrate Material 12.4.4 Variation of the Length of the Dual Arms of the Fork 12.4.5 Variation of Width of the Base Connecting the Two Arms of the Fork 12.4.6 Variation of Distance of the Patch from the Ground Plane 12.5 Fabrication and Measurement 12.5.1 Test of Wearable Antenna at Several Positions of Human Body 12.5.2 Test of Wearable Antenna for Crumpling Conditions 12.5.3 Test of Wearable Antenna for Bending Conditions 12.6 Conclusion References Chapter 13 A Review on Wearable Antenna Design for IoT and 5G Applications 13.1 Introduction 13.2 Types of Wearable Antenna 13.2.1 Microstrip Patch Antenna 13.2.2 Monopole Antenna 13.2.3 Printed Dipole Antenna 13.2.4 Printed Loop Antenna 13.2.5 PIFA 13.3 Material Used in Wearable Antenna 13.3.1 Conductive Material 13.3.2 Substrate 13.4 Selection Criteria of Substrate for Wearable Antenna 13.4.1 Thickness of Substrate 13.5 Design Procedure 13.6 Design of Wearable Antenna (for IoT Application) 13.6.1 Design 1 13.6.2 Design 2 13.6.3 Design 3 13.6.4 Design 4 13.6.5 Design 5 13.6.6 Design 6 13.7 Design of Wearable Antenna (for 5G Applications) 13.7.1 Design 1 13.7.2 Design 2 13.7.3 Design 3 13.7.4 Design 4 13.8 Wearable Antenna Fabrication Method 13.9 Wearable Antenna Measurement 13.10 Antenna-Based IoT Applications 13.11 Conclusion References Chapter 14 Investigation of Interface Trap Charges and Temperature on RF Performance with Noise Analysis for IoT Application of a Heterojunction Tunnel FET 14.1 Introduction 14.2 Device Architecture and Simulation Strategy 14.3 Basic Operation Mechanism of TFET 14.4 Results and Discussion 14.4.1 Impact of Interface Trap Charge 14.4.2 Impact of Temperature Sensitivity 14.4.3 RF/Analogue Behaviour Characterization 14.4.4 Impact of Electrical Noise 14.5 Future Scope 14.6 Summary References Chapter 15 Application and Utilization of High-Aspect-Ratio Anti-reflective Si Nanostructure-Embedded Optical Sensor for IoT Applications 15.1 Introduction 15.2 Simulation and Optimization 15.3 Simulation Setup 15.4 Results and Analysis 15.5 Reflectance Profile 15.6 Optical Response in Higher Angle of Incidence 15.7 Conclusion References Chapter 16 RF and Microwave Energy Harvesting Antennas for Self-Sustainable IoT 16.1 Introduction 16.2 Design of RF Energy Harvest System 16.2.1 Antenna Design Requirements 16.2.2 RF to DC Conversion Module 16.2.3 Matching Network 16.3 Different Antennas Used for RF Energy Harvesting 16.3.1 Antenna 16.3.2 Antenna 16.3.3 Antenna 16.4 Conclusion References Chapter 17 An Extremely Compact and Low-Cost Antenna Sensor Designed for IoT-Integrated Biomedical Applications 17.1 Introduction 17.2 Method of Analysis and Design Procedure of the Bio-sensor antenna 17.3 Results and Discussion 17.4 Conclusion References Index