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

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