A 360-degree View of Iot Technologies (Integrated Microsystems)

A 360-Degree View of IoT Technologies
	Contents
	Preface
	Chapter 1 Introduction to the Internet of Things
		1.1 Defining IoT
		1.2 Why IoT Now?
			1.2.1 Technology Acceleration
			1.2.2 People Connect to Things
			1.2.3 Things Connect to Things
			1.2.4 Climate Change
			1.2.5 The Rise of the Fourth Industrial Revolution (Industry 4.0)
		1.3 IoT Versus Related Technologies
			1.3.1 Ubiquitous Sensor Networks (USN)
			1.3.2 Machine-to-Machine (M2M) Communications
			1.3.3 Internet of Everything (IoE)
			1.3.4 Cloud of Things (CoT)
			1.3.5 Web of Things (WoT)
			1.3.6 Cyber-Physical Systems (CPS)
		1.4 IoT Technologies and Applications
			1.4.1 IoT Technologies
			1.4.2 IoT Applications
		1.5 Reference Models and Architectures for IoT Systems
			1.5.1 Industrial Internet Consortium Reference Architecture (IIRA)
			1.5.2 OpenFog Reference Architecture
			1.5.3 IoT Reference Architecture Model
			1.5.4 ISO/IEC CD 30141 Internet of Things Reference Architecture (IoT RA)
		1.6 The Different Layers and Viewpoints of IoT Systems
			1.6.1 Layers of IoT Systems
			1.6.2 IoT System Perspectives
		1.7 Evolution of IoT Systems
		1.8 Getting Started with IoT Devices: Sensors and Actuators
			1.8.1 Introduction to Sensors and Actuators
			1.8.2 Sensor Selection Criteria
			1.8.3 Simple IoT Devices: Arduino Boards and Raspberry Pi
		1.9 Summary
		References
	Chapter 2
Wireless Sensor Networks
		2.1 Introduction to WSN
		2.2 WSN Applications
		2.3 WSN Characteristics and Design Challenges
		2.4 WSN Layers
			2.4.1 Overview
			2.4.2 The Data Link Layer
			2.4.3 The Network Layer
			2.4.4 The Application Layer
			2.4.5 Cross-Layer Functionalities
		2.5 WSN Middleware
			2.5.1 Middleware Functionalities
			2.5.2 Types of WSN Middleware Platforms
		2.6 WSN Standards
			2.6.1 IEEE 802.15.4
			2.6.2 International Society of Automation (ISA) 100 Committee Standards
			2.6.3 WirelessHART
			2.6.4 ZigBee
		2.7 Future Trends in WSN
		2.8 Summary
		References
	Chapter 3 Radio Frequency Identification
		3.1 The Basics of RFID Technology
			3.1.1 RFID as a Forerunner of IoT
			3.1.2 Operation and Components of an RFID System
			3.1.3 RFID Numbers: The EPC
		3.2 RFID Benefits, Opportunities, and Risks
			3.2.1 RFID Versus Barcodes
			3.2.2 The Importance of Serialization
			3.2.3 Benefits of RFID Applications
			3.2.4 From RFID Retail Deployments to Amazon GO
			3.2.5 RFID in the Current Industrial IoT Era
			3.2.6 RFID Privacy Challenges
		3.3 RFID Middleware
			3.3.1 Drivers and Motivation
			3.3.2 RFID Middleware Functionalities
			3.3.3 RFID Middleware Architectures
		3.4 The EPC Architecture Framework
			3.4.1 Introduction
			3.4.2 EPC RFID Reader
			3.4.3 EPC RFID Middleware
			3.4.4 EPCIS: Sharing EPC Information
			3.4.5 EPCIS: A Warehouse Management Example
			3.4.6 Security and Privacy Challenges of the EPCglobal Network
		3.5 Summary
		References
	Chapter 4
IoT in the Cloud
		4.1 Introducing Cloud Computing
			4.1.1 Cloud Computing Properties
			4.1.2 Cloud Computing Stakeholders
			4.1.3 Cost Models and Business Drivers
			4.1.4 Cloud Delivery Models
			4.1.5 Examples of IaaS and PaaS Clouds
		4.2 IoT and Cloud Convergence
			4.2.1 IoT and Cloud Integration: The Motivation
			4.2.2 History of IoT and Cloud Convergence
			4.2.3 IoT and Cloud Platform Characteristics
			4.2.4 Delivery Models for IoT Services in the Cloud
			4.2.5 IoT and Everything as a Service
		4.3 Edge Computing
			4.3.1 Limitations and Problems for IoT-Cloud Integration
			4.3.2 The Edge Computing Distributed Paradigm
			4.3.3 Fog Computing Versus Edge Computing
			4.3.4 Edge Computing Applications
			4.3.5 Multi-Access Edge Computing (MEC)
			4.3.6 Public Cloud Infrastructures for IoT
		4.4 Summary
		References
	Chapter 5
IoT Analytics
		5.1 Analyzing IoT Data
			5.1.1 IoT Analytics: The Business Drivers
			5.1.2 Properties of IoT Data
			5.1.3 The IoT Data Life Cycle
			5.1.4 The Vs of Big Data and IoT Data
			5.1.5 Properties of IoT Analytics
		5.2 Understanding Streaming Data
			5.2.1 Streaming Data Nature and Challenges
			5.2.2 Streaming Queries
			5.2.3 Distributed Streaming Systems
			5.2.4 Streaming Systems and IoT Data Processing Architectures
			5.2.5 Evolution of Stream Processing Platforms and Technologies for IoT
		5.3 Popular Big Data Management and Distributed Streaming Platforms
			5.3.1 Big Data Storage and Management: The Hadoop Distributed File System (HDFS)
			5.3.2 Apache Kafka
			5.3.3 Apache Spark
			5.3.4 Apache Storm
			5.3.5 Apache Flink
		5.4 Summary
		References
	Chapter 6 Mining IoT Data
		6.1 IoT Data-Mining Activities
			6.1.1 Overview
			6.1.2 Standardized Data-Mining Processes
			6.1.3 A Closer Look at CRISP-DM
			6.1.4 IoT Data-Mining Challenges
		6.2 Data Mining and Machine Learning
			6.2.1 Definitions and Common Data-Mining Tasks
			6.2.2 Classification of Machine Learning Techniques
		6.3 Popular Machine Learning Models and Techniques
			6.3.1 Decision Trees
			6.3.2 Least Squares Regression (LSR)
			6.3.3 Naïve Bayes Classification
			6.3.4 Logistic Regression
			6.3.5 Support Vector Machines (SVN)
			6.3.6 Ensemble Methods
			6.3.7 Clustering
			6.3.8 vPrincipal Component Analysis (PCA)
			6.3.9 Independent Component Analysis (ICA)
		6.4 Models Evaluation
			6.4.1 Overview
			6.4.2 Classification Techniques Evaluation
			6.4.3 Classifier Error Rate
		6.5 Data-Mining Models for IoT
			6.5.1 Overview of IoT Data-Mining Models
			6.5.2 The Multilayer Data-Mining Model
		6.6 Summary
		References
	Chapter 7
IoT Security and Privacy
		7.1 Understanding IoT Security
			7.1.1 The IoT Security Jargon
			7.1.2 Security Drivers for Modern IoT Systems
			7.1.3 Notorious IoT Security Attacks
			7.1.4 Technical Challenges of IoT Security
		7.2 IoT Security Risk Assessment
			7.2.1 Overview of the Risk Assessment Process
			7.2.2 Risk Management Standards
			7.2.3 Peculiarities of IoT Security Risk Assessment
		7.3 IoT Security Solutions
			7.3.1 IoT Security Architectures
			7.3.2 Firmware Over The Air (FOTA) Mechanisms
			7.3.3 Network-Level IoT Security
			7.3.4 Multilevel Security for IoT and CPS
			7.3.5 IoT Security Systems Monitoring and Threat Intelligence
			7.3.6 OWASP IoT Privacy Recommendations
			7.3.7 SKBs
			7.3.8 Supply Chain Security
			7.3.9 Decentralized Secure Data Sharing for Security in IoT Value Chains
			7.3.10 Machine Learning and AI Solutions for Data-Driven IoT Security
			7.3.11 Identify and Access Management (IAM)
			7.3.12 Data Encryption and Decryption Solutions
		7.4 Summary
		References
	Chapter 8
IoT Standards and Ecosystems
		8.1 IoT Standards
			8.1.1 The Wealth of IoT Standards
			8.1.2 3GPP LTE Standards for IoT Networking and Connectivity
			8.1.3 LPWAN Standards
			8.1.4 IETF Constrained Application Protocol (CoAP)
			8.1.5 oneM2M
			8.1.6 IETF 6LoWPAN
			8.1.7 HyperCat
			8.1.8 Open Geospatial Consortium (OGC) Standards
			8.1.9 Standards-Based IoT Architectures
		8.2 IoT Ecosystems
			8.2.1 Introduction to IoT Ecosystems
			8.2.2 Data-Centric IoT Products
			8.2.3 Vendors’ Ecosystems
		8.3 Summary
		References
	Chapter 9 Emerging IoT Technologies
		9.1 5G Networking
			9.1.1 5G for IoT: The Motivation
			9.1.2 Introducing 5G
			9.1.3 5G Network Functions Virtualization (NFV) for IoT Systems
			9.1.4 Deploying 5G for IoT
			9.1.5 5G Deployment Roadmap
		9.2 Blockchain Technology
			9.2.1 Introducing Bitcoin and Blockchain Technology
			9.2.2 Ethereum and Smart Contracts
			9.2.3 Uses of Blockchain Technology
			9.2.4 Blockchain Technology and Internet of Things
		9.3 AI Trends for IoT
			9.3.1 Overview
			9.3.2 XAI
			9.3.3 AI Security for IoT Systems
			9.3.4 Automated Machine Learning and AI
		9.4 Summary
		References
	Chapter 10
IoT Applications
		10.1 Smart Cities
			10.1.1 Smart City Definitions
			10.1.2 Smart City Drivers
			10.1.3 IoT for Smart Cities
			10.1.4 IoT Standards and Vertical Applications for Smart Cities
			10.1.5 Maturity Model for IoT in Smart Cities
			10.1.6 IoT Applications’ Interoperability in Smart Cities
			10.1.7 IoT in Smart Cities and Open Data
			10.1.8 Trends in IoT for Smart Cities
		10.2 Wearables
			10.2.1 Introducing Wearables
			10.2.2 IoT Wearables
			10.2.3 Examples of IoT Wearable Devices and Ecosystems
			10.2.4 IoT Wearable Trends
		10.3 IoT in Smart Manufacturing: Industrial IoT (IIoT)
			10.3.1 Introduction to IIoT and Industry 4.0
			10.3.2 Popular IIoT Use Cases
		10.4 IoT in Healthcare
			10.4.1 Overview
			10.4.2 Popular Healthcare Use Cases
		10.5 Connected Vehicles
			10.5.1 Introduction
			10.5.2 Developing Connected Vehicle Applications
			10.5.3 Indicative Applications
		10.6 Summary
		References
	About the Author
	Index