Industrial Internet of Things: Technologies, Design, and Applications (Artificial Intelligence (AI): Elementary to Advanced Practices)

Cover
Half Title
Series Page
Title Page
Copyright Page
Table of Contents
Foreword
Editors
Contributors
Chapter 1: Introduction to Industrial Internet of Things (IIoT)
	1.1 Industrial Internet of Things
	1.2 IoT, IIoT and Industry 4.0
	1.3 IIoT Architectures and Frameworks
	1.4 Challenges of IIoT
	1.5 Conclusion
	References
Chapter 2: Challenges in Industrial Internet of Things (IIoT)
	2.1 Introduction
	2.2 Application of IIoT
		2.2.1 Manufacture Industry
			2.2.1.1 Sectors Where IIoT Has Been Adopted in the Manufacturing Industry
			2.2.1.2 Challenges for IIoT in Manufacturing
		2.2.2 Agriculture Industry
			2.2.2.1 Sectors That Implement IIoT in Agriculture Industry
			2.2.2.2 Challenges for IIoT in the Agriculture Industry
		2.2.3 IIoT in Connected Logistics, Transportation, and Warehousing
			2.2.3.1 Sectors That Implement IIoT in Connected Logistics and Transportation
			2.2.3.2 Challenges of IIoT in Logistics and Transportation
		2.2.4 IIoT in Healthcare
			2.2.4.1 Sectors That Implement IIoT in Healthcare
			2.2.4.2 Challenges of IIoT in Healthcare
	2.3 Challenges Based on IIoT Components
		2.3.1 Challenges in Devices
		2.3.2 Challenges in Network
		2.3.3 Challenges in Data
	2.4 Future Technology and Its Challenges
		2.4.1 5G-based IIoT
		2.4.2 Blockchain-Based IIoT
	2.5 Conclusion
	Bibliography
Chapter 3: IoT-Based Automated Healthcare System
	3.1 Introduction
		3.1.1 Software-Defined Network
		3.1.2 Network Function Virtualization
		3.1.3 Sensor Used in IoT Devices
	3.2 SDN-Based IoT Framework
	3.3 Literature Survey
	3.4 Architecture of SDN-based IoT for Healthcare System
	3.5 Challenges
	3.6 Conclusion
	References
Chapter 4: Internet of Things (IoT)-Based Industrial Monitoring System
	4.1 Introduction
		4.1.1 Background
		4.1.2 Project Organization
	4.2 Literature Review
		4.2.1 “IoT” and Its Smart Applications
		4.2.2 Health Monitoring and Management Using Internet-of-Things (IoT) Sensing with Cloud-based Processing: Opportunities and Challenges
		4.2.3 IoT (Internet of Things)-Based Monitoring and Control System for Home Automation
		4.2.4 Industrial Automation Using IoT
	4.3 Hardware and Software
		4.3.1 Hardware
			4.3.1.1 NODEMCU
			4.3.1.2 ESP8266
			4.3.1.3 Gas Sensor
			4.3.1.4 DHT11
			4.3.1.5 PIR Sensor
			4.3.1.6 Breadboard
			4.3.1.7 Power Board
			4.3.1.8 MCP3008
			4.3.1.9 Buzzer
		4.3.2 Software
			4.3.2.1 Web Server
			4.3.2.2 Arduino Studio
	4.4 Experimental Studies and Results
		4.4.1 Sensor Analysis
			4.4.1.1 Thinger.io Overview
		4.4.2 DHT11 Sensor Analysis
		4.4.3 MQ-2 Gas Sensor Analysis
		4.4.4 PIR Sensor Analysis
		4.4.5 Block Diagram of this System
		4.4.6 Sensor Recognition Process
		4.4.7 Real Life Implementation
	4.5 Conclusion
		4.5.1 Future Work
		4.5.2 Discussion
	References
Chapter 5: Internet Working of Vehicles and Relevant Issues in IoT Environment
	5.1 Introduction
	5.2 VANETs Architecture
	5.3 Communication Architecture
		5.3.1 In-vehicle Communication
		5.3.2 Vehicle to Vehicle Communication (V2V)
		5.3.3 Vehicle to Roadside Infrastructure (V2I) Communication
		5.3.4 Vehicle to Broad Cloud (V2B) Communication
	5.4 VANETs Applications
		5.4.1 Traffic Signal
		5.4.2 Weather and Other Hard Conditions
		5.4.3 Vision Enhancement
		5.4.4 Assistance to the Driver
		5.4.5 Automatic Parking
		5.4.6 Information On Roadside Locations
		5.4.7 Entertainment
		5.4.8 Safety
	5.5 DSRC Channels Access
	5.6 A Case Study of Accident Detection on Road
	5.7 Introduction to Clustering
		5.7.1 Data Aggregation
		5.7.2 Data Aggregation and Fusion Schemes in VANETs
	5.8 Requirements of Security in VANETs
	5.9 Menace to Availability
	5.10 Menace to Authenticity [ 22, 23 ]
	5.11 Issues in VANET
		5.11.1 Security
		5.11.2 Overheads Reduction
		5.11.3 Power Consumption
		5.11.4 Computational Time
	5.12 Conclusion
	References
Chapter 6: Adoption of Industry 4.0 in Lean Manufacturing
	6.1 Introduction
	6.2 Related Work
	6.3 Cyber-Physical Systems (CPS)
	6.4 Importance of CPS Applications
	6.5 Smart and Connected Products
	6.6 Applications of Smart and Connected Products
	6.7 Industry 4.0
	6.8 Identification, Sensing and Communication
	6.9 RFID and Networks
	6.10 Middleware
	6.11 Applications
	6.12 Lean Manufacturing
	6.13 Principles of Lean Manufacturing
	6.14 Definition of Values
	6.15 Mapping of Value System
	6.16 Flow Establishment, Pull System and Origin of the Toyota Production System
	6.17 Lean Learning Industries
	6.18 Challenges of Lean Manufacturing
	6.19 Conclusion
	References
Chapter 7: Internet of Things-Based Economical Smart Home Automation System
	7.1 Introduction
	7.2 Pros of Home Automation Systems (HAS)
	7.3 Existing System
	7.4 Research Gaps
	7.5 Proposed System
	7.6 Methodology
		7.6.1 Framework
		7.6.2 Component Requirement Analysis
			7.6.2.1 Hardware Requirements
			7.6.2.2 Software Requirements
	7.7 Implementation
	7.8 Functional Requirements
	7.9 Results and Discussion
	7.10 Conclusion
	References
Chapter 8: Machine Vision Technology, Deep Learning, and IoT in Agricultural Industry
	8.1 Introduction to Smart Farming
		8.1.1 Crop Management
		8.1.2 Field Condition Management
		8.1.3 Livestock Management
		8.1.4 Pest Management
		8.1.5 Weather Forecasting
	8.2 Machine Vision Technology
		8.2.1 Components of Machine Vision
		8.2.2 Machine Vision in Agriculture
	8.3 Deep Learning and Its Techniques
		8.3.1 Feed-Forward Neural Network and Back Propagation (BP)
		8.3.2 Convolutional Neural Networks (CNN/ConvNet)
		8.3.3 Recurrent Neural Networks (RNN)
		8.3.4 Generative Adversarial Networks (GAN)
	8.4 Advantages of Combining Machine Vision and Deep Learning
	8.5 IoT Solutions to Agricultural Problems
		8.5.1 Advantages of IoT in Smart Farming
		8.5.2 IoT Use Cases in Smart Farming
			8.5.2.1 Climate Conditions Monitoring
			8.5.2.2 Automation of Greenhouse
			8.5.2.3 Management of Crops
			8.5.2.4 Cattle Monitoring and Management
			8.5.2.5 Precision Farming
			8.5.2.6 Agricultural Drones
			8.5.2.7 Predictive Analytics for Smart Farming
		8.5.3 Challenges in IoT Based Smart Farming
			8.5.3.1 Sensor Selection
			8.5.3.2 Appropriate Data Analytical Tools
			8.5.3.3 Maintenance of IoT Setup
			8.5.3.4 Connectivity
			8.5.3.5 Data Security
			8.5.3.6 Data Collection Frequency
	8.6 Agrobots – Agricultural Robots
		8.6.1 Agrobots Working in Fields for Different Agricultural Activities
		8.6.2 Harvesting Robots
		8.6.3 Challenges in Implementing Agrobots
		8.6.4 Conclusion and Future Work
	References
Chapter 9: IIoT Edge Network and Spectrum Scarcity Issue
	9.1 Introduction
		9.1.1 IoT and IIoT
	9.2 IIoT Edge and Edge Devices
	9.3 Computing Strategies for IIoT
		9.3.1 Cloud Computing
	9.4 Edge Computing
	9.5 Fog Computing and Hybrid Techniques
	9.6 Connectivity on IIoT
	9.7 CR for Future IIoT
		9.7.1 Spectrum Scarcity Problem in IIoT and Cognitive-IIoT
		9.7.2 Cognitive LPWAN for IIoT
	9.8 Conclusion
	References
Chapter 10: Review on Optical Character Recognition-Based Applications of Industrial IoT
	10.1 Introduction
	10.2 Literature Review
	10.3 Conclusion
	References
Chapter 11: Using Blockchain in Resolving the Challenges Faced by IIoT
	11.1 Introduction
	11.2 What is a Blockchain? Structure and Concepts
	11.3 Smart Contracts
	11.4 Consensus Algorithm
	11.5 Internet of Things (IoT) and Its Technologies
	11.6 Trust and Information Security in IoT
	11.7 Blockchain and IoT
	11.8 Industrial IoT (IIoT) and Emergence of Industry 4.0
	11.9 Technological Advancements Related to Industry 4.0
	11.10 Use Cases of IIoT
	11.11 IIoT Architecture and Scenario
	11.12 Aims and Limitations of IIoT
	11.13 Challenges Faced by IIoT and How Blockchain Helps in Resolving These Challenges
	11.14 Blockchain in Resolving the Challenges Faced by IIoT
	11.15 Conclusion
	References
Chapter 12: Internet of Things-Based Arduino Controlled On-Load Tap Changer Distribution Transformer
	12.1 Introduction
	12.2 Review of Literature
	12.3 Block Diagram
	12.4 Design Solutions
	12.5 Working
	12.6 Conclusion
	12.7 Future Scope
	References
Index