A Roadmap for Enabling Industry 4.0 by Artificial Intelligence

Cover
Title Page
Copyright Page
Contents
Preface
Chapter 1 Artificial Intelligence—The Driving Force of Industry 4.0
1.1 Introduction
1.2 Methodology
1.3 Scope of AI in Global Economy and Industry 4.0
1.3.1 Artificial Intelligence—Evolution and Implications
1.3.2 Artificial Intelligence and Industry 4.0—Investments and Returns on Economy
1.3.3 The Driving Forces for Industry 4.0
1.4 Artificial Intelligence—Manufacturing Sector
1.4.1 AI Diversity—Applications to Manufacturing Sector
1.4.2 Future Roadmap of AI—Prospects to Manufacturing Sector in Industry 4.0
1.5 Conclusion
References
Chapter 2 Industry 4.0, Intelligent Manufacturing, Internet of Things, Cloud Computing: An Overview
2.1 Introduction
2.2 Industrial Transformation/Value Chain Transformation
2.2.1 First Scenario: Reducing Waste and Increasing Productivity Using IIoT
2.2.2 Second Scenario: Selling Outcome (User Demand)–Based Services Using IIoT
2.3 IIoT Reference Architecture
2.4 IIoT Technical Concepts
2.5 IIoT and Cloud Computing
2.6 IIoT and Security
References
Chapter 3 Artificial Intelligence of Things (AIoT) and Industry 4.0–Based Supply Chain (FMCG Industry)
3.1 Introduction
3.2 Concepts
3.2.1 Internet of Things
3.2.2 The Industrial Internet of Things (IIoT)
3.2.3 Artificial Intelligence of Things (AIoT)
3.3 AIoT-Based Supply Chain
3.4 Conclusion
References
Chapter 4 Application of Artificial Intelligence in Forecasting the Demand for Supply Chains Considering Industry 4.0
4.1 Introduction
4.2 Literature Review
4.2.1 Summary of the First Three Industrial Revolutions
4.2.2 Emergence of Industry 4.0
4.2.3 Some of the Challenges of Industry 4.0
4.3 Application of Artificial Intelligence in Supply Chain Demand Forecasting
4.4 Proposed Approach
4.4.1 Mathematical Model
4.4.2 Advantages of the Proposed Model
4.5 Discussion and Conclusion
References
Chapter 5 Integrating IoT and Deep Learning—The Driving Force of Industry 4.0
5.1 Motivation and Background
5.2 Bringing Intelligence Into IoT Devices
5.3 The Foundation of CR-IoT Network
5.3.1 Various AI Technique in CR-IoT Network
5.3.2 Artificial Neural Network (ANN)
5.3.3 Metaheuristic Technique
5.3.4 Rule-Based System
5.3.5 Ontology-Based System
5.3.6 Probabilistic Models
5.4 The Principles of Deep Learning and Its Implementation in CR-IoT Network
5.5 Realization of CR-IoT Network in Daily Life Examples
5.6 AI-Enabled Agriculture and Smart Irrigation System—Case Study
5.7 Conclusion
References
Chapter 6 A Systematic Review on Blockchain Security Technology and Big Data Employed in Cloud Environment
6.1 Introduction
6.2 Overview of Blockchain
6.3 Components of Blockchain
6.3.1 Data Block
6.3.2 Smart Contracts
6.3.3 Consensus Algorithms
6.4 Safety Issues in Blockchain Technology
6.5 Usage of Big Data Framework in Dynamic Supply Chain System
6.6 Machine Learning and Big Data
6.6.1 Overview of Shallow Models
6.6.1.1 Support Vector Machine (SVM)
6.6.1.2 Artificial Neural Network (ANN)
6.6.1.3 K-Nearest Neighbor (KNN)
6.6.1.4 Clustering
6.6.1.5 Decision Tree
6.7 Advantages of Using Big Data for Supply Chain and Blockchain Systems
6.7.1 Replenishment Planning
6.7.2 Optimizing Orders
6.7.3 Arranging and Organizing
6.7.4 Enhanced Demand Structuring
6.7.5 Real-Time Management of the Supply Chain
6.7.6 Enhanced Reaction
6.7.7 Planning and Growth of Inventories
6.8 IoT-Enabled Blockchains
6.8.1 Securing IoT Applications by Utilizing Blockchain
6.8.2 Blockchain Based on Permission
6.8.3 Blockchain Improvements in IoT
6.8.3.1 Blockchain Can Store Information Coming from IoT Devices
6.8.3.2 Secure Data Storage with Blockchain Distribution
6.8.3.3 Data Encryption via Hash Key and Tested by the Miners
6.8.3.4 Spoofing Attacks and Data Loss Prevention
6.8.3.5 Unauthorized Access Prevention Using Blockchain
6.8.3.6 Exclusion of Centralized Cloud Servers
6.9 Conclusions
References
Chapter 7 Deep Learning Approach to Industrial Energy Sector and Energy Forecasting with Prophet
7.1 Introduction
7.2 Related Work
7.3 Methodology
7.3.1 Splitting of Data (Test/Train)
7.3.2 Prophet Model
7.3.3 Data Cleaning
7.3.4 Model Implementation
7.4 Results
7.4.1 Comparing Forecast to Actuals
7.4.2 Adding Holidays
7.4.3 Comparing Forecast to Actuals with the Cleaned Data
7.5 Conclusion and Future Scope
References
Chapter 8 Application of Novel AI Mechanism for Minimizing Private Data Release in Cyber-Physical Systems
8.1 Introduction
8.2 Related Work
8.3 Proposed Mechanism
8.4 Experimental Results
8.5 Future Directions
8.6 Conclusion
References
Chapter 9 Environmental and Industrial Applications Using Internet of Things (IoT)
9.1 Introduction
9.2 IoT-Based Environmental Applications
9.3 Smart Environmental Monitoring
9.3.1 Air Quality Assessment
9.3.2 Water Quality Assessment
9.3.3 Soil Quality Assessment
9.3.4 Environmental Health-Related to COVID-19 Monitoring
9.4 Applications of Sensors Network in Agro-Industrial System
9.5 Applications of IoT in Industry
9.5.1 Application of IoT in the Autonomous Field
9.5.2 Applications of IoT in Software Industries
9.5.3 Sensors in Industry
9.6 Challenges of IoT Applications in Environmental and Industrial Applications
9.7 Conclusions and Recommendations
Acknowledgments
References
Chapter 10 An Introduction to Security in Internet of Things (IoT) and Big Data
10.1 Introduction
10.2 Allusion Design of IoT
10.2.1 Stage 1—Edge Tool
10.2.2 Stage 2—Connectivity
10.2.3 Stage 3—Fog Computing
10.2.4 Stage 4—Data Collection
10.2.5 Stage 5—Data Abstraction
10.2.6 Stage 6—Applications
10.2.7 Stage 7—Cooperation and Processes
10.3 Vulnerabilities of IoT
10.3.1 The Properties and Relationships of Various IoT Networks
10.3.2 Device Attacks
10.3.3 Attacks on Network
10.3.4 Some Other Issues
10.3.4.1 Customer Delivery Value
10.3.4.2 Compatibility Problems With Equipment
10.3.4.3 Compatibility and Maintenance
10.3.4.4 Connectivity Issues in the Field of Data
10.3.4.5 Incorrect Data Collection and Difficulties
10.3.4.6 Security Concern
10.3.4.7 Problems in Computer Confidentiality
10.4 Challenges in Technology
10.4.1 Skepticism of Consumers
10.5 Analysis of IoT Security
10.5.1 Sensing Layer Security Threats
10.5.1.1 Node Capturing
10.5.1.2 Malicious Attack by Code Injection
10.5.1.3 Attack by Fake Data Injection
10.5.1.4 Sidelines Assaults
10.5.1.5 Attacks During Booting Process
10.5.2 Network Layer Safety Issues
10.5.2.1 Attack on Phishing Page
10.5.2.2 Attacks on Access
10.5.2.3 Attacks on Data Transmission
10.5.2.4 Attacks on Routing
10.5.3 Middleware Layer Safety Issues
10.5.3.1 Attack by SQL Injection
10.5.3.2 Attack by Signature Wrapping
10.5.3.3 Cloud Attack Injection with Malware
10.5.3.4 Cloud Flooding Attack
10.5.4 Gateways Safety Issues
10.5.4.1 On-Boarding Safely
10.5.4.2 Additional Interfaces
10.5.4.3 Encrypting End-to-End
10.5.5 Application Layer Safety Issues
10.5.5.1 Theft of Data
10.5.5.2 Attacks at Interruption in Service
10.5.5.3 Malicious Code Injection Attack
10.6 Improvements and Enhancements Needed for IoT Applications in the Future
10.7 Upcoming Future Research Challenges with Intrusion Detection Systems (IDS)
10.8 Conclusion
References
Chapter 11 Potential, Scope, and Challenges of Industry 4.0
11.1 Introduction
11.2 Key Aspects for a Successful Production
11.3 Opportunities with Industry 4.0
11.4 Issues in Implementation of Industry 4.0
11.5 Potential Tools Utilized in Industry 4.0
11.6 Conclusion
References
Chapter 12 Industry 4.0 and Manufacturing Techniques: Opportunities and Challenges
12.1 Introduction
12.2 Changing Market Demands
12.2.1 Individualization
12.2.2 Volatility
12.2.3 Efficiency in Terms of Energy Resources
12.3 Recent Technological Advancements
12.4 Industrial Revolution 4.0
12.5 Challenges to Industry 4.0
12.6 Conclusion
References
Chapter 13 The Role of Multiagent System in Industry 4.0
13.1 Introduction
13.2 Characteristics and Goals of Industry 4.0 Conception
13.3 Artificial Intelligence
13.3.1 Knowledge-Based Systems
13.4 Multiagent Systems
13.4.1 Agent Architectures
13.4.2 JADE
13.4.3 System Requirements Definition
13.4.4 HMI Development
13.5 Developing Software of Controllers Multiagent Environment Behavior Patterns
13.5.1 Agent Supervision
13.5.2 Documents Dispatching Agents
13.5.3 Agent Rescheduling
13.5.4 Agent of Executive
13.5.5 Primary Roles of High-Availability Agent
13.6 Conclusion
References
Chapter 14 An Overview of Enhancing Encryption Standards for Multimedia in Explainable Artificial Intelligence Using Residue Number Systems for Security
14.1 Introduction
14.2 Reviews of Related Works
14.3 Materials and Methods
14.3.1 Multimedia
14.3.2 Artificial Intelligence and Explainable Artificial Intelligence
14.3.3 Cryptography
14.3.4 Encryption and Decryption
14.3.5 Residue Number System
14.4 Discussion and Conclusion
References
Chapter 15 Market Trends with Cryptocurrency Trading in Industry 4.0
15.1 Introduction
15.2 Industry Overview
15.2.1 History (From Barter to Cryptocurrency)
15.2.2 In the Beginning Was Bitcoin
15.3 Cryptocurrency Market
15.3.1 Blockchain
15.3.1.1 Introduction to Blockchain Technology
15.3.1.2 Mining
15.3.1.3 From Blockchain to Cryptocurrency
15.3.2 Introduction to Cryptocurrency Market
15.3.2.1 What is a Cryptocurrency?
15.3.2.2 Cryptocurrency Exchanges
15.4 Cryptocurrency Trading
15.4.1 Definition
15.4.2 Advantages
15.4.3 Disadvantages
15.5 In-Depth Analysis of Fee Structures and Carbon Footprint in Blockchain
15.5.1 Need for a Fee-Driven System
15.5.2 Ethereum Structure
15.5.3 How is the Gas Fee Calculated?
15.5.3.1 Why are Ethereum Gas Prices so High?
15.5.3.2 Carbon Neutrality
15.6 Conclusion
References
Chapter 16 Blockchain and Its Applications in Industry 4.0
16.1 Introduction
16.2 About Cryptocurrency
16.3 History of Blockchain and Cryptocurrency
16.4 Background of Industrial Revolution
16.4.1 The First Industrial Revolution
16.4.2 The Second Industrial Revolution
16.4.3 The Third Industrial Revolution
16.4.4 The Fourth Industrial Revolution
16.5 Trends of Blockchain
16.6 Applications of Blockchain in Industry 4.0
16.6.1 Blockchain and the Government
16.6.2 Blockchain in the Healthcare Sector
16.6.3 Blockchain in Logistics and Supply Chain
16.6.4 Blockchain in the Automotive Sector
16.6.5 Blockchain in the Education Sector
16.7 Conclusion
References
Index
EULA