-
Browse Book Series
- Adhesion and Adhesives: Fundamental and Applied Aspects
- Advances in Additive Manufacturing Technologies
- Advances in Antenna, Microwave and Communication Engineering
- Advances in Biofeedstocks and Biofuels
- Advances in Cyber Security
- Advances in Data Engineering and Machine Learning
- Advances in E-Mobility
- Advances in Hydrogen Production and Storage
- Advances in Intelligent and Scientific Computing (AISC)
- Advances in Learning Analytics for Intelligent Cloud-IoT Systems
- Advances in Membrane Processes
- Advances in Nanotechnology and Applications
- Advances in Natural Gas Engineering
- Advances in Pipes and Pipelines
- Advances in Production Engineering
- Advances in Solar Cell Materials and Storage
- Applied Functional Materials
- Artificial Intelligence and Soft Computing for Industrial Transformation
- Astrobiology Perspectives on Life in the Universe
- Bioprocessing in Food Science
- Computational Intelligence and Biomedical Engineering
- Concise Introductions to AI and Data Science
- Cyber Systems and Quantum Engineering
- Decentralized Systems and Next-Generation Internet
- Diatoms: Biology and Applications
- Digital Convergence in Engineering Systems
- Emerging Trends in Medicinal and Pharmaceutical Chemistry
- Engineering Systems Design for Sustainable Development
- Fintech in a Sustainable Digital Society
- Industry 5.0 Transformation Applications
- Infectious and Rare Diseases
- Innovations in Materials and Manufacturing
- Machine Learning in Biomedical Science and Healthcare Informatics
- Materials Degradation and Failure
- Mathematics and Computer Science
- Next-Generation Computing and Communication Engineering
- Performability Engineering Series
- Rotating Machinery Fundamentals and Advances
- Studies in Computational Intelligence and Smart Technologies
- Sustainable Computing and Optimization
Browse Subject Areas
For Authors
Submit a ProposalA Roadmap for Enabling Industry 4.0 by Artificial Intelligence
 | Edited by Jyotir Moy Chatterjee, Harish Garg and R. N. Thakur
Copyright: 2023 | Status: Published ISBN: 9781119904854 | Hardcover | 336 pages | 73 illustrations Price: $195 USD  |
One Line Description
The book presents comprehensive and up-to-date technological solutions to the main aspects regarding the applications of artificial intelligence to Industry 4.0.
Audience
Computer and artificial intelligence scientists, information and communication
technology specialists, and engineers in electronics and industrial
manufacturing will find this book very useful.
Computer and artificial intelligence scientists, information and communication
technology specialists, and engineers in electronics and industrial
manufacturing will find this book very useful.
Description
The industry 4.0 vision has been discussed for quite a while and the enabling
technologies are now mature enough to turn this vision into a grand reality
sooner rather than later. The fourth industrial revolution, or Industry 4.0,
involves the infusion of technology-enabled deeper and decisive automation
into manufacturing processes and activities. Several information and communication technologies (ICT) are being integrated and used towards
attaining manufacturing process acceleration and augmentation. This book
explores and educates the recent advancements in blockchain technology,
artificial intelligence, supply chains in manufacturing, cryptocurrencies, and
their crucial impact on realizing the Industry 4.0 goals. The book thus provides
a conceptual framework and roadmap for decision-makers for implementing
this transformation.
Back to Top
The industry 4.0 vision has been discussed for quite a while and the enabling
technologies are now mature enough to turn this vision into a grand reality
sooner rather than later. The fourth industrial revolution, or Industry 4.0,
involves the infusion of technology-enabled deeper and decisive automation
into manufacturing processes and activities. Several information and communication technologies (ICT) are being integrated and used towards
attaining manufacturing process acceleration and augmentation. This book
explores and educates the recent advancements in blockchain technology,
artificial intelligence, supply chains in manufacturing, cryptocurrencies, and
their crucial impact on realizing the Industry 4.0 goals. The book thus provides
a conceptual framework and roadmap for decision-makers for implementing
this transformation.
Back to Top
Author / Editor Details
Jyotir Moy Chatterjee is an assistant professor in the Information Technology department at Lord Buddha Education Foundation (LBEF), Kathmandu,
Nepal. He has published more than 60 research papers in international publications, three conference papers, three authored books, 10 edited books,
16 book chapters, two Master’s theses converted into books, and one patent.
Jyotir Moy Chatterjee is an assistant professor in the Information Technology department at Lord Buddha Education Foundation (LBEF), Kathmandu,
Nepal. He has published more than 60 research papers in international publications, three conference papers, three authored books, 10 edited books,
16 book chapters, two Master’s theses converted into books, and one patent.
Harish Garg, PhD, is an associate professor at Thapar Institute of Engineering & Technology, Deemed University, Patiala, Punjab, India. His research interests include soft computing, decision-making, aggregation operators, evolutionary algorithm, expert systems, and decision support systems. He has published more than 300 papers published in refereed international journals. Dr. Garg is the Editor-in-Chief of Annals of Optimization Theory and Practice.
R N Thakur, PhD, is a senior lecturer in the Information Technology
Department, Lord Buddha Education Foundation (LBEF), Kathmandu, Nepal.
He has published about 20 research articles in various journals.
Department, Lord Buddha Education Foundation (LBEF), Kathmandu, Nepal.
He has published about 20 research articles in various journals.
Back to Top
Table of Contents
Preface
1. Artificial Intelligence—The Driving Force of Industry 4.0
Hesham Magd, Henry Jonathan, Shad Ahmad Khan and Mohamed El Geddawy
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
2. Industry 4.0, Intelligent Manufacturing, Internet of Things, Cloud Computing: An Overview
Sachi Pandey, Vijay Laxmi and Rajendra Prasad Mahapatra
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
3. Artificial Intelligence of Things (AIoT) and Industry 4.0–Based Supply Chain (FMCG Industry)
Seyyed Esmaeil Najafi, Hamed Nozari and S. A. Edalatpanah
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
4. Application of Artificial Intelligence in Forecasting the Demand for Supply Chains Considering Industry 4.0
Alireza Goli, Amir-Mohammad Golmohammadi and S. A. Edalatpanah
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
5. Integrating IoT and Deep Learning—The Driving Force of Industry 4.0
Muhammad Farrukh Shahid, Tariq Jamil Saifullah Khanzada and Muhammad Hassan Tanveer
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
6. A Systematic Review on Blockchain Security Technology and Big Data Employed in Cloud Environment
Mahendra Prasad Nath, Sushree Bibhuprada B. Priyadarshini, Debahuti Mishra and Brojo Kishore Mishra
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
7. Deep Learning Approach to Industrial Energy Sector and Energy Forecasting with Prophet
Yash Gupta, Shilpi Sharma, Naveen Rajan P. and Nadia Mohamed Kunhi
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
8. Application of Novel AI Mechanism for Minimizing Private Data Release in Cyber-Physical Systems
Manas Kumar Yogi and A.S.N. Chakravarthy
8.1 Introduction
8.2 Related Work
8.3 Proposed Mechanism
8.4 Experimental Results
8.5 Future Directions
8.6 Conclusion
References
9. Environmental and Industrial Applications Using Internet of Things (IoT)
Manal Fawzy, Alaa El Din Mahmoud and Ahmed M. Abdelfatah
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
10. An Introduction to Security in Internet of Things (IoT) and Big Data
Sushree Bibhuprada B. Priyadarshini, Suraj Kumar Dash, Amrit Sahani, Brojo Kishore Mishra and Mahendra Prasad Nath
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
11. Potential, Scope, and Challenges of Industry 4.0
Roshan Raman and Aayush Kumar
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
12. Industry 4.0 and Manufacturing Techniques: Opportunities and Challenges
Roshan Raman and Aditya Ranjan
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
13. The Role of Multiagent System in Industry 4.0
Jagjit Singh Dhatterwal, Kuldeep Singh Kaswan and Rudra Pratap Ojha
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
14. An Overview of Enhancing Encryption Standards for Multimedia in Explainable Artificial Intelligence Using Residue Number Systems for Security
Akeem Femi Kadri, Micheal Olaolu Arowolo, Ayisat Wuraola Yusuf-Asaju, Kafayat Odunayo Tajudeen and Kazeem Alagbe Gbolagade
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
15. Market Trends with Cryptocurrency Trading in Industry 4.0
Varun Khemka, Sagar Bafna, Ayush Gupta, Somya Goyal and Vivek Kumar Verma
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
16. Blockchain and Its Applications in Industry 4.0
Ajay Sudhir Bale, Tarun Praveen Purohit, Muhammed Furqaan Hashim and Suyog Navale
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
Back to Top
Preface
1. Artificial Intelligence—The Driving Force of Industry 4.0
Hesham Magd, Henry Jonathan, Shad Ahmad Khan and Mohamed El Geddawy
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
2. Industry 4.0, Intelligent Manufacturing, Internet of Things, Cloud Computing: An Overview
Sachi Pandey, Vijay Laxmi and Rajendra Prasad Mahapatra
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
3. Artificial Intelligence of Things (AIoT) and Industry 4.0–Based Supply Chain (FMCG Industry)
Seyyed Esmaeil Najafi, Hamed Nozari and S. A. Edalatpanah
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
4. Application of Artificial Intelligence in Forecasting the Demand for Supply Chains Considering Industry 4.0
Alireza Goli, Amir-Mohammad Golmohammadi and S. A. Edalatpanah
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
5. Integrating IoT and Deep Learning—The Driving Force of Industry 4.0
Muhammad Farrukh Shahid, Tariq Jamil Saifullah Khanzada and Muhammad Hassan Tanveer
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
6. A Systematic Review on Blockchain Security Technology and Big Data Employed in Cloud Environment
Mahendra Prasad Nath, Sushree Bibhuprada B. Priyadarshini, Debahuti Mishra and Brojo Kishore Mishra
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
7. Deep Learning Approach to Industrial Energy Sector and Energy Forecasting with Prophet
Yash Gupta, Shilpi Sharma, Naveen Rajan P. and Nadia Mohamed Kunhi
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
8. Application of Novel AI Mechanism for Minimizing Private Data Release in Cyber-Physical Systems
Manas Kumar Yogi and A.S.N. Chakravarthy
8.1 Introduction
8.2 Related Work
8.3 Proposed Mechanism
8.4 Experimental Results
8.5 Future Directions
8.6 Conclusion
References
9. Environmental and Industrial Applications Using Internet of Things (IoT)
Manal Fawzy, Alaa El Din Mahmoud and Ahmed M. Abdelfatah
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
10. An Introduction to Security in Internet of Things (IoT) and Big Data
Sushree Bibhuprada B. Priyadarshini, Suraj Kumar Dash, Amrit Sahani, Brojo Kishore Mishra and Mahendra Prasad Nath
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
11. Potential, Scope, and Challenges of Industry 4.0
Roshan Raman and Aayush Kumar
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
12. Industry 4.0 and Manufacturing Techniques: Opportunities and Challenges
Roshan Raman and Aditya Ranjan
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
13. The Role of Multiagent System in Industry 4.0
Jagjit Singh Dhatterwal, Kuldeep Singh Kaswan and Rudra Pratap Ojha
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
14. An Overview of Enhancing Encryption Standards for Multimedia in Explainable Artificial Intelligence Using Residue Number Systems for Security
Akeem Femi Kadri, Micheal Olaolu Arowolo, Ayisat Wuraola Yusuf-Asaju, Kafayat Odunayo Tajudeen and Kazeem Alagbe Gbolagade
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
15. Market Trends with Cryptocurrency Trading in Industry 4.0
Varun Khemka, Sagar Bafna, Ayush Gupta, Somya Goyal and Vivek Kumar Verma
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
16. Blockchain and Its Applications in Industry 4.0
Ajay Sudhir Bale, Tarun Praveen Purohit, Muhammed Furqaan Hashim and Suyog Navale
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
Back to Top