Handbook of Industry 4.0 and SMART Systems

Chapter 1: Fundamentals of Industry 4.0
1.1 Introduction
1.2 Industry 4.0
1.3 RAMI 4.0 (Reference Architecture Model Industry 4.0)
1.4 Servitization
1.5 Product Service-System (PSS)
References
Chapter 2: SMARTness and Pervasive Computing
2.1 Pervasive Computing
2.2 Problems of Pervasive Computing
2.3 Proposed Infrastructure for Pervasive (Ubiquitous) Computing: UbiCloud
2.4 Applications of Pervasive Computing
2.5 Healthcare
2.6. Two Stages of Pervasive Computing Development
2.7. Impact of Pervasive Computing
2.8. Differences between Traditional Networking and Pervasive Computing
2.9. Typical Sensors needed in Pervasive Computing
2.10. Defining Smart Spaces 
2.11. Attributes of Smart Spaces in Pervasive Computing
2.12. Pervasive Computing and Internet of Things (IoT)
References
Chapter 3: The Industry 4.0 architecture and Cyber Physical Systems
3.1 Cyber-Physical Systems (CPS)
3.2 CPS 5C Level Architecture
3.3 Implementation of 5C CPS Architecture for Factories
3.4 Adaptive Clustering for Self-Aware Machine Analytics
3.5 Classic Applications of CPS
3.6 Classification of CPS in Context of \"Industry 4.0\"
3.7 Operational Technology (OT) and Information Technology (IT)
3.8 IT and OT Convergence – Two Worlds Converging in Industrial IoT
3.9 Data and Optimization Across the Value Chain: Benefits and IT, OT and Cyber-Physical Systems in \"Smart Anything\"
3.10 Industry 4.0 Principles: Horizontal and Vertical Integration
3.11 Basic Functions and Uses of CPS
3.12 Practical Example of a Cyber Physical Systems: The Self-Modifying Machine
3.13 Digital Platforms
References
Chapter 4: Cloud computing, data sources and data centers
4.1 IT vs OT
4.2 CMMS, ERP, MES, EMS, PLM and other actors
4.3 Cloud Computing Taxonomies
4.4 Cloud Services
4.5.Data Repositories and Data Centers
References
Chapter 5: Big Data Analytics as Service Provider
5.1 Connection: Sensors and Networks
5.2 Content or Context
5.3 Data Sharing and Collaboration
5.4 Big Data Analytics
5.5 Descriptive Analytics
5.6 Diagnostic Analytics
5.7 Prescriptive Analytics
5.8 What Types of Data Analytics Do Companies Choose
Chapter 6: IoT and the Need for Data Rationalization
6.1 Internet of Things (IoT)
6.2 Internet of Things Vision
6.3 Internet of Things (IoT) Frameworks
6.4 Architecture of Internet of Things (IoT)
6.5 Visualizing the Internet of Things (IoT)
6.6 Essential Technologies of the Internet of Things (IoT)
6.7 Key Technologies Involved in Internet of Things
6.8 Enablers of IoT
6.9 Why the Internet of Things is Important?
6.10 The IoT Is Transforming Industry and Society
6.11 Types of Services of IoT
6.12 Internet of Things (IoT) Applications
6.13 The Internet of Things Today
6.14 The Internet of Things Tomorrow
6.15 Internet of Things (IoT) Ecosystem
References
Chapter 7: OPERATOR 4.0.
7.1 Augmented Reality for O&M
7.2 Wearable Devices
7.3 Wearables and Localization Devices
7.4 Intelligent Health and Safety Devices for Operators
7.5 Sensors used in Wearable Devices
7.6 Collaborative Robotics in Industry 4.0
7.7 Human Factors in Industry 4.0: Ergonomic and Psychological Issues and Challenges
References
Chapter 8: Cybersecurity and Risk
8.1 Cybersecurity in OT level
8.2 Cybersecurity in IT level
8.3 IT-OT Cybersecurity Convergence
8.4 Risks and threats of sharing data
8.5 Blockchains in cybersecurity
Chapter 9: Industry 4.0 across the Sectors
9.1 Introduction
9.2 Transportation 4.0: Multimodal Transportation Systems
9.3 Rail 4.0
9.4 Digital Transformation of Railways
9.5 Logistics 4.0 (Implications)
References