Intro
Introduction
Contents
Part I Fundamentals of Industry 4.0
1 Opting for Industry 4.0: Challenge or Opportunity
1.1 Introduction
1.1.1 Role of Technologies in Industry 4.0 Transformation
1.1.2 Key Technologies to Transform Production Industry
1.2 Challenges When One Wants to Switch to Industry 4.0
1.2.1 Major Challenges
1.2.2 Some More Challenges
1.3 Benefits of Industry 4.0
1.4 Applications
1.5 Societal Impact
1.5.1 Relation Between Profit and Purpose
1.5.2 Employee and Customer Advocacy Is Increased

1.6 Case Study: Challenges in Manufacturing Sector
1.7 Conclusion
References
2 Exploring Human Computer Interaction in Industry 4.0
2.1 Introduction
2.2 Related Work
2.3 Research Questions
2.4 Research Solutions
2.5 Discussion and Recommendations
2.6 Conclusion and Future Work
References
3 Embedding Affect Awareness in e-Learning: A Systematic Outline of the Literature
3.1 Introduction
3.2 Motivation
3.3 Research Strategy and Research Questions
3.4 Literature Review
3.5 Survey Outcome and Discussion
3.6 Conclusion
References

4 Edge Computing: A Paradigm Shift for Delay-Sensitive AI Application
4.1 Introduction
4.2 Edge Computing Overview
4.2.1 The Origin of Edge Computing
4.2.1.1 Three Paradigms of Edge Computing: Cloudlets, Fog Computing, and Mobile Edge Computing
4.2.2 Criteria-Wise Difference Between Edge Computing and Cloud Computing
4.2.3 Layered Architecture of Edge Computing
4.2.3.1 Device Layer
4.2.3.2 The Edge Layer
4.2.3.3 The Cloud Layer
4.2.4 Software and Hardware Requirements to Implement Edge Computing (Table 4.2)
4.2.5 Characteristics of Edge Computing

4.2.5.1 Edge Computing Has Many Characteristics [9] as Cloud Computing
4.2.5.2 Close Proximity to the End Device
4.2.5.3 Support for Mobility Management
4.2.5.4 Location Awareness
4.2.5.5 Low Latency
4.2.5.6 Low Computation Power
4.2.6 Disadvantages of Edge Computing
4.2.7 Overview of Edge AI
4.2.8 Why Deep Learning with Edge Computing
4.2.9 Edge Intelligence-Enabled Applications of IoT
4.2.9.1 Smart Wearables
4.2.9.2 Smart City
4.2.9.3 Smart Home
4.2.9.4 Smart Building
4.2.9.5 Smart Grid
4.2.9.6 Smart Vehicle
4.2.9.7 Smart Multimedia

4.2.9.8 Video Analytics
4.2.9.9 Adaptive Video Streaming
4.2.9.10 Smart Transportation
4.2.9.11 Autonomous Driving
4.2.9.12 Traffic Analysis
4.2.9.13 Traffic Signal Control
4.2.10 Challenges in Edge-Enabled IoT Systems
4.2.10.1 Modal Training
4.2.10.2 Modal Deployment
4.2.10.3 Delay-Sensitive Applications
4.2.10.4 Hardware and Software Support
4.2.10.5 Integration and Heterogeneity
4.2.10.6 Naming
4.2.11 Research Opportunities in Edge AI and or Edge Computing
4.2.12 Conclusion
References
Part II Emerging Trends in Artificial Intelligence