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Introduction

In recent years, the advancement of technology has led to the emergence of the Internet of Things (IoT) which has revolutionized various industries. The integration of Artificial Intelligence (AI) into IoT, known as Edge AI, has further enhanced the capabilities of IoT devices in various applications. One of the key areas where Edge AI has shown immense potential is in the industrial sector, known as Industrial Internet of Things (IIoT).

The combination of Edge AI and IIoT has the potential to transform industrial operations by enabling intelligent decision-making at the edge of the network, reducing latency, and improving efficiency. This thesis aims to explore the application of Edge AI in IIoT and its impact on industrial processes.

Chapter 1: Introduction
1.1 Introduction
1.2 Background of study
1.3 Problem Statement
1.4 Objective of study
1.5 Limitation of study
1.6 Scope of study
1.7 Significance of study
1.8 Structure of the Thesis
1.9 Definition of Terms

Chapter 2: Literature Review
2.1 Evolution of Industrial Internet of Things (IIoT)
2.2 Role of Artificial Intelligence in IIoT
2.3 Edge Computing in IIoT
2.4 Applications of Edge AI in IIoT
2.5 Challenges and Opportunities in Edge AI for IIoT
2.6 Edge AI frameworks and tools
2.7 Case Studies on Edge AI implementation in IIoT
2.8 Future trends in Edge AI for IIoT
2.9 Security and Privacy in Edge AI for IIoT
2.10 Integration of Edge AI with Cloud Computing in IIoT

Chapter 3: Research Methodology
3.1 Research Design
3.2 Data Collection Methods
3.3 Data Analysis Techniques
3.4 Sampling Techniques
3.5 Research Instrumentation
3.6 Ethical Considerations
3.7 Data Validation Techniques
3.8 Limitations of Research Methodology

Chapter 4: Discussion of Findings
4.1 Analysis of Data Collected
4.2 Comparison of Findings with Existing Literature
4.3 Implications of Findings on Industrial Applications
4.4 Recommendations for Future Research
4.5 Practical Implications for Industry
4.6 Theoretical Contributions
4.7 Case Studies Validation
4.8 Potential Challenges and Mitigation Strategies

Chapter 5: Conclusion and Summary
5.1 Summary of Findings
5.2 Conclusion
5.3 Contributions to Knowledge
5.4 Future Directions for Research
5.5 Recommendations for Industry

Thesis Overview:

The integration of Edge AI into IIoT has the potential to revolutionize industrial processes by enabling real-time decision-making, reducing latency, and improving efficiency. This thesis aims to explore the application of Edge AI in IIoT and its impact on industrial operations. The literature review will provide an overview of the evolution of IIoT, the role of AI in IIoT, Edge Computing, applications of Edge AI in IIoT, challenges and opportunities, frameworks and tools, case studies, future trends, and security considerations. The research methodology will outline the design, data collection methods, analysis techniques, and ethical considerations. The discussion of findings will analyze the data collected, compare findings with existing literature, and provide recommendations for future research and industry. The conclusion will summarize the findings, discuss contributions to knowledge, suggest future research directions, and provide recommendations for industry adoption of Edge AI in IIoT.

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