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Introduction

In recent years, there has been a growing interest in Edge AI for real-time decision making in various industries such as healthcare, finance, transportation, and manufacturing. Edge AI refers to the deployment of artificial intelligence algorithms on edge devices such as sensors, smartphones, and IoT devices, enabling real-time decision making at the source of data generation. This thesis aims to explore the potential of Edge AI for improving decision-making processes in real-time scenarios.

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 Two: Literature Review
2.1 Evolution of Edge AI
2.2 Applications of Edge AI in different industries
2.3 Challenges and limitations of Edge AI
2.4 Comparison of Edge AI with other AI technologies
2.5 Edge computing and its relevance to Edge AI
2.6 Real-time decision making and its importance
2.7 Case studies on successful implementation of Edge AI
2.8 Security and privacy concerns in Edge AI
2.9 Future trends in Edge AI
2.10 Summary of the literature review

Chapter Three: System Design and Methodology
3.1 Research design and approach
3.2 Data collection and preprocessing techniques
3.3 Selection of Edge AI algorithms
3.4 Development of the decision-making model
3.5 Integration of Edge AI with existing systems
3.6 Evaluation metrics for real-time decision making
3.7 Testing and validation of the system
3.8 Ethical considerations in system design
3.9 Tools and technologies used in the implementation
3.10 Summary of the system design and methodology

Chapter Four: System Implementation
4.1 Implementation of Edge AI algorithms on edge devices
4.2 Integration of sensors and IoT devices with the Edge AI system
4.3 Real-time data processing and analysis
4.4 Visualization of decision-making outcomes
4.5 Performance evaluation of the system
4.6 Optimization of the system for real-time decision making
4.7 Scalability and flexibility of the system
4.8 User interface design and usability testing
4.9 Challenges faced during system implementation
4.10 Summary of the system implementation

Chapter Five: Conclusion and Summary
5.1 Summary of key findings
5.2 Discussion of results
5.3 Contributions to the field of Edge AI
5.4 Implications for future research
5.5 Limitations of the study
5.6 Recommendations for practitioners
5.7 Conclusion
5.8 Reflection on the research process
5.9 Final thoughts and acknowledgments
5.10 References

Thesis Overview on Edge AI for Real-time Decision Making

Edge AI is a cutting-edge technology that has the potential to revolutionize decision-making processes in real-time scenarios. By deploying artificial intelligence algorithms on edge devices, organizations can make quicker and more accurate decisions at the source of data generation. This thesis explores the evolution of Edge AI, its applications in various industries, challenges and limitations, comparison with other AI technologies, and relevance to edge computing. The research design and methodology involve data collection, selection of Edge AI algorithms, development of decision-making models, integration with existing systems, and evaluation metrics for real-time decision making. The system implementation covers the deployment of Edge AI algorithms on edge devices, integration with sensors and IoT devices, real-time data processing and analysis, performance evaluation, and user interface design. The conclusion summarizes key findings, discusses results, suggests implications for future research, and makes recommendations for practitioners. This thesis contributes to the field of Edge AI by providing insights into its potential for real-time decision making and offering recommendations for its implementation in various industries.

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