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Introduction

With the rise of advanced technologies in the field of healthcare, there has been a growing interest in utilizing Artificial Intelligence (AI) to improve monitoring and management of patient health. In recent years, the emergence of Edge AI has provided a new dimension to healthcare monitoring by enabling real-time data processing and analysis at the edge of the network, closer to the source of data generation. This thesis aims to explore the potential of Edge AI in smart healthcare monitoring and its implications for improving patient care and outcomes.

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 Healthcare Monitoring
2.2 Artificial Intelligence in Healthcare
2.3 Edge Computing in Healthcare
2.4 Edge AI Applications in Healthcare Monitoring
2.5 Challenges and Opportunities of Edge AI in Healthcare
2.6 Case Studies of Edge AI Implementation in Healthcare
2.7 Current Trends in Smart Healthcare Monitoring
2.8 Regulatory and Ethical Considerations in Edge AI Healthcare
2.9 Future Directions in Edge AI for Healthcare
2.10 Critical Analysis of Existing Literature

Chapter Three: System Design and Methodology
3.1 Overview of Edge AI Architecture
3.2 Selection of Edge Devices and Sensors
3.3 Data Collection and Preprocessing Techniques
3.4 Edge AI Model Development
3.5 Model Optimization and Training
3.6 Real-time Data Processing and Analysis
3.7 Integration with Healthcare Systems
3.8 Performance Evaluation Metrics

Chapter Four: System Implementation
4.1 Hardware and Software Requirements
4.2 Data Collection and Integration
4.3 Edge AI Model Deployment
4.4 Testing and Validation
4.5 Performance Optimization Techniques
4.6 User Interface Design
4.7 Security and Privacy Measures
4.8 Scalability and Future Expansion

Chapter Five: Conclusion and Summary
5.1 Recap of Research Objectives
5.2 Key Findings and Contributions
5.3 Implications for Healthcare Practice
5.4 Limitations and Future Research Directions
5.5 Conclusion

Thesis Overview on Edge AI for Smart Healthcare Monitoring

The integration of Edge AI technology in healthcare monitoring systems has the potential to revolutionize the way patient data is collected, analyzed, and utilized to improve healthcare outcomes. This thesis delves into the use of Edge AI for smart healthcare monitoring, exploring its benefits, challenges, and implications for patient care. The literature review provides a comprehensive overview of the evolution of healthcare monitoring, the role of AI in healthcare, and the emergence of Edge Computing in healthcare settings. By examining case studies and current trends in smart healthcare monitoring, the thesis aims to highlight the potential of Edge AI in transforming healthcare practices.

The system design and methodology chapter outlines the architecture of Edge AI systems, selection of edge devices and sensors, data collection and preprocessing techniques, model development, optimization, and integration with existing healthcare systems. The system implementation chapter delves into the hardware and software requirements, data collection, model deployment, testing, validation, user interface design, security measures, and scalability of the Edge AI system.

In conclusion, this thesis provides a comprehensive analysis of the potential of Edge AI for smart healthcare monitoring, highlighting its benefits in providing real-time data analysis, improving patient outcomes, and enhancing healthcare practices. The limitations and future research directions section identifies areas for further exploration and development in the field of Edge AI in healthcare.

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