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Introduction

In recent years, the advancements in artificial intelligence (AI) have revolutionized various industries, including the field of smart lighting systems. Edge AI, which involves processing data on decentralized devices such as sensors and smart bulbs, has emerged as a powerful tool for enhancing the efficiency and intelligence of smart lighting systems. This thesis investigates the use of Edge AI for smart lighting systems, aiming to optimize energy consumption, increase automation, and improve user experience.

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 Overview of Smart Lighting Systems
2.2 Artificial Intelligence in Smart Lighting
2.3 Edge Computing in Smart Lighting
2.4 Benefits of Edge AI in Smart Lighting Systems
2.5 Challenges of Implementing Edge AI in Smart Lighting
2.6 Previous Studies on Edge AI for Smart Lighting
2.7 Comparison of Edge AI and Cloud Computing in Smart Lighting
2.8 Current Trends in Smart Lighting Systems
2.9 Future Directions for Edge AI in Smart Lighting
2.10 Conclusion

Chapter Three: System Design and Methodology
3.1 System Architecture of Edge AI for Smart Lighting
3.2 Data Collection and Preprocessing
3.3 Edge Computing Algorithms for Smart Lighting
3.4 Sensor Selection and Integration
3.5 Communication Protocols for Edge AI in Smart Lighting
3.6 User Interface Design
3.7 Testing and Validation Methods
3.8 Ethical Considerations in Implementing Edge AI for Smart Lighting

Chapter Four: System Implementation
4.1 Hardware and Software Requirements
4.2 Setting up Edge AI Environment
4.3 Integration of Edge AI Algorithms
4.4 Data Processing and Analysis
4.5 Optimization Techniques for Smart Lighting Systems
4.6 Real-world Deployment of Edge AI in Smart Lighting
4.7 Performance Evaluation Metrics
4.8 Troubleshooting and Maintenance Considerations

Chapter Five: Conclusion and Summary
5.1 Summary of Findings
5.2 Contribution to the Field
5.3 Future Research Directions
5.4 Conclusion

Thesis Overview:

Edge AI has shown promising potential for revolutionizing smart lighting systems by providing real-time processing of data at the edge devices. This thesis aims to explore the implementation of Edge AI in smart lighting to optimize energy consumption, increase automation, and enhance user experience. The literature review will provide an overview of previous studies on Edge AI and smart lighting systems, highlighting the benefits, challenges, and future directions in the field. The system design and methodology chapter will detail the architecture, data collection, preprocessing, algorithms, and testing methods used in implementing Edge AI for smart lighting. The system implementation chapter will focus on hardware and software requirements, deployment strategies, optimization techniques, and performance evaluation metrics. The conclusion and summary chapter will summarize the findings, contributions, and future research directions in Edge AI for smart lighting systems. This thesis aims to provide a comprehensive understanding of the potential of Edge AI in enhancing the efficiency and intelligence of smart lighting systems.

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