Earticle

초록

영어

As generative AI becomes increasingly integrated into various applications, its role in enhancing smart home IoT systems has gained significant attention. This study explores the impact of prompt engineering on the performance of generative AI within smart home IoT environments. By optimizing input prompts, we investigate how AI can more effectively control smart home devices, improving performance metrics such as task execution and system efficiency. Using an experimental method, we compare the outcomes of different prompt designs, focusing on key metrics: generation accuracy, completion time, and task performance. Our findings provide insights into how prompt engineering can maximize the utility of generative AI in smart home settings, contributing to advancements in smart home automation and personalized services. This research adds to the growing body of knowledge on AI-IoT integration, highlighting the potential of prompt optimization in real-world applications.

목차

Abstract
1. Introduction
2. Literature review
2.1 Generative AI(GAI)
2.2 Internet of Things(IoT)
2.3 Propmt Engineering
2.4 AI-IoT Integration
3. Methods
3.1 Research Design
3.2 Variables
3.3 Experimental Environment
3.4 Experimental Procedure
3.5 Data Analysis Method
4. Result
4.1 Introduction to Results Chapter
4.2 Descriptive Statistics
4.3 Two-Way ANOVA Results
4.4 Error Analysis
4.5 Summary of Results
5. Conclusion
5.1 Summary
5.2 Contributions and Practical Implications
5.3 Limitations
5.4 Future Research Directions
References

저자

• 진홍우 [ 전남대학교 일반대학원 디지털미래융합서비스협동과정 ]
• 이상준 [ 전남대학교 일반대학원 디지털미래융합서비스협동과정 ]

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