• Journal of Advanced Navigation Technology
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• v.28 no.5
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• pp.745-753
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• 2024

In this paper, we propose a system that extracts customer data from self-photos taken through a photo booth and automatically generates an operation report consisting of analysis results for each data and marketing strategy suggestions. The customer data to be extracted was selected based on attributes that could be used to analyze event operation results or to plan next year's event and establish promotional strategies. We utilize ChatGPT4o in image analysis, customer data analysis, and next marketing strategy proposal. As a result of analyzing self-photos taken at a local festival through the proposed system, customer data such as the number of people photographed, gender, age, relationship, and hairstyle were analyzed with high accuracy. In addition, the proposed system was shown to automatically generate operational reports based on customer data and marketing strategies extracted and analyzed by ChatGPT4o.

• Structural Engineering and Mechanics
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• v.91 no.4
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• pp.393-401
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• 2024

This study explores the integration of the generative AI, specifically ChatGPT (GPT-4o), into the field of structural analysis and design using the finite element method (FEM). The research is conducted in two main parts: structural analysis and structural design. For structural analysis, two scenarios are examined: one where the FEM source code is provided to ChatGPT and one where it is not. The AI's ability to understand, process, and accurately perform finite element analysis in both scenarios is evaluated. Additionally, the application of ChatGPT in structural design is investigated, including design modifications and parameter sensitivity analysis. The results demonstrate the potential of the generative AI to assist in complex engineering tasks, suggesting a future where AI significantly enhances efficiency and innovation in structural engineering. However, the study also highlights the importance of ensuring the accuracy and reliability of AI-generated results, particularly in safety-critical applications.

• Annual Conference of KIPS
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• 2024.10a
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• pp.475-476
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• 2024

온라인 쇼핑의 증가로 인해 상품평(리뷰)의 중요성이 높아지고 있다. 본 연구에서는 리뷰 데이터를 수집하고 이를 분석하여 상품의 판매 전략 개선 모델을 개발하였다. 이를 위해 웹 크롤링과 OCR 기술을 활용하여 댓글을 텍스트로 변환하고, Chat GPT 4o model를 사용해 댓글을 분석하였다. 모델을 통해 얻은 결과 데이터는 상품의 품질, 가격, 배송 등의 측면에서 주요한 피드백 요소들을 도출하는데 사용되었다. 본 연구는 IT 기술과 심리학적 요소를 결합하여 소비자 행동을 분석하는 새로운 접근 방식을 제시하며, 이를 통해 보다 효과적인 마케팅 전략을 수립할 수 있음을 보여준다.