• Title/Summary/Keyword: ChatGPT4o

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Self-Photo Image Analysis and Reporting System Using ChatGPT4o (ChatGPT4o를 활용한 셀프포토 이미지 분석 및 리포팅 시스템)

  • Bong-Ki Son
    • 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 analysis and design using generative AI

  • Moonsu Park;Gyeongeun Bong;Jungro Kim;Gihwan Kim
    • 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.