Exploring the Dual Potential of Artificial Intelligence-Generated Content in the Esthetic Reproduction and Sustainable Innovative Design of Ming-Style Furniture

Author:

Wang Yali1ORCID,Xi Yuchen1ORCID,Liu Xinxiong1,Gan Yan1ORCID

Affiliation:

1. School of Mechanical Science & Engineering, Huazhong University of Science and Technology, Wuhan 430074, China

Abstract

The present research aims to explore the dual potential of artificial intelligence-generated content (AIGC) technology in the esthetic reproduction of Ming-style furniture and its innovative design while promoting sustainable practices and cultural heritage preservation. For this purpose, a combination of methodologies integrating the principles of grounded theory, empirical research, sustainable design, and design practice and evaluation techniques is employed. The results are as follows: First, the three-level coding method in grounded theory is used to construct a multi-dimensional esthetic feature library of Ming-style furniture, including 6 esthetic feature dimensions and 102 groups of esthetic elements. Second, a set of databases specifically for Ming-style furniture is developed based on the Midjourney platform. The AIGC exclusive toolkit for furniture (MFMP) contains a language package of 61 keywords and a basic formula for Ming-style furniture design. The MFMP toolkit accurately reproduces Ming-style furniture esthetics through empirical validation. Finally, combined with sustainable design principles, a new path is explored in order to utilize the MFMP toolkit for the sustainable and innovative design of new Chinese-style furniture. The research results demonstrate that AIGC enhances traditional and modern furniture design, offering tools for industry growth in a sustainable way and preserving cultural heritage.

Funder

Major Philosophy and Social Science Research Project for Hubei Province Colleges and Universities

Fundamental Research Funds for the Central Universities of China

Publisher

MDPI AG

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