Synergizing Artificial Intelligence Algorithms with Bio design for Innovative Industrial Product Appearance

Abstract

In the rapidly evolving landscape of industrial design, the integration of cutting-edge technologies has paved the way for transformative advancements. This abstract explores the convergence of artificial intelligence (AI) algorithms and biodesign principles to revolutionize the appearance of industrial products. Biodesign, inspired by the elegance and functionality of nature, provides a rich repository of strategies honed by millions of years of evolution. Leveraging this wisdom, in tandem with AI algorithms, holds the promise of yielding innovative and captivating product aesthetics. Through the lens of this abstract, we delve into the potential of AI algorithms to decipher and replicate the intricate patterns, textures, and configurations found in biological entities. By emulating nature's principles, the design process can transcend the conventional, leading to products that not only captivate the eye but also embody enhanced functionality. The interplay between biologically-inspired design and AI algorithms presents a unique opportunity to optimize aspects such as material utilization, structural integrity, and ergonomic considerations. The results from this study point out that IPD does not have any significant impact on the physical attractiveness of these products; however, it has an effect on their perceived attractiveness and can increase their appeal rating in certain cases. A three-dimensional Otsu threshold segmentation method based on BAS-CS is proposed. Aiming at the problem that the segmentation results of the traditional two-dimensional Otsu threshold segmentation method and the three-dimensional Otsu threshold segmentation method are susceptible to noise, the gray morphology and the three-dimensional Otsu threshold segmentation method are combined to form a three-dimensional gray Otsu model. The three-dimensional gray Otsu model is used to design the fitness function of the BAS-CS algorithm, and the BAS-CS algorithm is used to optimize the fitness function, and the specific implementation scheme and flowchart are given. Experiments verify the effectiveness, high efficiency, noise resistance and versatility of the proposed algorithm.