The interior environment design for entrepreneurship education under the virtual reality and artificial intelligence-based learning environment

Abstract

Nowadays, with the rapid growth of artificial intelligence (AI), entrepreneurship education has attracted more and more attention from society. To this end, it is necessary to gradually transform the traditional teaching mode into a new type of teaching that is more innovative, practical, and inclusive and in line with entrepreneurship education. The focus of the teaching mode change is on the optimization of the teaching environment. For this purpose, a method derived from distributed virtual reality (DVR) technology is specially designed. It refers to the fact that multiple users can join together through a computer network and participate in a virtual space at the same time to experience the virtual experience together. Based on this, the distributed 3D interior design is innovatively proposed. The innovation is mainly reflected in the application of VR technology, which is different from traditional software design. According to the functions and needs of the entrepreneurship teaching environment, first, the distributed feature information is collected, and second, the corresponding color image model is constructed by the fusion method, and edge contour detection and corresponding feature data extraction are carried out for the distributed image. Using a Red, Green, and Blue (RGB) color decomposition method, the pixel feature decomposition of spatially distributed image color is performed. And the feature reorganization of the 3D point cloud is combined to optimize the color space and color features of the combined design. On this basis, the distributed 3D interior design system is designed with VR and visual simulation technology. Finally, the Three-Dimensional Studio Max (3ds MAX) is used to establish 3D modeling, and the modeling software Multigen Creator is adopted to carry out the hierarchical structural design. The test results manifest that the Normalized Root Mean Square Error (RMSE) and information saturation of the distributed 3D interior design are reduced by 0.2 compared with the traditional design, the time overhead is shortened to one-sixth of the original, and the effect is more in line with the design requirements. It is hoped that this design method can provide new ideas and new perspectives for the optimization of the entrepreneurship teaching environment.