Automatic generation of virtual architecture using user activities in metaverse

Recently, architectural offices and IT companies have undertaken projects to build and sell cities in metaverses. However, it is considered inefficient to undertake such construction individually, building-by-building, using 3D modeling techniques. Fortunately, the use of artificial intelligence (AI) offers a breakthrough solution. This paper proposes a method of automatic generation of architectural spaces that is based on user activities in a metaverse and that can analyze users' perceptions of such spaces. To this end, in the present study, by referencing the theory of environmental psychology, we constructed a theoretical framework that can quantitatively analyze activities, based on which, we developed a metaverse space. Architectural space images were produced based on grammatical rules, which converted the analysis results into text, as well as a deep-learning-based text-to-image generator. Twenty participants responded to two questionnaires on their perceptions and opinions after participating in the metaverse experience and after receiving the architectural space image. Consequently, we analyzed the users' opinions on the architectural space created using the data they provided. Further, we reviewed the validity of the architectural design of the virtual space created using the proposed approach and explored the possibilities of its future utilization.