Projecting Residents’ Intentions: Participatory Interior Renovation Design through AI Image-Generation Workshops

Graduate School of Architecture and Architectural Engineering, Shibaura Institute of Technology, Saitama, Japan

^* Corresponding author: This email address is being protected from spambots. You need JavaScript enabled to view it.

Abstract

This study explores a participatory design methodology for renovating a vacant unit in Haraichi Complex, a large-scale housing estate built in 1966, which faces an aging population. As an extension of the "Satellite Lab Ageo" community hub, the project aims to expand resident-led activities to the vacant unit on the second floor. To overcome the limitations of traditional participatory methods—such as the time-consuming nature of physical modeling and difficulties in consensus building—this research introduces generative AI as a tool for rapid visualization. While previous applications of AI in planning have struggled with realism and implementation, this study focuses on the process of integrating diverse resident needs into a cohesive architectural design. By verifying the transition from "idea projection" via AI to physical spatial realization, this research proposes a new framework for participatory design that facilitates collective intent in the revitalization of aging housing complexes.