Abstract
To improve the efficiency and accuracy of aging-friendly renovation in old residential areas, this study proposes an AI-driven innovation platform integrating environmental recognition, elderly demand analysis, and spatial decision support. Based on the CIM platform, the system uses YOLOv8 to identify environmental problems from image data and applies the Kano model to classify and prioritize elderly residents’ needs. WebGIS is employed to visualize spatial information and renovation priorities. The results show that the platform can effectively detect typical environmental issues and support priority setting by combining problem severity, demand sensitivity, and spatial importance, thereby improving the scientificity and precision of aging-friendly renovation decisions.
Recommended Citation
Ma, Tie; Wang, Zhibo; Liu, Xinyi; and Xia, Meimei, "Research on AI Driven Innovation Platform for Aging Adaptation of Old Residential Areas" (2026). ICEB 2026 Proceedings (Beijing, China). 70.
https://aisel.aisnet.org/iceb2026/70