Yuzhuo Gao

As smart cities increasingly integrate digital technologies into urban life, older adults are often overlooked in the design of smart urban environments. My research explores how smart and conventional environmental features jointly shape older adults’ lived experience in smart communities. Focusing on Guangzhou, China, the project combines street-view imagery analysis, semantic segmentation, and vision–language models to extract environmental features under both daytime and nighttime conditions. Older adults’ environmental experience across seven dimensions — accessibility, health, safety, stress reduction, sociability, sense of belonging, and cultural identity — is analysed using explainable AI techniques (XGBoost–SHAP–GAM) and Multiscale Geographically Weighted Regression (MGWR) to identify nonlinear relationships and spatially heterogeneous effects. The research aims to support the development of smarter and more age-friendly urban communities through evidence-based design guidelines.