Research on Aging Adaptation of Urban Residential Environment Design in the Era of Artificial Intelligence

Abstract

Abstract Under the background of aging, how to make the elderly live comfortably and improve the quality of life have all become the main problems solved by the current society. Based on the relevant theoretical foundation, this paper constructs a aging adaptation design model of the urban residential environment. Principal component analysis and factor analysis are employed to simplify the data structure of living environment design and decrease the complexity of data analysis. Regression analysis and structural equations are combined to investigate the relationship between the living environment and age appropriateness. PLS regression analysis was used to solve the external weights or factor loadings to obtain the estimates of the latent variables and the path coefficients among the latent variables. To demonstrate the reasonableness of the factors influencing the quality of the environment, the reliability and validity of the perceived quality are analyzed. Combining the basic attributes and needs of the elderly is the basis of proposing an aging-friendly environment design strategy. The results show that In terms of architectural spatial perception, the master bedroom space scale exceeds 3.92m × 4.61m, which is a relatively optimal choice that can simultaneously meet the diversified needs of the family’s living behavior at different stages. In terms of road accessibility and greening perception, the width of the age-appropriate walkway can vary depending on different locations and the unit time flow of people. In the era of artificial intelligence, the design of the aging-adapted living environment should fully consider the physiological characteristics of the elderly and formulate more suitable living data for the elderly.