Data-driven Optimization Research on Ageing-Responsive Design of Building Space in Urban Elderly Institutions

In recent years, with the aggravation of population aging and the continuous improvement of people’s living standards, the design of ageing-adapted architectural space for senior care institutions to improve the quality of senior care has become the focus of current research. Based on the Kano model and ERG demand hierarchy theory, the study firstly conducts demand research on the design of ageing-adapted architectural space in urban senior care institutions, explores the satisfaction of senior care groups with each demand, divides the demand attributes and establishes the order of priority, and then optimizes the design of ageing-adapted architectural space in urban senior care institutions in terms of environmental monitoring and control and health monitoring of the elderly. In the humidity data fusion experiment, the accuracy of the collected data was obviously improved after data fusion, which is conducive to the further control and execution operations of the environmental monitoring system. The health monitoring system designed for the elderly designed in this paper achieves 100% accuracy in detecting behaviors such as walking, sitting down and standing up, going downstairs, weightlessness-like processes, and standing up after falling. The health system proposed in this paper is able to distinguish whether the elderly are engaged in daily activities or in a state of falling, which is feasible and practical.