Segmentation of Older People's Needs and Readiness for Smart Homes by Residentially Based Lifestyles in Spain: Survey...

Globally, the older population is increasing rapidly, becoming one of the most significant demographic trends of the 21st century. This growth poses important social, health, and technological challenges for societies that must adapt their environments and services to promote independent and healthy aging. In Spain, the population aged 65 years and older reached 18% of the total population in 2020, and projections indicate that this proportion will continue to rise in the coming decades. Within this context, smart homes have emerged as one of the most promising avenues to support aging in place and improve the quality of life. Smart homes encompass a wide variety of functions, including environmental control, safety monitoring, communication, and other assistive technologies, that may help older people stay healthy, safe, and independent in their own homes. However, older people are not a homogeneous group. Their lifestyles, health conditions, and technological experiences differ substantially, which means that, as with any assistive technology, smart home functions must match the real and perceived needs of the target users to ensure acceptance, adoption, and long-term use.

In this study, as a step forward toward the adaptability of smart home technology, we present a method to analyze the practical needs of smart home functions for older people. Specifically, we aim to understand the Spanish older population's readiness and needs for smart homes and to provide insights that can guide the design of more adaptive and user-centered solutions.

We conducted an online survey focusing on residentially based lifestyles, health conditions, and preferences for smart home functions, targeting older adults living in Spain. The survey collected information about participants' demographic profiles, daily activities, health self-assessment, and attitudes toward technology. A total of 102 valid responses were analyzed. We then classified the older adults according to their residentially based lifestyles using clustering techniques and analyzed the preferences and needs for smart home functions in each identified group.

Four clusters emerged based on the information provided by the participants: (1) high quality of life and independent life, (2) poor quality of life, (3) social-centered life, and (4) creative and personal-centered hobbies at home. On the basis of this classification, we explored each group's specific needs for smart homes and estimated their readiness to embrace different aspects of technology. As a result, the top-priority smart home functions for each group were identified and compared.

This research contributes to understanding the practical user needs of smart homes as assistive technologies for older people. It provides a methodological approach to anticipate and prioritize functions according to user characteristics, supporting the development of personalized, adaptive, and more acceptable smart home solutions for aging populations.