Mapping forty years of smart environments for older people research: A scientometric review
As global ageing accelerates, built environments struggle to meet living requirements of older adults. Smart environments, leveraging Information and Communication Technology (ICT), Artificial Intelligence (AI), and the Internet of Things (IoT), support independent living, yet research remains predominantly technology-oriented, with insufficient integration of spatial planning and inclusive design. This gap limits technological implementation in daily life and neglects seniors' lived experiences. Utilising scientometric analysis of 6371 publications (1983–2024), this paper investigates evolution, current trends, thematic shifts, and gaps in research on Smart Environments For Old People (SEFOP). The findings indicate: (a) SEFOP research has consistently expanded in an uneven manner across thematic areas; (b) five dominant clusters—Quality of Life and Health Management, Smart City and Intelligent Systems, Smart Home and IoT, Intelligent Buildings and Artificial Intelligence of Things (AIoT) and Assisted Living and AI—are identified, exhibiting asynchronous evolution and shifting importance over time; (c) Current smart systems remain misaligned with environmental design, revealing a technology–space disconnect; (d) Evidence on Smart Precinct Design and social inclusion remains scarce, despite its importance for age-friendly cities; (e) A four-dimensional framework—linking time, technology, spatial typologies, and research goals—is proposed to advance more inclusive smart ageing strategies.
Authors
- Kirsty Volz (ORCID: https://orcid.org/0000-0001-5787-6845)
- Bo Xia (ORCID: https://orcid.org/0000-0001-7694-4743)
- Yu‐Tang Gao (ORCID: https://orcid.org/0000-0003-3904-1777)
- Mirko Guaralda
Institutions
- Queensland University of Technology (AU)
- Guangzhou University (CN)
- Queensland Department of Environment and Science (AU)
Publication Details
- Journal
- Cities
- Published
- 2025-09-25
- DOI
- https://doi.org/10.1016/j.cities.2025.106505
- Primary Topic
- Context-Aware Activity Recognition Systems
- Type
- article
- Field-Weighted Citation Impact
- 0.00