Age Sustainability in Smart City: Seniors as Urban Stakeholders in the Light of Literature Studies

Abstract

Objectives: An aging population and declining birth rates are among the challenges that smart cities currently face and will continue to face in the near future. In light of the above, this article seeks to answer the following question: Are older people (seniors) taken into account and described in the literature on smart cities, and if so, how? Methods: To answer this research question, a systematic literature review was conducted using the Bibliometrix package in R. In the process of systematizing the publications, the authors additionally used the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) method and qualitative text analysis. Findings: The research shows that relatively little attention is paid to seniors in smart cities in the literature on the subject. Among the few publications on smart aging, the technological trend dominates, in which researchers present the possibilities of using IT and ICT to improve medical and social care for seniors, and to improve their quality of life (Smart Living, Smart Mobility). In the non-technological trend, most analyses focus on the determinants of quality of life and the distinguishing features of senior-friendly cities. Implications: There is a clear lack of a “human” perspective on aging in smart cities and publications on Smart Governance and Smart People that would provide guidelines for making elderly people full and equal stakeholders in smart cities. It is also necessary to develop practical documents and procedures that define a comprehensive and long-term urban policy for elderly adults. The analyses contribute to diagnosing current and determining further directions of research on smart aging in smart cities. The results clearly imply the need to intensify social, humanistic, and governance research on the role of seniors in smart cities.

1. Introduction

Smart cities (SC) are increasingly prevalent in the literature on urban management [1,2,3]. The SC concept is also being increasingly implemented in practice, both in fragmented and holistic approaches. Municipal authorities and researchers are constantly evaluating the development of smart urban structures by creating new rankings and comparative analyses [4,5,6,7,8]. Urban competition is growing, and the battle to be smart is becoming increasingly fierce [9].

Given these phenomena and processes, the validity of Smart City assumptions is undeniable, especially since they are aimed at improving the quality of life of residents. They therefore contribute to socio-economic and civilizational development and benefit local communities and individual residents. However, it is essential to examine more closely the individual aspects to ensure that the process runs smoothly and does not lead to pathologies and distortions, because even the most noble theoretical ideas can be seriously distorted in practice.

Therefore, the smart city concept does not impress everyone. It also raises serious reservations and concerns. Intelligent urban structures are criticized primarily for excessive technologization and digitization, which indirectly leads to the dehumanization of cities [10,11]. It may also contribute to an increase in environmental pollution [12,13]. The complexity of technical, IT, and communication systems in smart cities also generates additional threats in cyberspace [14,15]. It compromises the privacy of residents and exposes cities to the risk of external attacks [16,17]. Smart cities are also criticized for promoting relationships between municipal authorities and local businesses, which are not always transparent and ethical. This results in the prioritization of economic goals and does not always serve to improve the quality of life of residents [18].

The above irregularities contribute to the imbalance of smart cities. In practice, this means neglecting social and environmental goals. These goals represent egalitarian values that do not bring material benefits to specific stakeholders.

In such unfavorable conditions, various forms of exclusion arise quickly and easily. This contradicts the idea of a smart city [19,20,21]. The smart city concept assumes improving the quality of life of all residents. It should not focus only on exceptional or selected groups.

One of the groups at risk of social exclusion is elderly people, who, for various reasons, are not always able to fully participate in the life of a smart city. Meanwhile, aging urban communities are increasingly made up of seniors, who deserve proper attention and care to ensure that the smart city is fully inclusive and sustainable. In the above circumstances, overlooking elderly people in discussions about the development of contemporary cities risks not only ignoring the problem but also leading to serious social consequences, such as the alienation of a significant and growing group of stakeholders, distortion of the smart city concept, the creation of social tensions, and an unrealistic perception of the smart city as a utopian place to live for the young and healthy only.

Given the above circumstances, the article authors seek answers to the following research question: Are older people (seniors) taken into account and described in the literature on smart cities, and if so, how? It is also notable that, due to current and widespread demographic trends, it is older people who will constitute a large, sometimes dominant and growing part of the population of modern cities in the near future.

Two phenomena clearly illustrate the aging of societies. The first is increasing life expectancy (Figure 1). The second is the systematically declining fertility rate among women (Figure 2).

In all analyzed regions, people currently live significantly longer than in the 1960s. Europeans are the oldest. However, all trends shown in Figure 1 are consistently increasing and statistically well-fitted. This indicates systematic aging of societies worldwide. This process will generate increasingly greater burdens for public budgets and healthcare systems. It will also pose an enormous challenge for smart cities. Currently, smart cities appear not to recognize this challenge.

The second unfavorable demographic trend is declining female fertility observed worldwide, in all presented regions. It deepens the aging process of societies and its negative effects. Generations are not being replaced. The size of the working-age population is decreasing. The percentage of seniors in the total population is increasing.

In light of the above statistics, seniors’ assessment of urban life may largely determine the status of what can be considered “smart”. Older residents should not be overlooked, underestimated or excluded in the process of implementing the smart city concept. It is therefore worth asking: are they perceived as full and equal stakeholders of the smart city? Contemporary smart cities must be well-prepared for adapting to an increasingly aging society. They must also include seniors in the city development strategy, because their presence and growing numbers are inevitable in light of the demographic data presented.

In order to answer the research question formulated above, a systematic literature review was conducted using the Bibliometrix package in R 4.3.3. CRAN 2025. In the process of systematizing the publications, the authors additionally used the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) method. The quantitative analysis of articles related to issues of aging in a smart city was then developed through a qualitative review of the presented research and considerations aimed at answering the research question and identifying gaps and directions for further research.

The originality of the systematic literature review presented in the article stems from the following circumstances:

• Focusing the analysis on the humanities and social sciences aspect of smart city considerations, which is much less frequently highlighted in the literature on the subject;
• Addressing the dark sides of the smart city related to social exclusion (which is not as spectacular a challenge as describing technological innovations);
• Narrowing the research to the issue of aging in a smart city (no literature reviews have been conducted in this area to date);
• The critical assessment of the subject matter and methodology of research on the functioning of older people in smart city structures;
• Conducting a multifaceted comparative analysis of the ways in which seniors are represented in smart city literature;
• Identification of the main research trends and themes concerning the perception of older adults and senior policy in the context of the smart city;
• Formulating recommendations for Smart Governance aimed at the full inclusion of seniors in the life of the smart city;
• The formulation of conclusions for further research and implementations supporting the sustainability of smart cities and preventing the exclusion of seniors.

2. Materials and Methods

The literature review conducted in this article consisted of two stages. Stage 1 was quantitative and involved selecting publications for further analysis based on selected keywords. Stage 2 focused on a qualitative analysis of the articles, including grouping them into coherent thematic areas [22].

The quantitative stage was developed using the PRISMA method—Preferred Reporting Items for Systematic Reviews and Meta Analyses [23], taking into account the three consecutive steps presented in Figure 3. The detailed course of this procedure, including the original methodological lists recommended in the PRISMA methodology, has been included in the Supplementary Materials. These are: PRISMA 2020 for Abstracts Checklist (Table S1) and 2020 PRISMA Checklist (Table S2).

Bibliometrix, an R language package [24], was used in the search and quantitative analysis of publications, while MS Excel and the VOSViewer 1.6.20 tool [25] were used for additional visualization. The search was conducted in the Scopus database. We treated this database on equal terms with Web of Science. Moreover, the institution we represent provides us with full-text access to publications contained in Scopus. For these reasons, we selected it as the database for further analysis.

In the first step, a pool of articles containing the following keywords was identified: age-friendliness smart cities, smart aging, aging in a smart city, smart senior, and age-friendly smart city. These are terms directly related to senior issues, including those related to smart cities. In selecting keywords, it was important for us to embed the issue of aging society within the smart city context. Therefore, we aimed to search for the combination of both studied terms.

The aforementioned phrases could be found in the title, abstract, or keywords. Furthermore, due to their specific nature and limitation to professional geriatric care, two disciplines were excluded from the search: medicine and nursing. Our research and considerations focus on smart cities. This subject matter does not belong to the field of medicine and nursing. However, these two areas use the combination of words ‘smart’ and ‘aging’ to describe medical inventions and achievements used in geriatric care. This research thread does not belong to the considerations undertaken in the article. Therefore, both mentioned disciplines were excluded from the search.

Ultimately, the query containing the above criteria was as follows:

(TITLE-ABS-KEY (“age-friendly smart city” OR “age-friendliness smart cities” OR “smart aging” OR “aging in a smart city” OR “smart senior”)) AND NOT (SUBJAREA (medi) OR SUBJAREA (nurs)) AND (LIMIT-TO (LANGUAGE, “English”)). The search was conducted in early January 2025 with no time restrictions. The first publications on the topics described appeared in the database in 2014. It can therefore be assumed that the analysis period covered 2014–2024.

Based on the above search criteria, 76 publications were obtained, from which items related to collective conference materials were removed, resulting in 73 publications for screening.

Next, 64 publications relating to the issue of aging in cities were selected from the defined set for further analysis (publications that did not contain direct or indirect references to urban issues were rejected). These publications were subjected to a qualitative analysis taking into account the main research theme, research method, and subject area.

To enhance the transparency and reproducibility of this qualitative phase, a structured classification procedure was applied. Each of the 64 publications was independently reviewed by two researchers and categorized as either technological or non-technological, based on the dominant research focus and methodological approach. Publications emphasizing the development, application, or assessment of smart technologies—such as ICT systems, sensor networks, AI tools, or digital platforms—were classified as technological. In contrast, studies primarily addressing social, managerial, policy-related, or quality of life dimensions of aging in urban contexts were considered non-technological.

In cases where articles addressed both aspects, the classification was based on the predominant thematic emphasis as determined through full-text review. Discrepancies in classification were resolved through consensus after discussion. This procedure ensured consistency and minimized subjectivity in the categorization process.

This allowed for the systematization of current research topics concerning the role and description of seniors in smart cities. It also enabled the identification of the most prominent topics and the indication of existing or research topics requiring supplementation and further consideration.

3. Results

As already mentioned, the analysis of the results was carried out in two stages. The first one was quantitative and helped organize the selected publications. The second one focused on analyzing the content of selected publications and gave a qualitative look at senior issues in Smart Cities. The analysis of results was conducted and described taking these phases into account and is presented in detail below.

3.1. Bibliometric Analysis—Quantitaive Approach

The first stage of the research involved carrying out a quantitative assessment of interest in senior-related topics in smart cities. Figure 4 shows the number of publications and citations of articles on seniors in smart cities in 2014–2024. The data presented there clearly shows that the annual number of publications throughout the analysis period is small, but nevertheless, since 2020, there has been a clear increase in interest in the issue. It is also worth noting that despite the low number of publications, they are often cited, which suggests a growing demand for discussions on smart aging.

The above phenomenon most likely results from two causes. The first is the growing interest in the smart city concept. The second is the increasingly observable aging of societies worldwide.

To provide more detail on the analysis,

Table 1. The most frequently used keywords.

Keyword	Occurrences	Number_of_Links	Total_Link_Strength
smart aging	12	19	23
elderly care	7	15	21
internet of things	7	18	24
older adults	7	7	9
aged	6	16	27
automation	6	17	32
smart city	6	2	2
aging	5	9	16
aging population	5	10	13
elderly	5	13	13
human	5	14	24
product design	5	10	11
artificial intelligence	4	11	13
diagnosis	4	17	21
human computer interaction	4	10	12
intelligent buildings	4	10	19
physiological models	4	9	12
smart homes	4	16	25

Source: own research.

shows the most frequently occurring keywords and the number and strength of their links.

Keyword analysis initially indicates the existence of three thematic groups in which senior issues are examined in smart cities. The first group covers issues related to aging (aging, older adults, aged, human). The second group is related to elderly care and geriatric medicine (elderly care, diagnosis, physiological models). The third refers to the technologization of SCs (Internet of Things, automation, Artificial Intelligence, intelligent buildings, smart home).

The existence of these three groups is also confirmed by the visualization of clusters of senior-related topics in the literature (Figure 5 and Figure 6). The figures show that the term “smart aging” appears quite frequently in the literature in connection with the Internet of Things and automation. It is also associated with the aforementioned medical care and the aging process of the modern urban population.

Both the keyword analysis and the graphic illustration of the connections between them presented in Figure 6 clearly indicate the dominance of technological themes in descriptions of senior issues, especially in the last five years. For this reason, the selected publications have been divided into two thematic groups in the further part of the article. The first group covers the links between smart aging and modern technologies used in smart cities. The second group includes publications in which the authors focus on non-technological issues.

Taking into account the trends in which smart cities are typically described, the observed quantitative tendencies indicate the persistent technologization of issues related to intelligent urban structures. Senior policy encompasses such issues as: Internet of Things, IT, and ICT—distinguishing features of smart cities.

In the humanistic, social, less technological trend, issues primarily related to healthcare and senior welfare appear. These are undoubtedly important issues for quality of life, but are they the only ones important for elderly people?

The quantitative analysis of selected articles also preliminarily indicates that social and technological issues are very often described together. An example of such an approach is the smart home—adapted to seniors’ needs while being modern and convenient.

We clarify and deepen the above conclusions and doubts in the next two sub-sections of the article, which include qualitative analysis of the selected publications.

3.2. Principles of Bibliometric Qualitative Analysis

Following the methodological assumptions, 64 publications were finally selected for qualitative analysis. They were divided into technological and non-technological based on an analysis of their content (Table 2 and Table 3). Forty-five articles were classified in the first group. The second group included 19 studies.

The classification presented above is based on two key research areas that describe the contemporary smart city. The first—somewhat foundational—refers to IT and ICT technologies, upon which the smart city concept was initially created. The second, which has evolved over time, is non-technological in nature and includes other aspects of smart city, such as social, environmental, and economic dimensions. This area highlights the level of sustainability in the thematic discussions within these domains, which was described in the introduction.

3.3. A Technological Perspective on Senior Policy in Smart City

The preliminary selection results therefore indicate a clear dominance of technological themes in the analysis of senior issues, which also suggests a continuing trend towards the strong technologization of the smart city concept in practice. This illustrates the imbalance within the concept, which is often criticized in both academic literature and practice by opponents of smart city development. It can therefore be stated that, despite calls for a more balanced approach to smart cities, technology remains at the center of attention.

Due to the large number of publications in the first group, they were further divided into research sub-areas covering the relationship between technology and:

• medical care [26,27,28,29,30,31,32,33,34,35,36,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56]: publications closely related to medical inventions and technologies dedicated to elderly adults;
• society [57,58,59,60,61,62,63,64,65,66,67]: publications that integrate medical and technological themes with social aspects;
• well-being [68,69,70]: studies on the well-being of older adults.

The first sub-area proved to be the most intensively analyzed (32 publications). It mainly includes properties and designs of systems and applications supporting medical care for seniors. These IT, ICT, and IoT-based solutions predominantly position seniors as passive research subjects or technology recipients. The technologies are primarily designed to assist healthcare professionals, care facilities, and family members—other smart city stakeholders—rather than to actively engage older adults as participants in the digital ecosystem.

Only a few take into account the preferences, expectations, or emotions of older people. These articles typically use methods of the social sciences, such as surveys, interviews, and observations. This allows for direct contact with seniors and humanizes the technological aspects of the research. For example, Yang and Cui (2021) [26] describe the amenities associated with smart urban infrastructure, but also take into account the physical and mental needs of the elderly. Zhou et al. (2024) [31] focus on determining the role of family relationships in reducing digital exclusion among seniors.

Within this trend, there is also a group of researchers working to increase acceptance of smart medical solutions at every stage of their implementation. Chowdhury and Ahmad (2023) [37] attempt to assess the demand for applications supporting senior medical care. Yao and Zhu (2024) [49] seek answers to the question of the determinants of positive perceptions of medical technologies. O’Dea et al. (2021) [23] identify opportunities and barriers to the use of smartphones for monitoring the health of older people. Neuhuettler et al. (2017) [50] examine the perception and quality of digital services offered to seniors in order to improve them and adapt them to individual needs.

In the second sub-area, which covers the relationship between technology and society and includes 12 publications, the authors describe humanistic themes slightly more frequently and willingly. Monsurro and Dezi (2021) [57] refer to family relationships and social ties that are important for the well-being of the elderly. Ma and Xu (2023) [62] and Jin (2022) [63] characterize technical systems for monitoring seniors, but their research also takes into account the sense of security and emotional reactions. An interesting and original analysis is also provided by Rinaldi and Kianfar (2020) [65]. It concerns the use of modern technologies in active aging in the workplace, which allows us to look at seniors not only in the context of medical or social care.

In summary, the first group of publications primarily focuses on ways to improve the lives of older adults through the use of modern technologies. These solutions are aimed at health monitoring, enhancing physical condition, and providing healthcare support. Undoubtedly, both the publications in this area and the innovations they propose are necessary and important for the civilizational and economic development of cities, as well as for the quality of life of the elderly.

Table 2. Properties of publications in the technological area.

Item	Authors	Subject	Keywords	Methodology	Research Trend
1.	Yang T.; Cui Y. [26]	Physical and psychological needs in interior design	for elderly-oriented; human factor characteristics; smart facilities; smart senior care community	Social studies	Technology and medical care
2.	Wang H.; Li A.; Chen T.; Liu J. [27]	Monitoring apnea in the elderly to improve the quality and efficiency of medical care	anomaly detection; data fusion; smart senior care	Machine learning	Technology and medical care
3.	Liu N. [28]	The use of biometrics for monitoring and healthcare for the elderly	biometric features; face recognition; Internet+; optimal feature parameters; smart aging	Biometrics	Technology and medical care
4.	Chen D.; Han J.; Song Y. [29]	Identification of digital exclusion among seniors, taking into account gender and its impact on access to medical care	aged; aging; article; digital divide; digital technology; female; gender; human; logistic regression analysis; male; minority group; regression analysis	Econometric models and case study	Technology and medical care
5.	Yamout Y.; Iqbal S.; Chakraborty N.; Zulkernine M. [30]	The use of biometrics and the Internet of Things in monitoring seniors and medical care	Authentication, Intrusion detection, Aging, Sensor systems and applications, User experience, Pattern recognition, Security	Biometrics	Technology and medical care
6.	Zhou J.; Zhao Q.; Zhou J. [31]	Identifying the role of parent–child relationships in the digitization of the elderly and ensuring their medical care	Health status; Internet use; Older adults; Parent–child relationship; Smart senior care cognition	Social studies and econometric models	Technology and medical care
7.	Xu L.; Zhang Y. [32]	The use of modern technologies in caring for the elderly, taking into account their individual preferences	Fuzzy-QFD; Grey relational analysis; Quality improvement; Service quality; Smart senior care	Fuzzy logic	Technology and medical care
8.	Chen S. [33]	Optimization of the interface design of an application facilitating care for the elderly	Age-appropriate design; APP interface; Deep learning; Deep Q-network algorithm; Smart senior care	Machine learning	Technology and medical care
9.	Yamout Y.; Yeasar T.S.; Iqbal S.; Zulkernine M. [34]	Intelligent systems for caring for the elderly and ensuring their safety	countermeasures; IoT; security issues; Smart aging care system; smart healthcare; smart home	Technical system analysis	Technology and medical care
10.	Deng Y. [35]	Modeling complex technical systems supporting intelligent aging	No data	Technical system analysis	Technology vs. society
11.	Zhang J.; Li L.; Qu X.; Zhang Y. [36]	Optimization of data analysis collected within a platform offering care services for the elderly	Dimensionality reduction; Factor analysis; Life satisfaction; Machine learning; Parameter optimization; Particle swarm algorithms; Smart aging; Support vector machines	Machine learning	Technology and medical care
12.	Chowdhury M.; Ahmad A. [37]	Assessment of demand and application supporting the organization of medical care for seniors in emerging economies	Emergency contact; Elderly assistance; Helping hand selection; Medicine remainder; Mobile Application; Old home search; Police help	Social studies	Technology and medical care
13.	Tost D.; von Barnekow A.; Felix E.; Pazzi S.; Puricelli S.; Bottiroli S. [38]	Assessment of the effectiveness of an intelligent telematics test in recognizing cognitive disorders in seniors	3D serious games; Mild cognitive impairments; Screening	Technical system analysis	Technology and medical care
14.	Malek M.S.; Gohil P.; Pandya S.; Shivam A.; Limbachiya K. [39]	Identification of behavioral patterns of residents in smart retirement homes	Activity modeling; Behavior pattern; Health monitoring; Sensor networks	Technical system design	Technology and medical care
15.	Ghayvat H.; Mukhopadhyay S.; Shenjie B.; Chouhan A.; Chen W. [40]	Monitoring lifestyle by diagnosing behaviors and distinguishing deviations from the norm	Activity of daily living; Ambient assisted living; Anomaly detection; Elderly; Smart home; Wellness; Wellness indices	Technical system design	Technology and medical care
16.	Ma R.; Lei L.; Li B.; Dan M.; Wang X.; Liu Y. [41]	Presentation of a multifunctional robot assisting in the care of elderly people	aging population; fall detection; Raspberry Pi; smart aging product	Technical system design	Technology and medical care
17.	Neagu G.; Ianculescu M.; Alexandru A.; Florian V.; Rǎdulescu C.T.Z. [42]	Review of ICT use in healthcare for an aging population	artificial intelligence; collaborative decision-making; edge computing; health monitoring; next-generation IoT; smart aging architecture	Technical system analysis	Technology and medical care
18.	Ghayvat H.; Awais M.; Pandya S.; Ren H.; Akbarzadeh S.; Mukhopadhyay S.C.; Chen C.; Gope P.; Chouhan A.; Chen W. [43]	Designing a system for monitoring and predicting the lifestyle of seniors in order to improve medical care	AAL; ADL; anomaly; forecasting; pattern generation	Technical system analysis	Technology and medical care
19.	Kibria M.G.; Chong I. [44]	A model for creating knowledge on an online platform focused on recognizing and meeting user needs, supporting smart aging.	Internet of Things; knowledge base; smart aging; smart home; Web-of-Objects	Machine learning	Technology and medical care
20.	Pandya S.; Mistry M.; Kotecha K.; Sur A.; Ghanchi A.; Patadiya V.; Limbachiya K.; Shivam A. [45]	Designing a system that detects behavioral patterns of elderly people in nursing homes and reports anomalies	activities of daily living; activity modeling; anomaly detection; cognitive computing	Technical system analysis	Technology and medical care
21.	Bottiroli S.; Tassorelli C.; Lamonica M.; Zucchella C.; Cavallini E.; Bernini S.; Sinforiani E.; Pazzi S.; Cristiani P.; Vecchi T.; Tost D.; Sandrini G. [46]	The use of an IT system to diagnose cognitive disorders in seniors with neurodegenerative diseases	cognitive impairment; global cognitive functions; neurodegenerative disease; serious games; virtual reality	Technical system design	Technology and medical care
22.	Li Y.; Zhang C.; Huang C.; Suo H.; Liu N.; Hu X.; Li Y.; Chen G. [47]	Identification of opportunities and barriers to the use of smartphones for monitoring the health of seniors in rural areas	influencing factors; propensity score matching; self-rated health; smartphones	Social studies	Technology and medical care
23.	Htet Y.; Zin T.T.; Tin P.; Tamura H.; Kondo K.; Watanabe S. [48]	Identification of daily activities of seniors in nursing homes, with particular emphasis on privacy and personal data protection	deep learning architecture; elderly activity monitoring; GUI; motion information; real-time action recognition; smart aging; stereo depth cameras; transition state recognition	Machine learning	Technology and medical care
24.	Yao X.; Zhu M. [49]	Identification of factors influencing the acceptance of smart healthcare among seniors	China; elderly; smart aging services; structural equation modeling; willingness to adopt	Social studies	Technology and medical care
25.	Neuhuettler J.; Ganz W.; Liu J. [50]	Presentation of an integrated approach to assessing the quality of smart services for seniors	Senior care services; Service innovation; Service quality; Smart services	Quality assessment	Technology and medical care
26.	Ahamed F.; Farid F.; Suleiman B.; Jan Z.; Wahsheh L.A.; Shahrestani S. [51]	The use of a multimodal AI-based biometric authentication model in senior care	biometrics; cybersecurity; ECG; internet of things; machine learning; personalized healthcare; PPG; smart aging	Technical system analysis	Technology and medical care
27.	O’Sullivan P.; Connolly A.; Carroll N.; Richardson I. [52]	Cooperation with IBM on the development of intelligent aging systems	Connected health; Smarter care; User-centric	Technical system analysis	Technology and medical care
28.	Ghayvat H.; Gope P. [53]	Properties of an intelligent system for monitoring aging and early detection of dementia	Cognitive impairment; Pre-trained deep learning model; Preventive healthcare diagnoses; Smart home monitoring; The activity of daily living; Transfer learning	Technical system analysis	Technology and medical care
29.	Wang B.; Chen D.; Xu L. [54]	Analysis of a disease prediction algorithm in health monitoring software for an intelligent care system for the elderly	No data	Technical system analysis	Technology and medical care
30.	Chakraborty N.; Iqbal S.; Zulkernine M. [55]	Development of secure software methods used in senior care	agile; scrum; security; smart aging care systems; software	Technical system analysis	Technology and medical care
31.	Zhang J. [56]	The demand of the elderly for smart urban elderly care services	No data	Social studies	Technology and medical care
32.	Monsurro L.; Dezi L. [57]	Identifying the role of parent–child relationships in seniors’ acceptance of technology and in strengthening autonomy and social bonds	Elderly; Smart Aging; Smart Objects	Social studies	Technology vs. society
33.	Yun Y.-D.; Lee C.; Lim H.-S. [58]	Analysis of possibilities for increasing the usability of smart devices for seniors based on an assessment of their cognitive responses	aging; cognitive response; intelligent UI/UX system; online education; senior; smart devices	Technical system analysis	Technology vs. society
34.	Kim C.; Pan Y. [59]	Identification of patterns of social network use (digital and real) by seniors, aimed at improving their quality of life	BAND; Private SNS; Senior; Smart senior; SNS (Social networking service)	Social studies	Technology vs. society
35.	Zhuan S.; Suqi L. [60]	Designing a smart home for seniors focused on improving quality of life	elderly care; human–computer interaction; smart apartment	Technical system analysis	Technology vs. society
36.	Torku A.; Chan A.P.C.; Yung E.H.K. [61]	Identification of barriers hindering the implementation of senior-friendly initiatives in smart cities	Age-friendly city; Barriers; Integrated conceptual model; Smart city; Systematic literature review; Urban aging	Literature Review	Technology vs. society
37.	Ma Y.; Xu W. [62]	Identifying the impact of monitoring systems on the sense of security of seniors in home care	a sense of security; home care; moderating effect; smart senior care; structural equation model	Social studies, case study	Technology vs society
38.	Jin Y.-S. [63]	Monitoring the elderly to identify patterns of behavior and emotional responses	No data	Machine learning	Technology vs. society
39.	Bottiroli S.; Bernini S.; Cavallini E.; Sinforiani E.; Zucchella C.; Pazzi S.; Cristiani P.; Vecchi T.; Tost D.; Sandrini G.; Tassorelli C. [64]	Description of the use of an online platform for assessing memory, executive functions, and spatial-visual processes in seniors	Cognitive assessment; Global cognitive functions; Normal aging; Serious games; Virtual reality	Technical system analysis	Technology vs. society
40.	Rinaldi A.; Kianfar K. [65]	Exploring the possibilities offered by smart technologies (AI and IoT) in the design of technological solutions aimed at active aging in the workplace	Active aging at work; Artificial intelligence; Human-centered design; Workplace 4.0	design thinking	Technology vs. society
41.	Syeda M.Z.; Park M.; Kwon Y.-M. [66]	Designing and testing an IT system that reduces digital exclusion among older people and strengthens their social relationships	Elderly; Family photos; Intergenerational communication; Photo Alive!; Social interaction	Technical system design	Technology vs. society
42.	Zallio M.; McGrory J.; Berry D. [67]	The use of participatory techniques to reduce digital exclusion, including among older people	Inclusive design; Internet of Things; Learning tools; Participatory design; Smart aging-friendly environments; Usability; User experience research	Social studies	Technology vs. society
43.	Syeda M.Z.; Syeda D.; Babbar H. [68]	Properties of the use of modern technologies in caring for seniors and improving their standard of living	3D printing; 5G networking; Artificial intelligence (AI); Blockchain; Emerging technology; IoT	Literature studies	Technology vs. well-being
44.	Wang X.; Song Y.; Chen W.; Du H.; Su X.; Wang H. [69]	Identifying the individual needs of seniors in terms of nutrition and physical activity	Collaborative Filtering Algorithm; Exercise Recommendation; Meal Recommendation; Personalization; Smart Aging	Machine learning	Technology vs. well-being
45.	Shen Z.; Hu R.; Wan D.; Bock T. [70]	Promoting physical activity among the elderly in smart cities in emerging economies using virtual reality	aging in China; COVID-19 pandemic; digital technology; Exergame; health; inclusive smart cities; population aging; smart aging	Virtual reality, functional tests	Technology vs. well-being

Table 2. Properties of publications in the technological area.

Item	Authors	Subject	Keywords	Methodology	Research Trend
1.	Yang T.; Cui Y. [26]	Physical and psychological needs in interior design	for elderly-oriented; human factor characteristics; smart facilities; smart senior care community	Social studies	Technology and medical care
2.	Wang H.; Li A.; Chen T.; Liu J. [27]	Monitoring apnea in the elderly to improve the quality and efficiency of medical care	anomaly detection; data fusion; smart senior care	Machine learning	Technology and medical care
3.	Liu N. [28]	The use of biometrics for monitoring and healthcare for the elderly	biometric features; face recognition; Internet+; optimal feature parameters; smart aging	Biometrics	Technology and medical care
4.	Chen D.; Han J.; Song Y. [29]	Identification of digital exclusion among seniors, taking into account gender and its impact on access to medical care	aged; aging; article; digital divide; digital technology; female; gender; human; logistic regression analysis; male; minority group; regression analysis	Econometric models and case study	Technology and medical care
5.	Yamout Y.; Iqbal S.; Chakraborty N.; Zulkernine M. [30]	The use of biometrics and the Internet of Things in monitoring seniors and medical care	Authentication, Intrusion detection, Aging, Sensor systems and applications, User experience, Pattern recognition, Security	Biometrics	Technology and medical care
6.	Zhou J.; Zhao Q.; Zhou J. [31]	Identifying the role of parent–child relationships in the digitization of the elderly and ensuring their medical care	Health status; Internet use; Older adults; Parent–child relationship; Smart senior care cognition	Social studies and econometric models	Technology and medical care
7.	Xu L.; Zhang Y. [32]	The use of modern technologies in caring for the elderly, taking into account their individual preferences	Fuzzy-QFD; Grey relational analysis; Quality improvement; Service quality; Smart senior care	Fuzzy logic	Technology and medical care
8.	Chen S. [33]	Optimization of the interface design of an application facilitating care for the elderly	Age-appropriate design; APP interface; Deep learning; Deep Q-network algorithm; Smart senior care	Machine learning	Technology and medical care
9.	Yamout Y.; Yeasar T.S.; Iqbal S.; Zulkernine M. [34]	Intelligent systems for caring for the elderly and ensuring their safety	countermeasures; IoT; security issues; Smart aging care system; smart healthcare; smart home	Technical system analysis	Technology and medical care
10.	Deng Y. [35]	Modeling complex technical systems supporting intelligent aging	No data	Technical system analysis	Technology vs. society
11.	Zhang J.; Li L.; Qu X.; Zhang Y. [36]	Optimization of data analysis collected within a platform offering care services for the elderly	Dimensionality reduction; Factor analysis; Life satisfaction; Machine learning; Parameter optimization; Particle swarm algorithms; Smart aging; Support vector machines	Machine learning	Technology and medical care
12.	Chowdhury M.; Ahmad A. [37]	Assessment of demand and application supporting the organization of medical care for seniors in emerging economies	Emergency contact; Elderly assistance; Helping hand selection; Medicine remainder; Mobile Application; Old home search; Police help	Social studies	Technology and medical care
13.	Tost D.; von Barnekow A.; Felix E.; Pazzi S.; Puricelli S.; Bottiroli S. [38]	Assessment of the effectiveness of an intelligent telematics test in recognizing cognitive disorders in seniors	3D serious games; Mild cognitive impairments; Screening	Technical system analysis	Technology and medical care
14.	Malek M.S.; Gohil P.; Pandya S.; Shivam A.; Limbachiya K. [39]	Identification of behavioral patterns of residents in smart retirement homes	Activity modeling; Behavior pattern; Health monitoring; Sensor networks	Technical system design	Technology and medical care
15.	Ghayvat H.; Mukhopadhyay S.; Shenjie B.; Chouhan A.; Chen W. [40]	Monitoring lifestyle by diagnosing behaviors and distinguishing deviations from the norm	Activity of daily living; Ambient assisted living; Anomaly detection; Elderly; Smart home; Wellness; Wellness indices	Technical system design	Technology and medical care
16.	Ma R.; Lei L.; Li B.; Dan M.; Wang X.; Liu Y. [41]	Presentation of a multifunctional robot assisting in the care of elderly people	aging population; fall detection; Raspberry Pi; smart aging product	Technical system design	Technology and medical care
17.	Neagu G.; Ianculescu M.; Alexandru A.; Florian V.; Rǎdulescu C.T.Z. [42]	Review of ICT use in healthcare for an aging population	artificial intelligence; collaborative decision-making; edge computing; health monitoring; next-generation IoT; smart aging architecture	Technical system analysis	Technology and medical care
18.	Ghayvat H.; Awais M.; Pandya S.; Ren H.; Akbarzadeh S.; Mukhopadhyay S.C.; Chen C.; Gope P.; Chouhan A.; Chen W. [43]	Designing a system for monitoring and predicting the lifestyle of seniors in order to improve medical care	AAL; ADL; anomaly; forecasting; pattern generation	Technical system analysis	Technology and medical care
19.	Kibria M.G.; Chong I. [44]	A model for creating knowledge on an online platform focused on recognizing and meeting user needs, supporting smart aging.	Internet of Things; knowledge base; smart aging; smart home; Web-of-Objects	Machine learning	Technology and medical care
20.	Pandya S.; Mistry M.; Kotecha K.; Sur A.; Ghanchi A.; Patadiya V.; Limbachiya K.; Shivam A. [45]	Designing a system that detects behavioral patterns of elderly people in nursing homes and reports anomalies	activities of daily living; activity modeling; anomaly detection; cognitive computing	Technical system analysis	Technology and medical care
21.	Bottiroli S.; Tassorelli C.; Lamonica M.; Zucchella C.; Cavallini E.; Bernini S.; Sinforiani E.; Pazzi S.; Cristiani P.; Vecchi T.; Tost D.; Sandrini G. [46]	The use of an IT system to diagnose cognitive disorders in seniors with neurodegenerative diseases	cognitive impairment; global cognitive functions; neurodegenerative disease; serious games; virtual reality	Technical system design	Technology and medical care
22.	Li Y.; Zhang C.; Huang C.; Suo H.; Liu N.; Hu X.; Li Y.; Chen G. [47]	Identification of opportunities and barriers to the use of smartphones for monitoring the health of seniors in rural areas	influencing factors; propensity score matching; self-rated health; smartphones	Social studies	Technology and medical care
23.	Htet Y.; Zin T.T.; Tin P.; Tamura H.; Kondo K.; Watanabe S. [48]	Identification of daily activities of seniors in nursing homes, with particular emphasis on privacy and personal data protection	deep learning architecture; elderly activity monitoring; GUI; motion information; real-time action recognition; smart aging; stereo depth cameras; transition state recognition	Machine learning	Technology and medical care
24.	Yao X.; Zhu M. [49]	Identification of factors influencing the acceptance of smart healthcare among seniors	China; elderly; smart aging services; structural equation modeling; willingness to adopt	Social studies	Technology and medical care
25.	Neuhuettler J.; Ganz W.; Liu J. [50]	Presentation of an integrated approach to assessing the quality of smart services for seniors	Senior care services; Service innovation; Service quality; Smart services	Quality assessment	Technology and medical care
26.	Ahamed F.; Farid F.; Suleiman B.; Jan Z.; Wahsheh L.A.; Shahrestani S. [51]	The use of a multimodal AI-based biometric authentication model in senior care	biometrics; cybersecurity; ECG; internet of things; machine learning; personalized healthcare; PPG; smart aging	Technical system analysis	Technology and medical care
27.	O’Sullivan P.; Connolly A.; Carroll N.; Richardson I. [52]	Cooperation with IBM on the development of intelligent aging systems	Connected health; Smarter care; User-centric	Technical system analysis	Technology and medical care
28.	Ghayvat H.; Gope P. [53]	Properties of an intelligent system for monitoring aging and early detection of dementia	Cognitive impairment; Pre-trained deep learning model; Preventive healthcare diagnoses; Smart home monitoring; The activity of daily living; Transfer learning	Technical system analysis	Technology and medical care
29.	Wang B.; Chen D.; Xu L. [54]	Analysis of a disease prediction algorithm in health monitoring software for an intelligent care system for the elderly	No data	Technical system analysis	Technology and medical care
30.	Chakraborty N.; Iqbal S.; Zulkernine M. [55]	Development of secure software methods used in senior care	agile; scrum; security; smart aging care systems; software	Technical system analysis	Technology and medical care
31.	Zhang J. [56]	The demand of the elderly for smart urban elderly care services	No data	Social studies	Technology and medical care
32.	Monsurro L.; Dezi L. [57]	Identifying the role of parent–child relationships in seniors’ acceptance of technology and in strengthening autonomy and social bonds	Elderly; Smart Aging; Smart Objects	Social studies	Technology vs. society
33.	Yun Y.-D.; Lee C.; Lim H.-S. [58]	Analysis of possibilities for increasing the usability of smart devices for seniors based on an assessment of their cognitive responses	aging; cognitive response; intelligent UI/UX system; online education; senior; smart devices	Technical system analysis	Technology vs. society
34.	Kim C.; Pan Y. [59]	Identification of patterns of social network use (digital and real) by seniors, aimed at improving their quality of life	BAND; Private SNS; Senior; Smart senior; SNS (Social networking service)	Social studies	Technology vs. society
35.	Zhuan S.; Suqi L. [60]	Designing a smart home for seniors focused on improving quality of life	elderly care; human–computer interaction; smart apartment	Technical system analysis	Technology vs. society
36.	Torku A.; Chan A.P.C.; Yung E.H.K. [61]	Identification of barriers hindering the implementation of senior-friendly initiatives in smart cities	Age-friendly city; Barriers; Integrated conceptual model; Smart city; Systematic literature review; Urban aging	Literature Review	Technology vs. society
37.	Ma Y.; Xu W. [62]	Identifying the impact of monitoring systems on the sense of security of seniors in home care	a sense of security; home care; moderating effect; smart senior care; structural equation model	Social studies, case study	Technology vs society
38.	Jin Y.-S. [63]	Monitoring the elderly to identify patterns of behavior and emotional responses	No data	Machine learning	Technology vs. society
39.	Bottiroli S.; Bernini S.; Cavallini E.; Sinforiani E.; Zucchella C.; Pazzi S.; Cristiani P.; Vecchi T.; Tost D.; Sandrini G.; Tassorelli C. [64]	Description of the use of an online platform for assessing memory, executive functions, and spatial-visual processes in seniors	Cognitive assessment; Global cognitive functions; Normal aging; Serious games; Virtual reality	Technical system analysis	Technology vs. society
40.	Rinaldi A.; Kianfar K. [65]	Exploring the possibilities offered by smart technologies (AI and IoT) in the design of technological solutions aimed at active aging in the workplace	Active aging at work; Artificial intelligence; Human-centered design; Workplace 4.0	design thinking	Technology vs. society
41.	Syeda M.Z.; Park M.; Kwon Y.-M. [66]	Designing and testing an IT system that reduces digital exclusion among older people and strengthens their social relationships	Elderly; Family photos; Intergenerational communication; Photo Alive!; Social interaction	Technical system design	Technology vs. society
42.	Zallio M.; McGrory J.; Berry D. [67]	The use of participatory techniques to reduce digital exclusion, including among older people	Inclusive design; Internet of Things; Learning tools; Participatory design; Smart aging-friendly environments; Usability; User experience research	Social studies	Technology vs. society
43.	Syeda M.Z.; Syeda D.; Babbar H. [68]	Properties of the use of modern technologies in caring for seniors and improving their standard of living	3D printing; 5G networking; Artificial intelligence (AI); Blockchain; Emerging technology; IoT	Literature studies	Technology vs. well-being
44.	Wang X.; Song Y.; Chen W.; Du H.; Su X.; Wang H. [69]	Identifying the individual needs of seniors in terms of nutrition and physical activity	Collaborative Filtering Algorithm; Exercise Recommendation; Meal Recommendation; Personalization; Smart Aging	Machine learning	Technology vs. well-being
45.	Shen Z.; Hu R.; Wan D.; Bock T. [70]	Promoting physical activity among the elderly in smart cities in emerging economies using virtual reality	aging in China; COVID-19 pandemic; digital technology; Exergame; health; inclusive smart cities; population aging; smart aging	Virtual reality, functional tests	Technology vs. well-being

Table 3. Properties of publications in the non-technological area.

Item	Authors	Subject	Keywords	Methodology	Research Trend
1.	Song I.-Y.; Song M.; Timakum T.; Ryu S.-R.; Lee H. [71]	The areas of smart aging are: technology, healthcare, and social behavior and issues.	Information communication technology; Self-care; smart aging; Well-being	Literature studies	well-being
2.	Labus A. [72]	Seasonal migration of the elderly to senior-friendly cities	age friendly cities; Benidorm; seasonal migration; smart city; smart destination (SD); urban renewal	Case study	well-being
3.	Li L.; Li D.; Zhou S.; Huang H.; Huang G.; Yu L. [73]	Identification of needs of seniors and of senior-friendly areas in smart cities	Age-friendly smart city; China; Elderly citizens; Heterogeneity analysis; IAHP-CRITIC-IFCE method	Econometric models and case study	well-being
4.	Baraković Husić J.; Baraković S.; Cero Dinarević E. [74]	Analysis of the impact of modern technologies on the quality of life of seniors, indicating their ineffectiveness	Elderly; Quality of life; Smart aging	Social studies	well-being
5.	Naccarelli R.; D’Agresti F.; Roelen S.D.; Jokinen K.; Casaccia S.; Revel G.M.; Maggio M.; Azimi Z.; Alam M.M.; Saleem Q.; Mohammed A.H.; Napolitano G.; Szczepaniak F.; Hariz M.; Chollet G.; Lohr C.; Boudy J.; Wieching R.; Ogawa T. [75]	Virtual e-coaching promoting active and healthy aging	active and healthy aging; older adults; sensors; smart aging; technical architecture; virtual coach	Case study	well-being
6.	Hyatt S. [76]	Planning of smart aging in the family	No data	Literature studies	well-being
7.	Matysiak I.; Peters D.J. [77]	Comparison of smart senior cities with senior-friendly cities	Aging in place; Population aging; Quality of life; Rural areas; Senior services; Small towns; Social capital	Social studies, case study	well-being
8.	Lee M.R. [78]	Identifying the role of the digital revolution in supporting smart aging of society	industrial revolution; Blue ocean; Senior bridge; Senior friendly industry; Smart aging	Multi-dimensional industry analysis	well-being
9.	Li W. [79]	Designing smart entertainment systems for seniors	Emotional experience; Entertainment products; Interaction design; Perceived affordances	Social studies	well-being
10.	Silva P.A.; Holden K.; Nii A. [80]	Assessment of the suitability of mobile health applications for the needs of seniors	Cognitive systems; Decision making; Health; User interfaces; Gamification; Google plays; Heuristic evaluation; heuristics; Older adults; Physical exercise; Potential benefits; Small targets; Human computer interaction	Social studies	well-being
11.	Um S.-B. [81]	Analysis of determinants of livability for the elderly in a smart city	age-friendly smart city; body sensor network; GWR; older adult classes; priority district; spatial weighting	Social studies and econometric models	well-being
12.	Zhang J.; Li L. [82]	Model for predicting life satisfaction among the elderly	Factor Analysis Dimensionality Reduction; Life Satisfaction Prediction Model; PSO Parameter Optimization; Smart Aging; Support Vector Machine	Social studies and econometric models	well-being
13.	Hu F.; Wen J.; Phau I.; Ying T.; Aston J.; Wang W. [83]	Identifying the role of tourism in smart aging	Age-friendly destinations; Ageism; Healthy aging; Healthy lifestyles; Human rights; Interdisciplinary literature review; Smart aging; Travel therapy	Literature review	well-being
14.	Jonek-Kowalska I. [84]	Confronting the availability of medical care with the needs of an aging society	age-friendly smart cities (SCs); aging of urban populations; city health care; human smart cities (SCs); sustainable smart cities (SCs)	Statistical analysis	well-being
15.	Shore L.; De Eyto A.; Kiernan L.; Bhaird D.N.A.; Connolly A.; White P.J.; Fahey T.; Moane S. [85]	Identification of areas for senior activation (mobility, public spaces, safety, social engagement, services, and amenities)	Co-design; Collaborative coalitions; Needs identification; Older adults; Product service systems	Social studies	City management
16.	Suopajärvi T. [86]	Experiencing smart urban solutions by seniors and their perception of themselves as smart citizens	Aging; Ethnographic composition; Feminist new materialism; Smart city; Urban assemblage	Social studies	City management
17.	Szczech-Pietkiewicz E.; Szweda-Lewandowska Z.; Felczak J.; Kubicki P. [87]	The use of ICT in coping with aging in urban environments	No data	Literature review, social studies	City management
18.	Suopajärvi T. [88]	Social workshops as a way of involving seniors in the design of public services in the city	Aging; Cultural anthropology; Ethnography; Feminist new materialism; Participatory action research; Smart city	Case study	City management
19.	Fan C.; Yu X.; Fan H. Y. [89]	Model for managing senior communities in smart cities	Smart Senior Citizens’ communities; social value	Social studies	City management

Table 3. Properties of publications in the non-technological area.

Item	Authors	Subject	Keywords	Methodology	Research Trend
1.	Song I.-Y.; Song M.; Timakum T.; Ryu S.-R.; Lee H. [71]	The areas of smart aging are: technology, healthcare, and social behavior and issues.	Information communication technology; Self-care; smart aging; Well-being	Literature studies	well-being
2.	Labus A. [72]	Seasonal migration of the elderly to senior-friendly cities	age friendly cities; Benidorm; seasonal migration; smart city; smart destination (SD); urban renewal	Case study	well-being
3.	Li L.; Li D.; Zhou S.; Huang H.; Huang G.; Yu L. [73]	Identification of needs of seniors and of senior-friendly areas in smart cities	Age-friendly smart city; China; Elderly citizens; Heterogeneity analysis; IAHP-CRITIC-IFCE method	Econometric models and case study	well-being
4.	Baraković Husić J.; Baraković S.; Cero Dinarević E. [74]	Analysis of the impact of modern technologies on the quality of life of seniors, indicating their ineffectiveness	Elderly; Quality of life; Smart aging	Social studies	well-being
5.	Naccarelli R.; D’Agresti F.; Roelen S.D.; Jokinen K.; Casaccia S.; Revel G.M.; Maggio M.; Azimi Z.; Alam M.M.; Saleem Q.; Mohammed A.H.; Napolitano G.; Szczepaniak F.; Hariz M.; Chollet G.; Lohr C.; Boudy J.; Wieching R.; Ogawa T. [75]	Virtual e-coaching promoting active and healthy aging	active and healthy aging; older adults; sensors; smart aging; technical architecture; virtual coach	Case study	well-being
6.	Hyatt S. [76]	Planning of smart aging in the family	No data	Literature studies	well-being
7.	Matysiak I.; Peters D.J. [77]	Comparison of smart senior cities with senior-friendly cities	Aging in place; Population aging; Quality of life; Rural areas; Senior services; Small towns; Social capital	Social studies, case study	well-being
8.	Lee M.R. [78]	Identifying the role of the digital revolution in supporting smart aging of society	industrial revolution; Blue ocean; Senior bridge; Senior friendly industry; Smart aging	Multi-dimensional industry analysis	well-being
9.	Li W. [79]	Designing smart entertainment systems for seniors	Emotional experience; Entertainment products; Interaction design; Perceived affordances	Social studies	well-being
10.	Silva P.A.; Holden K.; Nii A. [80]	Assessment of the suitability of mobile health applications for the needs of seniors	Cognitive systems; Decision making; Health; User interfaces; Gamification; Google plays; Heuristic evaluation; heuristics; Older adults; Physical exercise; Potential benefits; Small targets; Human computer interaction	Social studies	well-being
11.	Um S.-B. [81]	Analysis of determinants of livability for the elderly in a smart city	age-friendly smart city; body sensor network; GWR; older adult classes; priority district; spatial weighting	Social studies and econometric models	well-being
12.	Zhang J.; Li L. [82]	Model for predicting life satisfaction among the elderly	Factor Analysis Dimensionality Reduction; Life Satisfaction Prediction Model; PSO Parameter Optimization; Smart Aging; Support Vector Machine	Social studies and econometric models	well-being
13.	Hu F.; Wen J.; Phau I.; Ying T.; Aston J.; Wang W. [83]	Identifying the role of tourism in smart aging	Age-friendly destinations; Ageism; Healthy aging; Healthy lifestyles; Human rights; Interdisciplinary literature review; Smart aging; Travel therapy	Literature review	well-being
14.	Jonek-Kowalska I. [84]	Confronting the availability of medical care with the needs of an aging society	age-friendly smart cities (SCs); aging of urban populations; city health care; human smart cities (SCs); sustainable smart cities (SCs)	Statistical analysis	well-being
15.	Shore L.; De Eyto A.; Kiernan L.; Bhaird D.N.A.; Connolly A.; White P.J.; Fahey T.; Moane S. [85]	Identification of areas for senior activation (mobility, public spaces, safety, social engagement, services, and amenities)	Co-design; Collaborative coalitions; Needs identification; Older adults; Product service systems	Social studies	City management
16.	Suopajärvi T. [86]	Experiencing smart urban solutions by seniors and their perception of themselves as smart citizens	Aging; Ethnographic composition; Feminist new materialism; Smart city; Urban assemblage	Social studies	City management
17.	Szczech-Pietkiewicz E.; Szweda-Lewandowska Z.; Felczak J.; Kubicki P. [87]	The use of ICT in coping with aging in urban environments	No data	Literature review, social studies	City management
18.	Suopajärvi T. [88]	Social workshops as a way of involving seniors in the design of public services in the city	Aging; Cultural anthropology; Ethnography; Feminist new materialism; Participatory action research; Smart city	Case study	City management
19.	Fan C.; Yu X.; Fan H. Y. [89]	Model for managing senior communities in smart cities	Smart Senior Citizens’ communities; social value	Social studies	City management

Nevertheless, publications in this area are somewhat overwhelming in both number and content, as they rarely portray older adults as anything more than technology testers. It is also worth noting that in the few studies incorporating social or humanistic perspectives, the main subjects tend to be the relatives or caregivers of seniors, rather than the seniors themselves. As a result, technologies are primarily used to mitigate the broadly defined “problems of old age.”

The authors therefore emphasize the need to include older adults as active participants in the design and testing of technologies intended for their use. This approach would make smart cities more sustainable, increase the visibility of seniors, and lead to a genuine improvement in their quality of life.

Figure 7 summarizes the qualitative analysis of the technological approach to senior policy in smart cities.

In the analyzed sub-area of technological research, considerations related to improving the quality of life of the elderly in smart cities also attract attention. This is a very important issue in the context of meeting the condition of inclusiveness. Some authors consider it directly, referring to the issue of age-related digital exclusion [67,68]. Some researchers analyze it indirectly, describing issues related to barriers to smart urban solutions [61] and the activation of older people to improve their well-being [44,45,46].

3.4. A Non-Technological Perspective on Senior Policy in Smart Cities

In the non-technological area of senior issues, which includes 19 publications (Table 3), issues related to quality of life and broadly understood well-being dominate. The view of the quality of life of the elderly in a smart city may concern individual issues, such as: Identifying the role of the digital revolution in smart aging [78,80], designing entertainment systems [79], and tourism for the elderly [83]. It may also include the characteristics of cities as senior-friendly places [72,73,77,81]. This research topic is significant due to its practical applications and potential to motivate cities to improve their efforts against age-based exclusion and discrimination.

The non-technological strand of research on smart aging also includes five publications describing city management. The low number of studies on this issue is somewhat worrying, as it indicates a lack of interest in city authorities’ activities for the elderly. However, one of the five articles mentioned follows the traditional path of analyzing the role of seniors in the city and concerns the use of ICT to improve quality of life [87]. Only three publications give older city residents a voice as full stakeholders in smart cities. Suopajärvi (2017, 2018) [86,88] proposes the use of workshops as a method of senior participation in city life and identifies their perception of themselves as SC residents. On the other hand, Shore et al. (2018) [85] undertake analyses aimed at defining areas for the activation of the elderly in smart cities, which is intended to strengthen their ties and role as full members of the local community. In the studies described, the analysis is also conducted in a bottom-up manner, which is rare and of particular cognitive value, as it allows us to learn about the opinions of those concerned about the quality of life in the city.

The management and non-technological research thread also includes one publication devoted directly to holistic diversity management. Fan et al. (2014) [89] present a model for managing senior communities in smart cities. However, this publication is a decade old, which illustrates the weak and distant interest in the aging of urban communities from the perspective of city authorities.

The presented publications undoubtedly contribute a valuable social perspective to the discussion on older adults in smart cities. However, they do not offer a holistic view of senior policy within the context of contemporary urban environments. It appears that this issue remains of limited interest to both researchers and urban decision-makers. This is particularly puzzling given that the challenges associated with population aging continue to intensify systematically.

There may be several reasons for this state of affairs. First, the topic is inherently complex—there are no ready-made solutions for aging, especially when it involves illnesses of both body and mind. Second, old age itself is not considered “attractive,” and thus is unlikely to draw the attention of observers or readers. Third, the smart city vision is often associated with the young and dynamic—so why burden it with the challenges of aging?

However, if we truly aim to create balanced smart cities, include all stakeholders in their development, and improve the quality of life for a significant portion of the local population, we must address the substantial research and practical gaps in discussions about older adults in the smart city context.

Within the senior-focused discourse, it is also worth paying attention to the positive activities of older adults, such as education, entertainment, tourism, sports, and recreation. Undoubtedly, the development of these areas contributes to increased life satisfaction and overall quality of life. Furthermore, significantly more attention should be devoted to senior policy as a coherent and long-term strategy. At present, references to this issue are difficult to find both in the academic literature and in municipal documentation.

Figure 8 summarizes the qualitative analysis of the non-technological approach to senior policy in smart cities.

4. Discussion

4.1. Critical Analysis of the Literature Review

Currently, in practice and in the literature on the subject, smart city is considered in six key research areas: Smart Living, Smart People, Smart Governance, Smart Mobility, Smart Environment, and Smart Economy [90,91]. The considerations presented above show that senior issues most often appear in the context of Smart Living and Smart Mobility [26,27,28,29,30,31,32,33,34,35,36,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65,66,67,68,69,70]. It mainly concerns the use of technological solutions to alleviate the health and mental problems of seniors. Therefore, in answer to the question posed in the title of this article, it can be said that seniors are primarily cared for by medical care and social assistance. These publications can therefore be seen as technology demonstrators potentially applicable within the smart city framework. However, the lack of social and humanistic dimensions may contribute to growing criticism of smart cities themselves—perceived as commercialized markets for sophisticated and modern inventions.

The vast majority of analyzed publications use a top-down research approach where seniors are primarily research subjects rather than active participants. This suggests that medical and social care systems are motivated by practical concerns about reducing the costs and challenges of an aging population rather than genuinely empowering older adults. In the face of rapidly declining birth rates and aging populations, such an approach is highly insufficient. It may lead to serious shortcomings in the planning of social and economic development in contemporary cities, as it signifies a disregard for mounting challenges.

The small number of publications in the social and humanities disciplines also suggests that the elderly have little chance of becoming full and equal stakeholders in smart cities, unlike young and healthy people (who are perceived as typical SC residents). Such an idealistic view of the urban community is unrealistic, dehumanizing, and exclusionary per se. The elderly are mainly associated with illness, isolation, mental health issues, and a need for medical care and social assistance. Of course, the deteriorating health condition of older adults is an undeniable fact, but it does not diminish their personhood. It is essential to seek both social and medical remedies—but these must be developed in consultation with, and with the participation of, the elderly themselves.

Obviously, the health problems associated with aging cannot be completely ignored, but they must be balanced by considerations of non-health aspects of quality of life in the city. Seniors can also be active stakeholders involved in management [86,88,89]. They can be active and participate in cultural life and enjoy tourist and entertainment attractions in the city [83,85]. They can also take advantage of lifelong learning opportunities. They can also be professionally active by becoming advisors or mentors for younger generations [65]. Therefore, the satisfaction and quality of life of the elderly should be considered and predicted [76,82].

Meanwhile, the literature review conducted in this article indicates a departure from optimistic visions of being a senior citizen in a smart city. Few publications can be placed within the framework of Smart People or Smart Governance [86,87,88,89], which means that other stakeholders, in particular municipal authorities, do not show excessive interest in older people. In the near future, an approach to planning life in a smart city that does not take into account the opinions and needs of older people may prove ineffective and inefficient, as seniors may constitute a significant, and in some regions a dominant, part of the urban community.

Interestingly, a technologically oriented approach to describing the role of seniors in smart cities, combined with abstraction from their needs and opinions, leads to the ineffectiveness of smart urban solutions [74]. This is a sign not only of ignorance, but also of waste and poor city management.

The lack of interest in the lives of older adults within the smart city framework appears surprising in light of the intensifying processes of population aging. These processes are most pronounced in Asia (Japan, South Korea) and Europe (Germany, Poland, Portugal, Italy). Many smart cities are located in these regions, yet there is still a lack of a comprehensive approach to senior policy—both at the research level and within institutional and governmental frameworks.

Nevertheless, it is worth noting certain thematic differences between European and Asian academic literature. In European publications, there is a stronger emphasis on technological solutions and medical care, whereas Asian literature more frequently highlights the role of family and interpersonal relationships. These distinctions likely stem from differing cultural traditions and societal values.

Under such conditions, we face not only a demographic crisis but also an organizational one, as pretending that the residents of smart cities are ‘forever young’ does nothing to change the facts or the reality. It is worth noting, however, that a significant portion of publications and references to the urban lives of older adults comes from regions most affected by population aging. This indicates that the problem has been recognized but not yet addressed in a comprehensive manner.

It is also worth mapping the main stakeholders who are either discussed or overlooked in the context of senior policy within the Smart City framework. Referring to the quintuple helix model, the following conclusions can be drawn:

• Local government—In the context of senior-related issues and their presence in urban governance, they are rarely involved or addressed. This indicates a lack of genuine interest in seniors as stakeholders in the urban environment. Their involvement is predominantly limited to the implementation of technological solutions in the urban context, while they more rarely act as initiators of senior-related policies or the programs and services developed within these frameworks.
• Entrepreneurs—Most often presented as providers of technology or recipients of medical care innovations. This group is relatively well represented.
• Universities and other research institutions—Acts as a source of technological concepts and new commercially oriented solutions dedicated to the health and well-being of older adults. These stakeholders are rarely acknowledged in their essential role as providers or facilitators of education, particularly with regard to older adults.
• Society—As representatives of the local community, older adults are most often framed as passive recipients of technological solutions, with limited opportunities to evaluate or actively participate in their co-creation. The literature also highlights the role of seniors’ relatives as individuals burdened with caregiving responsibilities and in need of technological support. However, a clear and explicit connection between technology and the human factor—a prerequisite for the effective functioning of economic helices—remains largely absent.
• Environmental organizations—A stakeholder absent from the discourse on aging and senior-related issues. This thus represents an underutilized potential, both in the literature and in practice.

The above considerations and observations clearly show that social and humanistic research on seniors in smart cities needs to be strengthened in terms of research and publications. Greater attention should also be paid to management methods and tools aimed at the full integration of older people into the urban community, including ways of preventing exclusion, activating them in their personal and professional lives, identifying their needs and expectations, and measuring their satisfaction and quality of life. All these issues should be analyzed and considered from a bottom-up approach involving older people. It is difficult to write about unrecognized emotions and attitudes. It is also difficult to effectively implement smart urban solutions dedicated to this social group.

4.2. Recommendations and Senior Policy Implications

Due to the lack of publications and conclusions concerning senior policy in smart cities aimed at the inclusion of elderly adults, the authors of the article have developed guidelines and recommendations in this area. These have been organized according to the subdomains of smart city analysis and are presented in

Table 4. Recomendaions to senior policy in Smart City.

Area	Recommendations
Smart Governance	Integrating senior-oriented actions into urban strategies. Participation of seniors in the development of urban planning documents (both strategic and operational). Providing training that enables seniors to use e-governance services and prevents their digital exclusion. Initiating social projects that integrate different age groups. Educating the urban community about initiatives supporting older adults, with particular focus on strengthening emotional and social relations. Assessment of seniors’ quality of life. Informing the senior community about initiatives aimed at improving their quality of life.
Smart Living	Development of technologies supporting health and care for eldery adults. Promoting age-friendly housing by integrating Smart Home technologies and ensuring access to both day and long-term care facilities tailored to the needs of the elderly population. Creating preferential conditions for seniors to access the city’s cultural, sports, and tourism offerings (e.g., senior cards, discounts).
Smart Environment	Developing systems that ensure the safety of eldery adults at home and in public spaces. Providing older adults with access to green recreational areas free from environmental pollution. Adapting urban municipal waste management systems to the needs of seniors.
Smart Mobility	Ensuring that all forms of urban transportation are accessible, safe, and user-friendly for eldery adults. Providing reduced-fare or free public transportation for seniors. Promoting a healthy lifestyle and physical activity regardless of age-related limitations. Adapting urban mobility applications to the needs and capabilities of older adults.
Smart People	Developing a municipal lifelong learning policy. Organizing courses and training programs to strengthen digital skills among seniors. Forging strategic partnerships with universities, adult education centers, and other learning institutions to promote inclusive educational programs tailored to the needs of older adults. Promoting intergenerational mentoring by encouraging older adults to share their expertise, life experience, and skills with younger generations as a means of fostering social cohesion and lifelong learning.
Smart Economy	Providing financial support to enable older adults to actively participate in cultural, social, and civic events and processes taking place across the city. Preventing economic and energy poverty among older adults. Preventing homelessness crises among eldery adults by monitoring their living conditions and providing access to social housing. Promoting the sharing economy as a way to optimize expenses while also fostering social interaction.

. A holistic senior policy should take all of the aforementioned areas into account.

As mentioned, the measures outlined in Table 3 should be embedded within a consistent and long-term senior policy framework, fully integrated into the broader smart city strategy. Fragmentary or ad hoc implementation would undermine their effectiveness and fail to address the structural needs of the aging urban population. It is also important that these actions do not focus solely on a single aspect of smart city development, as was the case in most of the publications analyzed in this article. Thus, technological advancement must be accompanied by a strong human dimension, ensuring that innovation serves inclusivity, empathy, and the well-being of all citizens.

An example of such comprehensive actions targeting older adults is the Spanish project Vincles BCN, implemented in Barcelona. It uses digital telecommunication technologies to strengthen seniors’ social participation and family connections [92,93].

Another noteworthy and comprehensive initiative targeting older adults is the Dutch project De Hogeweyk. This innovative model involves the creation of a village specifically designed for individuals with dementia, enabling them to live as normally and independently as possible—outside institutional isolation—while remaining under continuous supervision to ensure both medical standards and personal safety [92,94].

The ideas presented above are both creative and sustainable. Their implementation goes beyond technological solutions and gadgets, focusing instead on the empowerment of elderly adults. As a result, a genuine improvement in their quality of life becomes possible.

5. Conclusions

5.1. Synthesis of Literature Review Findings

The systematic review of the literature conducted in this article has identified two main areas of research related to senior issues. The first, clearly dominant area is technology, where authors focus on the use of IT and ICT in medical and social care for the elderly in smart cities. It is highly technical and mathematical, with seniors appearing mainly as recipients of smart urban solutions. This area therefore refers to the original concept of smart cities, in which development is driven primarily by modern technologies and the relationship between city authorities and the business environment.

The second research area, which is non-technological and enjoys much less interest, includes publications focusing primarily on the well-being of seniors in smart cities. Analyses conducted on the topic cover not only individual determinants of quality of life in cities, but also refer to the distinguishing features of senior-friendly cities.

City management in the context of senior issues is described very rarely. There are only a few interesting grassroots analyses of senior participation in city life and their role as full-fledged urban stakeholders. Nevertheless, only one publication contains model and holistic management recommendations aimed at empowering seniors and making them equal members of the smart city community.

The literature review conducted in this article identifies the main research gaps concerning senior issues in smart cities. These include the need to develop considerations and analyses involving:

• Social and humanistic issues;
• Those conducted from the perspective of seniors in smart cities (bottom-up analyses), focused on their needs, expectations, and quality of life;
• Non-medical aspects of the quality of life of older people in cities, enabling seniors to participate fully in urban life;
• In the area of city management, taking into account the inclusion of older people in both the decision-making process and the use and evaluation of smart city solutions.

5.2. Limitations and Directions for Future Research

The main limitation of the analysis carried out in the article is the narrowing of the research area to the literature on the subject, and thus a certain abstraction from the practice and reality of smart cities. It is therefore worthwhile in future research on aging in SCs to also consider municipal strategic and implementation documents, as well as case studies of good practices in the inclusion of seniors in smart city communities as full and equal local stakeholders.

As part of future research, it would be valuable to conduct an analysis of urban policy documents with a focus on senior-oriented strategies—not merely as isolated case studies. A thorough and broad review at the national or international level would enable a holistic understanding of the role of older adults in smart cities and support the development of a model strategy for their participation across the various smart city domains.

As part of the effort to empower older adults in smart cities, it is worth directly asking them to evaluate their quality of life in the urban environment. Such bottom-up and comprehensive studies are rarely conducted—either for management purposes or within academic research. As a result, we lack a full understanding of the needs, expectations, and satisfaction levels of the senior population.

It would also be worthwhile to conduct a comparative analysis of the development of senior policies in the context of the advancing aging of societies across different world regions. Such an approach would have both diagnostic and educational value.

In addition to comprehensive discussions, considerations regarding elderly adults in smart cities can also be embedded within specific, not necessarily technology-focused, areas of smart city development. Particularly interesting—and still underexplored—are domains such as Smart Economy, Smart Environment, and Smart People.