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Review

Smart City Technologies and Health Equity: A Review of Urban Health Outcomes and Sustainable Development (2019–2026)

by
Mehdi Rezaei
1,†,
Seungok An
2,†,
Ehsan Heidarzadeh
3 and
Ladan Rokni
4,*
1
Sogang Future Education Innovation Research Institute, Sogang University, Seoul 04107, Republic of Korea
2
Department of Special Physical Education, Yongin University, Yongin 17092, Republic of Korea
3
Department of Urban Planning, Faculty of Art and Architecture, Persian Gulf University, Bushehr 7516913817, Iran
4
Asia Contents Institute, Konkuk University, Seoul 05029, Republic of Korea
*
Author to whom correspondence should be addressed.
†
The two first authors (Mehdi Rezaei and Seungok An) contributed equally to this work.
Sustainability 2026, 18(17), 8864; https://doi.org/10.3390/su18178864 (registering DOI)
Submission received: 27 July 2026 / Revised: 22 August 2026 / Accepted: 24 August 2026 / Published: 29 August 2026
(This article belongs to the Special Issue Measuring What Matters: Outcomes of Smart-City Innovation for Sustainability)
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Abstract

This review examines how smart city technologies have influenced health equity in urban settings between 2019 and 2026, guided by a dual-lens framework that assesses both equity-related outcomes and the systemic factors enabling or constraining their realization. As cities increasingly turn to digital tools to strengthen healthcare delivery, it remains unclear whether these interventions narrow or widen existing health disparities. Drawing on interdisciplinary literature spanning public health, urban informatics, and digital governance, this synthesis finds that smart health initiatives have improved healthcare access for some underserved populations, but their overall effect on health equity remains modest, inconsistent, and highly dependent on local context. Persistent structural obstacles, including digital divides, socio-economic inequality, and fragmented governance, continue to limit equitable implementation, while institutional barriers emerge as the most widespread challenge. Conversely, people-centered design, participatory governance, inclusive digital infrastructure, and equity-sensitive policy frameworks stand out as critical enablers of more just outcomes. The review further identifies an underexplored link between environmental sustainability and smart city technology, showing that AI-driven tools addressing emissions and urban environmental quality can indirectly support more equitable health systems. Overall, the findings underscore that technological innovation alone is insufficient; realizing the equity potential of smart cities requires deliberate integration of social justice, environmental sustainability, and collaborative governance into digital health strategy and practice.

1. Introduction

Rapid urbanization has triggered the importance of addressing healthcare challenges and reducing persistent health disparities for city dwellers. With over 68% of the world’s population expected to live in urban areas by 2050 [1], cities’ design, governance, and technological infrastructure are increasingly recognized as critical determinants of health and well-being for citizens [2,3]. In this context, smart city technologies—ranging from telemedicine and environmental sensors to digital health platforms and AI-driven services—are often positioned as innovative solutions to improve health outcomes and enhance urban living conditions [4,5].
The concept of a smart city is multifaceted, typically encompassing the integration of information and communication technologies (ICTs) to enhance urban management, service delivery, sustainability, and citizen quality of life [5,6,7,8], clearly showing the multidimensional concept of smart cities. Smart cities leverage data and digital infrastructure to enable more responsive and efficient systems across various domains such as transportation, energy, education, and public health [9]. For instance, Internet of Things (IoT)-enabled multiagent frameworks have been applied to adaptive traffic management in urban environments, demonstrating how real-time data systems can optimize city-wide mobility, a domain with direct implications for environmental health and equitable access to services [10]. Key features of smart cities include the widespread use of sensors, real-time data analytics, IoT devices, artificial intelligence (AI), and cloud computing to monitor and manage city functions in real time [11]. From the public health perspective, these technologies might facilitate early disease detection, support remote healthcare delivery, and improve environmental health monitoring. This has led to the emergence of the concept of ‘smart health’, which refers to the delivery of health services through the digital infrastructure of smart cities [12].
In fact, smart health innovations are increasingly being integrated into urban systems. For instance, a systematic review identified IoT devices, Mobile Health (mHealth) applications, and artificial intelligence (AI) and data analysis as fundamental technologies for smart city healthcare services, highlighting that these technologies are enhancing healthcare delivery by driving real-time health monitoring, early disease detection, and increasing overall efficiency [13]. Similarly, the Smart City Pilot Policy in China significantly enhanced the efficiency and distribution of public health services by employing integrated data platforms and automated health governance frameworks [14]. The use of digital technologies in healthcare within smart cities, especially AI and machine learning, has also enabled personalized healthcare delivery and predictive diagnostics, thus expanding the role of urban infrastructure in supporting population health [15]. However, many of these applications are still in the early stages of development [16], and the implementation of smart city health technologies also raises concerns regarding data privacy, digital inequality, and governance; it also highlights ethical and operational risks. For instance, health equity concerns persist when digital health innovations are deployed in socially or economically marginalized communities [13,14]. However, the Urban Health Equity Assessment and Response Tool (Urban HEART) exemplified how ICT-supported urban health planning can guide more inclusive and just interventions, ensuring that smart innovations do not exacerbate existing disparities but rather help to mitigate them [17]. Additionally, the adoption of smart city services varied significantly across neighborhoods, with lower adoption rates in areas with lower digital proficiency and higher privacy concerns, indicating that such interventions may not effectively reach or benefit all segments of the urban population equally [18]. A systematic review revealed that among various smart city health interventions, few incorporated explicit equity considerations in their design or evaluation, highlighting a significant gap in addressing health disparities [12]. Therefore, it seems that despite these technological advancements, the impact of smart cities on health equity remains unevenly realized.
Many early smart city initiatives, characterized as “Smart City 1.0” [19], have prioritized technological innovation and economic efficiency, often driven by private sector agendas and top-down governance structures. These models have been criticized for marginalizing equity and social inclusion concerns, thereby risking the reinforcement of existing spatial and socio-economic disparities [9,12,19]. This adds a critical perspective on equity and social inclusion, highlighting how technology-oriented urban development may reproduce or reinforce existing spatial and socio-economic inequalities when unequal access, participation, and governance are not adequately addressed. In response to these limitations, an alternative “Smart City 2.0” paradigm has emerged [20,21], emphasizing citizen-centric planning and participatory governance. This approach integrates the social determinants of health, recognizing that smart technologies can contribute to health equity only when inclusively designed and equitably implemented [22,23]. By focusing on inclusive governance and public participation, Smart City 2.0 aims to shift the role of technology from a driver of innovation to a tool for improving social justice and population well-being. This concern is echoed in Southeast Asia, where smart city initiatives have been shown to reproduce existing inequalities and create new forms of digital exclusion, particularly for marginalized and vulnerable urban populations. The concept of “digital stratification” has been introduced to explain how smart cities create new social hierarchies based on digital access and engagement [3]. At a global scale, a systematic review identified six major structural barriers to justice in smart city development—institutional, legacy, economic, social, technical, and geographical—with institutional barriers being the most prevalent worldwide, underscoring that equity failures in smart cities are systemic rather than incidental [2].
Despite this conceptual evolution, empirical evidence on whether smart health interventions have effectively addressed health inequities in urban settings remains limited. Many implementations lack comprehensive equity evaluations or fail to prioritize the needs of underserved populations. This review builds on this evolving discourse by examining how smart city technologies have influenced health equity across diverse urban contexts from 2019 to 2026. It investigates whether and how digital health interventions have been deployed to address the health needs of marginalized urban populations. Furthermore, it explores the systemic enablers and barriers shaping the equitable implementation of smart health initiatives, considering infrastructure, governance, policy, and socio-cultural contexts. By synthesizing recent findings, this review aims to clarify the extent to which smart city technologies have led to tangible health equity outcomes. It also explores what/if structural changes are necessary to advance this goal. In doing so, the insights contribute to a growing body of scholarship that seeks to align the smart city agenda with global health equity goals.

Conceptual Framework

This review adopts a dual-lens conceptual framework to critically examine the relationship between smart city technologies and urban health equity, integrating two key analytical dimensions: (1) the degree to which smart city technologies contribute to health equity outcomes in urban settings, and (2) the systemic enablers and barriers that influence the equitable implementation of these technologies. The framework is situated at the intersection of public health equity, urban informatics, and digital governance, drawing from interdisciplinary scholarship on smart cities, social determinants of health, and equity-focused evaluation models (Figure 1).
We applied Braveman and Gruskin’s (2003) definition of health equity, which emphasizes fairness and justice in health opportunities and outcomes, especially for disadvantaged populations [24]. Within this scope, smart health technologies—defined as digital tools integrated into the infrastructure of smart cities to deliver or enhance health services [11]—are evaluated in terms of their capacity to reduce disparities in health access, quality, and outcomes. This includes technologies such as telemedicine, mHealth, AI-driven diagnostics, and IoT-enabled monitoring systems [14,15,16], which constitute the health-related applications of smart city technologies.
The framework also focuses on enabling and constraining contextual factors, considering the Urban Health Equity Assessment and Response Tool (Urban HEART), which advocates for data-driven, participatory, and equity-sensitive urban health planning [25]. This lens allows the review to assess whether smart city interventions align with broader public health goals and consider the socio-economic and environmental determinants that shape health inequities.

2. Materials and Methods

2.1. Review Approach

This literature review explored how smart city technologies are implemented in urban health systems and assessed their implications for health equity. The review approach was chosen for its flexibility in synthesizing interdisciplinary literature and capturing diverse forms of evidence from both public health and urban technology fields. Given the interdisciplinary scope of the literature (spanning public health, urban planning, and digital technology), this review also acknowledges the heterogeneity in study designs and outcome measures.

2.2. Search Strategy and Data Sources

The literature search was conducted using two major academic databases: PubMed and Scopus. These platforms were selected for their broad and complementary coverage of the peer-reviewed literature. PubMed is widely recognized as a premier biomedical database, particularly suited to capturing digital health and clinical studies, while Scopus offers comprehensive indexing of interdisciplinary publications relevant to urban planning, policy, and technology studies [26,27].
To capture recent advancements in digital health technologies and smart city innovations, a comprehensive literature search was conducted, covering publications from November 2019 to May 2026. This timeframe was selected as 2019 is recognized as a significant turning point for global technological integration, largely catalyzed by the recent pandemic. Figure 2 represents the distribution of the included studies by publication year.
The following search strings were applied: 1—(“smart city” AND “health”) AND (“Telehealth” OR “Telemedicine” OR “AI” OR “IoT” OR “big data”) AND (“implementation” OR “policy”) AND (“equity” OR “social justice”), 2—(“digital health” OR “telemedicine” OR “smart health technologies”) AND (“urban settings” OR “city health systems”) AND (“access” OR “barriers” OR “enablers”) AND (“equity” OR “inclusion”). This structured keyword strategy is consistent with best practices for literature reviews that aim to explore interdisciplinary themes [28,29]. Accordingly, the use of compound search terms and Boolean operators ensured the retrieval of studies that intersect technology, health, policy, and equity within urban environments.

2.3. Screening Process

The article identification and screening were guided by PRISMA 2020 reporting conventions, adapted for a non-systematic review (Figure 3). All 357 selected articles were initially screened based on their title and abstract. At this stage, articles were considered eligible if they contained relevant keywords, resulting in 68 articles for full-text assessment. Two authors independently screened the contents of 68 records against predefined operational relevance, including substantive relevance to smart city technologies in relation to health, policy, or equity/access in an urban context. Any disagreements between the reviewers were discussed and resolved through consultation with a third author to reach a consensus decision. Following the full-text relevance assessment, 22 articles were ultimately included in the review.
The contents were reviewed based on a dual-lens conceptual framework, encompassing the extent of health equity outcomes in smart health interventions and the enabling factors and barriers influencing equitable implementation of smart health interventions in urban contexts. During the review, selected studies were examined for their technological focus, implementation context, policy and governance elements, attention to health equity, access, or social inclusion, and identification of barriers and enablers.
The PRISMA diagram reflects the structure of this study and screening process. As shown, 357 unique records were screened by title/abstract, of which 289 were excluded as not relevant to the smart city health/equity focus; 68 full-text articles were then assessed for eligibility, leaving the final 22 studies included in the qualitative contents review.

3. Results

3.1. Contribution to Healthy Smart Cities

Not all research directly quantified the impact or contribution of smart city technologies on urban health equity [30,31,32,33], nor did it necessarily quantify the extent of improvement in urban health equity outcomes [34] (Table 1). While the potential for promising impact exists, the current evidence suggests that equity considerations have often been insufficiently addressed in the ‘design’ and ‘implementation’ of many smart city initiatives [13,35]. In fact, while equity is being considered in some smart city health interventions, a lack of practical evidence of their efficiency on urban health equity is still emerging [9].
Targeted Disease Management: Several articles directly focused on the contribution of health technologies by mentioning a specific health issue and diseases. By focusing on a smart system called ‘Remote Patient Monitoring (RPM)’ in regional Australia, researchers suggested the potential of digital health tools to address healthcare disparities in non-metropolitan settings [30]. Likewise, the application of digital health technologies for neglected tropical diseases was examined in various settings, including urban and rural ones. The authors noted the use of technologies like mHealth and eHealth for case detection, disease management, and treatment outcomes, suggesting a potential for technology to improve health services for neglected tropical diseases [34]. A telemedicine outreach model was implemented in underserved urban communities in West Baltimore, where a virtual hospital initiative proactively provided screening and health services via a mobile health clinic. The program facilitated increased access to healthcare services for a predominantly African American population with higher rates of chronic conditions like diabetes and hypertension, suggesting the efficiency of telemedicine in underserved urban settings, potentially contributing to health equity [36]. But another study evaluated the expansion of a Telehealth Program (TelePrEP) for HIV pre-exposure prophylaxis in small urban areas and demonstrated that while telehealth can expand access in urban contexts, it was insufficient to overcome racial disparities, indicating that technology alone may not fully address equity issues [37]. The potential of telemedicine was also discussed for buprenorphine to increase access to opioid use disorder treatment in both rural and urban settings [38], as well as for diabetes management, highlighting the potential of telemedicine to improve HbA1c levels, medication adherence, and timely care management support. The paper suggests the potential of remote healthcare for the management of chronic conditions [39]. The COVID-19 pandemic also accelerated the use of digital health technologies for monitoring and managing health conditions, although equitable access was not directly the main concern [39,40].
Healthcare Accessibility: Several studies discussed the issue from the perspective of healthcare accessibility. A study on telehealth in non-urban areas considered six dimensions of access and concluded that telehealth shows promise for improving healthcare access, but notes incomplete assessments of equity impacts [32]. An investigation on telemedicine in the UK found that it significantly improves access by reducing travel barriers and enhancing mental health services. While focused on rural areas, the paper implies that similar improvements and considerations for equity apply to urban contexts as well [40]. Likewise, IoT-enabled adaptive traffic management improved urban mobility, which directly led to equitable access to urban services and indirectly contributed to health equity [10]. However, another study noted the disparities in access to surgical care using mobile platforms, which were due to the limitation of a well-trained workforce and infrastructural gaps that hinder equity outcomes [45].
Environmental Sustainability and AI: AI played a crucial role in advancing urban environmental sustainability during the pandemic. By optimizing energy usage and reducing emissions, AI-driven solutions have not only fostered cleaner, healthier urban environments but also supported an indirect pathway to equity by improving the core environmental determinants of health in urban contexts [10,46]. Similarly, AI supported healthy smart city development by linking AI-driven sustainability with human well-being, providing a foundation for more equitable urban health governance [48]. Finally, a study of AI in metaverse environments for smart city health services contributes to healthy smart cities by proposing AI-enabled virtual health platforms that can improve healthcare access and potentially enhance equity [47]. However, concerns related to the digital divide and governance remain unresolved in these studies.
Urban Governance and Policy: The importance of integrating urban public health into urban planning was the main insight of some sources, in order to create healthy smart cities, for example, through implementing a data-driven approach [33], re-conceptualization of ‘digital divides’ in terms of socio-economic gradients [35], and policy changes to improve digital access and literacy, as well as pay parity for telehealth services [38]. Moreover, a study introduced a Civil City Framework for implementing nature-based smart innovations with a focus on the right to a healthy city. The framework proposes using various data collection methods, including health monitoring apps, to assess the impacts of interventions. This suggests a pathway for future improvements in urban health, potentially contributing to equity through community involvement and data-driven planning [42].
Therefore, the potential of smart cities (the application of digital technologies in urban planning) to transform healthcare was well discussed in the sources, specifically through enhanced access, improved health outcomes, reduced costs, and increased efficiency [13]. However, most studies focus on characterizing exposure to health determinants rather than the direct impact on population health [43,49]. Several sources critique the historical focus of smart city initiatives on technology and economic growth, often at the expense of social equity and public health. For instance, these initiatives may exacerbate existing divides, benefiting affluent populations while marginalizing vulnerable communities who are often disproportionately impacted [12,41]. Certain equity topics such as occupation, gender, religion, race, ethnicity, culture, language, and education were less featured in the literature [12,30,35,41]. Therefore, even though the equity considerations are being included in some interventions, many are in the early phases, and challenges related to the integration of social and environmental factors persist.

3.2. Enabling Factors and Barriers

As illustrated in Figure 4, various enabling factors and barriers influence the equitable implementation of smart health technologies in urban settings. These enabling factors are designed to integrate equity into the system’s core and establish a framework for ensuring equitable outcomes.

3.2.1. Enabling Factors

People-Centered Design and Targeted Outreach: To achieve more equitable health outcomes, a “people-first” approach is essential, prioritizing citizen well-being and the mitigation of social challenges over purely technological objectives [12]. Implementing this requires a deep understanding of diverse needs and preferences, which can be facilitated through feedback mechanisms [33,42] and the assessment of patient preferences across diverse demographic groups [44]. Research suggests that models must emphasize acceptability and adaptability to local settings to be effective [37].
Key determinants of health equity, including infrastructure, demographics, and social characteristics, must be integrated into smart city planning [12,31,44], particularly because these factors influence the accessibility and distribution of technology-enabled urban services and may shape health outcomes across different population groups. Social factors directly influence care preferences; for example, while some older patients may prioritize in-person visits, non-English speakers might prefer the convenience of telehealth [44]. Furthermore, while telemedicine can bridge geographical gaps, systemic social factors such as income and education remain primary drivers of accessibility [31]. Place of residence, socio-economic status, and social capital are frequently identified as critical equity considerations [12].
Ultimately, aligning smart city initiatives with social and democratic objectives is vital to addressing health disparities [41]. This involves proactively targeting underserved populations, including those in regional areas or those facing specific socio-economic disadvantages, to ensure equitable resource distribution [30,32,36,39], emphasizing equitable access to digital and urban health resources and the importance of addressing spatial and socio-economic disparities in technology-enabled service provision. Implementing proactive mobile health outreach strategies is a particularly effective way to engage residents who face significant barriers to traditional healthcare access [36].
Participatory Governance and Strategic Policy: Engaging citizens and local stakeholders in the co-creation of smart health technologies ensures solutions are contextually relevant and address the needs of diverse communities [12,42]. Facilitating equitable implementation requires participatory processes, community involvement, and the engagement of public health partners through multi-governance models [13,37,42]. Integrating public health perspectives, such as consistent patient–provider interactions and multidisciplinary collaboration, is essential [33,39]. Furthermore, collaboration between public health professionals and urban planners is vital to designing initiatives that prioritize health equity and improve outcomes [35,43], while data-driven approaches that integrate health and urban datasets foster sustainable progress [33].
These initiatives require comprehensive policy and governance frameworks that explicitly address equity and ethical considerations [13,30]. Effective governance must include coordinated policy changes, equitable resource allocation, and strategies to guarantee healthcare access, especially in resource-limited settings [30,39]. For instance, increasing access to opioid treatment demonstrates how policy-driven interventions—such as enhancing digital literacy and establishing pay parity for telehealth—are essential for ensuring equitable implementation and improving outcomes [38].
Robust Digital and Urban Infrastructure: Robust, accessible infrastructure, including reliable broadband and connectivity, is fundamental to the equitable deployment of digital health solutions, particularly in regional areas [13,39,40]. This encompasses essential digital healthcare systems and the implementation of telemedicine [13,39,45]. Beyond healthcare-specific tools, interconnected smart city infrastructure, such as adaptive traffic management, highlights how broader IoT applications can improve environmental health and population well-being [10]. Furthermore, advanced data analytics and real-time monitoring through mobile applications are essential for facilitating timely, equitable care [35].
Digital Literacy and Capacity Building: Technological infrastructure will not be effective unless it supports the appropriate usage of such facilities and users possess the skills to navigate them. Implementing programs to improve digital literacy across all population segments—especially among vulnerable groups such as older adults—is essential to ensure equitable access and utilization of smart health technologies [30,39]. Furthermore, combining these literacy efforts with targeted resource distribution is critical to maximizing the effectiveness of such interventions [40].

3.2.2. Friction Points (Barriers)

The resources also identify several significant barriers hindering equitable health access in urban settings.
Structural and Infrastructure Barriers: Disparities in IT infrastructure, device reliability, and affordability create a fundamental barrier to equitable smart health access [12,13,30,40]. The risk of uneven resource allocation often exacerbates existing health inequities [30]. Economic hurdles, such as high implementation costs, inequitable pricing, and limited public funding, are core drivers of exclusion, particularly in African and Southeast Asian urban contexts where infrastructure is disproportionately concentrated in affluent areas [3]. The barriers stemming from historical inequalities and exclusionary policies mean that without explicit intervention, smart technologies risk compounding past injustices rather than resolving them [2].
Socio-Technical and Literacy Barriers: Even when physical infrastructure is present, significant socio-technical hurdles prevent equitable utilization. Digital literacy deficits, language barriers, and cultural factors significantly impede equitable telehealth access [30,33,40]. A persistent challenge is the difficulty in engaging underserved populations when an overemphasis on technology neglects the social context, specific patient complexities, and the increased workload on healthcare providers [12,37,39]. Furthermore, socio-economic gradients and racial disparities heavily influence a user’s ability to navigate digital tools [35,38]. These challenges are worsened by technical barriers, such as algorithmic bias and insufficient transparency in AI-driven systems, which deepen digital exclusion for populations already facing socio-economic disadvantages [2].
Institutional, Legal and Governance Barriers: The equitable deployment of smart health technologies is significantly impeded by legal complications and a lack of clear regulatory frameworks [30,40]. This is compounded by “pilot-project syndrome,” where many interventions remain in early testing phases without robust evaluative designs, making long-term scalability and integration into existing public health infrastructure highly challenging [12,39]. Furthermore, governance models often prioritize economic benefits and technological efficiency over democratic participation and social impact [12,45]. Top-down technocratic governance, dominant in many smart cities, effectively filters out local community voices and fails to understand local needs, resulting in technologies that are not relevant or accessible to all [3,12,41].
Ethical, Trust and Privacy Barrier Concerns: The privacy and security of personal health data generate profound mistrust, making vulnerable populations reluctant to engage with smart technologies [13]. In certain urban contexts, the expansion of surveillance infrastructure disproportionately impacts marginalized groups, such as informal workers and migrants, who lack adequate legal protections [3]. When digital monitoring systems are perceived as surveillance-driven social control that might criminalize informal economic activities, it completely undermines the trust required for public health engagement [3]. Additionally, data collection methods risk imposing a “response burden” or inadvertently excluding participants based on age, gender, or socio-economic background, underscoring the urgent need for accessible communication and diverse feedback mechanisms [42].
Ultimately, a critical yet often overlooked challenge to equitable smart city health technologies is institutional and environmental sustainability. Misalignments between technological advancement and sustainable urban governance result in systems that are not resilient to future urban stressors like climate change, economic shifts, or population growth. Consequently, environmental justice concerns are gaining traction, emphasizing the need for initiatives that are both accessible and ecologically sound [41]. While AI-driven solutions have shown potential to bridge this gap by enhancing environmental sustainability in urban systems, their integration into health-focused frameworks remains limited [46]. Recent evidence confirms that AI’s impacts on environmental sustainability and human well-being are deeply intertwined, reinforcing the argument that digital health strategies cannot be designed in isolation from their broader ecological and social consequences [48].

4. Discussion

This review examined the contribution of smart technologies to urban health equity and explored the systemic enablers and barriers shaping their equitable deployment between 2019 and 2026. The findings reveal that while the digital transformation of urban health systems has accelerated considerably over this period, its realized impact on health equity outcomes remains limited, uneven, and highly context-dependent. The evidence base reflects a growing recognition that health equity must be integrated into smart city planning at the design stage [12,30,35,41]; however, practical evidence of equitable outcomes remains sparse, and a significant gap persists between the promise of smart health technologies and their demonstrated capacity to reduce health disparities in urban populations. This gap is not incidental but structurally embedded: comparative evidence from Southeast Asia confirms that smart city technologies reproduce existing inequalities and generate new forms of digital exclusion, particularly for marginalized groups [3], while a global analysis of smart city development identified six interconnected categories of structural barriers—institutional, legacy, economic, social, technical, and geographical—with institutional barriers being the most prevalent worldwide [2]. These findings underscore that achieving health equity in smart cities is inseparable from broader systemic reform and cannot be achieved through technological solutions alone.
The review confirms that advanced digital health tools have improved healthcare access for underserved communities. Remote patient monitoring programs in regional Australia demonstrated potential for reaching populations facing geographical disadvantages [30], while mobile telemedicine clinics in underserved urban areas expanded access to chronic disease screening [36]. Telehealth initiatives also broadened access to opioid use disorder treatment [38] and improved diabetes management outcomes [39]. At the same time, the evidence consistently shows that technology alone is insufficient to overcome deeply rooted inequities: the TelePrEP program expanded HIV prevention access but failed to eliminate racial disparities [37], and neighborhood-level analyses revealed that adoption of smart city services was systematically lower in areas with reduced digital proficiency and heightened privacy concerns [18]. This pattern demonstrates that a technology-driven approach without concurrent attention to social readiness, cultural context, and structural accessibility may unintentionally deepen existing inequalities. Equity dimensions remain underrepresented in the literature [12,30,35,41], reflecting a systemic blind spot in how smart health technologies are conceptualized and evaluated.
Beyond direct health services, smart city technologies indirectly drive health equity by improving physical and digital infrastructures. For instance, IoT traffic management enhances urban mobility, environmental health, and equitable access [10], while AI optimizes energy and curbs emissions to improve core environmental health determinants [46]. Because AI’s benefits to sustainability and human well-being are mutually reinforcing, smart city health governance must integrate both ecological and social goals [48]. Consequently, health equity frameworks must broaden to encompass these foundational systems, including mobility, energy, and environmental monitoring. Finally, while AI-powered metaverse environments offer a conceptual frontier for extending healthcare access, their actual equity implications—particularly regarding the digital divide and governance accountability—demand rigorous empirical evaluation [47].
The governance dimension emerges as perhaps the most decisive determinant of equitable smart health outcomes. The review finds that many early smart city initiatives—aligned with the “Smart City 1.0” paradigm [19]—prioritized technological efficiency and economic productivity at the expense of social inclusion, reinforcing spatial and socio-economic disparities rather than addressing them. The shift towards a “Smart City 2.0” model [20,21], which centers citizen participation, participatory governance, and explicit equity commitments, offers a more promising direction. However, evidence from Southeast Asia exposes a disconnect between the rhetoric and reality of inclusive governance: while digital platforms exist, public participation is frequently “tokenistic” and yields minimal policy impact [3]. Consequently, technocratic models that systematically exclude marginalized voices have driven measurable digital stratification, wherein smart city technologies forge new social hierarchies based on unequal digital access [3]. At the global level, achieving justice in smart city development requires attention to four interlocking dimensions: distributional justice (equitable health outcomes), procedural justice (inclusive governance processes), recognitional justice (acknowledging the diverse needs and identities of marginalized groups), and restorative justice (addressing historical and structural disadvantage) [2]. The dual-lens framework guiding this review aligns strongly with distributional and procedural justice; however, recognitional and restorative justice dimensions remain underexplored in smart health research and represent a critical priority for future inquiry.
Environmental sustainability constitutes an increasingly critical yet underappreciated dimension of health equity in smart cities. Long-term health equity outcomes are inseparable from the ecological conditions of urban environments. Smart health technologies should, therefore, be embedded within broader urban strategies that promote climate resilience, low-carbon digital infrastructure, and nature-based planning solutions. Sustainable urban design interventions, including green infrastructure, thermal comfort mapping [41], and real-time pollution monitoring, can mitigate the environmental health risks that fall most heavily on vulnerable communities. The evidence that AI simultaneously advances environmental sustainability and human well-being reinforces the case for an integrated “whole-of-system” approach that connects public health, environmental planning, and digital governance [48]. This perspective reframes smart city health equity not as a purely technological or social challenge, but as an ecological imperative requiring the co-design of digital and green urban infrastructure. Without this integration, digital health systems risk being environmentally unsustainable and socially inequitable, which means generating technological progress for the privileged while compounding ecological burdens for the disadvantaged.
Taken together, the findings of this review reinforce the need for equity-sensitive evaluation metrics, meaningful participatory governance, and sustained intersectoral collaboration to ensure that the digital transformation of urban health systems serves all residents equitably, especially the most disadvantaged. Without deliberate integration of social, ecological, and institutional considerations into smart city health planning, cities risk becoming technologically sophisticated yet fundamentally unjust: efficiently connected for the privileged and inaccessible for those most in need.

4.1. Limitations

This review is subject to several limitations that should be considered when interpreting the findings. First, the inclusion criteria restricted the scope to English-language articles published between November 2019 and May 2026. This boundary may have excluded significant case studies, policy reports, and gray literature. The rapidly evolving nature of the field means that emerging frameworks, such as the global justice analysis and regional stratification evidence, may require supplementation with policy documents [2,3]. Second, the studies were manually selected based on relevance to the smart city–health equity nexus rather than a quality score. Third, no critical appraisal tool (e.g., AMSTAR-2, MMAT) was applied to individual studies because the review synthesizes heterogeneous evidence types for which a single appraisal instrument was not uniformly applicable; in addition, the heterogeneity of study designs, technologies, and equity concepts across the included literature made direct comparisons challenging and limited the generalizability of certain findings, clarifying that the findings should be read as an indicative narrative synthesis rather than a quality-weighted evidence hierarchy. Larger-scale reviews of such literature might consider bibliometric mapping tools such as VOSviewer or Dimensions once the corpus size warrants network-level analysis. Fourth, the review relied on primary studies that, in many cases, lacked rigorous equity-specific evaluation designs; as a result, the conclusions drawn reflect the limitations of the existing evidence base, which continues to evolve. Finally, the evidence for emerging technologies such as AI applications in metaverse environments and IoT-enabled adaptive urban systems is addressed at a conceptual or early-implementation level, limiting the availability of longitudinal and real-world evidence regarding their longer-term implications for urban health and equity.

4.2. Practical Implications

Based on the findings of this review, the following recommendations are proposed to advance health equity through smart city technologies:
Institutionalize equity in digital health governance: Urban policymakers and planners should adopt governance frameworks that explicitly embed equity principles at every stage of smart health technology design. Participatory governance models that genuinely engage local communities, health professionals, and civil society actors—rather than token consultation processes—are essential to producing technologies that reflect and respond to the full diversity of urban populations. Accordingly, participation must be structurally embedded and meaningfully empowered.
Adopt a people-centered and proactive design approach: Smart health technologies must be designed from the outset around the needs, preferences, and constraints of diverse urban populations, with special attention to underserved, elderly, linguistically diverse, and socio-economically disadvantaged groups [12,30,36,44]. Feedback mechanisms, patient preference assessments, and community co-design processes should be incorporated throughout development and implementation cycles [33,42].
Invest in inclusive digital infrastructure and literacy: Equitable access to smart health technologies requires sustained investment in both physical digital infrastructure and in human digital capacity. Digital literacy programs targeting older adults, low-income populations, and non-English speakers are essential to ensure that infrastructure investment translates into genuine utilization and health benefit [30,32,40]. Broader IoT infrastructure, such as adaptive traffic management systems [10], should also be recognized as part of the equity-relevant smart city ecosystem, given its indirect contributions to health and urban accessibility.
Develop and apply equity-sensitive evaluation metrics: Health equity indicators should be systematically embedded in smart city health program monitoring frameworks from the outset, enabling assessment of reach, differential impact across population subgroups, and unintended consequences. Current evidence reveals a persistent absence of rigorous equity evaluations in smart health interventions [12,32].
Strengthening legal, ethical, and privacy protections: Clear, enforceable regulatory frameworks for data privacy, informed consent, and algorithmic transparency are urgently needed in digital health. This regulation is critical because smart city surveillance disproportionately harms marginalized groups like informal workers and migrants [3], while biased AI health systems can exacerbate digital exclusion [2]. Ultimately, building trust among vulnerable populations requires going beyond regulatory clarity to establish visible institutional accountability and community-controlled data governance.
Integrating environmental sustainability into smart health planning: Future smart city strategies must align digital health investments with environmental sustainability to promote both ecological and social equity. AI tools proven to reduce emissions and improve urban environmental health [46,48] should be integrated alongside traditional health technologies. Additionally, sustainable urban design elements—including green infrastructure, thermal planning, and low-carbon digital systems—must be prioritized as essential, co-equal components of an equitable health ecosystem [15,41].

5. Conclusions

The findings confirm that while digital health innovations have expanded considerably in scope and application, their contributions to advancing health equity remain limited, uneven, and highly contingent on the social, institutional, and governance contexts in which they are deployed.
Three overarching insights emerge from this synthesis. First, smart health technologies can contribute to equitable health outcomes only when they are designed and implemented with explicit attention to social determinants of health, inclusive accessibility, and the diverse needs of marginalized urban populations. Second, systemic enablers including participatory governance, robust and inclusive digital infrastructure, people-centered design, and equity-oriented policy frameworks are indispensable for overcoming the persistent barriers that prevent equitable implementation. Third, equity failures in smart cities are structurally generated rather than incidental. Institutional barriers remain a major obstacle to the development of just and inclusive smart cities, while differences in digital access and engagement can reinforce existing social hierarchies. These inequalities are closely linked to governance structures that fail to ensure equitable access to digital technologies and opportunities for participation.
This review also highlights an underappreciated dimension of smart city health equity: the interdependence of social and ecological justice. AI-driven applications that are relevant to environmental sustainability can strengthen the environmental conditions that support human health and well-being. Such environmental-based infrastructures might make indirect but meaningful contributions to more equitable urban health by improving the efficiency, accessibility, and responsiveness of urban services. These findings call for a “whole-of-system” approach to smart city health governance that integrates digital transformation, public health planning, and environmental sustainability as mutually reinforcing rather than competing priorities.
Emerging technologies at the frontier of this space hold potential to further expand health service access, but their equity implications require careful and proactive governance from the earliest stages of development. Achieving health equity in the smart city era demands more than technological innovation. It requires deliberate, sustained institutional commitment to the principles of justice, participation, inclusion, and shared well-being. The dual-lens framework applied in this review offers a replicable structure for future research seeking to evaluate the equity performance of smart health interventions across diverse urban settings. Future inquiry should prioritize the recognitional and restorative justice dimensions that remain underexplored in this field, apply longitudinal and disaggregated evaluation designs, and engage directly with the communities most affected by smart city health decisions.

Author Contributions

Conceptualization, M.R., L.R.; methodology, M.R., L.R., E.H. and S.A.; software, M.R., E.H.; validation, M.R., L.R., S.A.; formal analysis, M.R., E.H.; investigation, L.R. and M.R., E.H.; resources, L.R., M.R., S.A.; data curation, L.R., M.R.; writing—original draft preparation, L.R.; writing—review and editing, L.R.; visualization, M.R., E.H.; supervision, L.R. All authors have read and agreed to the published version of the manuscript.

Funding

This paper was supported by the KU Research Professor Program of Konkuk University.

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

No new data were created or analyzed in this study. Data sharing is not applicable to this article.

Conflicts of Interest

The authors declare no conflicts of interest.

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Figure 1. Conceptual framework of the study.
Figure 1. Conceptual framework of the study.
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Figure 2. Distribution of the 22 included studies by publication year (November 2019–May 2026).
Figure 2. Distribution of the 22 included studies by publication year (November 2019–May 2026).
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Figure 3. PRISMA-style flow diagram of the identification, screening, eligibility, and inclusion process.
Figure 3. PRISMA-style flow diagram of the identification, screening, eligibility, and inclusion process.
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Figure 4. Framework for promoting health equity through smart city technologies.
Figure 4. Framework for promoting health equity through smart city technologies.
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Table 1. Contribution of smart city technologies to urban health equity (2019–2026).
Table 1. Contribution of smart city technologies to urban health equity (2019–2026).
Ref.Technology or
Initiative		ContextKey Findings
[10]IoT-enabled adaptive traffic management (multiagent framework)Urban environments (mobility optimization)Improved urban mobility through real-time IoT data, with indirect benefits for environmental health and equitable access to urban services; indirect link to health equity; mobility focus does not directly address health disparities (equal access for all)
[12]Smart city interventionsMultiple urban contextsIncluded socio-economic and spatial equity variables in the interventions; no coverage of other equity dimensions
[13]Smart healthcare technologies (IoT, AI, mHealth)Global, with focus on developing nationsEnhanced efficiency and access in digital healthcare systems; risk of digital inequality; requires regulatory clarity and infrastructure
[30]Remote Patient Monitoring (RPM)Regional/urbanImproved healthcare access for underserved communities; primarily rural focus; urban equity impact inferred
[31]Macro-level socio-technical determinants in telemedicineUrban–rural comparisonsHighlighted how income and infrastructure influence digital health access
[32]Access dimensions of telehealthLow- and middle-income countriesIdentified barriers (affordability, literacy, accessibility) in telemedicine
[33]Data-informed urban health planningVietnam (urban planning)Advocated health-integrated urban design with smart tools (e.g., wearables, air monitors); traditional technocratic urban planning fails unless health metrics are embedded into smart city design frameworks
[34]mHealth and eHealth for NTDsUrban/ruralImproved disease detection and management
[35]Reframing digital divide in smart citiesUrban settingsEquity-focused model integrating digital infrastructure with healthy city principles; emphasized socio-economic gradients and institutional ICT capacity; conceptual commentary; no intervention evaluation
[36]Mobile telemedicine clinicUnderserved urban areasIncreased access for African American populations with chronic illnesses; context-specific
[37]TelePrEP programSmall urban areasExpanded HIV care access; did not specifically eliminate racial disparities
[38]Telemedicine for opioid use disorderRural/urban Expanded access to addiction treatment; equity outcomes not practically evaluated
[39]Telemedicine for diabetesGeneral populationImproved disease management and adherence; no explicitly assessment of urban equity impacts
[40]Telemedicine in rural UKRural UK settingsReduced travel barriers and improved access, especially for mental health; challenges in digital literacy and regulations
[41]Thermal comfort mappingUrban planningIdentified vulnerable zones for heat stress interventions; indirect link to health equity
[42]Civil City FrameworkEuropean citiesIntroduced equity-focused, community-based smart city governance; still at the theoretical or pilot level
[43]Deep learning for urban health mappingUrban environmentsLinked urban landscape features to health outcomes; focused on determinants
[44]Teledermatology
(hybrid vs. virtual-only models)		Urban populationsDirect access impact; demonstrated that integrating age-specific and language-tailored digital features can mitigate baseline barriers for older adults and non-English speakers; technology adoption and care-seeking preferences varied across demographic groups
[45]Surgical and diagnostic digital toolsSub-Saharan AfricaAddressed disparities in access to surgical care using mobile platforms; workforce limitations and infrastructural gaps hinder equity outcomes
[46]AI for environmental sustainabilityUrban settings (pandemic context)AI contributed to optimizing energy use and reducing emissions during the pandemic, supporting healthier urban environments indirectly; indirect pathway to equity through environmental improvement
[47]AI in metaverse environments for smart city health servicesGlobal; smart city urban health contextsProposed immersive AI-driven health platforms in smart city metaverse environments as an emerging avenue for expanding health service access and equity; largely conceptual; equity governance of metaverse health platforms not yet empirically evaluated; digital divide risks remain unaddressed
[48]AI impacts on environmental sustainability and human well-beingGlobal; urban and environmental contextsDemonstrated that AI’s environmental sustainability and human well-being effects are mutually reinforcing, supporting an integrated approach to equitable smart city health governance; broad scope; does not directly evaluate health equity outcomes in specific urban populations; lacks intervention-level analysis
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Rezaei, M.; An, S.; Heidarzadeh, E.; Rokni, L. Smart City Technologies and Health Equity: A Review of Urban Health Outcomes and Sustainable Development (2019–2026). Sustainability 2026, 18, 8864. https://doi.org/10.3390/su18178864

AMA Style

Rezaei M, An S, Heidarzadeh E, Rokni L. Smart City Technologies and Health Equity: A Review of Urban Health Outcomes and Sustainable Development (2019–2026). Sustainability. 2026; 18(17):8864. https://doi.org/10.3390/su18178864

Chicago/Turabian Style

Rezaei, Mehdi, Seungok An, Ehsan Heidarzadeh, and Ladan Rokni. 2026. "Smart City Technologies and Health Equity: A Review of Urban Health Outcomes and Sustainable Development (2019–2026)" Sustainability 18, no. 17: 8864. https://doi.org/10.3390/su18178864

APA Style

Rezaei, M., An, S., Heidarzadeh, E., & Rokni, L. (2026). Smart City Technologies and Health Equity: A Review of Urban Health Outcomes and Sustainable Development (2019–2026). Sustainability, 18(17), 8864. https://doi.org/10.3390/su18178864

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