Integrating City Master Plans with Sustainable and Smart Urban Development: A Systematic Literature Review

Abstract

Urban configurations have substantial impacts on lifestyles, behaviors, and people’s daily lives. Elaborating urban plans based on smart and sustainable initiatives is a challenging task as it encompasses numerous multidisciplinary premises due to the dynamics of the urban context. This research aims to conduct a systematic review of the literature in three axes: sustainable urban development, city master plans, and smart cities. From the portfolio of papers built, it was possible to map projects designed for sustainable urban development in order to verify the integration of these projects with city master plans, specifically for smart cities. The content analysis also sought to identify global regions that use robust models, their frameworks, and technologies for this purpose as a strategy to identify which research or frameworks can be replicated in the future, helping to develop city master plans for smart cities. Although some results were found, it was observed that there is a lack of studies integrating the topics of smart cities, sustainability, and city master plans in the same discussion. Few types of research involve the three themes or their full application, being mostly described in isolation. Thus, the originality of this study is filling this gap in the literature.

1. Introduction

The UN Sustainable Development Goals (SDGs) aim to foster inclusive and sustainable economic growth, full employment, and decent work for all, necessitating an open, rules-based, predictable, and non-discriminatory trade and financial system [1]. Urban centers, which concentrate significant resources and populations, play a crucial role in achieving these goals. Therefore, urban planning is increasingly challenging, requiring established cities to continuously consider their futures. Sustainable urban transformation depends on the collective efforts of numerous communities and regions worldwide [2].

In this sense, urban planning is a multidisciplinary and communicative practice that aims to create and stimulate livable cities and areas, making them sustainable, functional, and successful. It plays a key role in decision-making and public policy formulation [3]. SDG 11 is the first with an exclusively urban focus; its definition is to make cities inclusive, safe, resilient, and sustainable.

Research shows that in addition to effective planning, development needs to be smart, especially through the use of digital solutions that aim to improve the challenges of cities [4]. In this sense, the concept of smart cities has been widely adopted as a solution [5]. Thus, movements for smart cities are growing worldwide [6].

Regarding the economic context, smartness can be associated with qualities at the firm level, such as innovation, productivity, business intelligence, transformative capacity, and resilience, and taken to the community level, a number of institutional and structural aspects of urban development must be analysed [7].

From these perspectives, aiming to include economic development aspects within a responsible urban transformation, municipal policymakers need data to know where and how many people live in poverty and what their real needs are [8]. Concerning this issue, sustainability indicators are essential tools to support Sustainable Urban Development (SUD). They represent a key step in guiding the decision-making process by indicating the strengths and weaknesses of common sustainability indices [9].

In search of works related to smart cities, sustainability, and city master plans, we observed that the literature involving and integrating these themes is scarce. Few works involve the three themes or their full application, and a lot of this research addresses only one of them. Therefore, the main objective of this article is to conduct a systematic review for the development of sustainable city master plans in smart cities. As complementary objectives, this article will fill gaps in the literature, building knowledge about sustainable urban development projects, integrating these projects into city master plans for smart cities, and determining the regions that stand out in implementing the theme, levels of innovation, and which technologies are used. The contributions of this study are aimed at offering guidelines directing, supporting, and stimulating the development of sustainable projects in smart cities and improving the processes of urban planning for sustainable smart cities.

The following sections of this paper are organised as follows: Section 2 presents the methods used for conducting this research. Section 3 presents the theoretical framework, contextualising smart cities, SUD, urban planning, and city master plans. Section 4 presents the results of the portfolio analyses. Section 5 reports the discussion of the issues, presenting the trends and perspectives of sustainable smart cities and sustainable innovative strategies for city master plans in smart cities. The last section describes the concluding remarks, limitations, and the call for further works.

2. Materials and Methods

Elaboration of the Systematic Review of the Literature

The literature review was performed by applying the methodology Methodi Ordinatio [10,11]. This methodology enables the construction of portfolios of articles with scientific relevance, from the application of the InOrdinatio Equation (1), which orders the portfolio using three criteria: journal metrics (here identified as Impact Factor—IF), number of citations (Ci), and publication year.

Following the nine steps of Methodi Ordinatio, we have:

Steps 1, 2, 3, and 4: Definition of the initial research intention; preliminary exploratory search; definition of the search syntax; and final search and metadata collection in the databases, respectively. The initial intention of this research was to find articles addressing the topics “master plan” and “smart cities”, seeking to identify any linkage concerning the research theme. Subsequently, preliminary searches were conducted in different databases, using the following features: The databases Scopus, Web of Science, and Science Direct were chosen due to their large scope. The combination “e-urban planning” or “urban e-planning” or “city master planning” and “smart cities” were defined as main keywords, along with the Boolean operators of proximity (quotation marks and parentheses). The types of documents selected were articles, or review articles. The search was performed on the titles, abstract, and keywords (TAK), and no temporal delimitation was established as so to make sure we could go through all the literature on the major theme.

Table 1. Search syntax and raw search and article-collection results.

Keyword Combination	Scopus	Web of Science	Science Direct	Gross Total of Articles
(“e-urban planning” OR “urban e-planning” OR “city master planning”) AND “Cidades Inteligentes”	112	14	38	164

presents the search syntax and the raw results per database.

Step 5: Filtering procedures: articles from conferences, books, and book chapters were eliminated; and articles that address topics outside the scope of this research were eliminated by reading the title, abstract, and keywords. After applying the procedures, the number of papers remaining was 84.

Steps 6 and 7: Identifying the variables: journal metrics (IF), number of citations (Ci), and publication year: The variables “IF” and “publication year” are collected automatically by the software RankIn^® (first version), provided by Methodi Ordinatio [11] The number of citations is collected individually, partially automatically, by RankIn^®. After collecting the variables, the InOrdinatio Equation (1) was applied.

InOrdinatio 2.0 = {[Δ*(IF)] − [λ* (ResearchYear − PubYear CitedHalfLife)] + Ω* [Ci (ReseachYear + 1) − PubYear]}

(1)

Step 8: Finding the full version of the articles: All 84 final articles were found in their full versions.

Step 9: Final reading and analysis: For this step, a spreadsheet in Excel was prepared with a reading protocol that aimed to mine the desired information from the texts. The information was organised according to the following clusters: the objective of the article; the geographic region where the research was conducted; the type of research: quantitative, qualitative, or bibliographic review; the technology used in the article; the solution proposed; the model or framework used; and, finally, a subjective analysis of the main points of interconnection between the themes proposed for this research.

In order to organise the information extracted from the texts, three portfolios were elaborated: (i) Models for urban planning and sustainability; (ii) frameworks for urban planning and sustainability; and (iii) the iterative sustainable city master plan model for smart cities. The three portfolios were defined according to the main objectives of the article, which is to map the sustainable urban development projects encompassing the three themes.

The next section presents the results of the systematic review of the literature on theoretical concepts of sustainable urban planning, smart cities, and city master plans. The content was drawn from the three portfolios of articles.

3. Smart Cities: Concepts, Structure, and Planning towards Sustainability

In the literature, the smart cities theme has occupied a prominent place since several researchers have sought to apply the concepts of increasingly smart and sustainable cities. However, similar terms have been used by researchers without a standardisation of nomenclatures.

In order to standardise, organise, and implement the concept of smart cities, several organisations started to develop a series of smart standards, specifications, and guidelines related to cities, essentially: British Standards Institution (BSI), International Organization for Standardization (ISO), and International Telecommunication Union (ITU) [4]. However, standards that help the development of smart cities stand out, including: energy, urban mobility, water, infrastructure, safety, and health.

Building smart cities is an important direction of global urban development; it reflects the bright future of human life. Nevertheless, the promotion of social development is an aspect that is not present in the extant literature so far. In this sense, an updated review of infrastructure issues and challenges is highlighted by [12] and observed by [13].

The smart cities movement can be classified into three phases: the initial focus of smart cities was placed on building infrastructure to maximise commercial opportunities; later, the focus shifted to protecting human health, safety, and increasing operational efficiency; currently, smart cities are using technology to make cities more sustainable, attractive, and adaptable (M. Singh and Leena, 2020) [14].

The functional structure of smart cities, proposed by [7], is composed of six dimensions: people, environment, economy, governance, mobility, and life [7]. In turn, the classification of smart city service domains occurs in six categories: resources, transport, and mobility; construction and infrastructure; and housing, governance, economy, and education [5]. However, most smart city studies focus on traffic control and management, transportation network design, smart grid initiatives, Internet of Things (IoT) integration, big data, land-use development, and how processes of urbanisation affect long-term land use [12]. Therefore, in order to implement smart city projects, many cities nowadays have partnered with big technology companies like IBM and Cisco, which provide technology infrastructure and make cities attractive for investments based on a market-led agenda [15].

Urban planning is an academic subfield that is interdisciplinary regarding the several subfields of the social sciences and engineering. In this way, urban planning deals with the bridge between scientific and technical knowledge and actions in the public domain [16]. When planning a city, many concerns arise; for instance: environmental issues have become a worldwide concern [1]; eco-cities and low-carbon cities reflect two trends to promote urban sustainability [17]; and the planning role in designing green infrastructure through policies to educate the masses about the importance of green in urban areas [18], among others. In terms of the structural composition of urban planning, in short, there are four major divisions: governance and politics; economy and markets; housing and built; and natural environment [19]. Thus, achieving sustainability in smart cities requires an SUD-relevant approach involving a balanced approach to SUD; sociocultural awareness; urban expansion; urban economy development; transport; urban renewal; greenhouse gases (GHG); urbanism and vegetation; evaluation systems; city structure; and land use [20].

However, an important issue raised by [20] is the fact that approaches to SUD are multiple and complex, as the relevant issues are intertwined, and it is difficult to separate them from each other. Therefore, SUD is perceived as an improvement in the quality of life in a city, including ecological, cultural, political, institutional, social, and economic components [21].

In this sense, city master plans play a crucial role in the overall operation of the project and lay the groundwork for regulations and rules in the operation phase [22]. Municipal master plans (MMPs) are the main legal instrument that guides urban development, growth, and planning, and it is mandatory for cities with populations greater than 20,000 inhabitants [23]. However, compared to conventional new city master plans, green and low-carbon city master plans incorporate more focus on sustainability principles [17].

There are three main elements for preparing city master plans for smart cities: human capital, financial, and governance structures; physical, digital, and social infrastructures and regional regulation; and institutional and implementation development based on aspects of smart cities [6].

Keeping in mind the importance of integrating these aforementioned elements in a city master plan, the next section presents the results extracted from the portfolio, specifically, which are the models and frameworks extracted that can serve as a basis for new projects of sustainable smart cities, sustainable planning, and city master plans with such characteristics.

4. Results

This section is divided into four subsections. The first one (Section 4.1) presents the bibliometric analysis of the following clusters of information: co-occurrence of keywords and research that presents models or frameworks for urban planning. This analysis was performed on the three portfolios of articles. The second subsection (Section 4.2) presents the analysis of the models for urban planning and sustainability portfolios. Section 4.3 presents the analysis of the portfolio frameworks for urban planning and sustainability. Finally, Section 4.4 presents the analysis of the portfolio city master plans in smart and sustainable cities.

4.1. Bibliometric Analysis

The keyword co-occurrence map (Figure 1) was created with VosViewer, using the 84 articles in the final portfolio, with the following settings: text data; fields: title and abstract; total count; minimum number of occurrences of a term: 5. Figure 1 presents the co-occurrence map of keywords, in which the central axes of the research in the final portfolio can be seen.

The map of words and their connections prove that the portfolio is adherent to the aimed research intention. The second analysis aimed to identify the number of papers that presented models, frameworks, and conceptual frameworks. Portfolio projects by region are presented in Table 4.

Of the total portfolio (84 papers), 17 researchers presented frameworks, 22 researchers presented models, 3 researchers presented model and framework, 5 researchers presented conceptual frameworks, and 37 researchers presented other information that was not characterized as a model or framework. Through the analysis of the portfolio, it was possible to map which models and frameworks addressed the proposal of this study. Therefore, the significant models and frameworks for SUD, smart cities, and city master plans were mapped. This mapping helped in the construction of the model proposed in this work.

In the next subsection, the models and frameworks mapped in Table 4 are described.

4.2. Models for Urban Planning and Sustainability

In [22], a Geographically Weighted Regression (GWR) model used to identify statistically significant factors that influence Urban Heat Island (UHI) intensities in Brisbane is presented. Ref. [13] The Intelligenter Method is a model for the elaboration of smarter urban policies and regulations.

In [24], an evaluation model to measure the degree of success of a city’s smart growth plan is presented. In [5], a GLP-ESA-ACO coupling model is presented to optimise landscape-pattern allocation under the objective of ecological security and economic coordination. In [25], a hybrid weighting model for evaluating urban underground space resources is presented, integrating the classic entropy weighting method with the time-dimension-weighting method.

In [26], a smart energy-system model for smart cities is presented. In [27], multinomial logistic regression models are used to explore the relationships between urban growth patterns and urban planning in Shenzhen, China. In [28], a participatory design model for the process of urban transformation in Istanbul is presented. In [29], an integrated participatory model is presented, which uses the opportunities embedded in grassroots actions to foster the development of green infrastructure.

In [30], the use of the FUTURES (Future Urban–Regional Environment Simulation) model is presented to simulate urban expansion and assess the impacts on ecosystem services in Hohhot, China. In [31], a different model is presented to explore the relationship between smart cities and clean energy development, using panel data from prefecture-level cities in China from 2009 to 2019.

Table 2. Summary of the models found on the portfolio model application.

Model	Application/Description	Authors
Geographically Weighted Regression (GWR)	Identification of factors influencing Urban Heat Island (UHI) intensities in Brisbane	[22]
Intelligenter Method	Elaboration of smarter urban policies and regulations	[13]
Evaluation model	Measurement of the degree of success of a city’s smart growth plan	[24]
GLP-ESA-ACO coupling model	Optimization of landscape-pattern allocation under the objective of ecological security and economic coordination	[5]
Hybrid weighting model	Evaluation of urban underground space resources using entropy weighting method and time-dimension-weighting method	[25]
Smart energy-system model	Development of smart energy systems for smart cities	[26]
Multinomial logistic regression models	Exploration of relationships between urban growth patterns and urban planning in Shenzhen, China	[27]
Participatory design model	Facilitation of urban transformation process in Istanbul	[28]
Integrated participatory model	Utilisation of grassroots actions to foster the development of green infrastructure	[29]
FUTURES model	Simulation of urban expansion and assessment of impacts on ecosystem services in Hohhot, China	[30]
Panel data model	Exploration of relationship between smart cities and clean energy development using data from prefecture-level cities	[31]

summarises the models.

Analysing the models presented can conclude that they present several conclusions regarding their applications and implications. They encompass a wide range of approaches, including statistical regression models like Geographically Weighted Regression (GWR), optimization models such as the GLP-ESA-ACO coupling model, and simulation models like the FUTURES model. This diversity reflects the multidisciplinary nature of urban planning and sustainability research.

Many of the models are specifically designed to address challenges related to smart cities and sustainability. For instance, the Intelligenter Method and the Smart energy-system model target the development of smarter urban policies and energy systems, respectively, to enhance sustainability and efficiency in urban environments.

Other models introduce innovative methodologies to tackle complex urban issues. For example, the hybrid weighting model integrates different weighting methods to evaluate urban underground space resources, while the participatory design model emphasises community involvement in the urban transformation process.

Each model addresses practical applications relevant to urban planning and sustainability. From evaluating the success of smart growth plans to optimising landscape patterns for ecological security, these models provide valuable tools for decision-makers and urban planners to enhance the sustainability and livability of cities.

It is worth noting that some models, like the Geographically Weighted Regression (GWR), may be tailored to specific geographical contexts. This highlights the importance of considering regional variations and local conditions when implementing urban planning strategies.

Many of the models require interdisciplinary collaboration, drawing insights from fields such as geography, ecology, economics, and social sciences. This interdisciplinary approach is crucial for addressing the multifaceted challenges of urban sustainability effectively.

4.3. Frameworks for Urban Planning and Sustainability

In [32], a framework that measures the intelligence indices of different subsystems of the urban transport system is presented. In [17], a framework that shows the relationship between city master plans and the current reality of new cities is presented. In [4], a conceptual framework for aligning infrastructure assets with citizen requirements within a smart city framework is presented.

In [33], the “Knowledge Product Evaluation (KnoPE) Framework” is presented as a tool to evaluate knowledge products developed to support decision-making in urban resilience. In [34], a framework to compare the smart city services offered by the National Strategic Smart Cities Program of South Korea (NSSP) with the services offered in 15 smart cities in Europe, Asia, and North America is presented. The framework classifies smart city services into six domains: natural resources and energy, transport and mobility, building and infrastructure, life, governance, economy, and human resources. These domains are subdivided into 20 subdomains to provide a more detailed analysis of the services offered. In [35], a framework for the planning and design of an urban flood ecosystem is presented, aiming at the enrichment of smart cities.

In [36], a framework to develop an index of Urban Ecological Efficiency (UEE) in the metropolitan area of Kolkata, India, from 2000 to 2020 is presented.

As we can infer from

Table 3. Summary of the frameworks found on the portfolio.

Framework	Description	Authors
Urban Transport Intelligence Indices Framework	Measures the intelligence indices of different subsystems of the urban transport system	[32]
Relationship Framework between City Master Plans and New Cities	Illustrates the relationship between city master plans and the current reality of new cities	[17]
Infrastructure Alignment Conceptual Framework for Smart Cities	Conceptual framework designed to align infrastructure assets with citizen requirements within smart cities	[4]
Knowledge Product Evaluation (KnoPE) Framework	Tool for evaluating knowledge products developed to support decision-making in urban resilience	[33]
Smart City Services Comparison Framework	Framework comparing smart city services between the National Strategic Smart Cities Program of South Korea (NSSP) and 15 Smart Cities globally	[34]
Urban Flood Ecosystem Planning and Design Framework	Framework for planning and designing urban flood ecosystems with the aim of enriching smart cities	[35]
Index of Urban Ecological Efficiency (UEE) Development Framework	Framework for developing an index of Urban Ecological Efficiency (UEE) in Kolkata, India, from 2000 to 2020	[36]
Sustainable Urban Development Framework	General framework addressing 10 topics relevant to sustainable urban development	[20]

, while many of them address elements of sustainability, there are areas where they could be further developed or expanded. These aspects are better detailed in the sequence:

• Social Equity and Inclusivity: While some frameworks touch upon citizen requirements and smart city services, there is often a lack of emphasis on social equity and inclusivity. Sustainable urban development should prioritise the needs of all residents, including marginalised communities, and ensure equitable access to resources and services. Integrating social equity considerations more explicitly into the frameworks would enhance their comprehensiveness and relevance;
• Environmental Justice: Few frameworks explicitly address environmental justice, which involves the fair distribution of environmental benefits and burdens across different social groups. Urban development initiatives should consider the potential environmental impacts on vulnerable communities and strive to mitigate disparities. Incorporating environmental justice principles into the frameworks would strengthen their sustainability focus and contribute to more equitable outcomes;
• Resilience to Climate Change: While resilience is a common theme in some frameworks, there is often limited emphasis on resilience to climate change specifically. Due to the increasing frequency and severity of climate-related events, urban planning frameworks should prioritise measures to enhance cities resilience to climate change impacts, such as flooding, extreme heat, and sea-level rise. Integrating climate resilience considerations into the frameworks would enhance their relevance in the face of growing climate risks;
• Cultural Preservation and Heritage: Many frameworks focus primarily on technical and infrastructural aspects of urban planning, overlooking the importance of cultural preservation and heritage conservation. Sustainable urban development should respect and integrate local cultures, traditions, and heritage assets into planning and design processes. Including cultural preservation considerations in the frameworks would promote more holistic and culturally sensitive approaches to urban development;
• Long-Term Sustainability Metrics: While some frameworks include evaluation and assessment tools, there is often a lack of emphasis on long-term sustainability metrics and indicators. Sustainable urban development requires monitoring and measuring progress towards sustainability goals over time, using robust indicators that capture social, environmental, and economic dimensions. Enhancing the frameworks with comprehensive sustainability metrics would enable more rigorous monitoring and evaluation of urban sustainability outcomes;
• Cross-Sectoral Collaboration: While some frameworks acknowledge the importance of interdisciplinary collaboration, there is often limited integration of perspectives from diverse sectors such as public health, education, and governance. Sustainable urban development requires cross-sectoral collaboration and coordination to address complex challenges comprehensively. Strengthening the frameworks’ emphasis on cross-sectoral collaboration would foster more integrated and holistic approaches to urban planning and sustainability.

4.4. City Master Plans in Smart and Sustainable Cities

In this section, the results are presented according to the regions, countries, and cities that have developed proposals or projects related to master plans in smart and sustainable cities. Fifty-eight projects involving the main themes of this study were found. Table 4 presents the relevant project information extracted from the final portfolio.

Table 4. Mapping the particularities of each project.

Region	Country	Project	Reference	Number of Articles
Asia	China	Framework that presents the relationship between the e-urban plan and the current reality of new cities.	[17]	12
		It presents an optimised GLP-ESA-ACO coupling model for landscape pattern allocation, aiming at ecological security and economic coordination.	[5]
		SLEUTH model is used to predict the future of land use. Predicts a population prediction model.	[37]
		Hybrid weighting model for evaluating urban underground space resources, integrating the classic entropy weighting method with the time dimension method.	[25]
		It presents multinomial logistic regression models to explore the relationships between urban growth patterns and urban planning in Shenzhen.	[27]
		Framework for planning and designing an urban flood ecosystem.	[35]
		Model to characterise the urban spatial structure using data from taxi trips.	[38]
		Conceptual framework for illustrating ideas.	[39]
		Citizen participation in the development of the Shanghai 2035 Master Plan.	[40]
		FUTURES model for simulating urban sprawl and assessing impacts on ecosystem services in Hohhot, China.	[30]
		Framework to explain the failure of urban planning in China.	[41]
		Differences model to explore the relationship between smart cities and clean energy development. We used panel data from prefecture-level cities in China from 2009 to 2019.	[31]
	Jordan	Criterion to help select the ideal site for a sustainable city in Jordan.	[42]	4
	Singapore	New paradigm of integrated urban mobility planning is derived from a different concept of a city centred on accessibility.	[43]
	Vietnam	Smart energy-system model for smart cities.	[26]
	Saudi Arabia	Willingness of the public to participate in the urban planning process through technologies applied in Saudi Arabia. Discussion of the implications of these findings for inclusive urban planning.	[44]
South Asia	India	Discusses approaches and solutions for transport planning (GIFT City).	[45]	6
		Taxonomy of mixed land-use types presents indicators and practice parameters.	[46]
		Typology of smart city approaches based on analysis of smart city policy documents.	[47]
		Systems-thinking approach to examine the concept of smart cities, and it proposes a conclusive definition.	[48]
		It uses multi-temporal satellite imagery and road network data to examine urban growth and its relationship to the transport network.	[49]
		Framework for the development of an index of urban ecological efficiency (UEE) in the metropolitan area of Kolkata, India, from 2000 to 2020.	[36]
Far East of Asia	South Korea	Transit Oriented Development (TOD) and Traditional Neighborhood Development (TND) models as frameworks to plan the urban structure of Sejong City.	[50]	5
		Co-creative planning approach based on design thinking for regional innovation in declining industrial areas.	[51]
		System dynamics model that analyses the effect of smart city planning in the urban region of Anyang.	[52]
		Comparative framework between the smart city services offered by the South Korea National Strategic Smart Cities Program (NSSP) with other regions.	[53]
		Gender analysis model is applied in three phases: planning phase, implementation phase, and post-occupation evaluation phase.	[54]
West Asia	Abu Dhabi	Masdar City is an example of an eco-city. Assessment of its effectiveness in terms of social sustainability.	[55]	1
Central Asia	Afghanistan	Travel demand model forecasts using the traditional four-step method to assess the current number of passengers on public transport in 22 districts.	[56]	1
Southeast Asia	Iran	Theoretical framework for the design process.	[1]	2
		Interviews with different planning actors and public and private sector planners, investigating what they perceive as barriers to employing e-participation in the Iranian planning system.	[57]
Asia and Oceania	Indonesia	Parametric simulation as a tool to examine the relationship between lot characters and regulations in a commercial corridor.	[58]	3
		Evaluation of six large cities in Indonesia in the development of smart city projects.	[6]
		Geotext data-processing framework, which consists of four workflows: data retrieval, data analysis, data evaluation, and data visualisation.	[59]
Oceania	Australia	Geographically Weighted Regression (GWR) model to identify statistically significant factors influencing UHI intensities in Brisbane.	[22]	3
	New Zealand	Theoretical framework that positions spatial decision support tools (SDST) in relation to planning processes and results.	[60]
	Australia	Introduction of the iHUB platform, Australia’s national urban research and development platform.	[61]
Europe	Spain	Intelligenter Method as a model for making smarter urban policies and regulations.	[13]	4
	Germany	Various approaches and strategies for improving sustainable urban mobility in German cities.	[62]
	Hungary	Different trends in urban planning based on the use of ICT.	[63]
	Türkiye	Participatory design model for the urban transformation process in Istanbul.	[28]
Northern Europe	Finland	It discusses the idea of a city as a platform, addressing how cities support innovation by creating smart environments.	[2]	5
		It discusses the role of participatory innovation platforms in urban economic development.	[7]
		It presents a crowdsourcing model that combines different data sources.	[64]
		It presents an exploratory analysis guided by digital urban platforms. It discusses platformization and its impact on urban planning.	[65]
		City-planning tool to measure the spatial distribution of urban green space diversity within a city.	[66]
Western Europe	UK	Conceptual framework for aligning infrastructure assets with citizen requirements in smart cities.	[4]	2
		Framework based on habitat–species models to predict bird counts in urban development plans.	[67]
Central Europe	Slovakia	Participatory integrated model that uses opportunities incorporated in grassroots actions to foster the development of green infrastructure.	[29]	1
North America	USA	It discusses the use of a set of highway air rights and transit-oriented development as a smart growth strategy.	[68]	3
		Framework Knowledge Product Evaluation (KnoPE) tool to evaluate knowledge products developed to support decision-making.	[33]
		Model called emotional data framework for the use of emotional data in the governance of smart cities.	[69]
South America	Brazil	It presents the concept of human mobility transition, relating ideas of major changes in mobility dynamics and how these affect the constitution and development of urban settlements.	[70]	4
	Brazil	It discusses the importance of articulations in the anti-asylum struggle with participatory master plans in Brazilian cities.	[23]
	Brazil	Procedural model for understanding e-participation practices and the mechanisms used over time to influence decision-making.	[71]
	Chile	RayMan model for conducting a parametric study in two urban development schemes: filling and expansion.	[72]
East Africa	Ethiopia	Identification of factors that impede the implementation of the urban structure plan in Nekemte, Ethiopia.	[73]	1

Table 4. Mapping the particularities of each project.

Region	Country	Project	Reference	Number of Articles
Asia	China	Framework that presents the relationship between the e-urban plan and the current reality of new cities.	[17]	12
		It presents an optimised GLP-ESA-ACO coupling model for landscape pattern allocation, aiming at ecological security and economic coordination.	[5]
		SLEUTH model is used to predict the future of land use. Predicts a population prediction model.	[37]
		Hybrid weighting model for evaluating urban underground space resources, integrating the classic entropy weighting method with the time dimension method.	[25]
		It presents multinomial logistic regression models to explore the relationships between urban growth patterns and urban planning in Shenzhen.	[27]
		Framework for planning and designing an urban flood ecosystem.	[35]
		Model to characterise the urban spatial structure using data from taxi trips.	[38]
		Conceptual framework for illustrating ideas.	[39]
		Citizen participation in the development of the Shanghai 2035 Master Plan.	[40]
		FUTURES model for simulating urban sprawl and assessing impacts on ecosystem services in Hohhot, China.	[30]
		Framework to explain the failure of urban planning in China.	[41]
		Differences model to explore the relationship between smart cities and clean energy development. We used panel data from prefecture-level cities in China from 2009 to 2019.	[31]
	Jordan	Criterion to help select the ideal site for a sustainable city in Jordan.	[42]	4
	Singapore	New paradigm of integrated urban mobility planning is derived from a different concept of a city centred on accessibility.	[43]
	Vietnam	Smart energy-system model for smart cities.	[26]
	Saudi Arabia	Willingness of the public to participate in the urban planning process through technologies applied in Saudi Arabia. Discussion of the implications of these findings for inclusive urban planning.	[44]
South Asia	India	Discusses approaches and solutions for transport planning (GIFT City).	[45]	6
		Taxonomy of mixed land-use types presents indicators and practice parameters.	[46]
		Typology of smart city approaches based on analysis of smart city policy documents.	[47]
		Systems-thinking approach to examine the concept of smart cities, and it proposes a conclusive definition.	[48]
		It uses multi-temporal satellite imagery and road network data to examine urban growth and its relationship to the transport network.	[49]
		Framework for the development of an index of urban ecological efficiency (UEE) in the metropolitan area of Kolkata, India, from 2000 to 2020.	[36]
Far East of Asia	South Korea	Transit Oriented Development (TOD) and Traditional Neighborhood Development (TND) models as frameworks to plan the urban structure of Sejong City.	[50]	5
		Co-creative planning approach based on design thinking for regional innovation in declining industrial areas.	[51]
		System dynamics model that analyses the effect of smart city planning in the urban region of Anyang.	[52]
		Comparative framework between the smart city services offered by the South Korea National Strategic Smart Cities Program (NSSP) with other regions.	[53]
		Gender analysis model is applied in three phases: planning phase, implementation phase, and post-occupation evaluation phase.	[54]
West Asia	Abu Dhabi	Masdar City is an example of an eco-city. Assessment of its effectiveness in terms of social sustainability.	[55]	1
Central Asia	Afghanistan	Travel demand model forecasts using the traditional four-step method to assess the current number of passengers on public transport in 22 districts.	[56]	1
Southeast Asia	Iran	Theoretical framework for the design process.	[1]	2
		Interviews with different planning actors and public and private sector planners, investigating what they perceive as barriers to employing e-participation in the Iranian planning system.	[57]
Asia and Oceania	Indonesia	Parametric simulation as a tool to examine the relationship between lot characters and regulations in a commercial corridor.	[58]	3
		Evaluation of six large cities in Indonesia in the development of smart city projects.	[6]
		Geotext data-processing framework, which consists of four workflows: data retrieval, data analysis, data evaluation, and data visualisation.	[59]
Oceania	Australia	Geographically Weighted Regression (GWR) model to identify statistically significant factors influencing UHI intensities in Brisbane.	[22]	3
	New Zealand	Theoretical framework that positions spatial decision support tools (SDST) in relation to planning processes and results.	[60]
	Australia	Introduction of the iHUB platform, Australia’s national urban research and development platform.	[61]
Europe	Spain	Intelligenter Method as a model for making smarter urban policies and regulations.	[13]	4
	Germany	Various approaches and strategies for improving sustainable urban mobility in German cities.	[62]
	Hungary	Different trends in urban planning based on the use of ICT.	[63]
	Türkiye	Participatory design model for the urban transformation process in Istanbul.	[28]
Northern Europe	Finland	It discusses the idea of a city as a platform, addressing how cities support innovation by creating smart environments.	[2]	5
		It discusses the role of participatory innovation platforms in urban economic development.	[7]
		It presents a crowdsourcing model that combines different data sources.	[64]
		It presents an exploratory analysis guided by digital urban platforms. It discusses platformization and its impact on urban planning.	[65]
		City-planning tool to measure the spatial distribution of urban green space diversity within a city.	[66]
Western Europe	UK	Conceptual framework for aligning infrastructure assets with citizen requirements in smart cities.	[4]	2
		Framework based on habitat–species models to predict bird counts in urban development plans.	[67]
Central Europe	Slovakia	Participatory integrated model that uses opportunities incorporated in grassroots actions to foster the development of green infrastructure.	[29]	1
North America	USA	It discusses the use of a set of highway air rights and transit-oriented development as a smart growth strategy.	[68]	3
		Framework Knowledge Product Evaluation (KnoPE) tool to evaluate knowledge products developed to support decision-making.	[33]
		Model called emotional data framework for the use of emotional data in the governance of smart cities.	[69]
South America	Brazil	It presents the concept of human mobility transition, relating ideas of major changes in mobility dynamics and how these affect the constitution and development of urban settlements.	[70]	4
	Brazil	It discusses the importance of articulations in the anti-asylum struggle with participatory master plans in Brazilian cities.	[23]
	Brazil	Procedural model for understanding e-participation practices and the mechanisms used over time to influence decision-making.	[71]
	Chile	RayMan model for conducting a parametric study in two urban development schemes: filling and expansion.	[72]
East Africa	Ethiopia	Identification of factors that impede the implementation of the urban structure plan in Nekemte, Ethiopia.	[73]	1

It can be seen through Table 4 that of the 58 projects that involve the main themes of this study, most of them are located in Asia, mainly China, India, and South Korea, adding up to 24 projects; 12 projects in the other regions of Asia: Singapore, Vietnam, Iran, Saudi Arabia, Afghanistan, Jordan, and Abu Dhabi. On the European continent, projects were identified in Finland, Germany, Italy, Spain, United Kingdom, France, Hungary, and Turkey. In North America and South America, projects were located in the USA and Brazil and Chile, respectively. Projects were also located in Oceania (Indonesia, Australia, and New Zealand). On the African continent, projects were identified in Nigeria, Kenya, and Ethiopia.

An interesting factor identified in the analysis is that most of the projects involving smart cities and SUD are in developing countries, meeting the eighth and eleventh UN Sustainable Development Goals (SDG), promoting sustained economic growth and sustainable, full, and productive employment and decent work for all, and making cities inclusive, safe, resilient, and sustainable, respectively. However, much needs to be done to fully achieve the two SDGs.

The conclusions from this analysis can be grouped in four clusters of information:

• Cluster 1. Geographic Distribution of Projects: The analysis reveals a diverse geographic distribution of projects related to smart cities and sustainable urban development (SUD). Asia emerges as a significant hub for such projects, with China, India, and South Korea leading in the number of initiatives. Other regions of Asia, including Singapore, Vietnam, Iran, Saudi Arabia, Afghanistan, Jordan, and Abu Dhabi, also contribute to the pool of projects. Europe hosts several projects across countries, such as Finland, Germany, Italy, Spain, the United Kingdom, France, Hungary, and Turkey. North America (USA), South America (Brazil and Chile), and Oceania (Indonesia, Australia, and New Zealand) also have notable representation. Africa, particularly Nigeria, Kenya, and Ethiopia, demonstrates some engagement in smart cities and SUD projects, albeit to a lesser extent compared to other continents;
• Cluster 2. Emphasis on Developing Countries: A noteworthy observation is the concentration of projects in developing countries, especially in Asia and Africa. This trend aligns with the broader global agenda of promoting sustainable development and inclusive growth, as outlined in the United Nations Sustainable Development Goals (SDGs). The projects contribute to SDG 8 (Decent Work and Economic Growth) and SDG 11 (Sustainable Cities and Communities) by fostering economic growth, creating employment opportunities, and enhancing the sustainability and resilience of cities. Despite the progress made, there remains a significant gap in fully achieving these SDGs, indicating the need for continued efforts and interventions;
• Cluster 3. Collaborative and Transnational Projects: Several projects exhibit a collaborative and transnational nature, involving partnerships between cities, organisations, and countries across different continents. Examples include the IntelCities project, the EU-GUGLE project, and the project described by [74], which span multiple countries in Europe, North America, and Africa. These collaborative endeavours leverage shared expertise, resources, and technologies to address common urban challenges and promote knowledge exchanges. Such projects underscore the importance of international cooperation and knowledge sharing in advancing smart cities and sustainable urban development on a global scale;
• Cluster 4. Technological and Socio-Economic Solutions: The projects encompass a wide range of technological and socio-economic solutions aimed at improving urban sustainability and resilience. These solutions include the use of Information and Communication Technologies (ICT), renewable energy integration, thermal renovation of buildings, and the application of digital tools such as Geographic Information Systems (GIS) and Computer-Aided Design (CAD) programs. The emphasis on both technical and socio-economic aspects reflects a holistic approach to urban development, addressing not only infrastructure needs but also social equity, environmental justice, and economic viability.

As can be observed, the analysis highlights the diverse and dynamic landscape of smart cities and sustainable urban development initiatives worldwide, underscoring the importance of collaborative, multi-dimensional approaches to address complex urban challenges and achieve sustainable, inclusive, and resilient cities.

5. Discussion

In this section, our objective is to conduct a comprehensive discussion of the subject matter, resulting in the identification of trends and perspectives of smart cities for sustainability, as well as identifying projects with innovative strategies that can be replicated in future endeavours. We aim to confront the literature with our findings, focusing on technological approaches, innovative sustainable strategies for city master plans within the realm of smart cities, and the transition from smart cities to sustainability.

5.1. Technological Approaches

The use of Information Technology (IT) technology in smart cities is fundamental in urban planning, development, systems integration, communication, evaluation, and the measurement of results. This section describes research that stood out in the use of IT. The cited studies were extracted from the portfolio of articles.

Table 5. Technological approaches.

Technology		Authors
	Remote sensing	[22,75]
	ICT, IoT, 5G communication technology, data structure, AI, autonomous vehicles, wireless networks, and renewable energy, among others.	[4]
	Renewable energy technologies, integrated systems, and smart grid techniques.	[26,31,42]
	e-participation, digital platforms, ICT decision-making, citizen engagement, urban transformation, internet, smartphones, public participation, and urban planning	[28,44,71]
	Smart cities, digital urbanism, technology, urban infrastructure, technological innovations, job creation, and residents’ quality of life.	[61,75]

approaches various elements of information technology mentioned in the portfolios. This highlights how technology plays a key role in increasing efficiency, sustainability, and overall quality of life in urban areas.

Table 5 presents the use of IT in different scenarios, showing trends in the use of technologies and how they have been applied in projects for smart cities. The presented applications involve the use of sensors in different aspects of urban monitoring: connectivity and real-time data exchange in smart cities, applied to natural resources, clean energy, transport and mobility, construction, infrastructure, life, governance, and the economy, impacting private companies, public services, and society; the incorporation of renewable energy sources; digital e-participation platforms; and focusing on creating jobs and improving the quality of life.

5.2. Innovative Sustainable Strategies for e-Urban Planning in Smart Cities

The aim of this section is to elucidate the role of innovation in urban planning and sustainable smart cities. The cited research was extracted from the portfolio of articles and shows how innovation can improve the quality of life in cities and improve processes of sustainable urban planning in smart cities.

In this study, current research was selected that uses state-of-the-art technologies to solve increasingly complex problems. Other research also presented innovative solutions in themes involving urban planning and smart cities. Table 4 complements these results.

Table 6. Innovative Sustainable Strategies for City Master Plans in Smart Cities.

Strategy		Authors
	Innovation hubs.	[61,75]
	Integration platforms.	[61]
	Sponge City and solutions for urban surfaces.	[35,76]
	AI technologies/digital technologies; smart city planning.	[52,77]
	3D visualisations and urban simulation.	[78]
	Automation of road vehicles.	[43]

demonstrates different ways of applying innovation in urban planning and in the development of smart cities.

Partnerships between universities, government, and industry use technologies such as artificial intelligence, IoT, blockchain, and advanced urban simulations.

Therefore, technological tools applied in various segments and in city governance stand out. There are several fields and directions for the future, including solutions based on ICT, IoT, cloud computing, big data, mobile, AI, 3D tools, 5G, simulation tools, eParticipation tools, sensing, and, mainly, the integration of different systems or even from different regions. Innovation will bring solutions to increasingly complex problems.

Table 7. Trends and perspectives from smart cities to sustainability.

Technological Tools		Uses and Purpose	Authors
	ICT-based solutions.	Application of technologies such as IoT, cloud computing, big data, mobile, and AI to improve the efficiency and quality of urban services.	[4]
	3D and simulation tools.	Use of 3D modelling tools and simulations to plan and visualise urban projects and their impacts.	[78]
	5G and advanced connectivity.	Deployment of 5G communication networks to support connectivity and real-time data exchange between devices and systems.	[4]
	e-participation Tools.	Digital platforms that allow citizen participation in the decision-making process and in urban planning.	[28,44,71]
	Sensors and monitoring.	Use of sensors to collect real-time data on different urban aspects, such as traffic, air quality, and energy consumption, among others.	[22,75]
	Integration of systems and regions.	Connection and integration of different urban infrastructure systems. Collaborations across different regions for efficiency and sustainability improvements.	[61]
	Innovation to solve complex problems.	Continuous use of cutting-edge technologies and innovative projects to face increasingly complex urban challenges and search for sustainable solutions.	[61,75]

presents the relationship between trends and perspectives and technological tools; these trends and perspectives point to a future that is increasingly connected and integrated with smart cities.

All these technologies contribute to the city planning process, as well as help the management of urban services offered to citizens of smart cities, seeking to establish environments based on sustainable issues; after all, a smart city must have this objective.

6. Conclusions

This research mapped sustainable urban planning and development projects and verified the integration of these projects into city master plans for smart cities, listing the regions that stand out in implementing the theme and evaluating the levels of innovation and which technologies are used in successful projects. Furthermore, it was identified which research or frameworks can be replicated in the future, helping to prepare city master plans for smart cities.

Urban planning is a multidisciplinary practice that aims to create and promote liveable, sustainable, functional, and successful cities and areas and is linked to decision-making, as well as public policies. Innovative ICT tools become essential to solve increasingly complex problems. With advances in artificial intelligence, there is a new technological revolution similar to the development of the internet; this factor will impact city planning at all management levels.

The models presented offer valuable contributions to the field of urban planning and sustainability, introducing innovative methodologies, addressing practical challenges, and emphasizing the importance of interdisciplinary collaboration. By leveraging these models, policymakers and urban planners can work towards creating more sustainable, resilient, and livable cities for future generations. As for the portfolio’s references, its analyses reveal urban and sustainable planning methodologies, with opportunities to increase its scope and relevance by addressing the aspects found in the content analysis.

While these are important for city improvements, other considerations must be incorporated into urban planning to better support efforts to create more inclusive, resilient, and sustainable cities.

To select relevant articles for building a portfolio, Methodi Ordinatio was applied, which generated a final portfolio of 84 articles, divided into three sub-groups: (1) Models for urban planning and sustainability; (2) frameworks for urban planning and sustainability; and (3) city master plans in smart and sustainable cities. These three portfolio themes guided the content analysis, which sought to establish correlations between them.

The results were presented according to the regions, countries, cities, and continents that developed proposals or projects related to the proposed theme. So far, the Asian continent has been prominent in the development of SUD projects. However, Europe, North America, South America, Oceania, and the African continent also present research that involves trends, mainly in the integration between government, industry, and civic organizations to drive sustainable urban transformation. In addition, other trends were also analyzed, such as the prioritization of investments in urban mobility and the implementation of intelligent transport systems. The concern with urban sustainability is notable, substantially in terms of mobility and the production of clean energy. Consequently, although the implementation of sustainable smart cities is a huge challenge, they have a high impact power to transform the environment into effective social practices, successfully producing enormous transformations of society in the environment and in cities. Developing countries stood out in this research.

The research limitations mentioned in the papers were, mainly: lack of integration of different software in government spheres; problems related to the collection of information relevant to the sustainable city master plans; complexity of SUD concepts related to legislation observations and quantitative and qualitative interpretations; and difficulties in listening to the population’s complaints or suggestions, mainly in the evaluation of city master plans.

Therefore, as suggestions for future work, it is recommended to apply SUD concepts in city master plans for smart cities; to address the efficiency of technology tools in SUD projects; present the integration of projects at different government levels; and apply the model of sustainable city master plans for smart cities proposed in this research.