Prototyping Smart City Solutions with Metaverse and Digital Twins: A

Systematic Literature Mapping

arcio Roberto Rizzatto

, Alexandre L’Erario

and Eduarda Maganha de Almeida

Programa de P

os-Graduac¸

ao em Inform

atica (PPGI-CP), Universidade Tecnol

ogica Federal do Paran

a (UTFPR),

Campus de Corn

elio Proc

opio, Av. Alberto Carazzai, 1640 - Centro, CEP 86300-000, Corn

elio Proc

opio-PR, Brazil

Keywords:

Smart Cities, Digital Twins, Metaverse, Prototype, Prototyping.

Abstract:

The concept of Smart Cities (SC) has emerged as a strategic approach to address contemporary urban chal-

lenges. The integration of innovative technologies, such as Digital Twins (DT or DTs), the Metaverse, pro-

totyping, and stakeholder participation, offers promising solutions for improving urban management. This

paper presents a systematic mapping of the main approaches and research on prototyping solutions in Smart

Cities, exploring how the metaverse and Digital Twins contribute to these advancements. Based on a detailed

analysis of relevant articles, this work investigates key trends and challenges, providing a consolidated view

of the state-of-the-art in these emerging areas.

1 INTRODUCTION

In recent decades, as noted by (Iliut¸

a et al., 2024), the

concept of Smart Cities (SC) has gained prominence

in urban studies and municipal governance. With ur-

banization and increasing demand for sustainable so-

lutions, cities face challenges in mobility, energy, in-

frastructure, and social interaction. The adoption of

technologies like Digital Twins (DT or DTs) and the

Metaverse offers promising solutions for integrating

various urban dimensions (Hu et al., 2023).

One key advancement in SC is the use of DT,

which creates virtual replicas of urban systems for

real-time simulation, monitoring, and optimization

(Iliut¸

a et al., 2024). When combined with the Meta-

verse, a 3D virtual space, it enables real-time inter-

action among citizens, authorities, and stakeholders

with digital city representations (Adnan et al., 2024).

This integration supports prototyping urban solutions,

allowing virtual tests before real-world implementa-

tion (Tupayachi et al., 2024).

DT represents a leap in urban system design

and management by connecting physical and digital

worlds. Powered by sensor data, DTs allow real-time

analysis of urban scenarios and simulate future condi-

tions, such as infrastructure performance during natu-

https://orcid.org/0009-0003-8663-8805

https://orcid.org/0000-0001-5233-7113

https://orcid.org/0000-0003-1379-5802

ral disasters or the impact of policies (Hu et al., 2023).

Their predictive abilities help prevent failures and im-

prove decision-making by balancing efﬁciency, sus-

tainability, and citizen well-being.

Prototyping is crucial in creating and evaluating

SC solutions, as it enables early-stage testing and

reﬁnement through iterative processes (Saeed et al.,

2023). Using DT and the Metaverse, prototyping

becomes more agile, allowing faster experimentation

and validation at lower costs (Salminen and Aromaa,

2024). This process improves user feedback, en-

hances scalability, attracts investments, and fosters

stakeholder engagement (Dane et al., 2024).

The combination of DT and the Metaverse ad-

dresses dual aspects of SC prototyping. DTs align

prototypes with real city data, while the Metaverse

enhances interactivity between stakeholders and pro-

totypes, promoting collaboration.

A Systematic Literature Mapping (SLM) investi-

gated how DT and the Metaverse are applied to SC

prototyping, mapping contributions, trends, and chal-

lenges in using these tools for complex urban systems.

This study highlights opportunities to integrate these

technologies effectively.

Digital twins and the Metaverse have transformed

smart city prototyping by enabling immersive, data-

driven simulations. DTs provide real-time virtual

replicas of city components for testing and reﬁning

systems without disrupting real environments. The

Metaverse adds immersive capabilities, fostering col-

Rizzatto, M. R., L’Erario, A. and Maganha de Almeida, E.

Prototyping Smart City Solutions with Metaverse and Digital Twins: A Systematic Literature Mapping.

DOI: 10.5220/0013279200003929

Paper published under CC license (CC BY-NC-ND 4.0)

In Proceedings of the 27th International Conference on Enterprise Information Systems (ICEIS 2025) - Volume 2, pages 193-200

ISBN: 978-989-758-749-8; ISSN: 2184-4992

193

laborative design through augmented and virtual real-

ity. This integration enhances decision-making, im-

proves resource efﬁciency, and reduces costs by iden-

tifying issues early. Together, DTs and the Metaverse

enable sustainable, resilient, and human-centric solu-

tions, bridging the gap between concept and imple-

mentation.

2 BACKGROUND

The evolution of Smart Cities (SC) is tied to ad-

vancements in technologies like IoT, AI, and big data

(Alaeifar et al., 2024). Recently, Digital Twins have

gained prominence for virtually replicating cities and

infrastructures, enabling efﬁcient management and

accurate resource predictions (Li et al., 2023). The

Metaverse, with its XR capabilities, extends this evo-

lution by offering a collaborative platform for urban

visualization, testing, and optimization (Rojek et al.,

2024; Papadopoulos et al., 2023). Prototyping within

the Metaverse fosters agility and enhances communi-

cation among stakeholders (Chen and Ruan, 2024).

Smart Cities apply ICT (Information and Commu-

nication Technologies) to improve urban quality of

life by optimizing services like transportation, energy,

waste management, and safety (Hu et al., 2023). They

use real-time data and sensors for informed decision-

making, creating more sustainable and responsive en-

vironments (Gilman et al., 2024). Beyond infrastruc-

ture, SC aim to promote economic and social inno-

vation, ensuring equity and resilience (Gilman et al.,

2024).

Digital Twins are virtual replicas of physical ob-

jects, systems, or processes connected via real-time

data (Iliut¸

a et al., 2024). They simulate physical

behavior, enabling monitoring, analysis, and opti-

mization. In SC, DTs replicate urban infrastructure,

predicting failures, improving processes, and test-

ing enhancements before real-world implementation

(Perisic and Perisic, 2024; Rojek et al., 2024). This

technology transforms urban planning and resource

management efﬁciency (Iliut¸

a et al., 2024).

The Metaverse is a shared 3D virtual space for

real-time interaction (Rojek et al., 2024). While

rooted in entertainment, it now spans education,

healthcare, and urban planning. For SC, it enables

immersive city simulations, facilitating collaboration

among architects, planners, and citizens to explore

scenarios and improve decision-making (Li et al.,

2023).

A prototype represents an initial solution design,

allowing for functionality testing and reﬁnement be-

fore ﬁnal production (Iliut¸

a et al., 2024). In SC, pro-

totypes validate concepts, identify ﬂaws, and enhance

design efﬁciency. They range from infrastructure

models to policy simulations, ensuring solutions ad-

dress population needs effectively (Iliut¸

a et al., 2024).

Prototyping, the iterative creation and evaluation

of prototypes, is essential in SC (Iliut¸

a et al., 2024).

Virtual environments like DTs and the Metaverse ac-

celerate prototyping by enabling scenario exploration

and reducing risks before implementation. Digital

prototyping allows for cost-effective innovation and

agile development, transforming SC solutions (Salmi-

nen and Aromaa, 2024).

3 RESEARCH METHOD

A systematic literature review is a method to collect

and analyze multiple studies in a structured way. This

research applied the approach outlined by (Kitchen-

ham et al., 2007).

Following the guidelines of (Kitchenham et al.,

2007; Petersen et al., 2015), the study investigated the

use of DT and the Metaverse for prototyping smart

city solutions. The adapted protocol ensured a rigor-

ous and reproducible systematic review process.

The research question is: ”How are digital twins

and the Metaverse used to prototype solutions for

smart cities?”

This question explores the application, trends,

challenges, and gaps in the literature surrounding

these technologies.

The study examined ﬁve scientiﬁc databases:

• SCOPUS;

• Elsevier ScienceDirect;

• IEEE Xplore;

• ACM Digital Library;

• MDPI.

The articles addressed the key terms: smart cities,

digital twins, Metaverse, prototype, and/or prototyp-

ing. The search string: ”smart cities” AND ”digital

twins” AND ”metaverse” AND (”prototype” OR

”prototyping”).

This string was applied across databases for the

period 2020–2024, ensuring recent and relevant arti-

cles, as noted by (Sampaio and Mancini, 2007). ”The

scarcity of relevant articles necessitated stricter inclu-

sion criteria. Limiting the period to 2020–2024 in-

creased the number of relevant results, as no pertinent

studies before 2022 were identiﬁed.”

The following inclusion and exclusion criteria

were outlined:

ICEIS 2025 - 27th International Conference on Enterprise Information Systems

194

• Inclusion Criteria (IC):

– IC1 - Articles in English;

– IC2 - Articles published between 2020 and

2024;

– IC3 - Complete articles;

– IC4 - Articles published in journals, periodi-

cals, and scientiﬁc conferences in the ﬁeld of

computing and peer-reviewed;

– IC5 - Articles with studies that discuss or

demonstrate the use of digital twins and the

Metaverse for prototyping solutions in smart

cities.

• Exclusion Criteria (EC):

– EC1 - Duplicate articles;

– EC2 - Articles that do not ﬁt the scope of this

work;

– EC3 - Articles that only mention the Metaverse

or DT.

The study selection process was conducted in two

phases, as described in the Petersen Protocol (Pe-

tersen et al., 2015):

1. First Phase of Article Inclusion. Articles were

initially numbered in ascending order by title, in-

cluding details such as identiﬁer, BibTeX key or

code, type (article, etc.), title, authors, publication

source (Scopus, IEEE, etc.), year, and relevant

terms or keywords (Smart Cities, Digital Twins,

etc.). Titles, abstracts, and keywords were ana-

lyzed to check for relevant keywords, excluding

references and non-informative content (e.g., ta-

bles, graphs). Articles meeting the inclusion cri-

teria advanced to the next phase, while duplicates

were marked and excluded. Figure 1 illustrates

the inclusion criteria applied during the selection

process.

2. Second Phase of Article Classiﬁcation. In this

phase (see Figure 2), the full texts of pre-selected

articles were analyzed in depth. Relevant terms

were noted in the text, excluding references or

simple citations. Articles were prioritized based

on the presence of keywords in the following or-

der: ”smart cities,” then ”prototype” or ”prototyp-

ing,” followed by ”digital twins” and/or ”meta-

verse.” Irrelevant articles were excluded. A new

ﬁnal table was created, retaining the structure of

the initial table but including only relevant arti-

cles, with a new ascending numbering system.

Figure 2 illustrates the inclusion criteria applied

during this phase.

The studies were categorized by their approaches

and contributions to the research theme. Categories

included digital twin-based prototyping for smart

cities, metaverse applications for urban interaction,

and studies combining digital twins and the meta-

verse for smart city prototyping. These classiﬁcations

helped identify key research areas, trends, and gaps in

the literature.

3.1 Data Extraction

The data extracted from the selected articles were or-

ganized in a table that includes the following informa-

tion:

Authors and Year of Publication Article Ti-

tle Source (Journal/Conference) Methodology Used

Main Conclusions Relevance for Prototyping Solu-

tions in Smart Cities using Digital Twins and/or Meta-

verse The data extraction was performed systemati-

cally and in a standardized manner to ensure consis-

tency in the results and facilitate comparative analysis

between the studies.

3.2 Classiﬁcation of Studies

The studies were classiﬁed into categories based on

their approaches and contributions to the research

topic. The categories included:

1. Prototyping based on DT for SC;

2. Use of the Metaverse in urban interaction and sim-

ulation;

3. Studies combining DT and the Metaverse for pro-

totyping in SC.

These categories allowed us to map the main re-

search areas and identify trends and gaps in the liter-

ature.

4 RESULTS AND DISCUSSIONS

The selected studies were synthesized to identify

trends, gaps, and future research opportunities. From

41 articles identiﬁed, 18 met the inclusion criteria.

The articles reveal strengths and weaknesses. The

paper (Hu et al., 2023) highlights geospatial intel-

ligence for urban digital twins, addressing techni-

cal challenges like small object detection. However,

ethical issues and practical applications are underex-

plored.

The article (Gilman et al., 2024) examines smart

city data challenges, proposing a ”systems of sys-

tems” framework and practical applications like

Seoul’s data use. However, it lacks focus on equity,

digital twins, and stakeholders.

Prototyping Smart City Solutions with Metaverse and Digital Twins: A Systematic Literature Mapping

195

Figure 1: First Phase of applying the inclusion criteria for the articles selected with the search string by publication.

Figure 2: Second Phase of applying the inclusion criteria for the articles selected in this phase by publication.

The study (Alaeifar et al., 2024) explores cyber

intelligence sharing, emphasizing IoT and blockchain

synergies. However, its focus on cybersecurity over-

looks smart city contexts and stakeholder engage-

ment.

The paper (Rojek et al., 2024) deﬁnes digital twins

for manufacturing, emphasizing efﬁciency and sus-

tainability. Yet, it offers limited insights into smart

city applications and social impacts.

The study (Iliut¸

a et al., 2024) outlines the evolu-

tion of digital twins, analyzing healthcare and indus-

trial uses. However, challenges in urban implementa-

tion are minimally addressed.

The article (Dane et al., 2024) proposes a virtual

reality framework for participatory urban planning,

focusing on stakeholder engagement. Its scope, how-

ever, is limited to public spaces.

The paper (Adnan et al., 2024) explores tech-

nological convergence in smart grids, proposing re-

source management models. However, practical ur-

ban links are minimal.

The article (Salminen and Aromaa, 2024) exam-

ines metaverse applications for road safety education

with interactive learning examples. Yet, its focus is

narrow, and empirical validation is limited.

The study (Chen and Ruan, 2024) investigates

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the metaverse in healthcare supply chains, addressing

barriers with blockchain solutions. Complexity and

lack of validation are notable challenges.

The paper (Alsamhi et al., 2023) integrates drones

and the metaverse into cyber-physical-social systems,

offering practical applications. However, complexity

and costs limit real-world feasibility.

The article (Papadopoulos et al., 2023) explores

mixed reality and IoT synergies but lacks emphasis

on smart city applications and privacy concerns.

The paper (Schmitt, 2023) addresses AI for cyber-

security in smart city infrastructure but relies heavily

on emerging technologies, limiting accessibility.

The study (Qu et al., 2024) introduces ”microver-

ses” for task-speciﬁc smart city applications, using

blockchain and IoT. However, technical complexity

and costs are challenges.

The paper(Tupayachi et al., 2024) applies lan-

guage models to urban planning, improving data in-

tegration. Yet, adoption is limited by technological

dependence and lack of social focus.

The article (Hasan et al., 2023) discusses NFTs

(Non-Fungible Tokens) for digital twin ownership,

proposing decentralized, validated solutions. How-

ever, its focus is primarily on manufacturing, with

limited smart city relevance.

The papers (Iliut¸

a et al., 2024), (Saeed et al.,

2023), (Schmitt, 2023), (Tupayachi et al., 2024),

(Hasan et al., 2023) report on the use of prototypes in

DT environments to create a virtual copy of the phys-

ical version. The studies (Hu et al., 2023), (Gilman

et al., 2024), (Papadopoulos et al., 2023), (Li et al.,

2022), (Qu et al., 2024) do not explicitly discuss or

use the terms ”prototype” and ”prototyping.” The arti-

cles (Alaeifar et al., 2024), (Perisic and Perisic, 2024),

(Rojek et al., 2024), (Dane et al., 2024), (Adnan

et al., 2024), (Salminen and Aromaa, 2024), (Chen

and Ruan, 2024), (Alsamhi et al., 2023) discuss or

use the terms ”prototype” or ”prototyping” but do not

explore them in depth.

Thus, the results of applying the protocol resulted

in Table 1 with the included articles.

Generating a Table 2 with the included articles and

applying this data in VOSviewer

, a line chart is ob-

tained for a better understanding of Table 2, as pre-

sented in Figure 3.

Figure 3 presents the publication of articles by

year, and for this reason, the search string was ap-

plied for the time frame from 2023 to 2024 to obtain

the most recent and relevant works, due to the scarcity

VOSviewer is a free tool for constructing

and visualizing bibliometric networks, available at

https://www.vosviewer.com/

of articles in previous years that met the inclusion and

exclusion criteria for this study.

The relationship between the names of the pub-

lications of the accepted articles, their citations, and

citation averages can be observed in Table 3, gener-

ated by VOSviewer, for the accepted articles, which

can be better understood through Figure 4.

The main ﬁndings in answering the research ques-

tion ’How are DT and Metaverse technologies being

used to prototype solutions for SC?’ were identiﬁed

from the 18 included articles. Three main themes

emerged: (i) prototyping urban solutions through DT,

(ii) the use of the Metaverse for urban visualization

and interaction, and (iii) the integration of both tech-

nologies for SC solutions.

4.1 Prototyping with DT and Metaverse

DT are essential for creating virtual replicas of ur-

ban systems and infrastructure. According to (Perisic

and Perisic, 2024), this technology enhances planning

by predicting failures and optimizing resources. Ad-

ditionally, (Iliut¸

a et al., 2024) note that DT enables

agile, iterative testing, offering controlled and cost-

effective environments for prototyping.

The integration of DT and the Metaverse is a

promising approach for SC prototyping. (Iliut¸

a et al.,

2024) suggest that combining these technologies al-

lows real-time modeling and validation of citizen be-

havior and infrastructure. Moreover, (Salminen and

Aromaa, 2024) emphasize exploring urban scenarios

to mitigate risks before physical implementation.

The Metaverse, highlighted by (Adnan et al.,

2024) and (Rojek et al., 2024), is a 3D environment

for visualization, simulation, and collaboration in SC

projects. It enables stakeholders to virtually experi-

ence and evaluate proposed changes, fostering trans-

parency and public participation.

4.2 Challenges and Gaps

Despite advances, the reviewed studies highlight chal-

lenges, particularly in prototypes and prototyping.

Most research focuses on technical aspects, with lim-

ited attention to social and ethical factors. Digital pro-

totyping, though powerful for testing, faces difﬁcul-

ties transitioning to practical implementation due to

urban complexity.

Adapting virtual prototypes to the physical world

efﬁciently and scalably remains challenging (Iliut¸

et al., 2024). The lack of empirical studies validating

DT and the Metaverse in real SC environments lim-

its understanding of their practical impacts (Qu et al.,

2024). Integration with public policies and addressing

Prototyping Smart City Solutions with Metaverse and Digital Twins: A Systematic Literature Mapping

197

Table 1: Results of included articles.

ID Reference Smart Cities Digital Twins Metaverse Prototype Prototyping

1 (Hu et al., 2023) yes yes yes yes no

2 (Gilman et al., 2024) yes yes yes yes no

3 (Alaeifar et al., 2024) yes yes yes yes no

4 (Perisic and Perisic, 2024) yes yes no yes yes

5 (Rojek et al., 2024) yes yes no yes yes

6 (Iliut¸

a et al., 2024) yes yes yes yes yes

7 (Dane et al., 2024) yes yes no yes no

8 (Adnan et al., 2024) yes no yes yes no

9 (Saeed et al., 2023) yes yes yes no yes

10 (Salminen and Aromaa, 2024) yes yes yes no yes

11 (Chen and Ruan, 2024) yes yes yes yes no

12 (Alsamhi et al., 2023) yes yes yes yes no

13 (Papadopoulos et al., 2023) yes yes yes yes no

14 (Schmitt, 2023) yes yes yes no yes

15 (Qu et al., 2024) yes yes yes yes no

16 (Tupayachi et al., 2024) yes yes no yes yes

17 (Hasan et al., 2023) yes yes yes no yes

18 (Li et al., 2022) yes yes yes yes no

Table 2: Articles included by year.

Year 2020 2021 2022 2023 2024

Publications Accepted (total) 0 0 1 6 11

Figure 3: Articles included by year according to Table 2.

accessibility and equity issues are also underexplored

(Gilman et al., 2024).

Prototyping requires methodologies that ensure

solutions are effective, sustainable, and adaptable to

diverse urban contexts. A holistic approach, encom-

passing technical, social, ethical, and practical as-

pects, is critical for successfully applying these tech-

nologies in SC.

5 FINAL CONSIDERATIONS

The SLM analyzed how DT and Metaverse technolo-

gies are applied to prototype SC solutions. These

technologies show great potential to transform urban

planning, enabling precise simulations and stake-

holder collaboration. DT optimize systems and pre-

dict failures, while the Metaverse enhances visualiza-

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198

Table 3: Citations per Publication.

Name Publications Citations Citations median

IEEE Internet of Things Journal 1 119 119

Journal of Industrial Information Integration 1 45 45

Future Internet 1 10 10

Future Generation Computer Systems 1 8 8

Engineering Applications of Artiﬁcial Intelligence 1 7 7

Smart Cities 1 5 5

Virtual Reality and Intelligent Hardware 1 3 3

Applied Sciences 1 3 3

Advances in Engineering Software 1 2 2

Procedia Computer Science 1 1 1

ACM Transactions on Intelligent Systems and Technology 1 1 1

Computers and Electrical Engineering 1 1 1

Journal of Information Security and Applications 1 1 1

Electronics 2 1 1

Computers Environment and Urban Systems 1 0 -

Figure 4: Citations per Publication of the included articles.

tion and communication among managers, citi-

zens, and developers.

Challenges remain, including social, ethical, and

equity issues. Implementation requires adequate in-

frastructure and integration with existing urban sys-

tems.

Future research should address:

• Validation in Real Environments. Empirical

studies to evaluate solutions in real cities, mea-

suring efﬁciency and public acceptance;

• Social and Ethical Aspects. Ensuring inclusivity

and beneﬁts for all communities;

• Integration with Public Policies. Aligning these

technologies with policies for sustainability and

equity;

• Digital Accessibility. Making DT and Metaverse

platforms accessible to all, including people with

disabilities.

In conclusion, DT and Metaverse technologies

hold transformative potential for SC. They enable

collaborative and efﬁcient prototyping of urban so-

lutions. Addressing social, ethical, and accessibility

issues, along with policy integration, is essential to

ensure inclusivity and sustainability. Continued re-

search will drive progress towards more connected,

Prototyping Smart City Solutions with Metaverse and Digital Twins: A Systematic Literature Mapping

199

responsive, and inclusive cities, beneﬁting society as

a whole.

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