Exploring the Role of Industry 4.0 Technologies in Smart City Evolution: A Literature-Based Study

Abstract

Smart cities are technologically advanced urban environments where interconnected systems and data-driven technologies enhance public service delivery and quality of life. These cities rely on information and communication technologies, the Internet of Things, big data, cloud computing, and other Industry 4.0 tools to support efficient city management and foster citizen engagement. Often referred to as digital cities, they integrate intelligent infrastructures and real-time data analytics to improve mobility, security, and sustainability. Ubiquitous sensors, paired with Artificial Intelligence, enable cities to monitor infrastructure, respond to residents’ needs, and optimize urban conditions dynamically. Given the increasing significance of Industry 4.0 in urban development, this study adopts a bibliometric approach to systematically review the application of these technologies within smart cities. Utilizing major academic databases such as Scopus and Web of Science the research aims to identify the primary Industry 4.0 technologies implemented in smart cities, assess their impact on infrastructure, economic systems, and urban communities, and explore the challenges and benefits associated with their integration. The bibliometric analysis included publications from 2016 to 2023, since the emergence of urban researchers’ interest in the technologies of the new industrial revolution. The task is to contribute to a deeper understanding of how smart cities evolve through the adoption of advanced technological frameworks. Research indicates that IoT and AI are the most commonly used tools in urban spaces, particularly in smart mobility and smart environments.

1. Introduction

The Industrial Revolution, which commenced in the 18th century, resulted in substantial city transformations across the globe. Urban infrastructure has been adapted to accommodate the growing population and the evolving needs of industrial society, including the necessity to commute to workplaces. In the present era, contemporary cities are undergoing another phase of transformation, this time dependent on the pervasive integration of digital technology. This transformation is expected to yield diverse and city-specific outcomes. Among the most notable objectives and outcomes being pursued by these cities is an increase in efficiency and performance in various urban domains [1]. Smart solutions are increasingly being used to address challenges facing cities, such as energy consumption, water management, pollution detection, material efficiency, people’s safety, cybersecurity, and traffic management [2,3]. It is therefore evident that the concept of smart cities in relation to Industry 4.0 represents a significant area of research across numerous fields and disciplines.

According to da Silva et al. [4], smart cities represent a paradigm shift away from traditional urban models. This involves integrating sensors, the Internet of Things (IoT), big data, cloud computing and artificial intelligence (AI). These technologies enable the development and delivery of more efficient public services that are flexible, transparent, accountable, and centred around the needs of citizens. Furthermore, it is noteworthy that smart cities are deliberately designed to be more environmentally sustainable, secure, efficient, and user-friendly than their traditional counterparts [5,6]. This is connected to the requirements of a contemporary society that is focused on economic, social and environmental advancement, which are supported by digital technologies.

This article examines the emerging field of Industry 4.0 within the context of smart cities through a bibliometric analysis, aiming to identify and classify the key concepts developing at the intersection of these domains. The research aims to quantify the amount of research on Industry 4.0 issues in smart cities over the years to identify growth trends, researchers working on the topic, types of publications and publishers. The authors of this study asked the following research questions:

RQ1. What are the main 4.0 technologies being implemented in smart cities?

RQ2. What are the implications of the use of Industry 4.0 technologies for the development of infrastructure, the economy and urban communities?

RQ3. What are the challenges and benefits of integrating Industry 4.0 technologies into the smart city concept?

The answers to such questions will provide a better understanding of how technologies are shaping contemporary approaches to urban management and the quality of life of residents. In addition, they will allow identification of the research gap in the area of Industry 4.0 technology applications in smart cities.

These research questions have been selected to address identified gaps in the existing literature on Industry 4.0 and smart cities. While both areas have been extensively studied in isolation, there is still a lack of comprehensive understanding of their interrelationship.

Firstly, while many technologies are associated with Industry 4.0, it is unclear which ones are most commonly used in smart city initiatives (RQ1). This makes it difficult to assess the technological landscape shaping urban environments.

Secondly, the broader implications of the implementation of Industry 4.0 technology for key urban dimensions, such as infrastructure development, economic growth and local community dynamics, have not yet been fully explored (RQ2). Understanding these impacts is crucial for policymakers and urban planners who wish to leverage these technologies effectively.

Thirdly, the challenges and benefits of integrating Industry 4.0 technologies within the smart city concept are under-researched (RQ3). This limits the ability to anticipate obstacles and maximise potential benefits, which is essential for sustainable and inclusive urban development.

This study therefore focuses on these questions, aiming to fill these gaps by offering a systematic analysis of the impact of Industry 4.0 technologies on smart city development, and by identifying directions for future research and practical applications in this emerging interdisciplinary field.

The current study consists of five sections. The second section of this study examines the concept of the smart city and the concept of Industry 4.0. Section 3 presents the review protocol constructed for the structured literature review along with a description of the research methodology. The systematic literature review was conducted using the PRISMA methodology. Thematic coding was performed using the VOSviewer version 1.6.20 tool to minimise the impact of subjective interpretations. The entire selection process was documented in detail and presented as a flow diagram. Section 4 discusses the results of the literature review in the context of the breakdown by bibliometric analysis, subject areas axes and technological applications. Section 5 contains a discussion, and Section 6 presents the conclusions of the study.

2. Literature Review

2.1. Smart City Concept

The term smart city remains ambiguous and multifaceted, which means that no single, uniform definition has emerged in the literature. The reasons for this should be sought primarily in the dynamic evolution of the phenomenon itself—not only is it a relatively new concept, but it is also open to reinterpretation depending on the local, institutional or political context. The difficulty in defining it unambiguously also stems from the fact that it covers a wide range of areas of urban reality: from digital infrastructure, through social co-management models, to sustainable development strategies.

The concept of the smart city has progressively evolved from a focus on individual technological components to an integrated perspective that views the entire city as a holistic system. The term “smart city” is employed across a range of multidisciplinary fields [7]. A literature review of the smart city concept by Ojo, Dzhusupov and Curry [8] indicated a growing interest in the topic since 2009, mainly in relation to computer science and engineering. With the passage of time and the experience gained in the field of activities, the characterisation of the smart city concept has become increasingly complex. Today, attempts to define the concept in question focus on improving the quality of life of residents, involving citizens in the of life for residents, involving citizens in the decision-making process, and building a city based on knowledge and friendly to knowledge-based city that respects the environment. It is generally assumed that smart cities will have a positive impact on the overall quality life of society. Conversely, the broader societal development also plays a significant role in shaping the evolution of smart cities [5].

According to ISO 37122:2019, which develops global standards related to the sustainability and management of smart cities proposed definition of smart city as “smart city that increases the pace at which it provides social, economic and environmental sustainability outcomes and responds to challenges such as climate change, rapid population growth, and political and economic instability by fundamentally improving how it engages society, applies collaborative leadership methods, works across disciplines and city systems, and uses data information and modern technologies to deliver better services and quality of life to those in the city (residents, businesses, visitors), now and for the foreseeable future, without unfair disadvantage of others or degradation of the natural environment” [9]. A smart city can be defines as “a developed urban area that creates sustainable economic development and high quality of life by excelling in multiple key areas; economy, mobility, environment, people, living, and government” [10]. Another definition proposed by European Union is as follows: “smart city is a place where traditional networks and services are made more efficient with the use of digital solutions for the benefit of its inhabitants and business. A smart city goes beyond the use of digital technologies for better resource use and less emissions. It means smarter urban transport networks, upgraded water supply and waste disposal facilities and more efficient ways to light and heat buildings. It also means a more interactive and responsive city administration, safer public spaces and meeting the needs of an ageing population” [11].

According to Cretu [12], the smart city pursues the principle of focusing on sensor networks, smart devices, real-time data and integration of Information and Communication Technologies (ICT) in every aspect of human life, which involves better management and governance of the city. A smart city uses information and communications technology to detect, analyse and integrate key information from the core systems operating in the city [13]. This is aimed at improving the quality of life of the city’s residents [14,15]. We can state that the concept of smart city embodies a vision for urban development that leverages advanced technologies and data analysis to enhance the quality of life, sustainability, and efficiency of cities [16].

A variety of analytical and practical approaches lead to different interpretations of this idea. Depending on whether it is applied by researchers, public administrators or private sector organisations, emphasis is placed differently, which can, on the one hand, lead to the term’s meaning becoming blurred, but, on the other hand, provide flexibility in its implementation. This plurality of meanings reflects the complexity of contemporary urban challenges and allows tools and strategies to be tailored to the specific needs of a community.

Smart cities aim to integrate physical, digital, and human systems within the urban environment in a coherent and effective manner, with the objective of promoting sustainability, economic prosperity, and social inclusivity. The implementation of smart city initiatives is occurring globally through coordinated efforts involving a wide range of public and private sector entities [5]. Smart cities fundamentally require innovative governance frameworks and knowledge-based design strategies, alongside public policies that foster well-being, support effective urban planning practices, and encourage sustainable economic development [17,18].

Thus, it can be seen that smart cities embody an environment where technology, urban planning, architecture, engineering, economics, governance, social dynamics, and education intersect to form an efficient and sustainable urban ecosystem [19]. Therefore, the concept of a smart city encompasses a multitude of facets, with the domains of smart mobility, smart economy, smart environment, smart living, smart governance, and smart people. Giffinger and colleagues [6], among others, proposed a model of six integrated areas to organise the understanding of the smart city concept. This model is widely cited as the analytical foundation of the smart city concept, comprising the following six areas: smart economy, smart mobility, smart environment, smart people, smart living and smart governance.

Smart cities are also part of the technological urbanism trend, in which spatial planning is increasingly intersecting with digital infrastructure and data management. This concept’s theoretical foundation draws on various fields, including space theory, systems thinking, and innovation diffusion models—particularly in the context of the so-called Fourth Industrial Revolution (Industry 4.0). This revolution is based on a new technological paradigm incorporating cyber-physical systems, the Internet of Things, artificial intelligence and advanced data analytics. Together, these are changing the way urban spaces function [20].

From an urban research perspective, cities are seen as complex systems of networked connections in which information and knowledge are key factors in the transformation of space, society and the economy. The city is no longer just a physical place; it is also beginning to function as a complex adaptive system based on data flows, connectivity and algorithmic management [21]. Smart city technologies, such as real-time traffic management systems, smart energy networks and digital public services, meet these criteria and are more prevalent in cities with robust governance, advanced technological infrastructure and engaged citizens.

In the literature, cities are viewed as hubs that connect three key components: intellectual capital, represented by universities; industrial activity, which generates economic value; and democratic governance, represented by civil society institutions [22].

The interactions between these three areas give rise to dynamic urban spaces where knowledge is used to drive technological development and innovation within regional innovation systems. Such spaces can be understood as environments saturated with information and communication technologies, forming the basis of the smart city concept.

Integrating Industry 4.0 technologies into the smart city model requires a multidimensional analytical approach. Focusing solely on technological narratives can result in important aspects such as social inclusion, governance structures and spatial inequalities being overlooked. Including theoretical frameworks from urban studies and innovation theory enables us to take a critical and in-depth look at the motivations, processes and consequences of developing smart cities in the era of the Fourth Industrial Revolution.

2.2. Industry 4.0 Concept

We currently stand at the threshold of a transformative era known as Industry 4.0, often referred to as the Fourth Industrial Revolution. This concept was initially introduced by the German government in 2011 with the goal of boosting and sustaining the productivity and adaptability of the German manufacturing sector [23]. This paradigm shift integrates digital networking with intelligent manufacturing systems, covering the entire value chain—from the initial design and development stages through production, maintenance, service, and ultimately recycling.

Industry 4.0 is characterized by the seamless horizontal flow of data between partners, suppliers, and customers, alongside vertical integration that connects all organizational functions, spanning from product conception to final delivery. This revolution blends physical processes with digital technologies, creating fully interconnected systems capable of real-time monitoring and analysis of information streams. Key enabling technologies include artificial intelligence, cyber-physical systems (CPS), the Internet of Things, digital twins, augmented reality, additive manufacturing, and cloud computing. These tools empower decision-makers to oversee physical operations and make timely, data-driven choices [24].

Since around 2013, Industry 4.0 has inspired a range of “smart” initiatives both in industry and academia, such as Smart Factory, Smart City, Smart Water, Smart Manufacturing, Smart Logistics, and Smart Enterprise [25]. The core idea involves linking physical machinery with virtual environments through internet connectivity and sophisticated information technologies. This connectivity facilitates uninterrupted communication among humans, machines, and IT systems, enabling automatic data exchange across production, logistics, and urban management processes—both within factories and across suppliers, government agencies, and various IT platforms used by organizations and municipalities [26].

A major advantage of Industry 4.0 is the ability to access critical information instantly from any location, leading to optimized process control. This flexibility supports the customization of products even in small batch sizes, a concept known as mass customization. By adopting Industry 4.0 principles, businesses and cities can lower manufacturing costs while more effectively addressing the evolving needs of customers, stakeholders, and market demands. Historically, industry has been an integral part of urban development and should always be considered within the broader city context [27].

2.3. Implementing Industry 4.0 Technologies in Smart Cities

As we can see, with the growth of urbanised populations, technology began to play a significant impact on the transformation of the city. The first were the introduction of electronic document management systems, the creation of electronic legal acts or the use of electronic maps in the in the decision-making process. The development of technology has led to the attribution of different names to the city, such as the digital city, in which the use of innovation helps to meet the needs of its inhabitants. In smart cities, real-time data generated by cloud-based IoT devices are analysed and managed to assist relevant stakeholders in making informed decisions and minimizing costs, while advancing sustainability objectives. These include optimizing energy distribution, mitigating traffic congestion, enhancing air quality, and improving the efficiency of waste collection systems [28].

In the context of urban governance, the collection, storage, analysis and interpretation of data assume particular significance. This is because such data can be harnessed to gain insights into the diverse dynamics of urban environments, thereby enhancing the quality of decision-making processes. Beyond data itself, the smart city concept depends on a broad spectrum of advanced technologies that not only facilitate the collection, storage, and utilization of data but also support the implementation of decisions and insights derived from its synthesis, analysis, and interpretation. These enabling technologies include AI, machine learning (ML), crowd computing (CC), connectivity solutions such as 5G and the anticipated 6G, robotics, among others. When combined, the majority of these technologies, plus various urban elements, will make smart cities and their market attractiveness very lucrative [29]. In the evolution of smart cities, the automation of processes is an inevitable consequence of rapidly advancing technologies [30]. Industry 4.0 enabling technologies—such as the IoT, cloud computing, big data analytics, autonomous robotics, simulation, additive manufacturing, horizontal and vertical system integration, digital twins, cyber-physical systems, cybersecurity, augmented and virtual reality, artificial intelligence, and blockchain—are fundamentally shaping the development of inclusive and resilient smart cities [31] (Figure 1).

Smart cities will be driven by advanced and complex ICT systems that leverage data collected from distributed sensor networks to deliver personalized information and services to citizens, while operating within the boundaries of sustainability and other contextual constraints [32].

The concept of the smart city encompasses a wide range of functions, including information management, the optimization of service delivery for citizen well-being, and the enhancement of governmental processes [32]. This concept is closely associated with the paradigm of Industry 4.0, referring to an advanced urban environment capable of ensuring quality of life, economic competitiveness, and the sustainable management of resources for both current and future generations [33]. At present, Industry 4.0 technologies and smart city applications are being deployed across various sectors, as well as within citizens’ homes. This integration facilitates rapid information transfer, enhances information transparency, and provides improved opportunities for time and cost management, ultimately driving greater efficiency [34].

The various elements of Industry 4.0 are possible to use to create smart cities.

Table 1. The technologies of Industry 4.0 used in smart cities.

Name of Technology	Description of Using Technology in the Area of Smart City
Internet of Things	The IoT helps decision makers and city managers to collect and analyse large amounts of data in order to project and implement the best practices to ‘regenerate’ the urban metabolism in a smart city context. Protection and resource conservation are typically environmental objectives. At the same time, prosperity and continuity in urban contexts are two economic goals, and social wellbeing and equity principle complete the characterisation of sustainability [35].
AI and machine learning	The modern phenomenon in AI has transformed innovative solutions and improved city external attacks against serious security threats [36]. The aspects such as smart adaptive advertising, smart travel experience, smart power grid, renewable energy and optimization, disaster prevention, smart agriculture, smart health, smart security and surveillance can be achieved if proper implementation of AI and IOT is introduced in smart city development program [37]. The proposed research on fairness-driven link scheduling for heterogeneous gateways in IIoT networks using digital twin technology and machine learning techniques has significant implications for the field of industrial automation and smart cities. The use of digital twin technology and machine learning in link scheduling ensures efficient data transmission and resource protection in IIoT networks [38].
Digital Twins	Digital Twin coupled with IoT data can augment the efficient planning of the smart city and execution of its building by supplementing financial progress, effectual administration of resources, lessening of environmental impression and escalate the complete worth of a resident’s life. The digital twin prototypical can aid city organizers and legislators in the smart city planning by retrieving the visions from numerous sensor networks and smart systems. The information received from the digital twins supports them in reaching well-versed choices concerning the future as well [39].
Big Data	Availability of a large number of data sources indicates importance of big data in supporting the smart city applications and services [40]. Analysis of big data sets particularly useful for areas such as smart transportation, smart governance, smart grid, smart healthcare [41].
Blockchain	Blockchain may be used to solve problems in transactions, supply chain management, workforce management, and legal difficulties. Blockchain technology can improve vehicle and passenger tracking, as well as the payment of transportation fees effectively [42].
Cloud computing	Big data and cloud computing are currently considered as key enablers that can lead to the building of the future industrial ecosystem by interlinking the cyber and physical worlds. The main reason is that these are able to manage the variety, velocity, volume and criticality of data that the industrial environment generates by means of highly distributed and scalable architectures that can be dynamically dimensioned to process workloads in real time [43].
Cyber-physical systems	Cyberphysical Systems are intelligently networked systems with sensors, instilled processors, and actuators installed within them that identify and interact with real-world aspects and human end-users; CPS support real-time, ensure quality and extent of performance within safety-oriented applications, especially in the smart city model [44].
Robots and drones	Drones have a great ability to assist in the planning of urban communities to rapidly transform the lives of their inhabitants for the better [45].
Augmented Reality	AR is a useful visualization technique and can be used in many domains such as medical, robotics, military, navigation, traveling, education, entertainment, marketing, tourism, urban planning, manufacturing, product assembly and repair, architecture, etc. Smart cities use ICT for enriching the quality and performance of mobile devices in the city, where AR can provide new solutions to various domains of a smart city [46].

provides an overview of selected tools and how they can be implemented in urban management areas.

The implementation of Industry 4.0 technologies in smart cities is reshaping urban environments through advanced tools such as IoT, AI, big data analytics, digital twins and blockchain. These technologies enable cities to address complex challenges, optimise resource utilisation, and improve the quality of life for their residents. The integration of these tools in smart cities aligns with sustainability goals and promotes greener, safer, and more efficient urban spaces.

IoT serves as a cornerstone technology, connecting sensors and devices to collect and analyse real-time data. This enables improvements in transportation through smart mobility solutions, environmental monitoring for pollution control, and more efficient energy management through smart grids. Similarly, AI is improving decision-making in urban governance, facilitating predictive maintenance of infrastructure, and supporting personalised services in smart living.

Digital twins create virtual models of urban systems, enabling city planners to simulate and optimise infrastructure projects, traffic management and emergency response scenarios. Big data analytics complements these efforts by providing actionable insights into patterns of energy use, transport demand, and public service needs, enabling cities to dynamically adapt to evolving challenges.

Blockchain technology enhances transparency and security in city management, particularly in areas such as transport fee payments, real estate transactions and supply chain operations. In addition, the use of robots and drones in urban planning, waste management and public safety are examples of how automation can effectively address pressing urban issues.

3. Research Methodology

The research review was carried out by a research protocol initiated in three stages, which included (1) study identification, (2) screening and choosing of articles, and (3) descriptive analysis. In the first instance, we defined the purpose of our review and formulated our research questions. To limit bias in the selection and coding of publications, a three-step review protocol was used in accordance with PRISMA guidelines (see the Supplementary Material—PRISMA 2020 Checklist). The PRISMA methodology refers to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses. It is a set of evidence-based guidelines designed to help researchers transparently report the rationale, process, and findings of systematic reviews and meta-analyses. The inclusion and exclusion criteria were defined prior to the analysis. Publications were selected independently by two researchers, and any discrepancies were resolved by consensus. Thematic coding was performed using the VOSviewer tool to minimise the impact of subjective interpretations. The entire selection process was documented in detail and presented as a flow diagram.

We set out to answer research questions related to the concept of Industry 4.0 in smart cities, focusing on the evolution, intellectual configuration, trends and gaps in the field through an interdisciplinary approach. The article employs a bibliometric approach, a common methodology in the systematic mapping of extant research trends within a defined domain. The building block technique was utilised as the principal approach for conducting literature searches, a method that has been extensively accepted and employed within the relevant research field [47]. The second stage of the research consisted of choosing Scopus and Web of Science as our databases, which includes peer-reviewed articles, books, book chapters and conference proceedings. The Scopus and Web of Science databases were selected because they index a wide range of journals in the fields of management, business, information technology, and engineering. The selection was limited to these two databases due to their high quality, peer-reviewed literature, ability to track citations and compatibility with bibliometric analyses. Google Scholar was not used because of its lack of transparency, the difficulty of replicating results and the presence of non-peer-reviewed sources. We also decided not to search publisher databases such as Taylor & Francis and Springer, since most of their publications are already included in WoS and Scopus. The ResearchGate database was also omitted due to ineffective data filtering, which prevents reliable systematic reviews.

To eliminate duplicates, bibliographic data from both databases were exported in CSV format and merged into a single spreadsheet. Duplicates were then removed in Excel by comparing the following fields: title, DOI, and authors. Ambiguous records were manually verified. Of the 1074 results, 288 duplicates were removed, leaving 786 unique publications for further analysis. This process was documented in accordance with PRISMA guidelines. The PRISMA flow diagram of the given systematic literature review (Figure 2) illustrates the number of studies identified, screened, excluded, and included in the final review.

The review was conducted in February–May 2024 and includes publications published in English between 2016 and 2023. The search was executed according to “Title, abstract, keywords”, where the search terms were “Industry 4.0 AND smart city”. Database searches preceded the selection of keywords for the literature review. For the term ‘smart city’, for example, synonyms such as ‘digital city’, ‘intelligent city’ and ‘modern city’ were also considered. Similarly, related concepts such as the Internet of Things (IoT), sensors, robots, cloud computing and big data were analysed for the term Industry 4.0. However, the large number of results (over 16,000 for many combinations) meant that it was not possible to review them all.

As part of the literature review, the search scope was deliberately narrowed to two key terms: ‘smart city’ and ‘Industry 4.0′. Even though other synonymous terms are also used in scientific literature, the use of variants of these two terms was deliberately limited: smart cities, digital city, intelligent city and ubiquitous city for ‘smart city’; industrial revolution 4.0, fourth industrial revolution, construction 4.0 and cyber-physical systems for ‘Industry 4.0’.

This decision was justified by the widespread and standardised use of these terms in scientific literature, thereby reducing the risk of omitting relevant publications. Narrowing the keywords was also motivated by a desire to ensure consistency and focus the analysis on literature directly related to the relationship between smart cities and Industry 4.0 technologies. Using a broader range of terminology could result in the inclusion of sources that are only marginally related to the subject of the study. For example, this could include sources that cover only aspects of city digitisation without reference to industrial technologies or sources that focus exclusively on industry without an urban context.

This methodological approach enabled the precise identification of scientific publications analysing the interdisciplinary links between the digital transformation of cities and the development of technologies characteristic of the Fourth Industrial Revolution. At the same time, the Section 5 of the paper refers to the aforementioned terminological variants as potential areas for further analysis in future research.

With the assumed search criteria, the number of publications found is 1074 documents (733 papers in Scopus and 341 papers in Web of Science). Full texts of the remaining articles were assessed for relevance and alignment with the research objectives. Inclusion criteria included empirical studies, conceptual papers, or reviews directly addressing the intersection of Industry 4.0 technologies and smart city applications. Final articles were selected for qualitative synthesis and, where appropriate, quantitative bibliometric analysis.

The next step was to remove the duplicates, leaving 786 documents. Restricting the publication date to 2023 resulted in a reduction in the number of articles to 708.

Examining the articles on Industry 4.0 tools used by cities, it is noticeable that academic interest in this topic has only taken place since 2016 (Figure 3). In 2016, only 12 publications related to the use of Industry 4.0 tools in the concept of smart cities appeared in databases. However, researcher interest has grown year on year. The largest increase in publications was in 2020—142 documents were published then. After this—probably due to a reduction in research activity by scientists during the pandemic—the number of articles decreased to 121. Nevertheless, interest in this topic is growing again, with 153 publications in 2023.

During the period under review, the largest number of articles were published in the areas of computer sciences and engineering.

In terms of the type of publication, the most prevalent were conference papers (41%), research articles (31.5%), and chapters in books (10%) (Figure 4). For the purposes of this study, only research articles, book chapters, and books were selected for further analysis. Consequently, the number of papers included in the study was limited to 708.

The largest number of studies on smart city and Industry 4.0 have been published by the IEEE and Springer (Figure 5). Also, academics have published their work in MDPI and Elsevier.

Among authors, scientists such as Miroslav Svítek and Michal Postranecky (Czech Technical University in Prague, Czech Republic), Daniel G. Costa (University of Porto, Portugal), Sudeep Tanwar (Nirma University, India), Neeraj Kumar (Thapar Institute of Engineering and Technology, India), João L. Marques and Leonor Teixeira (University of Aveiro, Portugal), Theodore E. Matikas and Anastasios C. Mpalaskas (University of Ioannina, Greece), and Lei Wang (Tongji University, China) were the most productive (Figure 6).

As part of the analysis and synthesis of the literature on smart cities a keyword analysis was also carried out. We used the Visualisation of Similarities (VOS) mapping technique, which allows the visualisation of similarities in order to similarities to show the co-occurrence network of keywords in scientific publications. In the 708 documents examined, Industry 4.0 was used 237 times and smart city 194 times. In addition, Internet of Thing (217 times), Artificial Intelligence (48 times), blockchain (33 times), cyber-physical system (29 times), Digital Twin (29 times), machine learning (29 times), big data (24 times), security (24 times), sustainability (22 times), and cloud computing (21 times) were popular. Links between keywords are shown using VOSviewer (Figure 7).

The visualisation reveals the presence of several distinct thematic clusters, marked with different colours:

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The red cluster focuses on issues such as smart cities, digitalisation, sustainability and the circular economy, suggesting a strong interest among researchers in aspects of sustainable development and the digital transformation of urban environments;

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The green cluster focuses on technologies related to security and privacy, such as blockchain technology, cyber security, cloud computing and machine learning;

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The blue cluster covers topics related to the future of industry and communication technology, including industry 5.0, 5G, 6G and artificial intelligence;

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The orange cluster represents the Internet of Things and related communication technologies, such as LoRaWAN and LPWAN;

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The purple cluster contains keywords related to advanced data analytics and artificial intelligence, including deep learning, computer vision and digital twins.

The distances between nodes reflect the strength of semantic relationships—the closer two concepts are to each other, the more frequently they co-occur in scientific literature. The central location of ‘industry 4.0′ emphasises its integrating role as a concept linking various technological, social and economic aspects.

The results obtained allow the identification of the main areas of research interest and confirm the multidimensional nature of the discussion on the applications of Industry 4.0 tools in urban spaces.

It was decided to only consider research articles and books or chapters in books. In the end, 316 papers were included in the analysis of abstracts. A detailed review of the abstracts resulted in 102 articles being highlighted. After reading the full texts, 79 texts were qualified for extensive analysis. The final stage of the research involved a descriptive analysis of our search results, extracting key areas of connection between Industry 4.0 and smart cities.

Following a keyword and abstract analysis, our assumption was that each of the smart city elements can use each of the mentioned Industry 4.0 tools to achieve a better functioning urban system, as well as to improve the livelihoods of stakeholders in the city (Figure 8).

4. Research Results

Table 2. Documents describing the implementation of Industry 4.0 tools in the smart city areas.

Industry 4.0 Tools in Smart Cities	Smart Mobility	Smart Economy	Smart People	Smart Environment	Smart Living	Smart Governance
Internet of Things	3, 5, 8, 12, 15, 19, 20, 22, 24, 29, 32, 34, 40, 41, 45, 47, 48, 49, 51, 52, 53, 60, 72	1, 8, 17, 26, 29, 36, 42, 60	4, 8, 17, 30, 42, 50, 62, 79	8, 21, 24, 26, 27, 33, 34, 35, 39, 42, 49, 54, 66, 73, 75, 76, 55	8, 11, 36, 64, 68, 77	8, 10, 13, 38, 39, 74
Artificial Intelligence and machine learning	4, 5, 18, 19, 25, 28, 32, 44, 45, 48, 53, 65, 71, 78	26, 28, 78	4, 25, 78	26, 28, 33, 35, 39, 75, 78, 55	61, 68, 78	39, 56, 78
Digital Twins	46, 57, 71, 78	78	78	69, 78	16, 59, 78	10, 16, 78
Big data	7, 43, 45		36	37	36, 64	7, 10, 31, 74
Blockchain	6, 22, 23, 51, 60	58, 60	79	35, 66	67
Cloud computing	6, 15	42	42	42
Fog computing	3, 49			49		14
CPS	8, 51	8	8	8	8	8
Robots, drones, autonomous vehicle	2, 19, 25, 48, 52	42	25, 42	42, 63
Augmented reality			62, 70

presents the results of the overall document analysis in terms of the application of Industry 4.0 tools in the areas of smart mobility, smart economy, smart people, smart environment, smart living and smart government. For a list of publications selected for analysis, see Supplementary Materials—Table S1.

The most prevalent technology across all urban areas is the IoT. This is particularly evident in the context of smart mobility, where the utilisation of diverse sensors facilitates enhancements in road safety, travel convenience within urban environments and the parking process. Concurrently, the IoT has the potential to enhance the quality of public transportation by facilitating the monitoring of transportation routes. The IoT is of particular importance in the context of smart environments, as it enables the monitoring of environmental indicators, including air, water, soil, and green areas quality, as well as energy consumption. This also contributes to the achievement of a correspondingly enhanced standard of living. The utilisation of the IoT in administrative contexts facilitates decision-making processes based on comprehensive data sets. In the domain of the smart economy, IoT enables the enhancement of operational efficiency through process automation, the deployment of predictive techniques, and the optimisation of supply chains. In the context of smart people, sensors can monitor student engagement, and connected devices provide adaptive educational materials tailored to individual needs. IoT supports virtual learning by connecting devices, enabling access to educational resources, and facilitating real-time communication between students and teachers.

The second most frequently mentioned Industry 4.0 tool in the documents is artificial intelligence. In the field of smart mobility, artificial intelligence has applications in traffic lights, smart transport systems, traffic guidance. Artificial intelligence in the context of environmental management enhances ambient monitoring by analysing data from IoT sensors to detect pollution, track climate patterns and respond to environmental threats in real time. AI also enables precision in waste management, water conservation and renewable energy systems, supporting green urban living. In terms of smart living, AI can facilitate personalised home automation, optimising energy consumption and enhancing security with smart devices such as voice assistants and surveillance systems. It improves healthcare through wearable technology and predictive analytics for early diagnosis and personalised treatment. In the smart people area, AI enhances digital inclusion by simplifying the use of technology and promoting collaborative, data-driven citizen engagement. In the smart economy, AI is used to create content and support decision-making. In city governance, AI enhances transparency and citizen engagement through chatbots, e-government platforms and real-time feedback systems. Furthermore, AI also improves resource allocation and crisis management, ensuring efficient and responsive governance in smart cities.

Digital twins for the city also have many benefits. In terms of mobility, DTs simulate traffic patterns to optimise traffic signal times and reduce congestion in real time. They also model public transport networks to improve planning and passenger experience. With the help of DTs, pollution hotspots arising in the city can be predicted. With this technology, sustainable urban planning can be implemented. Digital building twins track energy consumption and optimise heating, cooling and lighting to increase efficiency. They also improve disaster preparedness by simulating emergency scenarios and evacuation plans. DTs provide virtual models of urban infrastructure, enabling decision-makers to effectively test and implement urban strategies. In the business environment, DTs optimise supply chains by modelling logistics and warehouse operations to increase efficiency. They simulate market behaviour, helping companies forecast demand and design innovative products or services. Computerized twin-based smart cities present numerous opportunities for economic transformation, urban intelligent governance, and public smart services, fostering a more harmonious development between humanity and the environment [48].

The application of big data analysis is beneficial for urban mobility management and governance planning processes. Admittedly, the use of big data was less common in the domains of smart economy, smart people and smart environment in the analysed articles. This is probably because, in most cases, research in these areas is not associated with smart cities.

The fundamental concept of blockchain technology in a smart city by the authors of the documents analysed is to establish a secure, transparent, and decentralised system for the management of data and transactions across a range of urban services. It serves to enhance trust and accountability by ensuring the immutable and tamper-proof nature of information, including utility usage, public records, and digital payments. By employing blockchain technology, smart cities can optimise efficiency, reduce costs, and facilitate the development of new decentralised services, thereby fostering enhanced collaboration and innovation in urban governance and management. To a somewhat lesser extent, researchers directed their attention towards the utilisation of cloud computing and fog computing. It is noteworthy that the concept of fog computing was first described between 2016 and 2019, with researchers subsequently directing their attention to cloud computing. The use of CPS systems in smart city areas has been described only infrequently. The studies analysed also included ideas about the use of robots, drones, automated vehicles and augmented reality. However, it seems that there are still many potential applications of Industry 4.0 tools in urban areas that have not yet been presented in the literature. It is possible that these applications are still in the early stages of testing, and that only their successive implementation will result in an increase in publications on the subject.

In

Table 3. Selected quotations on Industry 4.0 tools used in smart cities areas.

Smart City Area	Industry 4.0 Tools Used in Key Areas of Smart Cities	Authors
Smart mobility	Internet of Things (IoT), big data systems and mobility are some of the services programmers of smart cities. Smart parking is the crucial parts of smart city. Connected automobile with its advanced technology reduces the chances of accident and help drivers save time and gasoline in their limits. More urban ourplanet becomes, smarter the cities have to be.	Rastogi et al., 2022 [49]
	Integrating blockchain technology and the IoT into city transportation systems will undoubtedly have many benefits. These benefits cover a widerange of data sharing and tracking to smart city residents’ transparency and privacy.	Abbas et al., 2021 [50]
Smart environment	The applications of IT software, AI and automation of one or more stages in the urban greenery management and development contributes to freeing human labor, increasing the storage capacity and the ability to enhance the integrated information processing between urban greenery and related fields.	Tuan, 2021 [51]
	IoT improves and simplifies our lives in numerous ways to protect our environment, and society by sensing and cooperatively communicating over the internet. Finding suitable and efficient techniques for greening IoT is required to improve our quality and sustainability of resources.	Alsamhi et al., 2021 [52]
	Digitally twinning the development process of smart energy systems for futuristic smart cities is essential for various benefits in the areas of operation and maintenance.	Musti and Tomar, 2023 [53]
Smart economy	A cloud-based continuum generative design with integrated hybrid additive subtractive manufacturing concept can provide a unique digital manufacturing system which is accessible from any IoT device	Dilibal et al., 2021 [54]
Smart people	The human resources are an important aspect of Industry 4.0 implementation. Although the introduction of automation, digitisation and CPS, the humans remain an important constituent part for planning, designing and implementing modern production systems and factories. A scarcity of skilled labour forces will be experienced by many industrial sectors. Especially, SMEs have great difficulties in finding highly educated employees. However, considering the increasing trend of urbanisation, factories close to metropolitan areas bear enormous advantages. One of these advantages is to address the lack of qualified labour-forces.	Matt et al., 2020 [55]
	The application of technology enabled solution in Industry 4.0 is estimated to rise and benefit a wide range of sectors. The result analysis indicates that the use of advance technology enhances and optimizes various HRM sectors to thrive in the digitization era for IOT smart cities.	Vijh et al., 2023 [56]
	Society 5.0 is a super-intelligent society in which emerging advanced technologies are integrated with industry and social life to solve numerous societal concerns and inhabitants’ lives will be more pleasant and sustainable. It envisions a society where everyone enjoys life to the fullest. The purpose of economic growth and technological development is not for the welfare of a select few, but to create prosperity for everyone. In the emerging technologies, the 5G-IoT is a potential contender, which plays a crucial role for Society 5.0 such as for facultative distribution of required resources across the inhabitant and identifying resources that are in excess supply, pooling information on wastage with its supply on demand. The societal concerns are global challenges therefore; the Society 5.0 does not serve the needs of one country alone.	Ferreira et al., 2022 [57]
	The town of Riihimäki [in Finland] has invested heavily in educational robotics activities, ranging from nurseries and elementary schools, to university level and lifelong learning for adults, integrating this with the needs of various sectors, including industry, health care, education, and traffic.	Ruohomaa et al., 2019 [58]
Smart living	The intelligent street landscape construction can ensure the rational resource allocation and construction efficiency through the in-depth survey of on-site environmental factors (e.g., soil quality, hydrological conditions, wind force, atmospheric pressure) using the sensing and RFID systems of IoT technology and the corresponding construction schemes and regulation.	Li et al., 2021 [59]
	The development of new monitoring technologies with reasonable processing power and affordable prices has the potential to transform the way we perceive our environment and detect critical events, potentially saving lives and reducing properties damages. Together with the maturation of communication protocols and the Internet of Things paradigm, the resulting scenario is fertile for the adoption of new services to improve our quality of life. In this scenario, with most people living in urban areas and with the proliferation of large cities around the world, the development of emergency alerting systems has become even more relevant, as critical events have the potential to affect a great number of people.	Costa et al., 2020 [60]
Smart governance	Open (government) data provide access to create added value in Industry 4.0 and Society 5.0, also known as the super-smart society, and support the idea of greater openness and accountability in business and administration governance	Nikiforova, 2021 [61]
	Public services should be administered using innovative AI technologies and e-governance in convenient modes to eliminate the barriers between stakeholders and city governments, while state officials can still sustain the model for better support.	Bokhari and Myeong, 2023 [62]

, there are some quotations for Industry 4.0 tools used in smart cities.

After analysing documents related to smart cities and Industry 4.0 technologies, we identified several common research areas in the collected sample of articles:

• Integration of IoT and smart city technologies: research focuses on the deployment of IoT technologies in urban environments to enhance connectivity and data-driven management of city services.
• Smart Mobility and transportation systems: this involves the development of intelligent transportation systems that utilize advanced technologies for traffic management and enhanced public transportation.
• Smart Infrastructure and building management: topics here cover the development of smart buildings and infrastructure that leverage digital technologies for better resource management and operational efficiency.
• Public participation and governance: this area explores how digital platforms and tools can enhance citizen engagement and governance transparency in smart cities.
• Data security and privacy: addressing the challenges related to securing the vast amounts of data generated by smart city technologies and ensuring privacy protections for individuals.
• Economic development through smart technologies: investigating how Industry 4.0 technologies can be leveraged to drive economic growth, attract investment, and improve city competitiveness.
• Sustainable urban development: this includes the use of smart technologies for sustainable planning, which often intersects with environmental goals like reducing carbon emissions and improving energy efficiency.

Despite the growing interest in using Industry 4.0 technologies in smart cities, a review of the literature reveals significant gaps in the research in several areas. These gaps may be related to a number of factors. Firstly, many solutions, such as cyber-physical systems, robotics, augmented reality, digital twins and blockchain, are still in the early stages of testing and experimental implementation in cities. Consequently, there is a dearth of large-scale empirical research and case studies on which to base comparative or quantitative analyses. Secondly, technologies such as fog computing, blockchain and cyber-physical systems are characterised by high infrastructure complexity and a lack of established implementation standards in urban environments. This hinders their widespread and consistent application, limiting the number of scientific studies. Thirdly, access to large urban datasets, which are often confidential or protected, is crucial for big data, AI and digital twins. The lack of open data and the difficulties in obtaining it limit the possibility of conducting application-oriented research. Fourthly, Industry 4.0 technologies are widely used in urban mobility and environmental management contexts, but less so in areas such as the smart economy, smart people and governance. This may be because technological implementations in these areas tend to be more social than infrastructural in nature, making them more difficult to measure and describe.

Despite the growing interest in using Industry 4.0 technologies in smart cities, a review of the literature reveals significant research gaps in several areas. These gaps may be due to a number of factors. Firstly, many solutions, such as cyber-physical systems, robotics, augmented reality, digital twins and blockchain technology, are still in the early stages of testing and experimental implementation in cities. Consequently, there is a dearth of large-scale empirical research and case studies on which to base comparative or quantitative analyses. Secondly, technologies such as fog computing, blockchain and cyber-physical systems are characterised by high infrastructure complexity and a lack of established implementation standards in urban environments. This hinders their widespread and consistent use, thereby limiting the amount of scientific research. Thirdly, access to large urban datasets, which are often confidential or protected, is crucial for big data, artificial intelligence and digital twins. The lack of open data and the difficulties involved in obtaining it restrict the scope for conducting application-oriented research. Fourthly, Industry 4.0 technologies are widely used in urban mobility and environmental management contexts, but less so in areas such as the smart economy, smart citizens and smart governance. This may be because technological implementations in these areas tend to be more social than infrastructural in nature, which makes them difficult to measure and describe.

5. Discussion

The findings of our analysis demonstrated that the industry tolls are also operational within an urban context. We concur with Nick et al. [63] argument that the implementation of Industry 4.0 in an urban setting necessitates the presence of a supportive infrastructural and social environment, which also has a significant urban dimension. The smart city development model requiring the utilisation of sophisticated technologies, including big data, IoT and cloud computing. By implementing Industry 4.0 tools, the government is able to effectively manage scarce resources in the present context, minimise pollution and also prepare to meet the demands of urbanisation [64].

Our findings are also in line with Mutavdzija’s [65] conclusions, where it was identified that the IoT plays a key role in the development of the smart city. We agree that a smart city can be considered as an ecosystem where Internet of Things and other digital technologies are used for remote data collection and processing, enabling better decision-making in managing urban resources such as water, energy, and transportation [66]. The links we have detected between the different areas of the smart city and the tools of Industry 4.0 are broadly in line with the results of Storolli [67]; however, we have noticed that in recent years researchers have placed less emphasis on the delineation of IoT, IoS, IoD or IoE.

The integration of Industry 4.0 technologies in smart cities reveals both extensive opportunities and notable challenges. The technologies of Industry 4.0 play an important role in improving the efficiency of urban management, the optimization of resources, and the overall quality of life of residents. The bibliometric analysis of the existing literature highlights their applications in different domains, including smart mobility, governance, economy, and living environment. This analysis demonstrates the interconnectedness of technological tools in promoting urban sustainability. However, challenges remain in terms of data security, infrastructure compatibility and equitable access, which require integrated governance models and robust cybersecurity frameworks. The theme of the co-creation of smart city strategies with citizens allied to the evolution of society and its demanding needs is evident in the literature we have analysed. We agree with Correira et al. [68] that this can lead the industry to adapt to their social wishes and adopt new practices. In the context of implementing Industry 4.0 technologies in smart cities, the observation that ‘success depends on maintaining a balance between technological progress and ethical, social and environmental issues’ is particularly relevant. The adoption of artificial intelligence, the Internet of Things (IoT), digital twins and data analytics not only presents technological challenges, but also raises questions regarding algorithmic transparency, citizen privacy, digital exclusion and environmental impact.

Stakeholder theory reinforces this argument by emphasising the need to consider the interests of a wide range of participants in urban transformation—not only authorities and investors, but also residents, social organisations and the scientific community. Furthermore, incorporating ethical strategies into technology management (e.g., AI ethics frameworks or principles of sustainable digital development) could lay the groundwork for developing responsible models for implementing technology in urban spaces.

Therefore, future research should analyse not only the technological potential of Industry 4.0 solutions in smart cities, but also their social and ethical impact. This requires an integrated approach that combines humanistic, legal and environmental perspectives with engineering and systems thinking.

Practical implementations, such as AI-driven traffic management and IoT-enabled environmental monitoring, demonstrate the tangible benefits of these technologies. However, the complexity of deploying such systems at scale highlights the need for multidisciplinary collaboration between policymakers, technologists and urban planners. The study concludes that while Industry 4.0 offers transformative potential for cities, its success depends on balancing technological advances with ethical, social and environmental considerations.

This discussion reinforces the notion that smart cities are dynamic ecosystems, where technology serves as both an enabler and a challenge in achieving sustainable urban growth.

6. Conclusions

Researchers in academic papers describe such Industry 4.0 tools being implemented by cities, such as Internet of Things, Artificial Intelligence and machine learning, blockchain, digital twins, big data, autonomous vehicles and drones, and augmented reality. The use of these tools is aimed at improving the quality of life for residents and stakeholders, as well as streamlining the city’s processes in pursuit of sustainable development.

Strategic initiatives enhance urban infrastructure and societal well-being. This involves smart grid implementation for energy efficiency and reliability, alongside proactive infrastructure failure prediction via big data analytics and pervasive sensors to optimize costs and minimize downtime. Integrating sustainability principles is crucial for urban development. Enhanced urban mobility stems from intelligent transportation systems and autonomous vehicles. Fostering new enterprises and employment drives economic growth. Increased productivity results from automating and standardizing municipal processes. Finally, improving public safety, civic engagement, and robust waste management with pollution mitigation elevates resident quality of life.

The integration of Industry 4.0 technology with the smart city concept also poses challenges, particularly related to data privacy, social equity, infrastructure integration, financial constraints, regulatory issues and environmental impact. Meeting these challenges requires a holistic approach that includes robust cybersecurity measures, equal access to technology, a thoughtful regulatory framework and sustainable practices.

Despite these challenges, Industry 4.0 technologies represent a paradigm shift in urban development. By leveraging these advanced tools, cities can enhance their operational efficiency, foster sustainable practices, and create inclusive environments that prioritize the well-being of all stakeholders. The continuous evolution of these technologies offers a promising pathway toward smarter, more resilient urban ecosystems.

Analysing the integration of Industry 4.0 technology in an urban context requires identifying general trends and specific implementation examples, as well as practical policy recommendations to enable effective translation of theory into practice.

Contemporary cities such as Barcelona and Singapore are prime examples of the use of modern technologies. Barcelona has introduced smart sensors to monitor energy consumption and air quality, contributing to a significant reduction in carbon dioxide emissions and improving living conditions for residents. Meanwhile, Singapore uses digital twins to enable precise spatial planning and real-time transport management, thereby increasing the efficiency of urban infrastructure.

To further develop and effectively implement Industry 4.0 solutions in cities, concrete action is needed at the level of urban policy and administration. Future research should take the following recommendations into account:

• Create open urban data platforms that enable access to a wide range of information in real time while ensuring user security and privacy.
• Establish a clear ethical and regulatory framework for the use of artificial intelligence in urban services. This is particularly important in areas such as urban monitoring, traffic management, and service personalisation.
• Investing in digital education for residents and public administration employees to combat digital exclusion and enable equal and effective use of new technologies.
• Supporting public–private partnerships to enable the development and integration of innovative solutions into existing urban infrastructure.
• Promoting interoperability between smart city systems to enable the smooth exchange of data between different platforms and institutions and improve the efficiency of city management.

Implementing the above measures can significantly contribute to the sustainable and responsible development of smart cities. This would enable the full potential of Industry 4.0 technologies to be exploited, improving the quality of life for residents and the efficiency of city management.