Research on Sustainable Building Development in the Context of Smart Cities: Based on CiteSpace, VOSviewer, and Bibliometrix

Abstract

Buildings play a pivotal role in the daily functioning of cities, and the development of smart cities is intricately linked to the sustainable development of architectural practices. However, existing reviews have predominantly concentrated on the development of smart cities, often overlooking the interdisciplinary complexities associated with integrating smart city technologies and sustainable building practices. This study systematically reviews 418 relevant papers from the Web of Science database, employing both quantitative and qualitative analytical methods to assess the current status and future trajectory of the field. Therefore, it bridges a significant gap in the existing literature. The findings underscore the contributions of technologies such as the Internet of Things (IoT), artificial intelligence, and big data in enhancing the sustainability of buildings within smart cities. The key areas of focus include energy management, smart building systems, and resource optimisation. Furthermore, the study identifies emerging research themes, such as smart city buildings, smart energy management, and digital twins, highlighting their potential to optimise building performance and foster sustainability within evolving urban systems. The keywords identified in the current body of research are categorised into six main areas: context, objectives, methods, artificial intelligence, emerging technologies, and opportunities and challenges. Research themes are seen to progress from “performance” to “building” and “sustainability” and from “city” to “city” and “sustainability”. Notably, themes such as “city”, “modelling”, and “design” have evolved into themes centred around the “Internet”. However, with the rapid expansion of digital technologies, scholars must also address several critical challenges, including data security and privacy protection, the complexity of cross-system data coordination, uncertainties in sustainable optimisation processes, and the ethical and societal implications of technology adoption. To ensure the successful and sustainable development of future urban smart buildings, it is essential to establish rigorous data security standards, harmonise technical protocols, implement effective global strategies, and prioritise ethical considerations. In addition, unmanned technologies and their associated systems offer valuable insights into the sustainability of buildings in smart cities. Finally, this study presents a comprehensive and systematic framework that provides invaluable insights for future strategic planning and technological advancements in the field.

1. Introduction

The significance of architecture in the urban context transcends its functional role as a physical space; it is also integral for shaping and reflecting the dynamics of society, economy, culture, and the environment [1]. Buildings do not merely constitute the tangible fabric of a city; they play a pivotal role in influencing its structure and ongoing evolution.

The development of smart cities is largely driven by information technology, which is embodied in an urban development model aimed at optimizing urban management, enhancing service efficiency, and improving the quality of life for residents. This is achieved through the integration of sensors and data collection technologies, such as information technology, the Internet of Things (IoT), and big data, which enable the real-time monitoring of and data collection for diverse urban activities [2,3]. Notably, smart cities offer a range of innovative solutions that contribute to the sustainable development of the built environment [4]. A key area in which smart cities make significant contributions is the design and construction of green buildings, which not only meet residential and office needs but also provide substantial benefits in energy efficiency, environmental protection, and resource conservation [5].

By integrating smart technologies, these cities enable the real-time monitoring and optimal management of building energy [6]. For instance, smart building management systems (BMSs) monitor variables such as temperature, humidity, air quality, and energy consumption. Based on data analysis, these systems automatically adjust the operation of components such as air conditioning and lighting, reducing energy wastage while maintaining a comfortable indoor environment [7]. Furthermore, smart cities encourage the adoption of renewable energy sources by combining clean energy technologies, such as solar and wind power, with smart grid systems. This reduces reliance on traditional energy sources, enhances energy self-sufficiency within buildings, and furthers the sustainable development of the built environment [8].

As urban intelligence increases, building clusters in smart cities benefit from more precise resource management [9]. Intelligent systems autonomously adjust resource consumption by identifying inefficiencies through sensors and data collection devices, leveraging big data analytics to optimise usage [10]. For example, smart water metres track water usage in real time and issue alerts when irregularities are detected, thereby preventing water wastage [11]. Smart cities also facilitate resource sharing across buildings, optimising energy use, rainwater recycling, and waste heat recovery systems to reduce operational costs, enhance resource efficiency, and promote sustainable development [12].

Simultaneously, intelligent urban transportation systems improve traffic flow, reduce congestion, and enhance accessibility, thereby facilitating the efficient use of buildings [13]. The space within buildings is also managed more effectively, with intelligent space management systems adjusting the allocation of office areas and meeting rooms based on occupancy and work demands, thus minimizing resource wastage [14]. Furthermore, smart cities prioritise the harmonious integration of buildings with the natural environment [15]. Through ecological monitoring systems, elements such as green spaces, water bodies, and air quality are effectively managed. These systems identify pollution sources and ecological degradation, enabling timely corrective actions [16]. Data gathered through these systems also inform building design, ensuring that urban development minimizes its impact on the natural environment.

Finally, smart cities bolster the resilience of buildings by incorporating safety monitoring and disaster warning systems [17]. In the event of a natural disaster, these systems can monitor structural changes in real time and issue early warnings, guiding residents to safety.

The role of smart city development in the sustainable advancement of buildings is increasingly significant. The concept of “sustainable buildings within smart cities” specifically addresses the sustainability of buildings in these urban environments. This concept focuses on the design and operational strategies of buildings or complexes, particularly regarding their incorporation of advanced technologies and environmental protection measures to reduce energy consumption, enhance resource efficiency, and minimise environmental impact.

From an academic perspective, the study of sustainable buildings in smart cities intersects architecture, environmental engineering, and intelligent technologies. It emphasizes green building design, which encompasses energy conservation, the use of renewable energy sources, and the integration of intelligent building systems, such as smart lighting [18], environmental control [16], and energy management systems (EMSs) [19]. Research in this area is closely linked to the established standards, including green building certifications (e.g., leadership in energy and environmental design [20]) and environmental impact assessments (e.g., lifecycle analysis [21]). This line of inquiry explores how buildings can seamlessly integrate into the broader infrastructure of smart cities, optimizing resources and minimising environmental burdens through efficient energy use, intelligent systems, and sustainable materials.

Thus, the sustainable development of buildings within smart cities focuses on creating a green built environment that not only meets basic functional needs but also integrates resource conservation, environmental protection, and pollution control throughout the design, construction, and operational phases of buildings. It is essential to recognize that the development of smart cities extends beyond buildings, encompassing the planning and development of entire urban communities. A comprehensive review of the evolution of smart city construction, through literature analysis, is therefore necessary to gain valuable insights into the sustainable development of the modern built environment.

The role of smart city construction in the sustainable development of buildings is becoming increasingly evident. Smart city development emphasizes the creation of a green built environment that not only fulfils the basic functional requirements of buildings but also incorporates resource conservation, environmental protection, and pollution control throughout the design, construction, and operational stages. Importantly, the development of smart cities extends beyond individual buildings to encompass the planning and expansion of entire urban communities. As such, reviewing the trajectory of smart city construction through literature analysis is crucial for gaining insights into the sustainable development of the modern built environment.

However, existing research on smart cities primarily addresses their sustainable development [22,23,24] and the impact of advanced technologies on urban environments [25,26,27]. A gap remains in the literature regarding the role of architecture in the construction of smart cities. Moreover, most existing reviews rely on systematic methodologies, overlooking the potential of bibliometric literature reviews in tracing the development of research. Econometric literature reviews, in contrast, offer more robust data support and empirical evidence through quantitative analysis, enabling the identification of research trends, academic networks, and emerging research directions [28]. These elements are critical for understanding the sustainable development of the built environment in future smart cities.

Given the rapid advancements in this field, the present study aims to provide a comprehensive and structured review of building sustainability in smart cities. By synthesising and analysing existing applications, this study will evaluate these technologies from a multidisciplinary perspective. Three bibliometric analysis tools will be employed to visualise, qualitatively analyse, and quantitatively assess the relevant data, shedding light on the current state and future trajectory of building sustainability in smart cities. Additionally, this study will identify key themes related to sustainable building development through co-word analysis and track the evolution of the knowledge base in recent years. This study will also explore potential future research directions within this domain.

2. Data Sources and Methods

2.1. Data Source

The research methodology employed in this study involved a comprehensive approach to data collection and selection. The first step was to conduct a review of references from the Web of Science Core Collection (WoS CC), a trusted and reliable source of high-quality citation data [29]. In the second step, the goal was to gather relevant database records. Papers were selected from academic journals present in multiple databases related to the research topic, based on specific inclusion criteria. The search was conducted in the WoS CC subject field using the following search terms: (TS = (“Construction” OR “Architectural” OR “Buildings”) AND TS = (“Smart Cities” OR “Intelligent City”) AND TS = (“Sustainability” OR “Sustainable”) AND DT = (“Article” OR “Review”) AND LA = (“English”)). Bibliometric studies indicate that articles and reviews are more pertinent to research than conference proceedings or book reviews. The third step involved a rigorous screening process to ensure the relevance of the selected references. A total of 430 articles were initially extracted and reviewed to confirm they met the inclusion criteria. Each article was carefully read and analysed to assess its alignment with the study’s focus. Papers that did not address the central themes or conclusions of the research were excluded, even if they contained occasional keywords relevant to the topic. Following this screening process, 418 papers were retained for further bibliometric analysis (Figure 1).

2.2. Research Methods

Bibliometric analysis is a quantitative method used to evaluate and track scholarly literature by examining citation patterns and reference publications. This study utilises three primary research tools: CiteSpace, VOSviewer, and Bibliometrix. These software applications are particularly effective for managing extensive datasets and generating visually informative representations of the data [30]. CiteSpace excels at identifying trends, patterns, and emerging topics within the academic literature, while VOSviewer employs advanced algorithms to process and visualise complex datasets, producing high-quality visual outputs [31]. Additionally, Bibliometrix, which is based on the R programming language, is specifically designed to map research themes and concepts, providing visual representations that chart the evolution of these themes over time [32].

3. Results

3.1. Spatial–Temporal Analysis

3.1.1. Publications

By analysing the complete dataset from the WoS CC database, the evolution of publications on this research topic from 2013 to 2025 can be divided into two distinct periods (Figure 2).

Phase I (2013–2019): The Exploration Phase

During this period, the number of publications increased steadily, though at a relatively slow pace, with the maximum annual publication count not exceeding 23. Following key events, such as the International Conference on New Concepts in Smart Cities: Fostering Public and Private Alliances and the IET International Conference on Smart and Sustainable Cities in 2013, attention shifted towards the sustainable development of urban buildings. The integration of information and communication technologies (ICTs) created significant opportunities to enhance urban infrastructure, including buildings [33,34]. Furthermore, the potential of emerging technologies to promote sustainability within urban building communities became a critical focus in the planning and implementation of smart cities [35]. These studies provided valuable insights into the possibilities for sustainable architectural development within the broader context of smart city construction.

Phase II (2019–2025): The Development Phase

This phase is characterised by a clear upward trend in the number of publications, although some fluctuations are observed. The minimum annual publication count reached 37. The Smart City Expo World Congress in 2018 highlighted various aspects of smart city applications. In addition, the IEEE International Smart Cities Conference addressed several critical topics related to building sustainability within the context of smart cities, including architectural culture [36], building energy efficiency [37], and architectural design [38]. These events provided valuable insights and practical references for both the application and in-depth study of building sustainability in smart cities, thus enriching scholars’ understanding of this rapidly evolving field.

3.1.2. Countries

The country cooperation map illustrates the global distribution of publications and the collaborative relationships between countries and regions (Figure 3). Darker areas on the map indicate higher publication volumes, with China making the most significant contribution to research in this field, followed by the UK, France, Australia, and others. Thicker lines represent stronger collaborative ties, such as those between China and the UK, the UK and South Africa, and the US and China.

3.1.3. Journal

Among the top five journals with the highest citation and publication counts, two stand out by excelling in both metrics (

Table 1. Journal.

Sources	Citations	Sources	Number of Citations per Article
Sustainable Cities and Society	1162	Technological Forecasting and Social Change	124
Sustainability	941	Sensors	58
Technological Forecasting and Social Change	746	Sustainable Cities and Society	52
Sensors	585	Journal of Cleaner Production	51
Journal of Cleaner Production	461	Applied Sciences-Basel	33

): Sustainable Cities and Society and Technological Forecasting and Social Change. While both journals lead in these areas, each excels in a distinct aspect. Technological Forecasting and Social Change is primarily a professional management journal, whereas Sustainable Cities and Society is categorized as an engineering and technology journal.

3.2. Co-Occurring Keyword Analysis

The co-occurring keyword analysis categorises the literature into five distinct groups, each corresponding to a specific research theme (Figure 4). The blue cluster represents the broader context of this study, encompassing terms such as “smart cities”, “systems”, “innovation”, and “technology”. These keywords highlight a focus on management systems and emerging technologies, indicating that building sustainability within smart cities is a complex, interdisciplinary challenge requiring a multifaceted approach. The green cluster reflects the central objective of this research, with “sustainability” linked to “energy”, “impact”, and “urbanization”. This grouping underscores the interdependence between the development of smart cities and the transformation of urban buildings. The red cluster focuses on key strategies for ensuring the sustainable development of buildings within smart cities, with “building design” emerging as a direct method of implementation. It also highlights the role of artificial intelligence in optimising building performance, particularly in enhancing energy efficiency and facilitating demand response. The yellow cluster examines the impact of emerging technologies on building sustainability, placing particular emphasis on “big data management” as a critical factor. Finally, the purple cluster explores future opportunities and challenges related to building sustainability within smart cities, suggesting that advances in Internet infrastructure could lead to significant breakthroughs and transformative developments in this field.

CiteSpace cluster analysis identified seven distinct clusters, each demonstrating strong internal coherence (modularity Q = 0.8755) and moderate similarity between clusters (S = 0.9327). These clusters, illustrated in Figure 5, exhibit a well-structured framework and satisfactory inter-cluster similarity (

Table 2. Clustering of literature co-citation.

Cluster ID	Size	Silhouette	Mean (Year)	Label
0	81	0.88	2021	smart city construction
2	57	0.924	2017	smart city development
3	56	0.924	2019	smart energy management
4	49	0.955	2016	cooperative EMS
5	39	0.972	2021	digital twin
7	24	1	2013	recent interpretation
9	18	0.972	2021	AI

). The most influential clusters were smart city construction (cluster #0), smart city development (cluster #2), and smart energy management (cluster #3), with smart city construction emerging as the most critical cluster. An analysis of the average formation time revealed that smart city construction (cluster #0), digital twins (cluster #5), and artificial intelligence (cluster #9) are the most recent developments. In contrast, the recent interpretation cluster (cluster #7) had an earlier formation date.

Figure 6 illustrates the evolution of citation clusters, where node sizes represent the number of citations and connecting lines denote citation relationships. Clusters #0, #7, and #8 demonstrate remarkable longevity, having sustained attention over time. These clusters are expected to remain central, continuing to attract significant interest and citations. This analysis offers valuable insights into the dynamics of these clusters, enabling scholars to identify topics with long-term relevance and informing strategic decisions for future research investments. While clusters #2, #3, and #5 have not exhibited the same level of persistence as clusters #0, #7, and #8, they have garnered substantial attention in recent years, suggesting that they will likely remain important research areas. In contrast, clusters #12 and #14 show significant publication gaps, indicating reduced activity or the potential cessation of research in these domains.

The bibliometric analysis identified three key clusters relevant to building sustainability within the context of smart cities. The five most cited and referenced articles within each cluster are presented below.

The primary feature of cluster #0 is the integration of urban architectural development with the requirements of buildings in smart cities (

Table 3. Citations and cited literature for cluster #0.

Cluster #0 Smart City Construction
Citing Articles		Cited References
Author (Year)	Coverage	Author (Year)	Freq
Yang, Su and Yu [39]	20%	Chu, Cheng, Yu, and Change [44]	14
Hui, Dan, Alamri, Toghraie, and Society [41]	15%	Syed, Sierra-Sosa, Kumar, and Elmaghraby [45]	13
Bastos, Costa, Rocha, Fernández-Caballero, and Pereira [42]	15%	Caragliu, Del Bo, and Change [46]	13
Wu, Shi, Luo, and Research [40]	14%	Camero and Alba [47]	13
Yue, Mao, Wang, Peng, Zhao, and Change [43]	14%	Ismagilova, Hughes, Dwivedi, and Raman [48]	12

). Smart city policies, particularly those implemented in pilot cities, focus on enhancing urban innovation capacity and green total factor productivity [39]. The Smart Cities Programme promotes urban sustainability by incorporating technologies that reduce environmental pollution, improve energy efficiency, and support green growth [40]. Green spaces are integral to the sustainability of smart city environments, particularly in the context of smart building development, where green infrastructure can significantly improve air quality, mitigate thermal effects, and enhance residents’ overall well-being [41]. The use of data collection, sensor systems, and IoT technologies is crucial for optimising energy consumption, minimising waste, and improving the sustainability of the built environment [42]. However, it is important to note that building practices in both developed and less developed regions may have contrasting effects on the overall development of smart cities [43]. Additionally, key publications such as those by Chu et al. [44], Syed et al. [45], Caragliu et al. [46], Camero and Alba [47], and Ismagilova et al. [48] represent foundational contributions to this area of research.

Cluster #2 primarily addresses the overarching development requirements for the construction of smart cities (

Table 4. Citations and cited literature for cluster #2.

Cluster #2 Smart City Development
Citing Articles		Cited References
Author (Year)	Coverage	Author (Year)	Freq
Yang, Kwon, and Kim [49]	20%	Silva, Khan, Han, and society [53]	19
De Marco and Mangano [50]	16%	Appio, Lima, Paroutis, and Change [54]	12
Kasznar, Hammad, Najjar, Linhares Qualharini, Figueiredo, Soares, and Haddad [52]	13%	Yigitcanlar, Kamruzzaman, Foth, Sabatini-Marques, Da Costa, Ioppolo, and society [27]	9
Rani, Mishra, Usman, Kataria, Kumar, Bhambri, and Mishra [25]	9%	Ruhlandt [55]	8
Berglund, Monroe, Ahmed, Noghabaei, Do, Pesantez, Khaksar Fasaee, Bardaka, Han, and Proestos [51]	9%	Myeong, Jung, and Lee [56]	6

). A key challenge today is ensuring the sustainability of smart cities, particularly in terms of environmental impact and resource management. This is especially critical in the building services sector, where there is a growing demand for environmentally friendly solutions related to energy, water, and waste management [49]. ICT services, particularly e-government frameworks, play a pivotal role in supporting more efficient urban management [25]. For example, the integration of sensors and actuators can enhance the resilience and sustainability of buildings within the smart city framework by automatically adjusting systems to respond to extreme weather events [50]. Additionally, the introduction of decentralized smart grid systems, combined with EMS, improves energy efficiency and facilitates energy trading, aligning closely with sustainable building practices [51]. However, the adoption of advanced encryption technologies and secure data management practices is essential for the sustainable development of smart cities. Given the vast network of interconnected devices involved in smart city construction, addressing citizens’ security and privacy concerns is critical to prevent potential risks [52]. Studies by Silva et al. [53], Appio et al. [54], Yigitcanlar, Kamruzzaman, Foth, Sabatini-Marques, Da Costa, Ioppolo, and society [27], Ruhlandt [55], and Myeong et al. [56] have made significant contributions to understanding the broader development of buildings in smart city research, laying the foundational groundwork for this area of study.

Cluster #3 highlights the critical role of energy management in the sustainability of buildings within smart cities (

Table 5. Citations and cited literature for cluster #3.

Cluster #3 Smart Energy Management
Citing Articles		Cited References
Author (Year)	Coverage	Author (Year)	Freq
Jain, Gue, and Jain [59]	8%	Allam and Dhunny [62]	12
Heidari, Navimipour, Unal, and Society [60]	7%	Ahad, Paiva, Tripathi, Feroz, and society [63]	10
Orejon-Sanchez, Crespo-Garcia, Andres-Diaz, Gago-Calderon, and Society [57]	7%	Al Dakheel, Del Pero, Aste, Leonforte, and Society [64]	8
Al-Obaidi, Hossain, Alduais, Al-Duais, Omrany, and Ghaffarianhoseini [61]	7%	Jia, Komeily, Wang, and Srinivasan [65]	5
Yang, Lv, and Wang [58]	6%	Apanaviciene, Vanagas, and Fokaides [66]	5

). In smart cities, energy management transcends basic monitoring and control, incorporating advanced systems designed to ensure that buildings operate at peak energy efficiency [57]. Zero-Energy Buildings (ZEBs) are a key component of smart city sustainability goals, as they generate energy equal to the amount they consume through renewable sources such as solar, wind, and geothermal. These buildings play a pivotal role in reducing reliance on non-renewable resources [58]. The application of Artificial Neural Networks (ANNs) and Machine Learning (ML) techniques in smart cities holds significant potential to reduce the environmental impact of buildings. These technologies, including the use of ANNs for energy prediction, air quality monitoring, and efficient resource management, enhance building sustainability by predicting energy usage patterns, optimising energy flows, and supporting sustainable building practices [59]. For instance, energy demand prediction using ML techniques, such as Long Short-Term Memory (LSTM) models, enables smarter, real-time energy management, thereby supporting energy efficiency in smart cities [60]. Furthermore, the integration of big data analytics into energy management systems helps optimise energy consumption, reduce waste, and achieve sustainability objectives in building operations [60]. A crucial aspect of this is the early integration of IoT technologies in building design, ensuring energy efficiency from the outset. This involves assessing the building’s physical layout, orientation, and energy systems to optimise the incorporation of IoT for long-term energy efficiency and sustainable operations [61]. Researchers such as Allam and Dhunny [62], Ahad et al. [63], Al Dakheel et al. [64], Jia et al. [65], and Apanaviciene et al. [66] have laid a strong foundation for advancing the research in this area.

3.2.1. High-Centrality Articles

This study has focused on key articles related to building sustainability within the context of smart cities, particularly those that have made a significant impact across multiple disciplines (

Table 6. Top 5 high betweenness centrality articles.

Centrality	Years	Author	Source
0.14	2017	Bibri S E	Sustainable Cities and Society
0.1	2015	Albino V M.	Journal of Urban Technology
0.09	2019	Allam Z	Cities
0.08	2020	Bibri S E	Energy Informatics
0.08	2019	Camero A	Cities

). These publications represent pivotal milestones that have contributed to advancing various research fields. Their value lies in their ability to bridge diverse areas of study, fostering a deeper understanding of complex issues. The analysis identifies four major publications that are particularly influential in the field, playing a central role in connecting different research domains. These works are crucial not only because they highlight the interconnected nature of architecture and smart city development, but also because they enhance scholars’ understanding of the potential for sustainable architectural development within smart cities.

3.2.2. Strongest Citation Bursts

This study examines the impact of specific publications in the field of building sustainability within smart cities, particularly those that have experienced a significant and rapid increase in citations, a phenomenon known as a “citation explosion”. This surge in citations reflects the growing interest and importance of a particular research area. Two main types of articles exhibit the highest citation rates (Figure 7): review articles and theoretical articles. Review articles provide comprehensive overviews and theoretical perspectives on sustainable buildings in smart cities, making them highly influential and frequently cited. Notable examples include works by [27,53,67]. In contrast, theoretical articles focus on defining the concept of smart cities, exploring their various dimensions, and developing research methodologies. Examples of such works include studies by [68,69]. These theoretical contributions are essential in advancing the understanding of sustainable development within the context of buildings in smart cities.

3.3. Theme Evolutionary Analysis

3.3.1. Thematic Evolution Map

Figure 8 presents a visual representation of the evolution of research themes, illustrating the interconnections between these themes and their various developmental trajectories within the field. Each node on the left and the right side of the figure represents a set of research themes, with the size of the node reflecting the volume of related articles. Solid lines connecting the nodes indicate shared significance between the themes, signalling the mainstream evolution of the research. The thickness and colour of the lines represent the degree of similarity between topics, with darker and thicker lines indicating stronger connections. The figure highlights the emergence of new research areas over time, emphasising the dynamic nature of the field. Notably, the term “Internet” emerged as the most significant keyword during this evolution, reaching its peak prominence in the second phase. Concurrently, research related to “Cities”, “Models”, and “Design” began to converge into the domain of the Internet. The connection between “Design” and “Buildings” has strengthened, highlighting the central role of design practices in the development of buildings in smart cities. Furthermore, research on “Cities” and “Models” is increasingly aligning with “Buildings”. Sustainability remains a key theme across both phases, underscoring that environmental protection and sustainability will continue to be central priorities in the future of architecture and urban planning.

3.3.2. Strategic Coordinate Diagram

Figure 9 visually illustrates the evolution of building sustainability research within the context of smart cities. The research themes are categorised into four quadrants of a strategic map, based on two key factors: centrality (the degree to which a theme is connected to other clusters) and density (the cohesion of keywords within a cluster). This categorisation highlights the key research hotspots in the field. Each circle on the map represents a research topic, with its size reflecting the frequency of related keywords. The top-right quadrant, labelled Motor Themes, encompasses driving themes that are well developed and critical to the field, such as image recognition in cultural heritage. The top-left quadrant, Niche Themes, contains highly specialised and relatively isolated topics that have attracted fewer researchers. The bottom-left quadrant, Emerging or Declining Themes, includes relatively underdeveloped themes that generally follow the thematic trajectory of the other quadrants. The bottom-right quadrant, Basic Themes, features topics with high centrality but low density, which could emerge as future research hotspots. In the first phase, most research themes were in an exploratory stage, characterised by low density and relative isolation. Notably, topics such as Framework System Smart Cities and Design Management Architecture and Model Systems for Residential Buildings began to garner attention, signalling new directions with growing academic interest and influence. In the second phase, the further development and deepening of core themes provided a more solid foundation for building sustainability research within smart cities. Topics like Design System Technologies, Sustainability Impact Consumption Models, and Building Performance Models emerged as key areas of focus. The high proportion of research conducted on Internet Cities Management has since paved the way for the future evolution of these themes. These topics have now become central drivers of smart city and building sustainability research, offering significant practical implications and applications.

4. Analysis of Results

4.1. Theme Evolulionary Analysis

From 2013 to 2025, there has been a consistent increase in the number of scientific publications on building sustainability within the context of smart cities, reflecting both growing interest and expanded research activity in this field. China, Australia, and the United States are leading the way in this area. China’s rapid advancements in technologies such as 5G, artificial intelligence (AI), and big data have provided a robust technological foundation for smart city development, thereby propelling research on the sustainability of buildings in smart cities [70,71]. In the United States, both academic institutions and companies are at the forefront of research on the Internet of Things (IoT), smart building technologies, building information modelling (BIM), and automated control systems—all of which are integral to the sustainability of smart cities and buildings [72]. Australia has also made notable contributions, particularly in the areas of building energy efficiency technologies, green materials, and intelligent building systems, positioning itself as a leader in these fields [73]. Furthermore, these three countries engage in frequent international collaborations, emphasising the importance of global cooperation in advancing the sustainable development of buildings in smart cities. Ultimately, the prominence of key journals underscores the significant role that both management and engineering technologies play in shaping the direction of this research.

4.2. Co-Word Analysis

This synthesis identifies six key categories of building sustainability within the context of smart cities: context, objectives, methods, AI, emerging technologies, and opportunities and challenges. These categories serve as the foundation for our analysis.

Firstly, the concept of smart cities plays a central role in this study of building sustainability. Despite the increasing global interest in smart city initiatives, it has been observed that such efforts are predominantly led by developed countries, which are actively experimenting with and implementing smart city projects [74]. Energy management and monitoring have emerged as some of the most pressing environmental concerns in the development of buildings in smart cities. Among the key challenges in energy management for smart buildings are inefficient energy recovery, high energy consumption, low energy utilization efficiency, and unsatisfactory emission profiles [6]. While the construction industry is continuously adapting its processes to meet sustainability goals in the context of smart cities—such as energy savings, waste reduction, maintaining building quality, and creating smart indoor environments—the sector remains relatively traditional and often hesitant to adopt new technologies. This reluctance results in lower efficiency levels [75]. Nonetheless, smart sustainable buildings are increasingly recognized as a crucial element of the technological infrastructure of smart cities [76]. The adoption of smart systems in buildings offers significant benefits, including cost-effectiveness and the ability to monitor and enforce environmentally friendly construction practices [77]. Consequently, smart buildings are seen as an emerging technology with numerous advantages and are expected to play an integral role in the future development of modern smart cities [78].

Secondly, sustainability is the central focus of this research. The sustainability of buildings is intrinsically linked to the broader sustainability of hard capital within smart cities, with the ultimate goal being the creation of a sustainable, livable, and efficient urban environment [79]. However, the existing literature lacks specific guidance on how new materials and technologies should be implemented in smart city construction projects [66]. This gap highlights the need for further exploration into the essential characteristics required to adapt future buildings to the digital smart city platform. Defining the integration requirements for building projects is critical to ensure their alignment with the broader smart city ecosystem [66]. Moreover, the integration of smart buildings within smart cities is shaped by various complex factors, including infrastructure sectors such as smart energy, smart transportation, and smart waste management [77]. Each of these sectors introduces unique requirements, frameworks, and technologies that facilitate the integration process. As such, effective governmental oversight and strategic, top-level design are essential mechanisms for achieving sustainability goals in smart city development [80].

Thirdly, design thinking plays a crucial role in addressing complex challenges. The process of co-constructing sustainable smart city architecture, involving human, non-human, and technological participants, challenges prevailing paradigms that prioritise homogenisation and time-efficiency constraints within hybrid digital–physical spaces [81]. The convergence of digital technologies such as BIM and blockchain has a positive impact on the sustainable design transformation of buildings in smart cities [72]. Moreover, during the design phase, it is essential to integrate various factors, including information, construction knowledge, and the environmental, social, and economic impacts of the project [82]. For effective collaboration, decision makers, supervisors, investors, designers, builders, owners, and other stakeholders must collectively engage in the BIM design process [83]. The integration of BIM with sustainable building design models facilitates the aggregation of large volumes of complex and dynamic data [84]. Concurrently, blockchain technology ensures the secure transmission of data to relevant organisations or devices, balancing privacy concerns with accessibility [85]. For instance, architects have examined the relationship between BIM and blockchain in building design information management, particularly from the perspective of stakeholders (BIM clients) involved in sustainable building design projects. These studies highlight the importance of effectively managing data to ensure the success of sustainable design initiatives [86].

Finally, three co-occurring word clusters—AI, emerging technologies, and opportunities and challenges—emerge as key factors for a sustainable future. Firstly, the development of smart cities will inevitably drive buildings towards greater intelligence, making the integration of AI technologies essential [87]. Within the smart city framework, the intelligence of buildings must prioritise sustainable development, particularly in reducing energy consumption and carbon emissions. AI enhances energy efficiency by predicting consumption patterns, optimising air conditioning and lighting systems, and shifting from traditional passive control to AI-driven active management [88]. Moreover, smart cities extend beyond the intelligence of individual buildings; they involve the collaborative operation of urban systems. AI facilitates real-time interactions between buildings and other smart systems, such as transportation, public safety, and environmental monitoring, optimising traffic flow and building energy use to improve overall city efficiency [89]. Secondly, the rise of new and emerging technologies offers expanded possibilities for the sustainability of buildings, enabling better integration into the smart city ecosystem. For example, the convergence of AI and ML allows buildings to autonomously optimise their operations based on data, predicting energy consumption patterns and adjusting systems like air conditioning and lighting to reduce energy use and enhance efficiency [90]. The integration of BIM and blockchain improves collaboration across design, construction, and operational stages by facilitating digital modelling and data integration. This enhances data transparency, security, and tracking throughout the process [91]. Furthermore, the IoT and smart sensors enable the precise management of energy efficiency, reducing consumption, extending the lifespan of buildings, and providing data support for green building certification [92]. Lastly, while the transformation of buildings driven by smart cities can significantly improve citizens’ well-being, concerns about information security in the digital realm persist [93]. Additionally, establishing a stable framework for the multifaceted coordination required for the sustainable development of buildings in smart cities remains a challenge for future progress in this field [94].

4.3. Co-Citation and Cluster Analysis

4.3.1. Cluster Analysis

The most frequently cited literature in clusters #0, #2, and #3 highlights distinct research directions. This study conducted an in-depth analysis of these three clusters to explore their interrelationships, obtain the underlying knowledge, and define the conceptual framework of each cluster by examining the highly co-cited and highly cited literature.

Smart City Construction

(1)

Foundation of research

Information technology is fundamental to the sustainable development of buildings in smart cities [47]. Smart cities are conceptualised as integrated systems that encompass smart architecture, environmental management, and governance. These components interact to foster the long-term sustainability of urban environments [48]. The alignment of information systems with the United Nations Sustainable Development Goals (SDGs) establishes a key connection between smart cities and sustainability, particularly concerning the relationship between environmental and social dimensions [95]. ICT serves as the technological backbone of smart cities, facilitating improvements in urban governance and environmental management while supporting sustainable development practices [46]. Its role in promoting citizen participation and supporting decision-making processes is crucial for creating sustainable and inclusive smart cities [96]. The study of smart buildings is essential for understanding the importance of sustainable urban planning and resource management in smart cities [97]. Through the integration of ICT, smart buildings contribute to energy-efficient and environmentally friendly urban structures, which are central to sustainable urban systems [98]. Furthermore, the application of IoT in buildings in smart cities plays a significant role in enhancing their sustainability [92]. However, researchers and policymakers are crucial in ensuring the effective integration of IoT technologies into urban planning and building design, particularly to maintain sustainability and ensure safety [45].

(2)

Areas of cutting-edge research

The integration of IoT technology with new information technologies is crucial for the future sustainable development of buildings in smart cities. Smart sensors and automated control systems enable the real-time monitoring of both the interior and exterior environments of buildings. These systems adjust equipment such as air conditioning and lighting to improve energy efficiency, reduce energy waste, and enhance the comfort of living and working spaces [98,99]. Additionally, intelligent EMSs that combine AI and big data analytics facilitate the real-time monitoring and regulation of energy consumption. These systems optimize energy usage strategies and support the integration of renewable energy sources and energy storage solutions, helping buildings achieve zero-energy and carbon-neutral objectives [100,101]. The integration of IoT with emerging information technologies also enhances the collaborative functioning of smart buildings and urban infrastructures, improving overall urban efficiency, reducing resource waste, and promoting greater sustainability [102]. Furthermore, edge computing technology enables local data processing and analysis within the building, reducing transmission delays and enhancing system responsiveness [103]. In scenarios such as real-time energy management and emergency response, the integration of edge computing and IoT plays a critical role in supporting the sustainable operation of buildings [104].

Despite technological advancements, some scholars argue that the governance of building technology in smart cities should adhere to the principles of Triple Bottom Line (TBL), which encompasses environmental sustainability, social responsibility, and economic viability [105]. Environmental sustainability emphasizes minimizing the environmental impact throughout the design, construction, and operation phases of buildings. It includes the use of green building materials, improving energy efficiency, reducing carbon emissions, utilizing renewable energy sources, and managing resources effectively over the building’s lifecycle. Environmental sustainability ensures that buildings do not deplete natural resources and support ecological balance [106]. Social responsibility focuses on how buildings can enhance residents’ quality of life, promote social welfare, and ensure the equitable distribution of resources [107]. This includes creating healthy, livable urban spaces, fostering social inclusivity, and increasing residents’ sense of participation in and benefits from intelligent building systems [108,109,110]. It also entails meeting the basic needs of diverse groups, such as low-income populations and the elderly [111]. Additionally, technological governance must address social ethical issues, including privacy protection and data security [112]. Economic viability centres on the feasibility and long-term economic returns of buildings in smart cities [113]. Construction projects must be economically sustainable, balancing capital investment, operational costs, and resource utilization while generating economic growth and employment opportunities for the city. This includes leveraging intelligent systems to enhance operational efficiency, reduce energy consumption, lower costs, and increase property value [114,115,116]. In the governance of buildings in smart cities, the integration of the TBL seeks to achieve a balanced development across the three dimensions. By aligning environmental, social, and economic factors, smart cities can create more livable spaces for residents while fully achieving technological innovation and sustainable development. This framework ensures the alignment of technological progress with social responsibility, thereby fostering the overall optimization of urban governance.

Smart City Development

(1)

Foundation of research

A collaboration among citizens, businesses, governments, and educational institutions is essential for fostering the development of new technologies and economic models that enhance the sustainability of urban infrastructure. This collaboration highlights the interdependence of technological innovation and human capital [117]. However, the implementation of smart city technologies varies significantly based on local governance structures, cultural contexts, and economic conditions [118]. Moreover, smart cities often exhibit an overwhelming emphasis on technology, which can result in insufficient integration with the SDGs [27]. To address this gap, some scholars have suggested that smart cities should be organized into four key layers: a sensing layer, a transmission layer, a data management layer, and an application layer. This structure would facilitate efficient collaboration among various systems, such as buildings, transportation, and energy networks [53]. Additionally, other scholars have proposed a hybrid framework for smart cities that combines physical infrastructure, technological innovation, and human capital. This approach provides a comprehensive understanding of how smart cities can promote sustainable development and improve the quality of life for residents [54]. Furthermore, some researchers utilize hierarchical analysis to prioritize critical factors in sustainable development, offering stakeholders valuable tools to assess and guide decisions on the sustainability of smart building designs and urban infrastructure, thus contributing to the broader SDGs [56].

(2)

Areas of cutting-edge research

Addressing the complexity in the development of smart cities is a critical factor in advancing sustainable building development [119]. Smart cities must adapt to evolving environmental, technological, and social demands, requiring urban systems and buildings to be highly flexible and capable of responding to potential future changes [120]. For example, smart buildings must automatically regulate energy consumption, optimize resource use, and accommodate diverse user needs in response to varying environmental conditions [98]. Effective complexity management ensures that these systems remain functional and adaptable to technological advancements and environmental shifts, thereby supporting sustainable development within the building sector [121]. Additionally, the establishment of robust governance structures and collaborative mechanisms is essential to ensure that smart building projects align with SDGs and foster innovation within the construction sector [122].

With the widespread adoption of smart city and green building concepts, Intelligent Building Management Systems (IBMSs) have emerged as a crucial element in modern architectural design and management [123]. These systems provide comprehensive building performance management, enabling reductions in energy consumption, optimizing resource utilization, and enhancing the overall sustainability of buildings, all while maintaining the comfort and well-being of occupants [124]. An IBMS is fundamentally based on information technology and automated control systems, designed to improve management efficiency, energy performance, safety, comfort, and environmental impact across various building facilities [125]. By integrating intelligent devices, sensors, control systems, and data analytics tools, the IBMS facilitates the real-time monitoring, regulation, and optimization of building operations [126,127]. Typically, the IBMS encompasses several core components: the EMS, Building Automation System (BAS), Environmental Monitoring and Intelligent Regulation System, and Safety Management and Emergency Response System. Among these, the EMS plays a pivotal role in monitoring and optimizing energy usage within buildings [128]. The EMS generally incorporates real-time energy monitoring, energy efficiency analysis, intelligent regulation, and predictive scheduling to enhance energy performance [101]. The BAS is another essential component, responsible for the automatic control of internal building systems [129]. By integrating sensors and controllers, the BAS enables autonomous adjustments to lighting, temperature, air quality, security, and other systems, ensuring optimal operation without manual intervention. The Environmental Monitoring and Intelligent Regulation System employs advanced sensors to track various environmental factors in real time [130,131]. This system works in collaboration with other building systems to optimize resource utilization and includes functionalities such as temperature and humidity monitoring, pollutant detection, and noise control. The Safety Management and Emergency Response System is designed to safeguard the well-being of building occupants and provide swift responses in emergencies [132,133]. It incorporates components like video surveillance, access control, fire alarm systems, emergency lighting, and evacuation guidance to ensure safety during critical events. As a cornerstone of modern building management, the IBMS is driving the construction industry towards greater intelligence, sustainability, and environmental stewardship. By integrating technologies such as energy management, safety control, and environmental monitoring, the IBMS not only enhances operational efficiency but also contributes significantly to environmental protection and resource conservation. Despite challenges such as technology integration and data security, the future of IBMS remains promising. It is expected to play an increasingly significant role in advancing smart city development and achieving Sustainable Development Goals.

Smart Energy Management

(1)

Foundation of research

Energy management is central to the sustainable development of buildings in smart cities. AI plays a crucial role in enhancing energy governance by enabling the real-time management of urban energy systems, from policy decisions to city services. This enhances the responsiveness of energy systems and their ability to adapt to the needs of residents [62]. On the other hand, IoT technologies provide solutions for monitoring energy usage, identifying inefficiencies, and optimising consumption [134]. However, the application of IoT in the building sector faces specific challenges, particularly related to interoperability and data security. As a result, there is an urgent need for increased interdisciplinary collaboration between civil engineering, information technology, and building science to optimise the management models of IoT in smart buildings [65]. Moreover, sustainable design experiments have become essential for understanding the overall operation of urban building energy systems [63]. Additionally, the concept of near-NEBs has emerged. These buildings primarily meet their energy demand through renewable sources [64]. NEBs are highly energy-flexible, capable of regulating both energy demand and generation capacity based on external factors such as climatic conditions, user demand, and grid requirements [66].

(2)

Areas of cutting-edge research

The integration and management of smart energy systems are central to research on buildings in smart cities, particularly in the areas of renewable energy integration and storage [135]. For instance, buildings can achieve energy self-sufficiency through the use of rooftop solar panels, wind turbines, and geothermal energy. Additionally, smart energy storage systems, such as home EMS, enable buildings to regulate energy demand and supply internally [136,137]. Furthermore, buildings can leverage AI and big data analytics to dynamically adjust the operation of Heating, Ventilation, and Air Conditioning Systems (HVACSs). This allows an optimal configuration based on external environmental conditions, building usage patterns, and the specific needs of occupants [127].

In the future, sustainable urbanism may serve as a guiding framework for intelligent energy management. This concept embraces a holistic approach of urban planning and development, aiming to achieve a harmonious balance between economic, social, and environmental considerations, ensuring the long-term sustainability of cities [138]. It goes beyond environmental protection to also include sustained economic growth and social equity, with a particular focus on the efficient use of urban resources, the promotion of social justice, and the preservation of ecological integrity. Sustainable urbanism seeks to transition cities from traditional “urban expansion” models to more sustainable development paradigms [139]. A key component of this transformation is the reduction in energy consumption and carbon emissions in buildings through thoughtful architectural design and energy management strategies. These strategies include the integration of renewable energy sources and the adoption of energy-efficient technologies [140,141]. Moreover, sustainable urbanism encourages the development of green infrastructure—such as rainwater management systems, green roofs, and vegetation belts—which not only improve the ecological quality of urban areas but also help mitigate the urban heat island effect and enhance air quality [142,143,144]. The optimization of land use is equally important. Strategies like intensive development, mixed-use planning, and efficient urban transportation networks are essential for minimizing land wastage and maximizing land use efficiency [140]. Therefore, sustainable urbanism represents a comprehensive approach to urban development. Its core principle is to ensure that cities can continue to grow and thrive without depleting finite resources, achieved through strategic planning, innovative design, and effective management. In architecture, the implementation of sustainable urbanism requires the careful integration of environmental, economic, and social sustainability throughout the design, construction, and operational phases [145]. This approach encourages the widespread adoption of green building practices and the creation of resilient urban ecosystems. Thus, architecture becomes more than just a space for living and working—it evolves into a pivotal element in advancing the sustainable development of cities.

4.3.2. High Betweenness Centrality

Bibri, Krogstie, and society [67] presented a seminal publication, with the highest centrality value of 0.14, that underscores the importance of optimising energy systems, facilitating the integration of renewable energy sources, and employing real-time data-driven building management strategies. These approaches aim to enhance the efficiency, livability, and environmental sustainability of urban buildings. The authors explore technologies such as building EMSs, smart grids, and renewable energy networks to foster more efficient energy usage.

Albino, Berardi, and Dangelico [68] highlighted the crucial role of smart building technologies and integrated EMSs in advancing sustainable development within smart cities. By optimising energy consumption, incorporating renewable energy sources, and improving operational efficiency through ICT, smart buildings can significantly contribute to the achievement of sustainability goals in urban environments.

Allam and Dhunny [62] argue that the processing of big data, powered by artificial intelligence (AI), can substantially improve the structure, sustainability, and quality of life within urban communities.

Bibri and Krogstie [146] identify key data-driven intelligent solutions—such as smart grids, smart metres, smart buildings, environmental monitoring systems, and urban metabolism models—as pivotal in enhancing environmental sustainability in both eco-cities and smart cities.

Camero and Alba [47] offered a comprehensive overview of the role of computer science and information technology in the context of smart cities, providing valuable insights for advancing building sustainability in urban development.

4.3.3. Citation Bursts

The high-impact literature on the sustainable development of buildings within the context of smart cities is predominantly concentrated in the second phase of research and development, with the top five publications experiencing notable citation surges. Among these, the framework for a smart sustainable city model proposed by Bibri, Krogstie, and society [67] has attracted significant attention in the field. This framework addresses key limitations, uncertainties, paradoxes, and fallacies present in the current sustainable city models, while promoting innovative pathways for urban sustainability through the application of next-generation computing technologies, such as ICT, big data, and context-aware computing. Silva, Khan, Han, and society [53] argued that a smart city should function as an integrated system that fosters interoperability among various subsystems, thereby improving the quality of life for urban residents. They further elaborate on the essential components required to build a smart city, underscoring their significance for successful urban development. Albino, Berardi, and Dangelico [68] examined various indicators of urban intelligent development, clarifying the composition and characteristics of smart cities while comparing their performance to that of traditional cities. Yigitcanlar, Kamruzzaman, Foth, Sabatini-Marques, Da Costa, Ioppolo, and society [27] highlighted three primary challenges that buildings in smart cities face in achieving sustainability: technological determinism, practical complexity, and the provisional conceptualisation of smart cities. Finally, Mohanty, Choppali, and Kougianos [69] discussed the multiple definitions of the concept of smart cities within both academic and practical contexts, noting that smart cities encompass a range of intelligent components, including smart transportation, smart power grids, intelligent healthcare, and intelligent governance.

4.4. Theme Evolutionary Analysis

The theme evolution diagram (Figure 9) illustrates the changes in research on sustainable architectural development within the context of smart cities over time. Significant shifts are evident between the first and second stages of research, revealing several key evolutionary trajectories.

The first path focuses on “performance” and gradually evolves towards “buildings” and “sustainability”. Early research on building sustainability was primarily centred on performance, emphasising aspects such as energy efficiency, thermal comfort, and air quality, with building performance serving as the key metric for measuring sustainability [147]. At this stage, scholars concentrated on reducing energy consumption and environmental impact by optimising the physical properties of buildings, such as designing facades to maximise natural lighting and implementing efficient heating and cooling systems [148]. However, with the emergence of smart cities, buildings are increasingly viewed not as isolated entities but as integral components of broader urban infrastructures, interconnected with transportation networks, energy systems, and information technologies [77]. This shift in perspective led to a transition from a focus on individual building performance to an emphasis on the integration and synergy of buildings with other urban systems [149]. The expanded role of buildings in the functioning of smart cities has become a pivotal research area, focusing on how intelligent systems can enhance building efficiency and integrate buildings with urban energy and transportation networks, thereby promoting overall urban sustainability [150]. The second path demonstrates how research topics such as “cities”, “model”, and “design” from the first stage converged into the theme of the “Internet” in the second stage. With the rapid advancement of technologies like the IoT, big data, and AI, cities are increasingly recognised not merely as physical spaces, but as intelligent systems consisting of interconnected information, data, services, and devices [151]. These technological developments have made the Internet a foundational infrastructure for building smart cities. As a result, the sustainability of buildings now involves not only optimising their design and structure but also leveraging advanced technologies for the dynamic management and real-time optimisation of building operations [152]. Consequently, research on building sustainability has increasingly focused on how digital tools and the Internet can be utilised to enhance building performance, energy efficiency, and resource utilisation [153]. The third path reflects a growing emphasis on “design”. In the second stage, the concept of “design” incorporates elements such as “model”, “Internet”, and “electric vehicles”. Achieving sustainability in buildings within dynamic and fluctuating environments requires more than just the design of individual buildings; it necessitates the optimisation of resource allocation across various systems [154]. Through the application of system models and Internet technologies, buildings can adjust parameters such as energy consumption, temperature, and lighting in real time to accommodate changing demands [155]. Furthermore, the intelligent parameters and energy efficiency of electric vehicles offer valuable insights for developing sustainable architectural designs [5]. For instance, the energy supply systems of buildings must be interconnected with electric vehicle charging infrastructure to maximise resource utilisation and prevent excessive power consumption or wastage [156].

The strategic coordinate diagram reveals that research on the sustainability of buildings in smart cities has evolved in response to technological progress and digital transformation. This evolution signifies a shift from isolated optimisation efforts to a focus on systemic collaboration. In the first stage, research predominantly centred on foundational areas such as building energy efficiency, design optimisation, and model development, relying heavily on traditional architectural theories and techniques. This phase emphasised the optimisation of individual buildings or systems [84,157,158]. However, with the rapid advancement of new technologies, research on building sustainability has expanded beyond the confines of individual buildings to encompass the interaction between buildings and other urban systems. For instance, intelligent buildings can now dynamically adjust energy consumption and environmental controls in real time, thereby improving resource utilisation [159]. In the second stage, buildings are increasingly conceptualised as integral components of larger urban systems, with a focus on their seamless integration with other urban functions [160]. This shift broadens the research focus, not only aiming to improve the energy efficiency of buildings themselves, but also exploring how buildings can collaborate with other urban elements via intelligent systems and information technologies. As a result, emerging topics such as design system technologies and building performance models have gained prominence. The former enhances design and operational efficiency through intelligent technologies, while the latter optimises energy consumption and reduces environmental impact through data integration and real-time feedback [6,123]. At the heart of this digital transformation is the growing prominence of research in Internet-based city management, which has emerged as one of the most promising areas of study in the second stage [161].

5. Discussion

This study identifies two distinct stages in the development of research on the sustainable development of buildings within smart cities, tracing its evolution from the early phases to the current era characterised by coordinated interactions between cities and buildings managed by digital systems. Between 2019 and 2025, both the volume and diversity of publications have increased significantly, underscoring the growing importance and scientific impact of sustainable development in the research, evaluation, and application of buildings in smart cities. The scope of sustainable research in buildings in smart cities has expanded to encompass the entire urban system, integrating technical, managerial, and humanistic perspectives. This expansion highlights the need for the adoption of various digital technologies and the integration of different digital management approaches to effectively address the challenges of sustainable development. China, the United States, and Australia have emerged as influential leaders in this field. Their prominence can be attributed to their advanced positions in digital technology, as well as their well-developed urban cultures and infrastructures. The growing emphasis on the sustainable development of buildings in smart cities reflects an increasing recognition of the role that advanced digital technologies play in optimising the urban living environment. It also underscores the expanding international collaboration in advancing the sustainability of buildings in smart cities.

5.1. Future Research Trends

Research into the sustainability of smart buildings within smart cities has evolved from an initial focus on the sustainable development of individual structures to a broader exploration of the digital collaboration between cities and their buildings. This transformation is being driven by key technologies such as AI, the IoT, and big data. These technologies enable real-time data collection and feedback, allowing buildings to autonomously adjust to environmental changes and varying demands [162]. For instance, smart buildings leverage IoT sensors to monitor indoor parameters such as temperature, humidity, and air quality. Then. AI uses these data to optimise energy consumption and comfort levels, thereby improving energy efficiency, reducing resource wastage, and fostering sustainability [163,164]. Moreover, big data and AI assist construction managers by extracting crucial insights from large datasets, enabling more informed decision making [127]. By analysing energy consumption patterns, environmental data, and the status of building systems, these technologies can pinpoint energy-saving opportunities, forecast system performance, and enable preventative maintenance. As a result, operational efficiency improves, maintenance costs are reduced, and environmental impact is minimised [165]. The IoT further facilitates the integration of building systems—such as heating, ventilation, air conditioning, lighting, and security—allowing for more flexible resource allocation [166]. By considering factors like human activity and weather conditions, the system can intelligently adjust energy usage, maximising resource efficiency and reducing carbon emissions [155]. The lifecycle of a building encompasses several stages, including design, construction, operation, maintenance, and decommissioning [167]. Through the integration of AI, the IoT, and big data, buildings can be managed intelligently throughout these stages. AI enhances energy efficiency during the design phase, the IoT enables the real-time monitoring of building performance during operation, and big data analytics help to predict equipment failures, thus minimising downtime and lowering maintenance costs [168,169]. Furthermore, these technologies provide the foundation for building synergy by facilitating connections to other systems, such as smart grids and intelligent transportation networks, thereby optimising resource allocation across the entire urban infrastructure [170]. AI enables global optimisation by integrating data from various sources, enhancing both the operational efficiency and sustainability of entire cities [171]. Consequently, AI, the IoT, and big data not only underpin the sustainable development of buildings but also transform their management and operation, making them more intelligent and adaptive [172]. These technologies enable seamless collaboration between buildings and urban systems, optimising resource use, lowering energy consumption, and reducing environmental impact, all while advancing the sustainability of buildings in smart cities. However, the sustainable implementation of smart buildings within smart cities faces a number of complex challenges. First, there are concerns regarding data security and privacy protection [173]. Second, the coordination of data across different systems introduces significant complexity [120]. Third, global optimisation processes are subject to variability and uncertainty [174]. Finally, ethical and social responsibility issues arise from the application of advanced technologies [93]. Finally, ethical and social responsibility issues arise from the application of advanced technologies. To ensure the successful advancement of sustainable development of smart buildings within smart cities, it is essential to establish stringent data security standards, unified technical protocols, and effective strategies that account for these ethical concerns. Furthermore, the development of autonomous technologies and their integration into building systems offers valuable insights into the sustainability of buildings within smart cities.

First, the establishment of strict data security standards is crucial. The construction of smart buildings within smart cities is heavily reliant on the collection, storage, and processing of vast amounts of data, spanning areas such as building management, energy consumption, and traffic flow. This extensive data exchange, particularly when it involves personal information, lifestyle data, and sensitive privacy information, heightens the risk of data breaches [175]. Intelligent management systems—including temperature control, surveillance cameras, and automation systems—along with city-wide data integration platforms such as smart grids and traffic management systems, often require the collection of sensitive data. Any leakage of this information could lead to privacy violations, identity theft, property loss, or security risks. Consequently, ensuring robust data security, encrypted transmission, and protection against cyberattacks are critical concerns for researchers. Key areas of focus include, for example, traffic classification for automatic access control [176], encrypted transmission protocols for bidirectional data flow [177], and secure distributed control mechanisms for demand response in power systems [178]. Furthermore, while many countries have implemented laws and regulations to address privacy breaches—such as the European Union’s General Data Protection Regulation, which governs the collection, storage, and processing of personal data and mandates user consent—these regulations do not directly provide technical solutions. Instead, they primarily regulate behavioural practices [179]. Laws alone cannot replace the necessary technological safeguards for privacy protection, such as encryption technologies, identity authentication, and multi-factor verification. Therefore, in the context of future smart cities, it is essential to prioritise and enforce advanced technological solutions to ensure the security and privacy of data.

Second, research on the complexity of data system coordination is essential. In the development of smart cities, various systems—such as buildings, transportation, energy, environmental management, and social services—must be interconnected through information technology [180]. While such cross-domain and cross-departmental collaborations and data sharing can enhance building management efficiency, they also introduce significant challenges in system coordination. Different systems may utilise diverse data formats, communication protocols, and processing technologies, making seamless data integration and inter-system collaborations highly complex [181]. For example, intelligent building systems need to exchange data with intelligent transportation systems, smart grids, and other urban infrastructure networks. However, discrepancies in technical standards, data interfaces, and protocols can obstruct smooth data exchange and hinder effective coordination [182]. Additionally, delays, errors, or inconsistencies during data exchanges can compromise the real-time performance and accuracy of system decisions, potentially undermining the overall efficiency and sustainability of urban building management [183]. Therefore, the development of unified standards and the facilitation of efficient data sharing and coordination across diverse systems are critical areas for future research. Tackling these challenges will require extensive collaboration with fields such as computer science.

Third, optimising the macro strategy for sustainable construction is crucial for achieving the long-term sustainability of buildings. This requires a comprehensive perspective that considers the interrelationships between buildings and other critical sectors, such as transportation, energy, and resource management. To address these interconnections, effective macro strategies for sustainability must be developed and implemented. However, the optimisation of such strategies presents several significant challenges. The first challenge is information asymmetry and complexity [184]. Smart buildings are a part of a broader, complex network influenced by numerous dynamic factors and multi-layered systems. Optimising building systems involves not only improving the energy efficiency of individual buildings but also ensuring coordination with urban systems such as transportation, energy supply, and waste management [99]. Achieving global optimisation is a highly intricate task, requiring the integration of large volumes of data for informed decision making while considering the interactions between various systems and subsystems. Moreover, formulating a long-term sustainable strategic plan for construction necessitates addressing uncertainties in the environmental, social, and economic spheres [106]. Factors such as shifts in energy demand, changes in policy, and evolving social trends can all significantly influence the effectiveness of sustainability strategies for smart city construction and building management [185,186]. Scholars have raised concerns that, if these variables cannot be accurately predicted or scientifically adjusted, the optimisation of macro strategies for construction may become unfeasible. In such instances, this could lead to resource waste, policy failures, or even adverse environmental outcomes [187].

Fourth, the challenges related to architectural technology and ethics are pivotal to the development of smart buildings within smart cities. In the processes of data collection, monitoring, and analysis, it is essential to strike a balance between the convenience offered by technology and the protection of personal privacy and social equity [188]. While intelligent systems can optimise building and urban management, a lack of transparency in their design and implementation, or the misuse of technology, may have negative social consequences [120,189]. Although laws generally mandate explicit user consent for data collection, many users remain unaware of how their data are used or stored—particularly regarding the private data collected by smart devices and smart buildings [190]. Users often provide consent under conditions of information asymmetry, and in some cases, they may not have the option to refuse. Moreover, when intelligent building systems or smart city infrastructures are compromised by hackers, leading to data breaches, it becomes difficult to determine who is responsible for the breach [191]. Additionally, when AI systems make decisions within intelligent buildings or smart cities, and problems arise—such as equipment malfunctions or energy inefficiencies—there is ambiguity regarding who should bear responsibility. Should the responsibility lie with the companies that develop the AI systems, or with the urban managers and construction operators who deploy these systems? This issue of responsibility attribution in AI decision making presents a complex ethical dilemma [87]. Therefore, ensuring that buildings in smart cities contribute to sustainable development while adhering to ethical and social values remains a critical academic challenge for future research [192].

Fifth, the construction of future cities hinges on advancements in electric vehicles (EVs), autonomous vehicles (AVs), and innovations in management and organizational structures. These developments are crucial for ensuring the sustainable and efficient growth of urban buildings. This integration not only marks the evolution of transportation systems but also serves as a core manifestation of intelligence within urban ecosystems [193]. The progress in electric and autonomous driving technologies has gradually blurred the lines between buildings and transportation infrastructure [194]. For instance, smart buildings can now interact with self-driving vehicles in real time, enabling dynamic scheduling and energy optimisation [195]. In smart cities, buildings no longer solely serve as spaces for living and working; they have also become integral nodes in energy management and traffic control. This shift has led to the reimagining of architectural design, moving from the concept of buildings as “containers” to that of “platforms” supporting more complex living functions and services. Moreover, the widespread adoption of electric vehicles has mitigated the environmental impact traditionally associated with fuel-powered vehicles, contributing to a reduction in greenhouse gas emissions. When combined with building energy systems—such as solar panels and energy storage systems—electric vehicles play a central role in forming an integrated “vehicle–grid–building” energy management model [196]. In this system, electric vehicles transcend their role as mere transportation tools, becoming mobile energy storage units capable of supplying electricity to buildings or the power grid during peak load periods [197,198,199]. This bidirectional energy flow ensures optimal energy allocation and contributes to overall system efficiency. The integration of electric and autonomous driving technologies has also catalysed innovations in governance models within smart cities. By leveraging the IoT, big data, and AI, urban systems—such as construction, transportation, and energy—are interconnected, forming a highly collaborative urban ecosystem [200]. This collaboration enhances the operational efficiency of cities while also strengthening their capacity to respond to and recover from emergencies. These technological and organisational advancements are steering the future trajectory of urban development. They have fundamentally reshaped transportation models and significantly influenced the spatial organisation, energy use, and governance structures of cities. As a result, buildings—now the fundamental “cells” of cities—are increasingly integrated with transportation, energy, and other urban systems, contributing to the creation of a sustainable, efficient, and intelligent urban environment.

5.2. Research Limitations

This study has several limitations. First, our data collection was exclusively based on publications from the WoS CC database, excluding other databases such as Scopus and Google Scholar. This limitation may have narrowed the scope of our research sample. Future studies could consider integrating multiple databases to enhance the robustness and validity of the findings. Additionally, our analysis included only articles published in English, excluding research published in other languages. Second, within the context of scientific bibliometric analysis, we relied solely on the LLR algorithm for cluster analysis. Incorporating multiple association analysis algorithms could improve the accuracy and comprehensiveness of the results. Furthermore, due to space constraints, this study focused primarily on the analysis and interpretation of key clusters, without exploring non-focus clusters in depth. Finally, while identifying research frontiers and future development trends through software analysis offers an objective overview, a more detailed review of the literature is required to obtain more nuanced and precise conclusions.

6. Conclusions

This study employs a combined approach of bibliometric analysis alongside both qualitative and quantitative methods to assess the research landscape on sustainable building development within the context of smart cities from 2013 to 2025. The findings establish a foundation for future research and provide valuable insights for managers and decision makers, contributing to the advancement of sustainable urban architecture and the broader welfare of society. The key conclusions of this study are as follows.

Research on sustainable building development in smart cities can be divided into two distinct stages. Current publishing trends indicate a growing interest in the sustainable development of buildings within smart cities. The integration of various information technologies has significantly improved building livability and energy efficiency. Key research topics in this field include the background and objectives of urban architecture, as well as the roles of AI, emerging technologies, and the opportunities and challenges they present. Technological advancements have shifted the focus from individual buildings to the interconnection of buildings within entire smart cities. The present research highlights the integration of digital technologies, with the IoT and AI emerging as crucial tools in this transformation.

Citation burst analysis reveals that the primary challenges in the field involve constructing an overarching framework for smart cities and achieving sustainability in urban buildings. These issues remain central to current research, underscoring the limited synergy between smart city development and the sustainability of urban buildings, which continues to attract significant scholarly attention.

The analysis of theme evolution and strategic coordination maps further indicates that management and modelling are key issues driving progress in this field. Additional research explores methods for improving design strategies along sustainable pathways, with technology identified as an essential tool for achieving comprehensive sustainability in buildings. While digital technologies offer considerable potential for the sustainable development of buildings in smart cities, they also present limitations, particularly concerning ethical concerns and privacy protection.

Looking ahead, the increasing complexity of information technologies will continue to shape the evolution of architecture. However, priority must be given to addressing challenges such as data security and privacy protection in buildings in smart cities, the complexity of data coordination among disparate systems, and the uncertainties encountered in global optimisation efforts. Technical solutions will be essential in addressing these issues. Furthermore, the ethical implications of future building technologies and smart city developments must be considered, ensuring that these advancements align with human values and societal needs. Notably, driverless technology and its associated systems provide valuable insights into the sustainability of buildings within smart cities.

This comprehensive analysis offers a clear overview of the current state and future directions for sustainable building development in smart cities, providing invaluable insights for researchers, managers, and decision makers in the field.