Smart Implementation and Expectations for Sustainable Buildings: A Scientometric Analysis

Abstract

Amidst global efforts toward sustainable development, this research addresses underexplored academic dimensions by evaluating the transformative potential of intelligent, sustainable architecture. Employing bibliometric techniques and Citespace 6.4.R1, we analyze two decades (2005–2024) of the Web of Science literature to identify patterns and challenges. Findings demonstrate rising scholarly output, dominated by themes like energy-efficient design, Building Information Modeling integration, and circular economy principles in urban contexts. While Europe and North America lead research activity, systemic limitations persist—including duplicated methodologies, fragmented institutional networks, and incompatible smart technologies. This study advocates for three strategic priorities: fostering interdisciplinary innovation to break homogeneity, establishing cross-sector collaboration frameworks, and accelerating industry–academia knowledge transfer. Intelligent, sustainable architecture emerges as a dual solution—technologically enabling carbon-neutral construction practices while redefining human-centric spatial quality. This dual advantage positions the International Sustainability Alliance as critical infrastructure for achieving UN Sustainable Development Goals, reconciling ecological responsibility with evolving societal demands for resilient, adaptive built environments.

1. Introduction

The global energy crisis and environmental issues have intensified, and the construction industry, which accounts for more than 40% of global carbon emissions, is facing systemic changes [1]. Sustainable building is not only a fine-tuning of traditional building concepts but a profound change in the whole life cycle from design and construction to operation, aiming to minimize the demand for natural resources, reduce waste and pollutant emissions, and at the same time, provide users with a healthy, comfortable and efficient spatial environment [2,3]. The World Green Building Council (WGBC) guides the building industry to take a more holistic view of the environmental impact of buildings throughout their life cycle, from construction to demolition. This approach empowers stakeholders to implement more sustainable practices at every stage, thereby reducing carbon emissions and promoting sustainable building practices [4]. Several regulatory and certification incentives to make buildings more sustainable, including the EU Energy Performance of Buildings Directive (EPBD), Building Research Establishment Environmental Assessment Method (BREEAM), country/regional building codes, and Leadership in Energy and Environmental Design (LEED) assessments, as well as local planning policies [5,6,7,8].

With the building industry being called explicitly upon to attain net-zero emissions by 2050 in the UN’s 2030 Agenda for Sustainable Development and with traditional building models characterized by high energy consumption, long lead times, and low synergies, achieving sustainability in the building and construction industry is critical to facilitating the global transition to a sustainable, carbon-neutral built environment [9]. In this regard, adopting the 2030 Agenda and the relevant sustainable development goals will play a strategic role [10,11]. The quick advancement of smart technology in recent years is similar to adding a potent “smart engine” for sustainable building and reshaping this field’s development pattern [12,13]. Cutting-edge technologies, such as smart sensors, automated control systems, big data analytics, and artificial intelligence algorithms, are gradually penetrating every aspect of sustainable buildings [14,15]. From accurate monitoring of indoor and outdoor environmental parameters and intelligent control of lighting, ventilation, and air-conditioning systems to achieve efficient use of energy to the use of Building Information Modeling (BIM) technology to optimize the design scheme, accurate planning of the use of materials, to reduce waste in the construction process, to the Internet of Things (IoT) to achieve interconnectivity of building equipment, real-time diagnosis of equipment failures, and to improve the efficiency of maintenance and management, the intelligent implementation of the means of sustainable development, and the development of the building industry, the development and implementation of the building industry, and the development of the building industry. The intelligent means of implementation provide unprecedented possibilities for achieving the goal of sustainable construction [16,17].

However, with the wave of smart implementation, the development of sustainable buildings is also facing several challenges that need to be addressed [12]. On the one hand, the initial investment cost of intelligent technology is high, which brings economic pressure to many building projects and hinders its wide application; on the other hand, the compatibility and interoperability between different intelligent systems are still imperfect, which makes it easy to form an “information silo” and weakens the overall performance [18,19]. In addition, the rapid iteration of technology and the uneven mastery of emerging smart technologies by building industry professionals have also constrained the pace of sustainable building intelligence implementation to a certain extent [20,21].

Nevertheless, underneath the challenges, expectations are flourishing. With continued technological innovation and cost reductions, smart implementation is expected to become a standard feature of sustainable buildings, thereby empowering the green transformation of the global construction industry [22]. The traditional wisdom and nature-based solutions (NbS) embedded in vernacular architecture provide another ecological path for sustainable building and smart implementation [23,24]. Vernacular architecture demonstrates the concept of harmonious coexistence with nature through site-specific material selection and a climate-adapted spatial layout. At the same time, nature-based solutions build a resilient framework against environmental risks through ecosystem services such as wetlands and vegetation. Through intelligent technology, we expect to create a more adaptive and self-regulating building environment so that the building can automatically optimize its operation mode according to the behavioral habits of users and dynamic changes in climate conditions and achieve the best balance between energy consumption and environmental benefits [25,26]. At the same time, intelligent implementation will promote the deep integration of the construction industry and other fields, giving rise to new business models and service forms and injecting new kinetic energy into the sustainable development of the social economy [27,28].

In this context, it is of great theoretical and practical significance to explore the intelligent implementation path of sustainable buildings, analyze the existing problems, and look forward to future expectations. In this study, we provide a chronological summary of the current understanding of architectural phenomena, suggesting directions for future research on sustainable and smart buildings [29]. Many academics have started to conduct comprehensive studies in intelligence and sustainable buildings in recent years, while there is relatively little literature on effective research from a temporal perspective.

Through Citespace visualization and bibliometrics, to provide valuable insights into expediting the planning and construction of smart, sustainable buildings, this study will look at sustainable building research trends, hotspots, and strategies [30]. At the theoretical level, with the help of bibliometric technology and Citespace software, we analyze the massive amount of the literature, sort out the development of this field from the exploration of fundamental concepts to the integration of technology to the deepening of the integration of multiple fields, and clarify the core issues such as the application of BIM technology, building sustainability, and energy research to enrich the theoretical system. In practice, it analyzes the current research status of countries/regions, institutions, and authors, points out problems such as insufficient cooperation, and proposes directions for improvement in the dilemma of smart technology application, providing practical guidance for the development of the industry. Methodologically, bibliometrics and visualization analysis methods are used to innovate research perspectives and efficiently mine literature information, providing new ideas and methods to draw on for subsequent research.

This study emphasizes the need for interdisciplinary collaboration and the importance of smart implementation in developing sustainable buildings. This study actively promotes knowledge sharing, provides solid decision support for stakeholders, and helps the deep integration of sustainable concepts with the building field, thus strongly promoting the development of sustainable buildings toward intelligence. We will systematically sort out the status quo of the application of intelligent technology in sustainable buildings, deeply analyze the difficulties and pain points in the process of intelligent implementation, and launch a forward-looking discussion on the future development direction of sustainable building intelligence to providing valuable references for promoting the construction industry toward a greener, smarter, and more sustainable tomorrow.

2. Literature Review

2.1. Definition of Sustainable Building and Intelligence

2.1.1. Sustainable Buildings

Sustainable Building refers to a building model that takes the concept of sustainable development as its core and realizes efficient use of resources and reduction in environmental loads in the whole life cycle of a building (design, construction, operation, and demolition) while taking into account social, cultural, and economic factors. According to the Organization for Economic Cooperation and Development (OECD) definition, sustainable buildings need to follow four main principles: resource efficiency, energy efficiency, pollution prevention, and environmental harmony [10]. Its development history reflects the evolution from a single energy-saving goal to integrated life-cycle management, which has become an important strategy for the global response to climate change and the resource crisis [31,32]. In the 1960s, Italian–American architect Paolo Soleri proposed “Arcology,” which emphasizes the integration of architecture and ecosystems and is regarded as an early prototype of sustainable architecture [33]. In 1993, Dr. Charles Kibert, an American scholar, first explicitly proposed the concept of “sustainable construction,” emphasizing the construction industry’s responsibility in achieving sustainable development [34]. The United States hosted the inaugural International Conference on Sustainable Building in 1994, which systematically explored the definition of sustainable building, its technological path, and its relationship with resources and the environment and further promoted the global dissemination of this concept [35].

As early as World War II, some isolated pioneers of modernism began to rethink architecture to harmonize it with nature [36]. In the 1970s and 1980s, sustainable building methods were mainly concerned with energy conservation and environmental protection [37,38]. Concepts such as eco-design and green design have emerged, emphasizing the harmonious coexistence of architecture and nature [39]. In the 1990s, the concept of sustainable buildings gradually gained widespread recognition. Governments and international organizations are beginning to formulate standards and codes for sustainable buildings and promote the development of sustainable buildings. For example, LEED certification in the U.S., BREEAM certification in the U.K., etc. [40,41]. Since the 21st century, sustainable buildings have entered a phase of rapid development. As the energy crisis and global climate change worsen, sustainable building has emerged as the dominant development direction in the construction industry. Governments have introduced policies to encourage and support the development of sustainable buildings. At the same time, the continuous emergence of new technologies and materials has provided strong support for the development of sustainable buildings.

2.1.2. Intelligence

On a philosophical level, the exploration of intelligence dates back to the ancient Greek period. In the 4th century BC, Aristotle proposed formal logic and trinitarianism, laying the foundation for symbolic reasoning [42]. In the 17th century, Leibniz proposed the idea of a “universal symbolic language” to mathematize human thought, which inspired the design of modern computer logic [43].

The modern systematic study of intelligence began in the mid-20th century, especially at the intersection of computer science and cognitive science. In the 1950s, Alan Turing published his paper “Computing Machinery and Intelligence,” proposing the “Turing Test,” which, for the first time, set a criterion for machine intelligence, i.e., whether a machine could simulate human intelligence through conversation [44]. In 1956, at the Dartmouth Conference, John McCarthy, Marvin Minsky, and other scholars formally proposed the term “Artificial Intelligence,” marking the shift of intelligence research from philosophical discourse to scientific practice [45]. The conference clarified the goal of simulating human intelligence through computers and established AI as a separate discipline [46]. The modern study of intelligence integrates multidisciplinary perspectives from philosophy, computer science, and neuroscience and continues to explore the essential boundaries between human and machine intelligence.

2.1.3. Sustainable Building and Smart Docking

The key to achieving low-carbon, high-efficiency, and humanization in the construction sector is the integration of smart technologies and sustainable building practices. By integrating cutting-edge technologies such as the Internet of Things (IoT), Artificial Intelligence (AI), big data analytics, and digital twins, smart systems offer technical assistance for managing sustainable buildings across their entire life cycle, including design, construction, operation, and maintenance [47]. The docking of sustainable building and intelligent technology is not only an innovation at the technical level but also an inevitable choice for transforming the construction industry into a green and human-oriented one [48]. Through technology integration and ecological synergy, intelligent systems inject new energy into the whole life cycle management of buildings, helping to achieve carbon neutrality and sustainable development [49]. In the future, it is necessary to break through technical bottlenecks, improve the policy framework, and promote interdisciplinary cooperation to build a more efficient, inclusive, smart, and sustainable building ecology.

2.2. Intelligent Implementation and Development Mechanisms for Sustainable Buildings

2.2.1. Current Situation

The intelligent implementation of sustainable buildings worldwide is in a critical transition period from demonstration and exploration to scale-up deployment. At the technical level, Building Information Modeling technology has become a mainstream design tool in developed countries/regions. IoT sensors and AI algorithms have effectively monitored energy consumption and optimized equipment. However, system compatibility and retrofitting of old buildings are still common pain points [50,51]. The cost of green building materials and assembly technology decreases yearly, and the gradual improvement in the conversion efficiency of building-integrated photovoltaic (BIPV) technology brings new opportunities for sustainable buildings.

Policy-driven, the EU’s “Building Energy Efficiency Directive” requires all new buildings to achieve zero emissions by 2030; China’s newly revised “Green Building Evaluation Standard” includes carbon intensity as a mandatory indicator, and the U.S. provides 30% tax credits to stimulate green retrofits through the IRA Act [52,53]. The number of green building certification programs is growing globally, but the localization rate of standards in developing countries/regions is insufficient.

Market mechanisms are polarized: developed countries/regions dominate green bond issuance globally, while developing countries/regions still rely on government subsidies; innovative models, such as Singapore’s “ultra-low-energy building certification trading” and Germany’s “energy efficiency performance contracting,” are gradually maturing [54]. Research shows that the percentage willing to pay for green facilities is higher in high-income groups but lower in emerging markets and lower-income groups [55].

Future breakthroughs lie in digital twin technology, which will make operations and maintenance more efficient, modular buildings, which will enable shorter construction periods, and community-level microgrids, which will promote energy sharing. The World Bank predicts that the market for smart and sustainable buildings will reach a trillion dollars by 2030. However, three major contradictions need to be resolved: the balance between technological sophistication and economic viability, the harmonization of policy compulsion and market autonomy, and the integration of global standards and regional specificities [56].

2.2.2. Development Paths

The intelligent implementation and development of sustainable buildings are undergoing a systematic change. Its development path can be summarized as follows: at the technical level, the intelligentization of the building’s entire life cycle will be facilitated by the close integration of Building Information Modeling, AI, and IoT; modular construction and the application of low-carbon materials will significantly improve energy efficiency, and the building integrated photovoltaic (BIPV) and microgrid technologies will transform the building into an energy production unit [57]. On the policy front, international carbon accounting standards are converging; major economies are adopting legislation to mandate net-zero emissions from new buildings and gradually bring the retrofitting of old buildings into regulation, and carbon taxes and trading have become important economic levers [58].

Market mechanisms are driving innovative breakthroughs; green financial instruments are lowering investment thresholds; the value chain is being restructured by new business models like “building as a service,” and consumer markets are being cultivated by developing carbon assets and carbon labeling of buildings [59]. Social synergy is increasingly important, with cross-industry data sharing and community energy democracy enhancing public participation. The next decade (2025–2035) will be a critical period of transformation in which buildings will go beyond their traditional functions to become energy nodes and carbon sinks in the intelligent city network, ultimately realizing a fundamental shift from “energy-consuming” to “energy-producing.”

This transformation requires the synergistic promotion of technological innovation, policy guidance, and market-driven and social participation. Its success is not only a matter of industry change but also an important pillar in realizing the goal of global carbon neutrality. As costs fall and standards improve, sustainable smart buildings will gradually become the industry’s new normal from demonstration projects, reshaping the future of the human environment.

3. Data and Methodology

3.1. Data Sources and Search Strategies

The Web of Science (WOS) Core Collection served as the data source for this investigation. It is internationally recognized as an authoritative academic retrieval system known for its rigorous journal selection mechanism and comprehensive subject coverage [60,61]. WoS has established itself as a top international academic search system, an indispensable knowledge discovery tool for research organizations, and a high-quality bibliometric database for interdisciplinary data research. Through its powerful citation analysis function and comprehensive coverage of academic resources, the platform serves the literature retrieval needs of global academic institutions. It provides reliable data support for researchers to conduct multi-field, data-driven academic exploration [62].

The theme of this study is to visualize and analyze the dynamics, research hotspots, and trends in sustainable building and intelligence. In the advanced search, we chose the Web of Science Core Collection and selected the full version to ensure this study’s accuracy. On 6 April 2025, we retrieved search topics for (“sustainable building*” OR “sustainable construction*” OR “green building*” OR “energy-efficient building*” OR “low-carbon architecture*”) AND (“smart*” OR “intelligen*” OR “IoT” OR “AI” OR “BIM” OR “digital twin” OR “automate*”), with a total of 1979 articles. When the search time range was set from 31 December 2024 to 1 January 2005, 1870 articles were found. The titles and abstracts were manually reviewed, and 8 “Retracted Publication” articles were excluded, resulting in a total of 1862 valid articles. To reduce the subjectivity of manual screening, 10% of the retained publications (186 articles) were randomly selected for review, and in case of disagreement, a second senior researcher was appointed to arbitrate. The results showed that the sampling agreement rate was 97.3%, and the overall accuracy rate increased to 98.9% after arbitration.

3.2. Scientometric Analysis Methods

This paper uses Citespace (6.4.R1) as a visualization tool. Citespace is a Java-based visualization tool that can be used on any platform because of its high level of data interoperability, which enables detailed data analysis and visualization from several dimensions, which is effective in illustrating the current state of the art and progress of research in a particular field [63]. With its intuitive user interface and rich visual presentation, CiteSpace can transform complex literature data into highly readable knowledge graphs [64]. The software has become an important tool in scientometric research due to its excellent citation network analysis capabilities [65,66]. The knowledge map generated by CiteSpace allows us to quickly identify the core literature, research frontiers, and development vectors in intelligence and sustainable buildings and grasp the relevance of different research themes. This visualization and analysis function greatly improves the mining efficiency of the research literature.

We labeled all the documents retrieved from the Web of Science Core Collection database and exported them as plain text files in “Full Record and Cited References” format. After all articles were de-duplicated, 1862 distinct papers with no duplicate data were found in the CiteSpace software. In order to conduct the co-occurrence analysis and visualize keywords, countries/regions, and institutions, these data were entered into the software. High-frequency terms that were not very important or search terms were removed. With a one-year time slice, the CiteSpace software’s period is from January 2005 to December 2024. Set the node types to “Country,” “Author,” “Institution,” and “Keyword.” The pruning methods “Pathfinder” and “Pruning sliced networks” should be chosen. The network was pruned using the pathfinder algorithm Chen Chao-mei recommended to obtain more precise visualization results [67]. All others are default settings of the software. The methodological framework for sustainable building intelligence implementation and foresight is shown in Figure 1.

4. Findings

4.1. Summary of Research Developments

4.1.1. Annual Publication Trends

Statistical and visual analysis of annual publications in this field shows the dynamic evolution of academic research, reflecting the shift of research hotspots, the advancement of technological innovation, and the cyclical changes in research activity [68].

This paper compiles the literature retrieved from the WoS database between 2005 and 2024. Using the year as the horizontal coordinate and the number of articles as the vertical coordinate, a time-series distribution graph, as shown in Figure 2, shows the number of publications on intelligent and sustainable buildings from 2005 to 2024. Overall, there is an increasing trend in the quantity of publications.

The change in the number of publications is a key indicator of the field’s development process. Based on Figure 2, the number of publications related to sustainable buildings and intelligence from 2005–2024 is analyzed in terms of the pace of development and growth. At the same time, technological progress, policy changes, and industry–academic research on the cyclical law of systematic combing, according to the five-year cycle division of the development history into four stages, are combined.

• Budding exploration period—slow growth at the beginning (2005–2010)

The number of publications, which stood at 4 in 2005, increased slowly from 4 to 20 between 2005 and 2010. During this period, the annual growth was relatively small and steady. During this period, technologies related to sustainable buildings and intelligence were in their infancy, with limited R&D and application scope and fewer outputs of related research results. All walks of life do not have enough knowledge and attention to sustainable buildings and intelligence, and the research resources and funds invested are relatively small, which leads to the slow growth of the number of articles published.

This stage is characterized by the construction of industry standards and the initial application of technology. 2007 saw the release of LEED v3 in the US, which innovatively introduced scoring systems such as “Sustainable Sites” and “Energy and Atmosphere” to provide a basis for the development of the industry. At the technical level, building automation systems (BAS) are beginning to integrate energy-saving algorithms, such as Honeywell’s launch of its first-generation intelligent temperature control system and Germany’s “passive house” concept, which reduces energy consumption through the building’s physical design. Autodesk Revit 2008 was released to promote BIM technology from a two-dimensional to a three-dimensional design transition;

• Technology integration period—steady growth (2010–2015)

The number of technology applications grew from 20 in 2010 to 88 in 2015. There has been a significant increase in each year of the period, with a gradual acceleration in the growth rate. The development of the Internet of Things (IoT), Big Data, and Artificial Intelligence (AI) provides technical means and research directions for the field of sustainable buildings and intelligence, such as Building Information Modeling technology, to enhance the digitalization of buildings, which has given rise to more topics [69]. Countries/regions pay attention to sustainable development and introduce policies to encourage green and intelligent buildings, enterprises, and research institutions to increase investment, and the number of publications increases. People’s environmental awareness and demand for building quality have increased; sustainable, intelligent building market demand has emerged, and the industry continues to explore more and more results [70].

At this stage, the systematic development of Internet of Things (IoT) technology and policy has become the core driving force. Smart meters and environmental sensors are deployed on a large scale; IBM’s “smart building” concept promotes the construction of a data center, and Johnson Controls’ Metasys system realizes real-time monitoring of equipment energy consumption. Building Integrated Photovoltaic (BIPV) technology is mature, and the efficiency of the calcium–titanium ore battery developed by NREL has achieved a breakthrough. At the policy level, the Paris Agreement (2015) has pushed countries/regions to set carbon emission reduction targets, and the EU has raised the carbon emission reduction target for buildings to 50–55% by 2030 compared with 1990; China’s Green Building Action Program (2013) requires that green buildings account for 50% of the total by 2020. With the synergy of technology and policy, the research direction is shifting to system energy efficiency improvement;

• Digital transformation period—continued and accelerated growth (2015–2020)

The number continues to grow from 2015 to 2020, and although the individual years in between are not as large, the overall growth trend is still maintained, and the growth rate is significantly higher than in the previous period. The trend of technology cross-fertilization has increased, like artificial intelligence and building energy efficiency, IoT and equipment management integration, etc., which brings innovation points and application scenarios, stimulating a large number of research and pushing up the number of publications [71,72]. Numerous enterprises and research institutes have entered the field of sustainable buildings and intelligence, and the competition has driven all parties to increase R&D and innovation and publish their results to compete for advantages and increase the number of publications. International cooperation on sustainable development is increasing, and multinational research teams are integrating resources and sharing results to promote research and increase the number of publications.

This phase is marked by Artificial Intelligence (AI), blockchain technology applications, and zero-carbon building policies. The NVIDIA CUDA framework (2016) is driving the application of AI in the field of building energy prediction; Autodesk Twin Motion enables real-time building simulation. Blockchain technology is piloted in microgrid transactions, such as TransActive Grid in the US, to enhance the efficiency of renewable energy consumption. On the policy front, France (2019) legislates for full lifecycle carbon neutrality in new buildings after 2022, and the UK launches its Ten Point Plan for a Green Industrial Revolution. The COVID-19 pandemic has prompted an update to the WELL v2 standard (2020) with new health and safety indicators. At this point, the research focus shifted to building resilience and health performance;

• Carbon-neutral offensive period—rapid growth (2020–2024)

The number of publications reached 145 in 2020 and increased significantly to 312 in 2024, a period of significantly faster growth and rapid upward mobility. Global climate change is severe, and the need for carbon neutrality and carbon emissions reduction has put sustainable buildings in the spotlight, coupled with rising expectations for healthy and smart environments, which has led to a surge in publications as a result of the large number of resources invested in research [73,74]. At the same time, the industrial ecology in this field is perfect, and all links in the industry chain need to be theorized and innovated, leading to the growth of research and publications. In addition, universities, research institutions, and enterprises improve the incentive mechanism, increasing the number of publications [75].

The current phase focuses on whole-life low-carbon management and in-depth application of AI. GPT-4 (2023) will empower building design; the ArchGNN platform will enhance design efficiency, and Microsoft’s “Building Carbon Calculator” will realize real-time monitoring of carbon emissions of building materials in the whole cycle. At the policy level, China’s “dual-carbon” target has pushed the energy efficiency rate of new buildings to 75% (2023), and the EU’s Carbon Border Adjustment Mechanism (CBAM) has forced the global building materials industry to upgrade. Germany’s Innogy integrates 10,000 green buildings through virtual power plants. Academic research is highly focused on AI-driven low-carbon design algorithms, building materials, circular economy models, and carbon-neutral policy simulation, with a significant trend of interdisciplinary research.

Between 2005 and 2024, the quantity of publications steadily increased, especially after 2015, with a significant acceleration in growth rate. This reflects a positive upward trend in the output of the relevant fields in this timeframe, implying positive factors such as increased research activity and enthusiasm for creativity.

4.1.2. Analyzing Major Journals

The significance and influence of the research findings in each field are highlighted by statistically analyzing the distribution of published journals and clarifying collaborative contributions and academic interactions [76].

Figure 2 displays the distribution of co-cited journals, providing examples of the categories, patterns of distribution, and interconnections of the journals from 2005 to 2024, when the node type is set to “Cited Journals” and the co-citation analysis is carried out. In Figure 3, the dots’ greater size indicates that the journal has been cited more frequently in the field of sustainable buildings and intelligence. The journal dispersed 1050 nodes, each with a density of 0.0047 and a connection value of 2566.

The top 10 journals in the discipline with the most papers are listed in

Table 1. Top ten journals publishing research on sustainable buildings and intelligence, 2005–2024.

No.	Freq.	Centrality	Year	Cited Journal
1	924	0.17	2007	ENERGY AND BUILDINGS
2	752	0.08	2007	BUILDING AND ENVIRONMENT
3	733	0.05	2010	RENEWABLE AND SUSTAINABLE ENERGY REVIEWS
4	627	0.11	2008	AUTOMATION IN CONSTRUCTION
5	609	0.02	2015	JOURNAL OF CLEANER PRODUCTION
6	559	0.06	2010	APPLIED ENERGY
7	520	0.03	2017	SUSTAINABILITY
8	469	0.02	2017	JOURNAL OF BUILDING ENGINEERING
9	430	0.03	2014	SUSTAINABLE CITIES AND SOCIETY
10	381	0.03	2011	ENERGY

. Not surprisingly, most of these articles were first published in 2007 and 2017. The top three cited journals are ENERGY AND BUILDINGS, BUILDING AND ENVIRONMENT, and RENEWABLE AND SUSTAINABLE ENERGY REVIEWS, in that order. From Figure 3, it is possible to distinguish which journals have a higher volume of publications, and it is also possible to see how the journals are related to each other. The current trends observed in numerous publications appear highly promising. We must commend the authors for their excellent work. Synthesizing the journal’s disciplinary orientation and main research content, it is concluded that the development of the field has a direct impact on the fields of energy, environmental sciences, architecture, automation, smart manufacturing, sensors, and the Internet of Things (IoT).

4.1.3. Major Country/Region Distribution

Knowing the distribution of collaborating regions is essential for fostering international academic exchanges, figuring out each country’s/region’s research concentration in this area, and predicting future collaboration chances and paths [77,78].

We have visualized and analyzed the collaborative network of countries/regions in sustainable building and intelligence by specifying the node type as “Country.” Figure 4’s knowledge map illustrates how closely regions cooperate. Nodes of different sizes represent individual countries/regions, with larger nodes usually indicating higher research activity and influence in the field. High centrality values are shown by the nodes’ thick purple outer boxes, and connections between the nodes show connections to other categories. The stronger the relationship, the thicker the line. The graph contains 95 nodes with a grid density of 0.0887 and a connection value of 396. The graph shows that MALAYSIA and SAUDI ARABIA have high centrality, although the number of articles is not as high, proving that they are of relatively high quality. China and the United States have the most significant amount of the published literature, occupying a central position on the map. While POLAND, BRAZIL, SWEDEN, and other countries/regions are located on the periphery of the cooperation map, there is an urgent need to strengthen cooperation and exchange. International collaboration and exchange can support the advancement of the research.

By setting the node type to “Country,” we visualized and analyzed the cooperation network between countries/regions regarding sustainable buildings and intelligence. The knowledge graph shown in Figure 4 presents the closeness of inter-regional cooperation: nodes of different sizes represent different countries/regions, and the country’s/region’s academic influence and research engagement in the topic are more substantial when the node size is larger; nodes with thick purple borders mark the high centrality value, and the cooperative relationship between the countries/regions is represented by the connecting lines between the nodes, with the thicker lines indicating the deeper cooperation. The map covers 95 nodes, with a grid density of 0.0887 and a connection value of 396. Analysis shows that MALAYSIA and SAUDI ARABIA do not dominate the total number of publications but highlight the high quality and value of their research results by high and medium-centered indicators; China and the United States, with their massive output of the literature, are at the core of the map, and POLAND and BRAZIL are on the outskirts of the cooperative network and need to increase scholarly contacts and global cooperation. POLAND, BRAZIL, SWEDEN, and other countries/regions are at the edge of the cooperation network and are in urgent need for expanding international cooperation and academic exchanges. It can be seen that transnational academic cooperation is significant in promoting the sustainable development of research in this field.

The top 10 countries/regions with the most publications in this area are listed in

Table 2. Top 10 countries/regions for sustainable building and smart research contribution, 2005–2024.

No.	Freq.	Centrality	Year	Country/Region
1	518	0.14	2005	CHINA
2	224	0.21	2005	USA
3	133	0.14	2005	ENGLAND
4	111	0.11	2009	AUSTRALIA
5	105	0.06	2009	INDIA
6	94	0.04	2006	GERMANY
7	83	0.03	2005	ITALY
8	80	0.15	2013	MALAYSIA
9	75	0.13	2014	SAUDI ARABIA
10	70	0.02	2010	SOUTH KOREA

. The data shows that China, the United Kingdom, and the United States are among the three countries/regions with the most publications from 2005 to 2024; Australia and India follow the three countries/regions in the fourth and fifth places, respectively, in terms of the number of publications for the period 2009–2024. Through consistent research funding and policy support, these countries/regions have significantly accelerated the development of research and related efforts in intelligence and sustainable buildings.

4.1.4. Author Collaboration Analysis

The distribution of author partnerships, a sense of collaboration between researchers, and insights into cross-border collaborations may provide a good image of the major participants in the field [79].

Figure 5 visualizes the collaborative network of authors in sustainable building and smart research. The network consists of 585 nodes and 443 connections, with a network density value of 0.0026, clearly outlining the collaborative relationships among scholars. The size of the annual cycle of the nodes in the graph reflects the authors’ publication frequency, and the connecting lines between the nodes indicate the collaborative relationship between the authors [80]. The graph shows that authors are more independent from each other and less collaborative.

As shown in

Table 3. Top 10 authors related to sustainable buildings and intelligence, 2005–2024.

No.	Freq.	Centrality	Year	Author
1	13	0.00	2010	Wang, Lingfeng
2	10	0.00	2010	Wang, Zhu
3	9	0.00	2010	Yang, Rui
4	9	0.00	2020	Moayedi, Hossein
5	9	0.00	2014	Granqvist, Claes G
6	8	0.00	2021	Liu, Sai
7	8	0.00	2019	Liu, Zhen
8	7	0.00	2021	Tso, Chi Yan
9	7	0.00	2018	Bakhouya, Mohamed
10	7	0.00	2020	Geyer, Philipp

, the top three researchers in this field are Wang, Lingfeng, Wang, Zhu, and Yang, Rui. All of them started their research in 2010, and in combination with Figure 5, it is found that after two or three years, they have no further research in this field, indicating no continuity in their academics. Despite scholars’ positive contributions to research in sustainable buildings and intelligence, the absence of cooperation in this area and the lack of continuity in the publication of articles in the field of scholars’ research have hampered comprehensive studies and diversified advancements in the topic. Throughout the Sustainable Buildings and Intelligence research area, the number of articles published by individual scholars is relatively limited.

4.1.5. Participating Institutions’ Distribution

By looking at how the contributing institutions are distributed, it is possible to identify institutions with significant outputs in sustainable building and smart research and collaborations between institutions that provide academic support and recognition in the field, thus enabling us to map the research pillars of the field [81,82].

To create an institutional knowledge graph, we utilize the Citespace tool in this study and set the node type to “Institution” to visualize and analyze the institutional collaboration network in smart research and sustainable building. With 449 nodes and 465 connections, the network has a density of 0.0046, as seen in Figure 6. Each node in the graph represents an organization, and the node size often indicates how much the organization has contributed to smart research and sustainable building. Nodes such as “University of New South Wales Sydney” and “Egyptian Knowledge Bank (EKB)” are large, indicating that they are central to the field. The large nodes of the “Egyptian Knowledge Bank (EKB)” and the “University of New South Wales Sydney” indicate that they are the core research forces in this field, playing a key role in the output of research results and the construction of cooperative networks. Institutions that publish research on sustainable buildings and intelligence show a wide distribution in the graph, indicating the diversity of contributing institutions. In addition, by observing the connectivity between nodes, it can be found that the “City University of Hong Kong,” for example, has more connectivity with some neighboring institutions, indicating that it has more extensive collaboration with other institutions. These institutions are closely connected in a collaborative network, with the university dominating as the primary institutional unit.

Information about the top ten institutions in terms of the total number of articles published in smart research and sustainable construction is shown in

Table 4. Top 10 Contributing Organizations for Sustainable Buildings and Intelligence, 2005–2024.

No.	Freq.	Centrality	Year	Institution	Country/Region
1	43	0.14	2012	Hong Kong Polytechnic University	China
2	42	0.08	2011	Egyptian Knowledge Bank (EKB)	Egypt
3	34	0.06	2012	City University of Hong Kong	China
4	24	0.06	2013	Hong Kong University of Science and Technology	China
5	21	0.02	2017	South China University of Technology	China
6	19	0.00	2010	University System of Ohio	USA
7	16	0.05	2011	Chongqing University	China
8	16	0.04	2012	Southeast University—China	China
9	16	0.09	2019	University of New South Wales Sydney	Australia
10	15	0.04	2013	Duy Tan University	Vietnam

. It can be seen that higher education institutions in this field are showing higher activity. Combined with Figure 6, it is clear from Table 4 that with 43 publications, Hong Kong Polytechnic University published the most. Among the top ten universities are six Chinese universities: Hong Kong Polytechnic University, City University of Hong Kong, Hong Kong University of Science and Technology, South China University of Technology, Chongqing University, and Southeast University. The different institutions in this subject collaborate internationally and regionally, contributing to the widespread exchange and dissemination of knowledge. In this process, universities play a leading role as the core force driving the entire network, greatly facilitating the development of related research. However, a relatively small number of articles are published by relevant research institutes and companies in sustainable building and smart-related areas. Further cooperation between institutions will revitalize research in this field and accelerate its development.

4.2. Field of Research

4.2.1. Highly Cited Articles

Conducting a co-citation network analysis of the highly cited literature enables us to pinpoint key methods, ideas, and theories [83,84]. With this analysis, we can identify the core research in the field of sustainable buildings and intelligence, clarify its knowledge base, identify gaps in current research, and identify areas where breakthroughs are expected to be realized in the future.

We set the node type to “Reference” in this visualization and analysis. By constructing the co-citation network, Figure 7 was generated. This knowledge graph contains 1077 nodes and 2248 connections, and the network density is 0.0039. Larger nodes in the graph show that there have been more citations to the article, and there is a positive correlation between the size of the nodes and the number of citations in the research literature. Based on the WOS citation report and Citespace analysis data,

Table 5. Top ten highly cited and stronger articles related to sustainable buildings and intelligence, 2005–2024.

No.	Reference	Topics	Year	JIF	Citations
					Average	Total
1	Building Information Modeling (BIM) for green buildings: A critical review and future directions	Construction and Building Technology; Engineering	2017	9.6	40.33	363
2	Enhancing environmental sustainability over building life cycles through green BIM: A review	Construction and Building Technology; Engineering	2015	9.6	39.81	438
3	A review and outlook for integrated BIM application in green building assessment	Construction and Building Technology; Science and Technology	2019	10.5	14.7	103
4	Green building assessment tool (GBAT) for integrated BIM-based design decisions	Construction and Building Technology; Engineering	2016	9.6	16.1	161
5	A mixed review of the adoption of Building Information Modelling (BIM) for sustainability	Science and Technology—Other Topics; Engineering; Environmental Sciences and Ecology	2017	9.7	32.4	259
6	A review of building information modeling (BIM) and the Internet of things (IoT) devices integration: Present status and future trends	Construction and Building Technology; Engineering	2019	9.6	74.3	520
7	Integration of BIM and LCA: Evaluating the environmental impacts of building materials at an early stage of designing a typical office building	Construction and Building Technology Engineering	2017	6.7	20.3	183
8	Building information modeling based building energy modeling: A review	Energy and Fuels; Engineering	2019	10.1	31.7	222
9	LCA and BIM: Visualization of environmental potentials in building construction at early design stages	Construction and Building Technology Engineering	2018	7.1	26.5	212
10	Life cycle energy efficiency in building structures: A review of current developments and future outlooks based on BIM capabilities	Science and Technology	2017	16.3	21.1	190

presents detailed information on the highly cited core literature in sustainable buildings and intelligence. Combined with Figure 7 and Table 5, the top three literature rankings of the Citespace analysis data are as follows: Building Information Modeling (BIM) for Green Buildings: A Critical Review and Future Directions [85], Enhancing environmental sustainability over building life cycles through green BIM: A review [86], A review and outlook for integrated BIM application in green building assessment [87]. Table 5 lists the specifics. In the co-citation network, those articles with high citation frequency tend to show significant aggregation characteristics, and they form a close association with other articles, with their connection strength and frequency at a high level. The Journal Impact Factor (JIF) is a key indicator of a journal’s academic impact by calculating the average number of citations a journal received in the previous year. On the other hand, the citation count of an article covers all citations to that article and is not limited by the frequency of citations or the size of the journal’s impact factor.

A closer look at Table 5 shows that the present body of fundamental knowledge in the discipline is split into three major sections based on these highly cited papers:

• Building Information Modeling technology

Several articles have explored the use of Building Information Modeling in the design and assessment of green buildings, such as design decisions, integration in green building assessment, etc. The integration of Building Information Modeling with other technologies involves the integration of Building Information Modeling with Internet of Things (IoT) devices and the integration of Building Information Modeling with Life Cycle Assessment (LCA) methodologies for the assessment of building materials, environmental impact, enabling building energy modeling, etc.;

• Building Sustainability

It focuses on the sustainability of buildings’ whole life cycles, including enhancing their environmental sustainability through green Building Information Modeling, studying the life cycle energy efficiency of building structures, and other related topics. It also focuses on buildings’ impact on the environment and the efficiency of resource utilization throughout these cycles;

• Energy-related

Focus on the building energy sector, e.g., BIM-based building energy modeling and visualization of environmental and energy-related potentials in the early design phase of building construction using Life Cycle Assessment (LCA) and Building Information Modeling (BIM) to optimize building energy use and environmental performance.

The analysis of the cited articles reveals that building information modeling technology is in the spotlight, and building sustainability is emphasized in terms of research hotspots. Most papers revolve around Building Information Modeling, such as its application in green building design, assessment, and integration with other technologies (Internet of Things, Life Cycle Assessment, etc.), indicating that Building Information Modeling technology is a hot research topic. Researchers attach importance to its potential to enhance building sustainability and optimize the design and assessment process. Several papers are related to the environmental sustainability and energy efficiency of the whole life cycle of buildings, indicating that the construction industry is practicing sustainable development and focusing on the performance of buildings at the environmental and energy levels. As for the influence of journals, the published journals are concentrated in “Construction & Building Technology” and “Energy & Fuels,” indicating that these journals strongly influence construction and related fields. This shows that these journals are influential in construction and related fields and are important platforms for researchers to publish their results. The impact factors of different journals are different, reflecting the differences in academic influence, manuscript quality requirements, dissemination scope, etc., and also affecting the attention and citation of papers. Regarding the citation status of the papers, the total citations of the papers are different. The highly cited papers have outstanding value regarding research content, methodology, or conclusions, which are recognized by peers and provide important references for subsequent research. In contrast, the low-cited papers need to be upgraded regarding innovativeness and influence. Combining the year of publication and citation volume, the speed and trend of acceptance and application of research results in the field can be inferred to a certain extent.

4.2.2. Research Areas

Analysis of time–zone co-occurrence is a crucial tool for monitoring academic developments. It reveals the development of the discipline by analyzing the connection of research contents in different periods and provides a basis for predicting research trends [88,89].

In this analysis, the node type is set to “category,” and the visual graphical representation of the categories is achieved by generating a time zone co-occurrence graph. Circles are used in the graph to represent each research theme, and their location in different time zones reflects the time of the first occurrence of the theme in the dataset. At the same time, the connecting lines between the nodes visualize the correlation and synergistic relationship between the research themes. As shown in Figure 8, there are a total of 109 nodes and 390 connections, with a grid density of 0.0663. The graphic shows that the traditional engineering specialties’ early research themes, CONSTRUCTION AND BUILDING TECHNOLOGY, ENGINEERING, CIVIL, and ENERGY AND FUELS, appeared earlier; over time, they emerged. As time goes by, emerging interdisciplinary fields and fields related to sustainable development, such as “GREEN AND SUSTAINABLE SCIENCE AND TECHNOLOGY,” appeared in 2011 and established connections with other fields, demonstrating the trend of disciplines expanding from traditional to emerging and interdisciplinary directions. Connections can be visualized across disciplinary fields, such as “COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS,” with connections to multiple fields, indicating that computer science is widely used in interdisciplinary research.

The top ten discipline groups are listed in

Table 6. Top 10 categories related to sustainable buildings and intelligence, 2005–2024.

No.	Freq.	Centrality	Year	Category
1	489	0.10	2005	CONSTRUCTION AND BUILDING TECHNOLOGY
2	462	0.11	2005	ENGINEERING, CIVIL
3	406	0.21	2006	ENERGY AND FUELS
4	365	0.03	2011	GREEN AND SUSTAINABLE SCIENCE AND TECHNOLOGY
5	287	0.20	2005	ENVIRONMENTAL SCIENCES
6	214	0.26	2005	MATERIALS SCIENCE, MULTIDISCIPLINARY
7	210	0.15	2006	ENGINEERING, ELECTRICAL AND ELECTRONIC
8	179	0.06	2005	ENVIRONMENTAL STUDIES
9	106	0.11	2005	ENGINEERING, ENVIRONMENTAL
10	105	0.13	2008	ENGINEERING, MULTIDISCIPLINARY

according to category size rankings, with the top five being CONSTRUCTION AND BUILDING TECHNOLOGY; ENGINEERING, CIVIL, ENERGY, AND FUELS; GREEN AND SUSTAINABLE SCIENCE AND TECHNOLOGY; and ENVIRONMENTAL SCIENCES. As seen from Table 6, the categories with the most articles are not the ones with the highest centrality, and some of the categories with the most significant number of publications have low centrality, meaning that articles in these categories have a low citation rate. They need to deepen the research to improve the quality of the results. In the subsequent research on sustainable buildings and intelligence, reading articles with high centrality can broaden the research horizon and help discover new research directions.

4.3. Research Hot Spots and Research Strategies

4.3.1. Co-Occurrence Network of Keywords

Keyword co-occurrence analysis is an effective means of understanding the core themes and capturing the hot research trends in the fields of sustainable buildings and intelligence. It also aids in elucidating the extent to which various study themes are related [90].

With the help of the Citespace tool, “keywords” is the node type we have set. The nodes in Figure 9 represent keywords; the connecting lines between the nodes indicate their liaison, and the circle size indicates how frequently the keywords appear in associated articles [91]. This analysis reveals a mesh density of 0.0109 with 586 nodes and 1876 connections.

Table 7. List of top ten co-occurrences of keywords from 2005 to 2024.

No.	Freq.	Centrality	Year	Keywords
1	271	0.21	2007	green building
2	229	0.06	2011	design
3	220	0.02	2012	bim
4	213	0.05	2008	performance
5	200	0.11	2007	system
6	137	0.14	2006	energy efficiency
7	100	0.05	2012	optimization
8	98	0.02	2014	sustainable construction
9	97	0.06	2012	construction
10	95	0.03	2016	management

lists the top ten keywords for sustainable building and smart co-occurrence from 2005 to 2024. It is found that the hotspots in the field of sustainable building and intelligence that scholars focus on are green building (271), design (229), BIM (220), performance (213), and system (200). As seen from Table 7, the frequency rating and centrality ranked first is a green building, followed by system and energy efficiency, which also have high centrality. This highlights their importance in sustainable building and intelligence.

Research on sustainable buildings and intelligence revolves around green buildings and covers various aspects, including design optimization and greater energy efficiency. For example, numerous studies have explored how to achieve energy efficiency goals in green buildings through efficient insulation materials, intelligent lighting systems, and more. The frequency and centrality of keywords such as “bim,” “design,” and “construction management” are outstanding. Reflecting the importance attached to the application of technical tools and process management in this field, Building Information Modeling technology is used for the integration and sharing of information in the whole life cycle of a building to optimize the design and construction process; the design process focuses on the integration of sustainable concepts; and the construction management emphasizes the rational allocation of resources and process control to achieve sustainable goals. The keywords “performance,” “energy efficiency,” and “optimization” are closely related. It shows that this study focuses on building performance enhancement, especially regarding energy efficiency, and maximizes comprehensive building performance through continuous optimization of building systems, equipment selection, and other means.

4.3.2. Analysis of Keyword Co-Occurrence by Time Zone

CiteSpace’s time–zone maps provide insights into what is hot and trending in sustainable buildings and intelligence and how to predict future trends [92].

We imported the relevant data into CiteSpace and generated a timeline map of sustainable building and smart research between 2005 and 2024. By analyzing high-frequency phrases, we found many studies on intelligence and sustainable buildings, with significant differences in focus at different research stages. The time zone map of sustainable buildings with smart counterparts is presented in Figure 10. In this study, we divided the keywords into four zones by time and sorted out the top five popular keywords in each zone to form

Table 8. The top five most frequently used keywords for articles published every five years between 2005 and 2024 on intelligence and sustainable buildings.

No.	Freq	Centrality	Year	Keywords
			2005–2009
1	271	0.21	2007	Green buildings
2	213	0.08	2006	Performance
3	200	0.04	2009	System
4	137	0.04	2008	Energy efficiency
5	73	0.11	2006	Artificial intelligence
			2010–2014
1	229	0.06	2011	Design
2	220	0.02	2012	BIM
3	100	0.05	2012	Optimization
4	98	0.02	2014	Sustainable construction
5	97	0.06	2012	Construction
			2015–2019
1	95	0.08	2015	Model
2	95	0.03	2016	Management
3	79	0.02	2016	Framework
4	65	0.02	2016	Buildings
5	57	0.01	2017	Technology
			2020–2024
1	27	0.00	2021	Challenges
2	22	0.00	2020	Industry
3	21	0.03	2020	Multiobjective optimization
4	21	0.01	2021	Circular economy
5	20	0.00	2021	Deep learning

.

Following a thorough examination of the pertinent literature, which combined high-frequency phrases from various years of study on this topic, we categorize the evolution of the field of sustainable buildings and the intelligence related to it into the following three phases:

• Nascent stage (around 2005–2009)

Themes such as “energy efficiency,” “sustainable building,” and “green buildings” took the lead at this stage. These themes are the foundation of sustainable building research, focusing on the basic concepts of energy efficiency and sustainability in buildings and emphasizing the sustainability of buildings through improved energy use efficiency. This research is in the preliminary exploration period; the nodes of the related themes are relatively few, and the connecting lines are not dense enough, indicating that the research direction is relatively concentrated; the connection between the themes is still being gradually established, and the depth and breadth of the research need to be expanded. The research’s primary subjects are using sustainable materials in buildings, energy-saving technology, and other fundamental areas;

• Development and Expansion Phase (2010–2016 or so)

Themes such as “design,” “performance,” “bim,” and “energy consumption” have emerged. The design process has begun to receive attention for research on integrating sustainability into building design. Building Information Modeling technology has been introduced to optimize the management of the whole life cycle of the building, and the study of building performance has expanded from a single energy performance to a comprehensive performance, with an in-depth focus on the quantitative analysis and control of energy consumption. The number of nodes increased significantly in this period, and the connectivity between themes became richer, indicating an expanding scope of research and an increasing trend of interconnection and cross-fertilization of themes. Research has begun to expand from basic concepts to technical applications, performance optimization, and other dimensions, and the trend of interdisciplinary research is emerging, such as the combination of computer science and the architectural field to apply Building Information Modeling technology;

• Deepening Diversity Phase (2017–2024 and beyond)

Themes such as “smart grid,” “construction industry,” “circular economy”, and “urban planning” emerged. This research is no longer limited to a single building. However, it starts moving in the direction of the industry’s overall sustainable transformation and the integration of the building and urban systems. Smart grid and building energy system integration is exploring the role of buildings in energy interconnection; the introduction of the circular economy concept focuses on the recycling of building materials, and the overall sustainable development path of the building industry and the synergy with urban planning has become the new focus. During this period, nodes continued to grow and become more widely distributed, with intricate connections forming a large and diverse research network. This research is highly interdisciplinary and comprehensive, integrating knowledge from energy, environment, economy, urban planning, and other fields, and is committed to constructing a macro system of sustainable architecture and solving complex real-world problems.

4.3.3. Cluster Analysis of Keywords

In this analysis section, research hotspots and themes are identified by clustering keywords based on the outcomes of the preexisting network and time division. This lays the groundwork for further timeline analysis and trend forecasting [93].

To create the visualization, we select “keywords” as the node type in Citespace; then, in the upper sidebar, select the “All in One: clustering, optimizing layout and style” option and a “style” option within the top sidebar. The LLR algorithm was selected to perform clustering operations to generate accurate clustering results; Figure 11 displays the outcomes. The labels in the graph represent the clustering themes, and the cluster size reflects the high number of keywords. The node size presents these keywords according to their frequency of occurrence, and the degree of correlation between the keywords is indicated by the connecting lines between the nodes, and different years correspond to different colors. The 11 clustering labels that emerged from this research are displayed in Figure 11, and

Table 9. List of cited clusters and the number of records contributed by Sustainable Buildings and Intelligent Research, 2005–2024.

Cluster ID	Size	Silhouette	Mean (Year)	Label (LLR)
0	87	0.766	2012	energy management (1087.76, 1.0 × 10−4); utility grid (662.72, 1.0 × 10−4); smart grid (613.16, 1.0 × 10−4); smart building (591.69, 1.0 × 10−4); efficient building operation (454.67, 1.0 × 10−4)
1	74	0.641	2017	computational intelligence solution (308.92, 1.0 × 10−4); large scale (308.92, 1.0 × 10−4); energy performance enhancement (304.02, 1.0 × 10−4); urban building (304.02, 1.0 × 10−4); iot-based prediction technique (299.1, 1.0 × 10−4)
2	70	0.697	2018	circular economy (512.95, 1.0 × 10−4); architecture engineering (363.28, 1.0 × 10−4); pls-sem approach (353.77, 1.0 × 10−4); new zealand (339.03, 1.0 × 10−4); construction industry (297.96, 1.0 × 10−4)
3	65	0.821	2016	thin film (644.37, 1.0 × 10−4); materials rejuvenation (562.61, 1.0 × 10−4); long-term durability (562.61, 1.0 × 10−4); optical constant (510.61, 1.0 × 10−4); metal-insulator transition (510.61, 1.0 × 10−4)
4	55	0.847	2014	smart building (1074.11, 1.0 × 10−4); case study (386.02, 1.0 × 10−4); energy management (359.21, 1.0 × 10−4); life cycle assessment (313.14, 1.0 × 10−4); predictive control (304.86, 1.0 × 10−4)
5	53	0.725	2017	predictive control (905.83, 1.0 × 10−4); smart building energy management (668.66, 1.0 × 10−4); predicting heating load (604.95, 1.0 × 10−4); smart building (558.99, 1.0 × 10−4); post-occupancy evaluation (499.92, 1.0 × 10−4)
6	50	0.703	2017	learning algorithm (532.02, 1.0 × 10−4); net zero energy building (406.1, 1.0 × 10−4); building energy saving (357.43, 1.0 × 10−4); research trend (357.43, 1.0 × 10−4); text mining (357.43, 1.0 × 10−4)
7	28	0.885	2016	inspecting post-construction energy efficiency (262.04, 1.0 × 10−4); knowledge-based building management system (262.04, 1.0 × 10−4); the modeling literature (252.91, 1.0 × 10−4); rating analyses (234.67, 1.0 × 10−4); advantages challenge (225.57, 1.0 × 10−4)
8	18	0.894	2020	things-assisted manufacturing (190.35, 1.0 × 10−4); 3D printing technology (190.35, 1.0 × 10−4); cloud manufacturing internet (190.35, 1.0 × 10−4); reliable tool (190.35, 1.0 × 10−4); existing building stock (169.28, 1.0 × 10−4)
9	17	0.852	2013	calculation tool (1011.82, 1.0 × 10−4); rwth aachen university (240.18, 1.0 × 10−4); software tool (205.7, 1.0 × 10−4); exemplary tasks series (182.78, 1.0 × 10−4); fg building physics (182.78, 1.0 × 10−4)
10	14	0.935	2018	compressive strength (283.07, 1.0 × 10−4); green concrete (212.68, 1.0 × 10−4); area-wide redevelopment planning (181.22, 1.0 × 10−4); indexing scheme (181.22, 1.0 × 10−4); residual strength properties (170.54, 1.0 × 10−4)

provides information on each label. The research directions shown in the tabs from 0 to 10 are energy management, computational intelligence solution, circular economy, thin film, smart building, predictive control, learning algorithm, inspecting post-construction energy efficiency, things-assisted manufacturing, calculation tool, and compressive strength. The clustering module Q has a value of = 0.5176, which ranges from 0 to ~ 1 and is greater than 0.3, implying that the delineated clusters are significant. The average profile value of the clusters is S = 0.7625 and is greater than 0.7, indicating that the clusters shown in this paper are convincing.

Table 9’s largest cluster (#0) has 87 articles with a silhouette value of 0.766, which is higher than 0.7 and suggests that the articles in this cluster have very high core consistency, and the research is mainly focused on energy management, utility grid, smart building, and efficient building operation. This research mainly focuses on energy management, utility grids, smart buildings, efficient building operation, etc., most of which were released in 2012. The second major category (#1) contains 74 articles on computational intelligence solutions, large-scale energy performance enhancement, urban building, and IoT-based prediction technology. The silhouette value of (#1) is 0.641; most of its pieces came out in 2017. There are 70 papers in the third major category (#2), which are dominated by the circular economy, architectural engineering, PLS-SEM approach, etc. Since three of the eleven clusters were founded in 2017, the field is thriving, with a comparatively better level of diverse research and cross-disciplinary collaboration.

The CiteSpace clustering results show multi-dimensional research directions around sustainable buildings and intelligence. It covers energy management and smart building technology applications, such as energy optimization, through computational intelligence and predictive control; research on building material performance, such as film durability and concrete compressive strength; and the integration of emerging technologies, including IoT-assisted manufacturing and 3D printing; as well as the management of the whole process of construction, from post-construction energy-efficiency testing to planning based on the circular economy. The clusters are interrelated and have their focus, and together, they build a research system in the field.

• Energy and Smart Technologies

It is centered around energy management and smart technologies in buildings. These include #0 Energy Management, #1 Computational Intelligence Solutions, #4 Smart Buildings, #5 Predictive Controls, and #6 Learning Algorithms. Smart energy technology realizes the coupling of system energy efficiency technology and IT smart technology, covering smart grids, smart meters, distributed energy management, etc. The smart grid can transmit power and information in both directions to enhance system efficiency and reliability; smart meters can monitor electricity consumption in real time, and distributed energy management systems can intelligently dispatch distributed power sources. At the same time, the deep integration of energy, artificial intelligence, big data analysis, Internet of Things, blockchain, and other technologies are used to mine the laws of power data, optimize energy transactions, monitor the energy equipment in real time, and enhance the level of intelligence of the energy system, which also involves key technologies such as optimal scheduling of the energy system, efficiency enhancement, energy storage and grid connection of renewable energy sources, and promotes the building energy sector to grow in a way that is low-carbon, intelligent, and highly efficient;

• Construction Materials and Engineering

Focuses on building material properties and engineering applications. Includes #3 film and #10 compressive strength. Various building materials are categorized by function, as wall and decorative materials, and by material, as natural and chemical. The properties include physical properties (e.g., density, water absorption, etc.), mechanical properties (strength, deformability, etc.), and durability. Regarding ecological building materials, resource and energy conservation, environmental friendliness, and recyclability are emphasized and need to be comprehensively assessed using life cycle assessment methods. This category covers the long-term performance of thin films in construction, the compressive strength of concrete and other materials, and other mechanical properties related to safety, durability, and functionality, and it provides a basic guarantee for the quality of construction projects;

• Emerging concepts and technology applications

These concepts focus on applying innovative ideas and cutting-edge technologies in the construction industry. These include #2 Circular Economy, #7 Post-Construction Energy Efficiency Testing, #8 IoT-Assisted Manufacturing, and #9 Computational Tools. The circular economy concept explores a new resource recycling model in this area to reduce waste and environmental impact. Post-construction energy efficiency testing improves the building energy assessment system to ensure long-term energy efficiency in buildings. IoT-assisted manufacturing transforms production methods by integrating cutting-edge technologies like cloud computing, 3D printing, and the Internet of Things into building manufacturing. Computing tools provide analytical tools for building performance research, helping to optimize building design and operation. These novel ideas and technological applications disrupt the conventional construction paradigm, which creates new avenues for the building industry’s intelligent and sustainable growth.

4.3.4. Research Clustering Time Plots

The clustered timeline diagram can more effectively analyze the process of emergence, each period’s growth, and fall in the research hotspots for intelligence and sustainable building. It can also clarify the specific time nodes to accurately give insight into the research hotspots in a specific period. Through the clustering of high-frequency words, the dynamic evolution of each cluster in the time dimension can be visualized [94].

During Citespace operation, the node type is selected as “Keyword” in the control pane, Time Zone View is selected as the layout model, and the visual analysis is generated with the help of the LLR algorithm. The timeline presented in Figure 12 uses the horizontal axis as the time dimension, displaying each node’s initial appearance from left to right, demonstrating this study’s evolutionary path from early germination to more recent development. A wide range of topics and technology areas related to intelligence and sustainable buildings are covered by the keywords shown in Figure 12, including energy efficiency, artificial intelligence, smart windows, smart buildings, phase change material, sustainable design, building construction, urban planning, etc. In addition, research and teaching, life cycle assessment, barriers, etc., are also included. These themes frame the research on sustainable buildings and intelligence in four dimensions: energy and technological innovation, sustainability, assessment and education, and problems and responses.

Based on the clustered time diagrams, it is possible to categorize the changes in the development of the field into three phases. In the first stage (2005–2010), starting from the left side of the graph, basic themes such as energy efficiency are the first to appear, representing that sustainable building research begins to pay attention to energy-related fundamental issues and is at the stage of exploring concepts and basic technologies. Relevant research is in the initial accumulation period. In the second stage (2011–2018), as time advances, the number of technical topics, such as artificial intelligence, smart windows, smart buildings, etc., increases, and the nodes become larger, indicating that the research enters the stage of technology integration and development, and a variety of emerging technologies are being continuously integrated into the field of architecture, promoting the rapid development of buildings in the direction of intelligence and the association between the technical topics also gradually tightens. In the third stage (2019–2024), the importance of sustainable design, urban planning, and other topics is highlighted later. This research is no longer limited to building monolithic technology and energy issues. It starts to consider the synergistic development of buildings, cities, and the environment from the perspective of comprehensive planning while deepening research tools such as life-cycle assessment appear, marking that the research on sustainable buildings and intelligence enters the stage of comprehensive planning and deepening application.

The three phases of sustainable building research and development each have their problems. The initial period focuses on the energy base, with a single direction, immature technology, and a lack of standards; the technology integration period is characterized by difficulties in integrating a variety of technologies, a shortage of talents, and the hidden dangers of security and privacy; and the comprehensive planning period is characterized by poor sectoral coordination and communication, an imperfect evaluation system, and high implementation costs, which are all constraints to the further development of the field.

These dilemmas highlight the need to move from purely theoretical research and conceptual explorations to an approach emphasizing practical applications in sustainable buildings and intelligence. By proactively adapting to the need for multidisciplinary integration, the changing nature of industry standards and codes, the market’s demand for cost-effectiveness, and a model of synergistic collaboration between different sectors, we can guarantee intelligent development of sustainable buildings by improving our research and implementation strategies.

4.3.5. Research Trend Analysis Chart

According to an analysis of emergent keywords, some key terms quickly amass a significant number of citations within a specific time frame, and they often serve as indicators of emerging research areas or topics [95].

With the help of the “Cluster Explorer” function in Citespace, we filtered out the top 25 most cited keywords and organized them into Figure 13. Meanwhile, Figure 13 presents the 25 citation bursts between 2005 and 2024. The evolution of the main trends in sustainable building and smart research presents three distinct phases. (1) The period from 2005 to 2012 was mainly a phase of exploration of basic concepts and technologies. At this stage, the keywords “energy efficiency,” “green buildings,” “sustainable design,” etc., represent the basic concepts in the field of sustainable buildings; “energy efficiency,” “green buildings,” “sustainable design”, and others keywords represent the basic concepts in the field of sustainable buildings, and the purpose of this study is to increase building energy efficiency, the promotion of green building concepts, and the exploration of sustainable design methods. At this time, the smart grid technology appeared in 2011 but has not yet formed a dominant trend. (2) From 2013 to 2018, smart technologies began to converge and evolve. “Smart buildings,” “architecture,” “energy-efficient buildings,” “intelligent buildings,” etc., have been manifested during this period. At the same time, some keywords related to smart technologies, such as “wireless sensor networks,” “big data,” and “building information modeling (bim),” etc., appear one after another and have some intensity in the corresponding period “information modeling (bim),” etc., appear one after another and have a certain intensity in the corresponding period. At this stage, intelligent technology integration and the construction field accelerate. The research focuses on utilizing intelligent technology to enhance building performance and sustainability, and the research and applications related to intelligent buildings are developing rapidly. (3) In 2019–2024, a comprehensive deepening and broadening phase of “building performance,” “cooling load,” “heating load,” “sustainability,” etc., had a certain intensity of performance in this stage of research on the previous period based on further deepening and expansion, paying more attention to the optimization of the comprehensive performance of the building, from the energy consumption related to the cooling load and heat load to the overall sustainability. The scope of this research is constantly expanding, focusing on the performance of the whole life cycle of the building to enhance sustainable development. The three phases described above represent the field’s evolution from basic concepts to technology convergence to complete performance enhancement.

5. Discussion

This study focuses on sustainable and smart buildings, using Citespace and bibliometrics for comprehensive visualization and analysis. Figure 14 presents the primary research fields about intelligence and sustainable buildings, demonstrating progress in intelligence and sustainable building research.

In terms of research results, we present a clear picture of the development of the field. In terms of the annual publication trend, the number of papers published is on the rise overall, and the growth rate accelerated significantly after 2015, reflecting that the research fever in this field continues to climb, attracting more and more scientific research forces to invest in it. The significance of journals like ENERGY AND BUILDINGS and BUILDING AND ENVIRONMENT in the area was made clear by examining key journals, and these publications have grown to be crucial channels for sharing research findings. Regarding country/region distribution, China, the United States, and other countries/regions dominate this research. However, some countries/regions, such as Poland and Brazil, still need to strengthen their cooperation to promote academic exchanges and common development on a global scale. The analysis of authors’ cooperation shows that there is insufficient intra-field cooperation and poor continuity of scholars’ research, which, to some extent, restricts the depth and diversification of research, and future measures need to be taken to encourage long-term cooperation among scholars. The distribution of participating institutions demonstrates how important universities are to research, with outstanding results from institutions such as the Hong Kong Polytechnic University. However, the participation of research institutes and companies needs to be improved, and enhanced collaboration among all parties will inject new vitality into the field.

The research area analysis provided us with an in-depth understanding of the core elements of the field. Highly cited articles focus on Building Information Modeling technology applications, building sustainability, and energy-related research, highlighting the key position of these aspects in the field. Time–zone co-occurrence analysis reveals the trend of disciplines expanding from traditional to new and interdisciplinary directions, with new interdisciplinary fields and fields related to sustainable development emerging and establishing close links with other fields. Keyword co-occurrence, clustering, and other analyses further clarify the research hotspots, covering green building, design, Building Information Modeling technology, performance optimization, energy efficiency, etc., which are interconnected and jointly promote the development of the field. The keyword co-occurrence time zone helps us to sort out the evolution of research hotspots, from the budding start-up stage focusing on the basic concepts of building energy efficiency and sustainability to the development and expansion stage emphasizing technology application and performance optimization to the stage of depth and diversification, which emphasizes the industry’s entire sustainable transformation as well as the integration of construction and urban systems, with the research continuously deepening and expanding.

Comparing the results of this study on sustainable buildings with similar studies, most studies show mutual support for each other’s core ideas. X Haiyirete et al. [96] consider the importance of smart buildings in the development of the construction industry, find an increasing trend in the number of publications of related studies, and suggest that the future development of this field is promising and will drive the construction industry in a more sustainable direction. H Huang et al. [97] emphasize the need for sustainable development, recognizing the key role of smart technologies in promoting sustainability and focusing on the optimal use of energy in buildings to achieve energy savings. M Asif et al. [12] point out that the building industry needs to reduce its energy consumption and environmental footprint in order to enhance sustainability, emphasizing the key role of digital technologies in this regard and mentioning the challenges faced in the development, such as the high cost, technology, and the need for a more sustainable building industry—compatibility, shortage of human resources, etc.

In the research on the intelligent implementation of sustainable buildings, Building Information Modeling (BIM), as a digital core tool running through the whole life cycle of design, construction operation, and maintenance, drives the optimization of building performance and the precise implementation of low-carbon goals by integrating multi-dimensional data such as climate simulation, energy management, and material cycle. Its visualization, collaboration, and dynamic simulation capabilities become the key technical support in the implementation path of intelligent, sustainable buildings. Internet of Things (IoT), as an intelligent nerve center connecting building equipment, environmental sensors, and management systems, empowers the optimization of building energy efficiency, enhancement of living comfort, and automation of operation and maintenance through real-time collection of data on energy consumption, indoor environmental quality, equipment operation status and construction of a dynamic interaction network, and its full-area sensing and interconnection of data have become the core infrastructure for the realization of intelligent landing of building sustainability. Reviewed from the logic of technological evolution, the application of such digital tools is essentially the construction industry to the intelligent transformation of the stage of practical results. With the continuous iteration of artificial intelligence, edge computing, digital twins, and other new-generation information technologies, more innovative tools with both data integration capabilities and scenario adaptability will emerge in the future, and they may further break through the existing technical boundaries in the form of cross-technology domain integration to promote the intelligent implementation of sustainable buildings to a more autonomous, ubiquitous and higher-order paradigm evolution.

The integration of sustainable building and intelligent integration with cutting-edge technology to realize the whole life cycle of intelligent management, promote the green transformation of the construction industry, and give rise to new economic forms. Future research should focus on solving existing problems and promoting the comprehensive and efficient application of smart technologies in sustainable buildings. In terms of technological innovation, the government should increase financial support for the research and development of intelligent technology, encourage deep cooperation among industries, universities, and research institutes, and promote the large-scale application of intelligent technology in order to achieve effective cost control; at the same time, it should formulate a unified technical standard specification, strengthen the industry’s supervision, and enhance the compatibility and interoperability of intelligent systems. For the research dilemma, the scientific research management department needs to strengthen the guidance and review of research topics to avoid repetitive research and build a scientific and reasonable research evaluation system, focusing on the long-term impact and practical application value of research results. Talent training is crucial, and universities and vocational colleges should optimize the professional curriculum and strengthen the practical teaching links. Enterprises should strengthen the technical training of their staff and establish incentive mechanisms to encourage their employees to improve their technical level. In order to promote interdisciplinary collaboration and international cooperation, it is necessary to build an interdisciplinary research platform, set up special incentives to break down disciplinary barriers, actively participate in international academic exchanges, establish close cooperation with international scientific research institutions and enterprises, carry out joint research projects, and share cutting-edge technologies and experiences, thereby promoting the sound development of the field of sustainable buildings and intelligence.

Smart solutions are significant in the field of sustainable buildings. Examples include Heating, Ventilation, and Air Conditioning (HVAC), energy management, building optimization methods, and urban heat island challenges. With the help of smart sensors and artificial intelligence algorithms, HVAC monitors environmental parameters in real time, automatically adjusts the equipment operation, realizes zoning control, reduces energy consumption, and links with other systems. Building energy management relies on intelligent collection equipment to obtain data, mining energy-saving opportunities through big data analysis, and optimizing energy scheduling remotely through energy management systems to reduce costs. Building optimization methods integrate BIM, VR, AR, and other technologies to comprehensively improve building performance during the design, construction, and operation phases. Intelligent greening, shading technologies, and innovative materials can mitigate the urban heat island effect.

There are some limitations to this study. For one thing, the data of this study only comes from the WOS database, which significantly limits the coverage of this study, resulting in the rich and diverse subject contents and multilingual research results in PubMed and CNKI databases not being included in the research field. Secondly, the period of the research data set is from 2005 to 2024, and due to the constraints of the search time, some relevant literature may be missed, and the results published in earlier or later periods may not be covered, which makes the research conclusions unavoidably have temporal limitations. Finally, regarding the choice of analysis tools, only Citespace was used in this study. Other software, such as VOS Viewer 1.6.20, Gephi 0.10.1, Sci2 Tool 1.3, etc., can also analyze the data from different perspectives and produce differentiated results. Of course, the methodology of subsequent studies may be further optimized and improved.

Compared to previous studies, this study’s theoretical value in sustainable buildings and intelligence is reflected in its in-depth bibliometric analysis, which reveals the development trends and implementation strategies of sustainable buildings. This study highlights the key role that smart technologies play in advancing sustainable building development while also making it clear to advance the field of sustainable building. It is necessary to strengthen interdisciplinary collaboration and proactively address several challenges, such as data security and technological innovation.

6. Conclusions

This study analyzed the current state of sustainable architecture and intelligence research from 2005 to 2024 through bibliometric analysis. This study found that sustainable buildings and intelligence are proliferating, and research results are emerging. However, it also faces problems such as insufficient author collaboration, and the need to improve the participation of some countries/regions and institutions needs to be addressed. At the same time, there are limitations in the research process, such as a single source of data, limited timeliness, and a single analytical tool.

This study found the following: (1) The number of papers published in this field is on an upward trend, and the growth rate accelerated after 2015, showing that the research heat continues to increase. (2) The research hotspots have evolved from exploring basic concepts and expanding technological applications to deepening multidisciplinary integration. (3) The highly cited articles are centered on Building Information Modeling technology applications, building sustainability, and energy research. (4) The development of disciplines shows an interdisciplinary trend, with emerging fields increasingly linked to traditional disciplines. At the same time, the following problems were found: (1) homogenization of research, lack of innovation in some studies, similarity in focusing on hotspots, neglecting some key and potential problems in the field, which is not conducive to the overall development of the discipline. (2) Insufficient cooperation and exchanges between authors and countries/regions, lack of coherence and depth of research, difficulty forming systematic results, and obstacles to the diversification of the field. (3) Poor compatibility and interoperability between different intelligent systems, easy to form “information islands,” reducing the overall effectiveness of the system, as well as a shortage of talent, unable to realize the efficient flow of data and collaborative work, affecting the effect of intelligent management of buildings. (4) Universities dominate the research in this field, and the participation of other organizations and companies is low, which is not conducive to the in-depth integration of industry, academia, and research and the practical application and transformation of research results.

The field of intelligence and sustainable building has a promising future. With the increasing global focus on sustainability and continued innovation in smart technologies, the field will play an increasingly important role in the green transformation of the building industry. In terms of technological innovation, digital twins, artificial intelligence, and the Internet of Things are among the technologies that will be progressively integrated and used to manage buildings during their entire life cycle, enhancing the level of intelligence and sustainability of buildings. At the policy level, countries/regions will introduce more stringent sustainable building standards and policies to promote the development of the construction industry in the direction of low-carbon and green practices. Market mechanisms will also continue to innovate, and green finance and carbon trading will provide more substantial support for developing sustainable buildings.

Future research should further explore key issues in the field of sustainable buildings and intelligence in depth to improve the inadequacies of existing research. For example, strengthening interdisciplinary research, integrating multidisciplinary knowledge of energy, environment, computer science, urban planning, and other disciplines, and solving the complex problems faced by the sustainable development of the building industry, focusing on the development of sustainable buildings in developing countries/regions and exploring the development mode and technology path suitable for their country/regional conditions; studying how to break the “information silos” between “intelligent systems,” improve system compatibility and interoperability, etc. Through continuous and in-depth research, we will provide more solid theoretical support and practical guidance for developing sustainable buildings and intelligent fields and help the global construction industry realize the goal of sustainable development.