INTEGRATING IoT, BIM, AND DIGITAL TWIN TECHNOLOGIES FOR SMART SUPER HIGH-RISE MANAGEMENT IN CHINA

ABSTRACT

Background. China operates the world's largest inventory of high-rise buildings — more than one million structures above 27 metres and over 3,400 skyscrapers — concentrating operational complexity, fire-safety risk, and energy consumption in a building typology for which conventional, siloed management systems are increasingly inadequate. This article examines how the convergence of the Internet of Things (IoT), Building Information Modelling (BIM), and Digital Twin (DT) technologies is being applied to the operational management of super high-rise buildings in China, quantifies the scale and growth rate of the underlying IoT, artificial-intelligence (AI), and digital-twin markets that make this convergence commercially and technically feasible, and identifies the regulatory, technical, and organizational barriers that constrain it.

Methods. The article combines a qualitative literature review and policy analysis — synthesizing peer-reviewed engineering-management research, Chinese national standards (including GB/T 51212 and GB 50352), and post-incident regulatory reporting published between 2012 and 2025 — with a quantitative market-sizing analysis drawn from eight industry-analytics sources (2025 editions) covering the global and China-specific IoT, digital-twin, AI-in-construction, smart-building, and BIM-software markets.

Results. Four findings emerge. First, the technology markets underpinning IoT–BIM–DT integration are large and growing quickly but unevenly: the global IoT market (US$864 billion in 2025) is roughly 47 times the size of the global AI-in-construction market (US$1.6 billion), while AI-in-construction and digital-twin segments are forecast to grow two to four times faster (31–44% CAGR) than the broader IoT or smart-building markets (12–23% CAGR) — evidence that the analytical layer, not the sensing layer, is the market's current growth frontier. Second, IoT–BIM–DT integration architectures reported in the literature converge on a common layered structure — data acquisition, transmission, analysis/integration, and service — that supports real-time monitoring, predictive maintenance, and fire/evacuation simulation beyond the capability of static BIM models alone. Third, adoption in China has been shaped as much by regulation as by technology or market size: fire-safety rules developed for buildings up to roughly 250 metres are applied case-by-case above that height, and a 2021 nationwide fire-safety regulation and post-2025 high-rise safety inspections have increased demand for continuous, sensor-based monitoring rather than point-in-time compliance checks. Fourth, persistent barriers — data interoperability gaps between BIM authoring tools and facility-management systems, fragmented information silos across the building lifecycle, and the higher adoption costs facing small and medium-sized specialist contractors — continue to limit the transition from pilot-scale digital twins to portfolio-wide deployment, even as the underlying technology markets expand.

Conclusion. Realizing the safety and efficiency potential of IoT–BIM–DT integration in China's super high-rise stock requires coordinated progress on three fronts simultaneously: technical interoperability standards, regulatory frameworks that recognize continuous digital monitoring as a compliance pathway, and financing or mandate mechanisms that extend adoption beyond large state-backed landmark projects to the broader building stock — a case where market growth is outpacing institutional diffusion rather than the reverse.

Keywords: Building Information Modelling; Digital Twin; Internet of Things; artificial intelligence; market analysis; super high-rise building; smart building management; fire safety; facility management; China construction industry; interoperability.

Introduction

China's urban skyline has grown faster than the regulatory and managerial infrastructure designed to keep it safe and efficient. The country contains more than one million buildings above 27 metres and 3,492 skyscrapers, with the number of households living in high-rises increasing 150 per cent between 2010 and 2020 [1]. Operating a portfolio of this scale and density — spanning aging structures from the 1980s–2000s alongside contemporary supertalls exceeding 400 metres — has exposed the limits of conventional facility management, in which fire alarms, evacuation routes, and structural sensors are monitored and reported as isolated, often paper-based systems [2].

This operational challenge is unfolding against a technology market that has itself scaled sharply. The global Internet of Things market was valued at US$864.32 billion in 2025 and is projected to reach US$5,552.48 billion by 2034 (23.10% compound annual growth rate, CAGR) [17], while China's domestic IoT market — valued at US$98.31 billion in 2025 — is forecast to grow to US$174.31 billion by 2030 [18]. The number of connected IoT devices worldwide reached 21.1 billion in 2025, up 14% year-on-year, and is projected to reach 39 billion by 2030 [22], supplying the raw sensing volume on which any building-scale digital twin ultimately depends. These figures matter for the argument developed here for a specific reason: they establish that the sensing and connectivity layer of IoT–BIM–DT integration is not a niche or experimental capability but a mainstream, rapidly commoditizing infrastructure — which sharpens, rather than answers, the question of why adoption in China's super high-rise stock nonetheless remains concentrated in a small number of landmark projects (see Results).

Two independent technological trajectories have converged to address the underlying operational gap. Building Information Modelling (BIM) has matured from a design-and-construction visualization tool into a lifecycle information backbone, formalized in China through the national standard GB/T 51212-2016 and adopted as a scoring criterion in public-sector tenders across more than thirty provinces and cities [11]; the global BIM-software market itself grew from US$9.67 billion in 2021 toward a projected US$23.95 billion by 2027, a 16.33% CAGR [23]. Separately, the Internet of Things has enabled continuous sensing of a building's physical state — temperature, occupancy, structural strain, air quality, energy consumption — at a resolution and frequency unattainable through periodic inspection. The Digital Twin (DT) concept sits at the intersection of the two: a live, sensor-updated virtual replica of the physical asset that uses the BIM model as its geometric and semantic foundation [7]. For super high-rise buildings, where the physical consequences of a fire or structural fault are amplified by height, occupant density, and extended evacuation times, this convergence is not merely an efficiency upgrade but a safety-critical capability.

The objective of this article is to examine how IoT, BIM, and Digital Twin technologies are being integrated for the operational management of super high-rise buildings in China, to quantify the size and growth trajectory of the markets that make that integration feasible, and to identify the principal regulatory, technical, and organizational barriers that constrain wider deployment. The article does not propose or test a new architecture; rather, it synthesizes the existing engineering-management literature, current market-sizing data, and China-specific regulatory record to characterize the current state of practice, its commercial context, and the constraints on its diffusion.

Theoretical Framework

The literature converges on the Digital Twin as a five-layer architecture: a data-acquisition layer (IoT sensors, Building Automation Systems, laser scanning), a data-transmission and management layer, a data-analysis layer (often incorporating machine learning for anomaly detection or predictive maintenance), a data/model-integration layer that binds sensor streams to the semantic BIM model, and a services layer that exposes the resulting insight to facility managers, often through mixed-reality or dashboard interfaces [7]. Eneyew, Capretz, and Bitsuamlak similarly frame smart-building digital twins as the product of BIM providing static semantic and geometric structure while IoT provides the dynamic, real-time state, arguing that neither technology alone is sufficient: BIM without live data ages into an inaccurate as-built record, and IoT without BIM produces sensor data with no spatial or systemic context for interpretation [8].

For super high-rise buildings specifically, this general architecture must accommodate two domain-specific requirements documented in the fire-engineering literature: the refuge-floor system mandated for buildings above 100 metres under Chinese code, which segments evacuation into discrete vertical stages and therefore requires floor-by-floor rather than whole-building occupancy and smoke modelling [6]; and the stack effect and extended egress times that make real-time occupancy and smoke-spread data materially more valuable in a 400-metre tower than in a low-rise building, where a static evacuation plan may remain adequate [3]. This leads to the article's guiding propositions, extended here to incorporate the market evidence presented in the Results section: P1: IoT–BIM–DT integration provides the greatest marginal safety benefit precisely in the super high-rise segment where conventional periodic inspection is least able to capture time-varying risk. P2: The rate of integration in China is constrained less by sensor, connectivity, or modelling technology — all of which sit within large, mature, and still fast-growing markets — than by interoperability standards and organizational fragmentation across the building lifecycle. P3: Regulatory recognition of continuous digital monitoring as a compliance mechanism, rather than a voluntary supplement to periodic inspection, is a precondition for portfolio-wide rather than landmark-project-only adoption, notwithstanding the scale of the underlying technology market.

Materials and Methods

This article employs a mixed literature-based and market-analytical method combining (i) a review of peer-reviewed engineering-management and construction-informatics research on BIM–IoT–DT integration in China and internationally, spanning 2012–2025; (ii) an analysis of the relevant Chinese national standards and regulatory instruments, including GB 50352-2019 (Uniform Standard for Design of Civil Buildings), the 2021 Ministry of Emergency Management fire-safety regulation for civil high-rise buildings, and the 2021 Ministry of Housing and Urban-Rural Development height-limitation regulation; (iii) post-incident and inspection reporting, including the nationwide high-rise fire-risk inspection conducted from July 2022 to June 2023 and the 2025 sweeping safety check ordered following a major fire in Hong Kong; and (iv) a quantitative market-sizing analysis drawing on eight 2025-vintage industry-analytics reports (Fortune Business Insights, MarketsandMarkets, GMI Insights, Mordor Intelligence, Precedence Research, IoT Analytics, and Pinnacle Infotech) covering the global and China-specific IoT, digital-twin, AI-in-construction, smart-building, and BIM-software markets, used to establish the scale, growth rate, and relative maturity of the technology segments discussed qualitatively elsewhere in the article. Sources were selected for direct relevance to super high-rise buildings (generally defined in China as exceeding 100 metres) rather than the broader high-rise category, and for documented China-specific application rather than purely international case studies, except where used for architectural, conceptual, or market comparison.

Results

Market context: the scale of IoT, AI, and digital-twin adoption

The regulatory and technical findings that follow sit within a technology market whose scale and growth rate this article now quantifies directly, addressing a gap in the qualitative literature this review otherwise draws on. Table 1 and Figure 1 summarize market-sizing estimates for the five segments most directly relevant to IoT–BIM–DT integration in super high-rise management.

Table 1. Market size, forecast horizon, and compound annual growth rate (CAGR) for the technology segments underlying IoT–BIM–DT integration, 2025 estimates. Sources: [17]–[23].

Figure 1. Current (2025) and forecast market size by technology segment, log scale. The four-order-of-magnitude spread between the global IoT market and the global AI-in-construction market illustrates that AI-specific analytical capability, not raw connectivity, remains the smallest and least mature layer of the stack. Sources: [17]–[21]

Two patterns in this data are analytically significant for the argument developed in this article. First, market size and market growth rate move in opposite directions across the stack. The general-purpose IoT market is both the largest (US$864.32 billion globally in 2025) and among the slowest-growing (23.10% CAGR) of the segments examined, consistent with a maturing, commoditizing technology. The AI-in-construction and digital-twin segments are, by contrast, orders of magnitude smaller in absolute terms — US$1.63 billion and US$18.9 billion globally in 2025, respectively — but are forecast to grow at 31.27% and 41.7% CAGR, with the Asia-Pacific digital-twin sub-segment forecast even faster, at 44.3% [19, 21]. Figure 2 makes this relationship explicit.

Figure 2. Forecast compound annual growth rate by technology segment, sorted ascending. Digital-twin and AI-in-construction segments — the analytical and integration layers of the IoT–BIM–DT stack — are forecast to grow two to four times faster than the underlying connectivity and building-automation markets. Sources: [17]–[22]

This inverse relationship between segment size and growth rate is consistent with Proposition P2. If the constraint on China's super high-rise adoption were primarily one of sensor or connectivity availability, the relevant market would already be the largest and most mature segment in Table 1 — which it is. The fact that adoption nonetheless remains concentrated in landmark projects (discussed below) indicates that the binding constraint sits further up the stack, in the smaller but faster-growing analytical and integration layers (AI-based anomaly detection, BIM–IoT data binding, digital-twin synchronization) where market capacity is still being built out, and in the organizational and regulatory barriers discussed in the following subsections — not in the underlying sensing infrastructure.

Second, the sensing layer itself is scaling at a pace that has direct implications for the interoperability barriers discussed later in this section. The global installed base of connected IoT devices reached 21.1 billion units in 2025, growing 14% over 2024, and is forecast to reach 39.0 billion units by 2030 (13.2% CAGR) [22], as shown in Figure 3.

Figure 3. Global connected IoT device base, 2024–2030. Source: IoT Analytics [22]

Applied to China's building stock — more than one million structures above 27 metres [1] — this trajectory implies that the number of discrete, heterogeneous sensor endpoints any portfolio-wide digital-twin programme would need to integrate is itself growing by roughly 2.6 billion devices per year worldwide. This scaling dynamic reinforces, rather than resolves, the interoperability problem documented later in this section: a larger and more heterogeneous device population raises the cost of the very data-standardization work that current case studies identify as the primary bottleneck to scaling BIM-enabled facility management in China [12, 13]. At the national level, China's own smart-building market — valued at US$96.31 billion in 2025 and forecast to reach US$206.44 billion by 2031 (13.55% CAGR) [20] — is large enough in absolute terms to fund portfolio-wide deployment, which sharpens the puzzle addressed in the Discussion: the constraint on adoption is not market capacity but the institutional and technical barriers examined next.

Regulatory drivers of digital adoption

China's fire code for buildings up to approximately 250 metres specifies firefighting access, refuge floors, rooftop helipads, and vertical fire compartmentation in prescriptive terms; above 250 metres, the code shifts to a case-by-case performance-based principle [3], a regulatory gap that effectively requires building-specific simulation and monitoring rather than standard checklist compliance for the tallest structures. The Shanghai Tower's own fire-safety assessment illustrates the consequence directly: its double-skin twisting facade and fireproof-elevator evacuation strategy required a dedicated, building-specific performance-based fire-safety study beyond standard code compliance before occupancy was approved [16, 15] — precisely the kind of building-specific performance verification that a calibrated digital twin can support on an ongoing basis rather than as a one-time certification exercise. More recently, the nationwide high-rise inspection conducted after the 2025 Hong Kong high-rise fire instructed inspectors to focus on fire alarms, hydrants, fire doors, and flammable exterior insulation, particularly in buildings constructed between the 1980s and early 2000s [1] — an inspection burden at national scale that manual, building-by-building auditing struggles to sustain with consistent rigor, creating a policy-level argument for continuous IoT-based alarm and equipment-status monitoring as a complement to periodic physical inspection.

Documented integration architectures and applications

Empirical implementations reported in the literature demonstrate the layered IoT–BIM–DT architecture applied to specific building subsystems rather than to whole buildings end-to-end. A digital twin of a typical floor and its central air-conditioning system in a high-rise office building in Foshan, Guangdong, integrated BIM, Building Automation System data, AI-based analysis, and mixed-reality visualization, and was validated through both on-site and cloud-based remote testing [7]. At the construction-management stage, BIM-driven digital twins have been used to simulate construction sequencing and structure the operations-and-maintenance system that a building will use once occupied, establishing continuity between the design-phase BIM model and the eventual operational digital twin rather than treating them as separate systems [9]. Complementary applications documented in Chinese construction practice include 5G-connected tower cranes with laser and GPS positioning for real-time lift supervision and IoT-connected dust-control systems that adjust automatically to on-site air-quality sensors, illustrating that IoT integration in Chinese high-rise construction extends beyond the completed building into the construction process itself. These applications, while individually modest in scale, sit within the AI-in-construction market segment that Table 1 shows growing at 31.27% CAGR globally [21] — among the fastest of any segment examined — suggesting that the pilot-scale pattern documented here is more plausibly an early stage of a still-forming market than a ceiling on the technology's applicability.

Interoperability and organizational barriers

Despite this range of pilot applications and a large, fast-growing underlying market, the literature identifies persistent barriers to scaling integration across China's building stock. A case-study analysis of BIM in the operational phase in China found that the primary obstacles were not technological capability but interoperability between BIM authoring software and facility-management systems, and the absence of a clear, agreed definition of what data a facility-management-enabled BIM model should contain, echoing international findings that open standards such as Industry Foundation Classes (IFC) and COBie remain insufficient in practice to guarantee accurate data exchange [12]. A quantitative policy analysis of BIM adoption in China identified information silos between the design, construction, and operational phases as a persistent structural barrier despite a substantial volume of national and provincial BIM policy issued between 2011 and 2021, and despite a global BIM-software market that itself grew at a 16.33% CAGR over 2021–2027 [13, 23]. At the firm level, an interpretive structural modelling study of small and medium-sized fire-protection enterprises in China found that cost sensitivity and limited in-house technical capability were dominant barriers to BIM adoption specifically among the smaller, specialized contractors responsible for a significant share of fire-safety system installation and maintenance [14] — a finding consistent with Proposition P2: the constraint is organizational and economic rather than a limitation of the underlying sensing, connectivity, or modelling technology, all of which sit within markets large and liquid enough, per Table 1, to supply that demand if the organizational and regulatory barriers were removed.

Discussion

The pattern across these findings suggests that IoT–BIM–DT integration in China's super high-rise sector has advanced furthest exactly where regulatory pressure, project prestige, and available capital coincide — landmark supertall towers and state-linked infrastructure such as major hydropower facilities — while remaining comparatively underdeveloped in the far larger population of ordinary high-rise residential and commercial buildings, particularly the aging 1980s–2000s stock that current safety inspections identify as highest-risk [1]. The market data presented in the Results section sharpens this diagnosis rather than complicating it: this is not a case of technology scarcity. Every segment of the IoT–BIM–DT stack examined in Table 1 is a multi-billion-dollar market growing in double digits, and the fastest-growing segments — digital twin (41.7% global CAGR) and AI in construction (31.27% CAGR) — are precisely the analytical layers most relevant to the predictive-maintenance and anomaly-detection capabilities this article's Theoretical Framework identifies as the value-adding function of a digital twin. The five-layer DT architecture is demonstrated and validated in multiple independent pilot studies, and the market underpinning it is expanding two to four times faster than the broader construction-technology sector, yet its default application remains bespoke and project-specific rather than standardized and portfolio-wide. This is a case where technological and market capability has outpaced institutional diffusion.

This asymmetry carries a specific policy implication consistent with Proposition P3. So long as fire and structural safety compliance is defined by point-in-time inspection and certification, continuous IoT–BIM–DT monitoring remains, from a building owner's perspective, an optional cost layered on top of mandatory compliance rather than a substitute compliance pathway — regardless of how large or fast-growing the underlying technology market becomes. Recognizing validated continuous monitoring as satisfying part of the periodic-inspection obligation — as some performance-based codes elsewhere already do — would realign incentives toward the buildings and owners most exposed to fire and structural risk, rather than concentrating digital investment in the highest-profile new-build projects where it is most visible but arguably least urgently needed. China's own smart-building market, valued at US$96.31 billion in 2025 and growing at 13.55% CAGR [20], is large enough in absolute terms that the binding constraint on portfolio-wide adoption is very unlikely to be capital availability at the national level; it is more plausibly the absence of a regulatory pathway that would let individual building owners capture the compliance value of that investment.

Three limitations should be noted. First, the literature reviewed is unevenly distributed across building subsystems: fire and evacuation applications and HVAC/energy applications are relatively well documented, while structural health monitoring and vertical transportation (elevator) digital twins in super high-rises are comparatively under-studied in the available China-specific literature. Second, most reported case studies describe single-building or single-floor pilots; systematic, multi-building evidence on cost, return on investment, or measured safety-outcome improvement from IoT–BIM–DT integration in China's super high-rise stock is not yet available in the peer-reviewed literature, and the market-sizing data added to this revision, while establishing the scale and growth rate of the relevant technology markets, is aggregate industry-analytics data rather than building-level financial evidence — it quantifies market capacity, not realized return on investment, and this article does not claim otherwise. Third, the regulatory record is evolving rapidly following the 2025 Hong Kong high-rise fire, and specific inspection or standard-setting outcomes referenced here may be superseded by subsequent rulemaking; similarly, market-size and CAGR estimates are vendor- and analyst-forecast figures subject to the usual revision risk of industry forecasting rather than audited financial data.

Conclusion

This article has examined the integration of IoT, BIM, and Digital Twin technologies for super high-rise building management in China, situating that integration within both the country's distinctive regulatory and building-stock context and the scale of the global and China-specific technology markets that make it feasible. The evidence indicates that the underlying technology — a layered architecture combining IoT sensing, BIM's semantic and geometric model, and digital-twin synchronization — is technically mature, commercially well-resourced, and validated across multiple documented pilot applications in China, from air-conditioning-system twins to construction-stage crane and dust-control automation. The global IoT market alone was valued at US$864 billion in 2025, the global digital-twin market is forecast to grow at 41.7% CAGR through 2034, and China's own smart-building market is expected to more than double, from US$96.31 billion in 2025 to US$206.44 billion by 2031 [17, 19, 20] — by any measure, a well-capitalized and fast-expanding technology base.

The principal constraint on wider deployment is therefore not technological or financial but institutional: interoperability gaps between BIM and facility-management systems, information silos across the building lifecycle, and adoption costs that fall disproportionately on the small and medium-sized enterprises responsible for much fire-safety system work. Extending IoT–BIM–DT integration from landmark supertall projects to the much larger stock of ordinary — and often older — high-rise buildings will likely require regulatory frameworks that credit continuous digital monitoring toward safety compliance, alongside continued standardization of the data interfaces between design-phase BIM models and operational facility-management platforms. The market will very likely continue to grow with or without these reforms; whether that growth translates into safer buildings across China's full high-rise stock, rather than a widening gap between a well-instrumented landmark tier and an under-monitored ordinary tier, depends on institutional choices this article's evidence base cannot itself resolve.

References:

1. Sixth Tone. After Hong Kong Fire, China Orders Sweeping High-Rise Safety Check [Electronic resource]. — 2025. — URL: https://www.sixthtone.com/news/1017915/after-hong-kong-fire%2C-china-orders-sweeping-high-rise-safety-check (date of access: 25.08.2026).
2. Fire safety knowledge and awareness in high-rise residential buildings: an empirical study in China // Scientific Reports [Electronic resource]. — URL: https://pmc.ncbi.nlm.nih.gov/articles/PMC12635177/ (date of access: 25.08.2026).
3. Towering Infernos — Fire Risk on the Rise in Asia [Electronic resource] // Gen Re. — URL: https://www.genre.com/us/knowledge/publications/2017/july/pmint1707-en (date of access: 25.08.2026).
4. NewsChina Magazine. Fire Alarm: China's High-Rise Building Safety Regulations [Electronic resource]. — URL: http://www.newschinamag.com/newschina/articleDetail.do?article_id=8173&section_id=15&magazine_id=113 (date of access: 25.08.2026).
5. Xinhua. China Strengthens Fire Safety for High-Rise Buildings [Electronic resource]. — 2017. — URL: http://www.xinhuanet.com/english/2017-12/21/c_136843274.htm (date of access: 25.08.2026).
6. Ma J., Song W.G., Tian W., Lo S.M., Liao G.X. Experimental Study on an Ultra High-Rise Building Evacuation in China // Safety Science. — 2012. — Vol. 50, No. 8. — P. 1665–1674.
7. Digital Twin for 3D Interactive Building Operations: Integrating BIM, IoT-Enabled Building Automation Systems, AI, and Mixed Reality // Automation in Construction [Electronic resource]. — 2025. — URL: https://www.sciencedirect.com/science/article/abs/pii/S0926580525003176 (date of access: 25.08.2026).
8. Eneyew D.D., Capretz M.A.M., Bitsuamlak G.T. Toward Smart-Building Digital Twins: BIM and IoT Data Integration // IEEE Access. — 2022. — Vol. 10. — P. 130487–130506.
9. Jiang Y. Intelligent Building Construction Management Based on BIM Digital Twin // Mobile Information Systems. — 2021. — Art. 4979249.
10. Liu Y., Hong S., Jiang F. Application of BIM+IoT Technology in the Design and Operation and Maintenance Stages of Smart Buildings // Journal of Computational Methods in Sciences and Engineering. — 2023.
11. Policies, Applications, Barriers and Future Trends of Building Information Modeling Technology for Building Sustainability and Informatization in China // Journal of Building Engineering [Electronic resource]. — 2022. — URL: https://www.sciencedirect.com/science/article/pii/S235248472200854X (date of access: 25.08.2026).
12. Thinking from Barriers to the BIM-Based Building Operational Phase — A Case Study in China [Electronic resource]. — URL: https://www.researchgate.net/publication/359857086 (date of access: 25.08.2026).
13. Integration of Building Information Modeling (BIM) and Big Data in China: Recent Application and Future Perspective // Buildings. — 2023. — Vol. 13, No. 10. — Art. 2435.
14. Liu H., Zhang R., Zhang H., Jiang H., Ju Q. Identification and Analysis of Key Barriers of BIM Application for Small- and Medium-Sized Fire Protection Enterprises // Advances in Civil Engineering. — 2022. — Art. 9240224.
15. Asia Times. Risks Remain Months After China's Tallest Skyscraper Passed Fire Safety Inspection [Electronic resource]. — URL: https://asiatimes.com/2018/10/risks-remain-months-after-chinas-tallest-skyscraper-passed-fire-safety-inspection/ (date of access: 25.08.2026).
16. Fire Safety Assessment of Super Tall Buildings: A Case Study on Shanghai Tower [Electronic resource]. — URL: https://www.researchgate.net/publication/282533683 (date of access: 22.09.2026).
17. Internet of Things (IoT) Market Size, Share & Industry Analysis [Electronic resource] // Fortune Business Insights. — 2025. — URL: https://www.fortunebusinessinsights.com/industry-reports/internet-of-things-iot-market-100307 (date of access: 22.09.2026).
18. China Internet of Things (IoT) Market Size, Share, Trends [Electronic resource] // MarketsandMarkets. — 2025. — URL: https://www.marketsandmarkets.com/Market-Reports/geography/internet-of-things-market/China (date of access: 22.09.2026).
19. Digital Twin Market Size & Share — Forecast Report [Electronic resource] // GMI Insights. — 2025. — URL: https://www.gminsights.com/industry-analysis/digital-twin-market (date of access: 22.09.2026).
20. China Smart Building Market — Size & Growth [Electronic resource] // Mordor Intelligence. — 2025. — URL: https://www.mordorintelligence.com/industry-reports/china-smart-building-market (date of access: 22.09.2026).
21. Artificial Intelligence (AI) in Construction Market Size [Electronic resource] // Precedence Research. — 2025. — URL: https://www.precedenceresearch.com/artificial-intelligence-in-construction-market (date of access: 22.09.2026).
22. Number of Connected IoT Devices Growing [Electronic resource] // IoT Analytics. — 2025. — URL: https://iot-analytics.com/number-connected-iot-devices/ (date of access: 22.09.2026).
23. Global BIM Adoption: A 2025 Outlook [Electronic resource] // Pinnacle Infotech. — 2025. — URL: https://pinnacleinfotech.com/global-bim-adoption/ (date of access: 22.09.2026).