Search Results (588)

Background: Urban disasters expose persistent gaps in the operational picture and timely decision-making for response teams, which require user-centred systems that connect analysis to action. This study proposes and formatively validates an integrated framework that couples digital twins and augmented reality for humanitarian logistics. Methods: A mixed methods design combined a structured literature synthesis with a practitioner survey across architecture, engineering, planning, BIM, and construction to assess perceived value and adoption conditions. Results: Findings indicate that practitioners prioritised digital twins for enhancing situational awareness (71.4%) and augmented reality for providing real-time information overlays (64.3%). A majority judged that integrating these technologies would yield substantial improvements in disaster response (67.9%), despite implementation challenges. Conclusions: The framework links live state estimation and short-horizon simulation to role-specific, in-scene AR cues, with the aim of reducing decision latency and improving coordination. Adoption depends primarily on human and organisational factors, including user accessibility, preparation needs, and clear governance. These results suggest a viable pathway to operationalise the bridge between analysis and field action and outline priorities for pilot evaluation. Full article

This study presents a novel integrative review of 329 review articles on sustainable buildings from 2015 to 2025, combining quantitative bibliometrics with qualitative insights to map the field’s evolution and pinpoint critical future pathways. Seven core research themes were identified in this study: (1) material and advanced construction technologies, (2) energy efficiency and renewable energy systems, (3) digitalization and smart technologies, (4) policy, standards, and certification, (5) sustainable design and optimization, (6) stakeholder and socio-economic factors, (7) other (cross-cutting) topics. Key findings reveal a surge in publications post-2020, driven by global net-zero commitments, with China, Australia, and Hong Kong leading research output. Innovations in low-carbon materials (e.g., hemp concrete, geopolymers), artificial intelligent (AI)-driven energy optimization, and digital tools (e.g., building information modeling (BIM), internet of things (IoT)) dominate recent advancements. However, challenges persist, including policy fragmentation, scalability barriers for sustainable materials, and socio-economic disparities in green building adoption. The study proposes a unique future research framework emphasizing nanotechnology-enhanced materials, interpretable AI models, harmonized global standards, and inclusive stakeholder engagement. This review provides actionable recommendations to bridge gaps between technological innovation, policy frameworks, and practical implementation in sustainable construction. Full article

Water pumping stations are essential components of national water infrastructure, yet their construction involves complex, high-risk processes, and traditional risk management approaches often show significant limitations in practice. To address this challenge, this study proposes a Building Information Modeling (BIM)-based approach that integrates structured risk information into an interactive nD BIM environment. We first developed an extended Risk Breakdown Matrix (eRBM), which systematically organizes risk factors, assessment levels, and causal relationships. This is linked to the BIM model through a customized BIM–risk integration framework. Subsequently, the framework is further implemented and quantitatively validated via a Navisworks plug-in. The system incorporates three core components: (1) a structured risk information model, (2) a visualization mechanism for dynamic, spatiotemporal risk representation and (3) risk influence path analysis using the Decision-Making Trial and Evaluation Laboratory–Interpretive Structural Modeling (DEMATEL–ISM) method. The plug-in allows users to access risk information on demand and monitor its evolution over time and space during the construction process. This study makes contributions by innovatively integrating risk information with BIM and developing a data-driven visualization tool for decision support, thereby enhancing project managers’ ability to anticipate, prioritize, and mitigate risks throughout the construction lifecycle of water pumping station projects. Full article

Given the construction industry’s significant contribution of approximately 39% of global CO₂ emissions, implementing effective carbon reduction strategies is becoming increasingly critical. In this context, Internet of Things (IoT) technologies present promising solutions for monitoring and reducing emissions. However, there is a lack of comprehensive understanding regarding specific IoT applications, implementation barriers, and opportunities for carbon reduction in construction practices. This study investigates the role of IoT in reducing carbon emissions in the construction industry. Following PRISMA guidelines, this study analyzed bibliometric data from Scopus and Web of Science databases using VOSviewer for science mapping visualization. Content analysis was conducted on 17 carefully selected articles to identify key research topics and applications. The analysis identified four mainstream application areas: (1) IoT-based smart monitoring systems for carbon emissions, (2) energy efficiency and management applications, (3) sustainable construction implementation frameworks, and (4) smart cities and other built environment applications. Key findings highlight growing research interest in IoT applications for sustainable construction, with China, the United States, and the United Kingdom leading collaborative efforts. Despite demonstrated carbon reduction potential, significant implementation barriers exist, including technical limitations, organizational resistance, skill gaps, and economic constraints. Key opportunities include Artificial Intelligence (AI) integration, Building information modeling (BIM)-IoT synergies, energy prosumer models, and standardization frameworks. This study provides the first focused review of IoT applications specifically targeting carbon reduction in construction, highlighting a critical technology-practice gap where organizational factors frequently outweigh technological barriers. A proposed socio-technical integration framework in this study bridges technical and organizational elements to overcome adoption barriers. Full article

Several studies have proven the impact of the quality of indoor environmental conditions on human professional and cognitive performances. Additionally, building energy efficiency and indoor comfort have attracted increasing interest, encouraging the implementation of advanced digital technologies and platforms for a more efficient management of buildings. In this context, this study proposes a new framework for an effective BIM-IoT integration leading to a nearly Digital Twin (DT) relying on a BIM model equipped with regularly-generated IEQ reports summarizing statistics from real-time collected data to support facility managers’ decision-making. Despite the relevant literature on the subject, the proposed methodology introduces some novelties, as monthly results of Indoor Air Quality (IAQ) and thermal comfort evaluation are provided by open HTML reports automatically generated through a Python 3.10 code from sensor data. These reports are easily readable without needing any external platform to be visualized and are directly accessible through BIM models. The proposed methodology has been validated on a pilot case study, thus proving its efficiency, effectiveness, and robustness in terms of automation level, interoperability, adaptability, reliability, accuracy in data visualization, and management. The study shows promising results but also some issues that could be addressed through further development of the research. Full article

This paper presents a BIM-oriented methodological framework for integrating air quality monitoring systems based on IoT sensors into building and infrastructure projects. A set of low-cost environmental sensors capable of measuring PM1, PM2.5, PM10, temperature, and humidity was deployed in a real residential setting to illustrate the proposed approach. To enable semantic integration within BIM workflows, a structured classification system, AllBIMclass, was developed. It provides dedicated hierarchical codes for environmental sensors, defined by monitored parameters, installation location (indoor, outdoor, or mixed), power supply, and data handling mode. The pilot experience demonstrated how sensors can be registered, classified, and linked to BIM models, supporting data visualisation and basic management tasks. AllBIMclass is available in Revit 2026 (version 26.6.4.409, build 20250227_1515, 64-bit) (TXT) and Archicad 28 (version 28.0.0, build 3001, x86–64-bit) (XML) formats and is fully compatible with IFC schemas. Although the framework has not yet been applied to large-scale projects, its components are technically operational and ready for implementation. This research contributes to bridging the gap between environmental monitoring and digital construction workflows, paving the way for integration into digital twins, smart buildings, and sustainable infrastructure systems. Full article

In recent years, the construction sector has experienced a significant technological transition, driven by the introduction of innovative digital tools and the evolution of the legislative environment. This article presents a Systematic Scoping Review conducted in accordance with the PRISMA-ScR guidelines, aiming to examine the role of Public Administration (PA) regarding the adoption of innovative technologies, such as Building Information Modelling (BIM) and Digital Twin (DT), to improve the management of construction and public procurement processes. The review analyses the state of the art in the implementation of digitalised procedures for project management in the construction phase, according to PA organisational purposes and national and international standard requirements. The data obtained was used to structure the analysis in order to provide a useful framework for understanding the level of convergence between the academic world and public administration in the use of digital technologies and their combined applications. The review results are organised in a thematic matrix classifying contributions according to key topics, building process phases, and operational aims. This approach highlights adopted strategies and emerging best practices, aiming to support both PAs and professionals in overcoming digitalisation challenges. A specific focus has been dedicated to the need for continuous training and legislative adaptation, which are essential for integrating digital technologies into building processes. The analysis and verification of the results of the systematic scoping review on the digitalisation process in the construction sector, conducted between academia and the public administration, is supported by a comparison with an Italian case study from the Emilia-Romagna region, which illustrates the specific application of the strategies identified in the digital management of public construction processes. Full article

As cities confront intensifying environmental challenges and increasing expectations for sustainable governance, extending Environmental, Social, and Governance (ESG) evaluation frameworks to the urban scale has become a pressing need. However, existing ESG systems are typically designed for corporate contexts, lacking city-specific indicators, integrated data representations, and reliable ESG information with high spatial and temporal resolution for informed decision-making. This study proposes a comprehensive ESG evaluation framework tailored to green cities, which consists of three core components: (1) The construction of a green-oriented ESG indicator system with an expert-informed weighting system; (2) the design of a GIS-BIM-IoT integrated ontology that semantically aligns spatial, infrastructure, and observational data with ESG dimensions; and (3) the implementation of a web-based data integration and visualization platform that dynamically aggregates and visualizes ESG insights. A case study involving a primary school and an air quality monitoring station in Hong Kong demonstrates the system’s capability to infer material recycling rates and pollution concentration scores using ontology-driven reasoning and RDF-based knowledge graphs. The results are rendered in an interactive 3D urban interface, supporting real-time, multi-scale ESG evaluation. This framework transforms ESG assessment from a static reporting tool into a strategic asset for transparent, adaptive, and evidence-based urban sustainability governance. Full article

Purpose: The construction industry is now experiencing a thorough transformation through digital technologies, especially with building information modeling (BIM). Despite significant BIM advantages, most construction projects suffer from low BIM performance due to the fragmented BIM use mode. To facilitate lifecycle-integrated BIM implementation, this study demonstrates that introducing BIM lifecycle service providers (BLSPs) is feasible and offers significant improvements in terms of BIM benefits. Hence, this study proposes a customized framework to select BLSPs. Approach: This study utilized both qualitative and quantitative methods. It first adopted semi-structured interviews as part of the qualitative method to deduce the initial criteria for BLSPs’ selection. 30 interviews were conducted iteratively with managers proficient and experienced in selecting BLSPs, through which 25 initial criteria were identified. Then, as the basis of the applied quantitative method, a questionnaire survey was used to evaluate these criteria by determining the critical ones, identifying the latent factor groupings, and assigning criteria weights. Subsequently, an assessment framework was established. Finally, the study was in favor of eight construction projects, highlighting the practicality and validity of the framework. Findings: The results depicted that project BIM service capability is a primary factor for BLSPs’ selection. Within this factor, several specialized criteria need to be considered, such as “boundary spanning competence of the BIM manager” and “BIM service plans with lifecycle cognition.” Meanwhile, “past innovative BIM service practices” and “BIM research and development (R&D)” that originate in corporate innovation capacity were emphasized when selecting BLSPs. Furthermore, for holistic assessment and recognizing the peculiarities of digital BIM service, the study found that criteria like “Privacy and security” and “Backup system” are required, which demonstrate BIM service reliability. Originality/value: This study expands on the conventional partner selection frameworks in the construction sector and thus defines and validates a tailored one for BLSPs’ selection. Moreover, drawing such a reference solution from the framework, the study enables the selection of appropriate BLSPs for clients. Full article

The increasing integration of digital technologies in the construction sector is transforming the processes of buildings design, management, and evaluation throughout their life cycle. Life Cycle Costing (LCC), Building Information Modeling (BIM), and openBIM standards play a key role in promoting economic and environmental sustainability. More recently, Artificial Intelligence (AI) has unlocked novel possibilities for data-driven decision-making and cost optimization. However, the integration of LCC, BIM, and AI is insufficiently explored in the current literature. This study presents a systematic literature review (SLR) aimed at analyzing two distinct lines of research, LCC–BIM and LCC–AI, and identifying underexplored opportunities for their future convergence. A dual-stream approach was adopted to analyze scientific contributions based on LCC–BIM and LCC–AI separately, using bibliometric analysis and the systematic screening of peer-reviewed articles from 2015 to 2025. The findings reveal that while LCC–BIM integration shows growing methodological maturity, AI-based applications are still in an early stage, with limited implementation in construction-specific contexts. The review identifies key challenges, including data fragmentation, a lack of interoperability, and limited standardization, as significant impediments to integrated digital workflows. By highlighting these gaps and proposing actionable future directions, the paper outlines future research directions focused on open data models, AI-enhanced cost estimation, and the development of interoperable frameworks to support sustainable and intelligent cost management in the Architecture, Engineering, and Construction (AEC) sector. Full article

This research conducts a systematic literature review of 189 peer-reviewed articles to explore integrating building information modelling (BIM) and offsite construction (OSC). It aims to identify emerging trends, methodologies, and technologies in BIM-OSC integration, focusing on construction stages, stakeholder roles, and BIM dimensions. The research highlights a growing interest in BIM-OSC, particularly in early construction stages, and emphasises 21 collaborative approaches and advanced technologies like artificial intelligence (AI), digital twins, the internet of things (IoT), blockchain, and 3D printing for sustainable development. Nine challenges identified include emerging technologies integration, standardised protocols, improved integration and interoperability of solutions, data management, costs, stakeholders, sustainability, geographical perspectives, and skills considerations. The findings offer a comprehensive roadmap for BIM-OSC implementation, contributing to construction innovation discourse and suggesting future research directions. This research advocates for the robust adoption of BIM and OSC to foster innovation and sustainability in the construction industry. Full article

A framework for rapid seismic vulnerability assessment and disaster management of urban buildings was developed, incorporating structural information from Building Information Models (BIM) integrated into a Geographic Information System (GIS). The Critical Seismic Wall Index (CSWI) was evaluated for 252 undamaged and damaged buildings and compared with their seismic performance analyses. The seismic vulnerability of these buildings was determined based on site-specific seismic hazard analysis and compared with each building’s CSWI. This study demonstrates the use of BIM within a GIS workflow to enable rapid wall index calculation. Building on previous research that identifies a Critical Seismic Wall Index (CSWI) of 0.0025 as an indicator of a building’s seismic vulnerability, it further proposes a CSWI threshold of 0.004 for buildings with structural irregularities, based on the analysis of the studied building. The implementation of the integrated BIM–GIS methodology could enable rapid risk and damage assessment, as demonstrated in the investigated case studies. This study is significant because it provides a model for quickly assessing the seismic vulnerability of buildings, supporting resilience planning and sustainability, particularly in earthquake-prone regions, by prioritizing seismic risk by identification of high-risk buildings for demolition and prioritization of retrofit. Full article

Digitalization in the construction industry has transformed efficiency and coordination, with Building Information Modeling (BIM) emerging as a central enabling technology. However, despite its potential, BIM usage during the implementation phase of Swedish construction projects remains limited. Using the Technology–Organization–Environment (TOE) framework, this study combines a systematic literature review with a quantitative survey of 220 professionals. The data were analyzed using descriptive statistics, correlation analysis, factor analysis, and ordinal logistic regression. The results show that technological and organizational barriers are present to a moderate extent, but they manifest as distinct and separate dimensions. In contrast, the most significant barriers to actual BIM adoption lie within the environmental domain. Specifically, the absence of clear external requirements, policies, and incentives is strongly and negatively associated with BIM implementation. The study concludes that although contractors demonstrate internal technical readiness, external systemic support is crucial for scaling up BIM in practice. These insights carry important implications for industry stakeholders and policymakers aiming to accelerate the digital transformation of the construction industry. Full article

Building fires are considered major disasters because of their significant effects on people, property, and the environment. This understanding has led to increased attention on developing preventive measures, particularly through the creation of effective methods for assessing fire risk. However, the effectiveness of these methods relies heavily on detailed physical and functional information of the building and data-driven decision-making. Building Information Modeling (BIM) has proven effective in representing structures, even in three dimensions. When integrated with Geographic Information Systems (GIS), it enhances spatial intelligence, leading to improved decision-making through robust multi-criteria approaches. Hence, this study develops a framework to assess fire risk in an indoor environment that deploys a BIM-based GIS and Multi-Criteria Decision-Making; this is specifically known as Technique for Order Preference by Similarity to Ideal Solution (TOPSIS). The developed framework consists of four steps: identifying fire risk parameters, calculating weights, conducting spatial fire risk assessments, and visualizing the results, where the developed concepts are tested and validated. According to the significant findings, the developed framework estimates that 18% of building rooms are at moderate risk, while the compared model identifies only 1%. This considerable difference could potentially arise from the detailed data structure of BIM and the spatial insights gained from GIS. By implementing the designed framework, key fire risk factors can be identified in three dimensions, accompanied by a comprehensive quantitative evaluation platform for fire risks within indoor environments. Full article

Parking space shortages are attributed to an increased density of vehicle presence in the urban context, necessitating the implementation of effective parking management strategies, especially in areas where facility expansion is constrained by limited land availability. Many parking facilities remain operationally inefficient and underutilized due to manual VP methods and having little access to parking resource utilization data. This study develops a DT-based SPMS integrating machine vision, data modeling, and DT technology to automate facility management operations. The system uses YOLOv7 for vehicle and License Plate Detection (LPD), and Deep Text Recognition–Scene Text Recognition (DTR-STR) for license plate recognition (LPR). The findings indicate an 89.89% accuracy for VP- and LPR-based occupancy tracking tasks, and 94.86% for vehicle detection or VD-based occupancy tracking. The system in the built environment comprises three features: (1) automated VP at parking entry and exit points, (2) occupancy monitoring through LPR, (3) Object Detection (OD) for occupancy tracking. The 3D BIM DT model in Autodesk Revit processes inference data from machine vision models to visualize parking activity. Full article