AEC Industry Research Articles

Earthwork Network Architecture (ENA): Research for Earthwork Quantity Estimation Method Improvement with Large Language Model

Accurate earthwork quantity estimation is essential for effective project planning and cost management in the Architecture, Engineering, and Construction (AEC) industry. Traditional methods for quantity takeoff are often time-consuming and susceptible to human error, particularly when working with unstructured datasets such as CAD drawings. This study introduces the Earthwork Network Architecture (ENA), a novel deep learning framework that incorporates Large Language Models (LLMs), Multi-Layer Perceptron (MLP), Long Short-Term Memory (LSTM) networks, and Transformers to automate and enhance the accuracy of earthwork quantity estimation. We assume that if LLMs can be trained effectively using such unstructured construction dataset, the effects such as improved accuracy and the challenges of LLMs can be clearly examined. Among the architectures tested, the LLM-based ENA demonstrated superior performance, achieving faster convergence, greater loss reduction, and higher classification accuracy, with a Quantity Takeoff Classification accuracy of 97.17%. However, the LLMs required significantly more computational resources compared with other models. These findings suggest that LLMs, typically used in natural language processing, can be effectively adapted for complex AEC datasets. This study lays the groundwork for future AI-driven solutions in the AEC industry, underscoring the potential of LLMs and Transformers to automate the quantity takeoff process and manage multimodal data in construction projects.

Evaluation of Instructor Capability: Perspective from Building Information Modeling Competition Students in Mainland China

Building information modelling (BIM) technology, which has experienced rapid development, has become the focus of digital education learning in architecture, engineering, and construction (AEC) related disciplines. However, BIM education is still confronted with the disconnection between theoretical education and engineering practice. In mainland China, BIM competitions are an important digital platform for higher education practice teaching. As the organizer and leader of student participants, BIM instructors, especially their BIM capability, have an important impact on digital education. Previous research on BIM capability did not involve the field of BIM education, and the existing BIM capability framework is not entirely applicable to evaluating the BIM capability of instructors. Semi-structured interviews based on grounded theory (GT) and structural equation modeling (SEM) were used to construct a five-dimensional model containing 23 capability indicators. The research findings highlighted the multi-dimensional nature of BIM capability for instructors and indicated that personnel capability was the most important for instructors, while process capability was considered the most dispensable. This is significantly different from the emphasis on technical and process capability in BIM capability research in the traditional AEC industry. It was also found that students from different levels of universities and different educational backgrounds had different demands for the BIM capability of instructors. The results of this study will help universities select excellent instructors, improve the quality of BIM education in universities, and cultivate more outstanding BIM talents for the development of BIM in the AEC industry, thereby promoting the digital practice of BIM education in universities.

Transdisciplinary education for reducing environmental impact of AEC industry

The Architecture, Engineering, and Construction (AEC) industry plays a crucial role in shaping the built environment but contributes significantly to environmental impact, accounting for nearly 40% of global energy-related carbon dioxide emissions. An interdisciplinary systematic literature review (SLR) explores how transdisciplinary education (TDE) can be integrated into AEC curricula to address environmental sustainability challenges. TDE facilitates students’ understanding of the environmental impact (EI) of their design projects and equips them with the knowledge and skills to develop sustainable solutions. This review examines various pedagogical models, including problem-based learning, to evaluate their effectiveness in fostering TDE for reducing EI in the AEC sector. Findings from the literature are synthesized to present a framework aligned with sustainable development goals (SDGs) that promotes sustainability in AEC education. The review aims to inform future research and curriculum development, advancing the role of education in equipping future professionals to mitigate environmental impacts in the AEC industry.

Factors That Facilitated the Development of Blockchain Technology in the AEC Industry: Study Based on System Dynamics

Factors That Facilitated the Development of Blockchain Technology in the AEC Industry: Study Based on System Dynamics

A Systematic Review of the Digital Twin Technology in Buildings, Landscape and Urban Environment from 2018 to 2024

Digital Twin (DT) technologies have demonstrated a positive impact across various stages of the Architecture, Engineering, and Construction (AEC) industry. Nevertheless, the industry has been slow to undergo digital transformation. The paper utilizes the Systematic Literature Review (SLR) approach to study a total of 842 papers on the application of DT in buildings, landscapes, and urban environments (BLU) from 2018 to 2024. Based on the research results, suggestions have been made for future research and practical directions. Meanwhile, it provides assistance to BLU’s designers, constructors, managers, and policymakers in establishing their understanding of the digital transformation of the AEC industry. The existing relevant research can be mainly divided into three categories: case study, framework study, and technology study. Compared with the buildings and urban environment industries, the number and depth of research in the landscape industry are relatively low. Through in-depth analysis of BLU projects, three research trends in the future are determined: (1) research and application of DT framework in the design and planning stage; (2) development of design tools and basic theory based on DT model; (3) application and exploration of DT technology in the landscape industry.

Exploring Alternative Revenue Models for Construction Consulting Firms in the Digital Era

The AEC industry, including construction consulting, is experiencing digitalization through technologies like Building Information Modeling (BIM), impacting firms’ business models. The traditional hourly-based model does not align with shortened project timelines driven by digitalization, design automation, and product-based approaches. This study uses a case study approach and explores and evaluates four selected alternative revenue models (freemium, subscription, out-come-based, and performance-based) for value creation using a digital tool developed by the consulting firm. The freemium model enhances market reach but requires a high conversion rate. The subscription model offers steady recurring revenue and supports client relationships. Out-come-based and performance-based models link payments to client outcomes and performance metrics, fostering efficiency and competitive advantages. The study identified multiple target markets for this tool and emphasized the importance of a portfolio revenue model to meet specific client needs in the digital era. Implementing alternative revenue models aids return on investments and avoids the digitalization paradox. Construction consulting firms must adeptly manage these models’ complexities to address diverse client needs and leverage digital transformation opportunities.

Optimizing the Utilization of Generative Artificial Intelligence (AI) in the AEC Industry: ChatGPT Prompt Engineering and Design

Generative Artificial Intelligence (AI) holds significant potential for revolutionizing the Architecture, Engineering, and Construction (AEC) industry by automating complex tasks such as construction scheduling, hazard recognition, resource leveling, information retrieval from BIM, etc. However, realizing this potential requires a strategic approach to ensure effective utilization and maximum benefit. This paper presents guidelines for prompt design and engineering to elicit desired responses from ChatGPT, a Generative AI tool, in AEC applications. Key steps include understanding user intent, leveraging model capabilities, and optimizing prompt structures. By following these guidelines, stakeholders in the AEC industry can harness the power of Generative AI to improve construction scheduling processes, increase project efficiency, and ultimately drive innovation and growth in the industry. Several illustrative examples on construction scheduling and hazard recognition are provided to demonstrate the methodology proposed in this research. It is concluded that Generative AI, when effectively utilized, significantly enhances project scheduling and hazard recognition capability in the AEC industry with minimal error.

VEIDEA: A Comprehensive Framework for Implementing Building Information Modeling-Based Value Engineering Within a Common Data Environment in Construction Projects

The Architecture, Engineering, and Construction (AEC) industry faces significant global challenges, including frequent project delays, budget overruns, and inadequate stakeholder collaboration. To address these issues, Value Engineering (VE) and Building Information Modeling (BIM) have been increasingly used in large-scale, complex construction projects. Although many studies highlight the benefits of integrating VE with BIM, its full practical potential has not yet been realized. This study aims to investigate the integration of VE and BIM within a Common Data Environment (CDE) to improve decision making and project outcomes. A comprehensive framework was developed, consisting of four interconnected modules: (1) Creating the CDE, (2) Developing the BIM Model, (3) Implementing Value Engineering, and (4) Conducting a Value Engineering Study. Central to this framework is the introduction of the VEIDEA” data bank, a structured system based on the OmniClass classification, which stores and organizes VE ideas. Additionally, the framework incorporates the Analytical Hierarchy Process (AHP) to automate the evaluation phase, assisting designers and VE teams in making data-driven decisions on design alternatives. Empirical results from a case study of an office building show significant cost savings, with a 20% reduction in reinforced concrete (RC) slab costs and a 39% reduction in flooring material costs. These findings demonstrate the potential for integrating VE and BIM to enhance cost-effectiveness and overall project performance. This study offers a novel approach to optimizing project collaboration, decision making, and efficiency in the AEC industry.

Impacts of human resources management strategies and practices on workers performance in construction industry: a review

Human resource management (HRM) plays a vital role in the growth and sustainability of companies and in achieving company objectives, as HRM relates to the workers’ practices and their functional roles. The main objective of this paper is to identify the HRM strategies, practices and their impact on worker’s performance in the Architecture, Engineering, and Construction (AEC) Industry. The method which was used in this study was based on three stages. After the completion of the database and web engine search, the total number of sources found were 149. Next, the sources’ titles and abstracts were reviewed and those marked as relevant to the review were chosen to be retrieved and thoroughly reviewed. The sources were chosen based on the following inclusion criteria: (a) the sources implied in HRM strategies in the AEC industry, (b) the sources released between 2010 and 2023, (c) the online sources, and (d) the English-language sources. Also, the selected sources are reviewed to extract the factors using the content analysis method which is a thorough and systematic study of the contents of a specific body of material. In addition, content analysis is carried out to extract practices of HRM strategies and their impact on worker performance. This can be followed up and observed through the figures and tables that come later. As a final result, which concludes the outputs of the previous stages which results in a first-round total of 31 HRM strategies practice but in the second-round result of reaching 39 different sources from 149 related sources. After that, discussing the most popular between them based on the appearance of it in the sources which reviewed beside that, the impact of it on worker’s performance were viewed in the AEC industry. Based on that, it was found the following 5 categories of strategies: (1) Human Resources Planning; (2) Polarization and Recruitment; (3) Training and Development; (4) Human Resources Following-up; (5) Career Planning. At the same time the most popular practices are based on appearance in sources: In terms of Human Resources Planning Strategy, “The company’s management analyses the functions accurately”. In Polarization and Recruitment Strategy, “The company’s internal resources are the best to provide its human resource needs” and “Selection and recruitment policies are in line with the company’s current and future needs”. In Training and Development of Human Resources Strategy, “The company evaluates the results of development and training programs to achieve the purpose of feedback”. In Human Resources Following-up Strategy, “There is a fair incentive system in the company”. In Career Planning Strategy, “There is a clear description of the relationship of workers to each other”. Finally, human resource management strategies and practices are one of the major players in the AEC industry, which is evidenced by its impact on the performance of workers. First published online 22 October 2024

Generative AI Applications in Architecture, Engineering, and Construction: Trends, Implications for Practice, Education & Imperatives for Upskilling—A Review

This study investigates the current landscape of generative AI and LLM applications in architecture, engineering, and construction (AEC), focusing on trends, practical implications, educational strategies, and imperatives for upskilling. Employing a six-stage systematic review sourced from Google Scholar, Scopus and Web of Science, 120 papers were analyzed to provide a comprehensive understanding of the role of these technologies in shaping the future of the AEC industry. By addressing these objectives, the research contributes to enhancing knowledge about the potential impacts of generative AI and LLMs on the AEC industry and provides insights into strategies for leveraging these technologies effectively. This study underscores the transformative impact of AI and advanced technologies on the AEC sector and education. By enhancing learning experiences and optimizing construction processes, AI fosters personalized education and efficient project management. The study’s significance lies in its identification of necessary skills and competencies for professionals, ensuring effective AI integration. Implications include the need for continuous professional development, formal education, and practical training to leverage AI’s potential fully. This paves the way for sustainable, intelligent infrastructure and accessible, adaptive learning environments, driving innovation and efficiency in both fields.

Efficient management and compliance check of HVAC information in the building design phase using Semantic Web technologies

Several OWL ontologies have been developed for the AEC industry to manage domain-specific information, yet they often overlook the domain of building services and HVAC components. The Flow Systems Ontology was recently proposed to address this need, but it does not include HVAC components’ size and capacity-related properties. Also, despite their strengths in representing domain-specific knowledge, ontologies cannot efficiently identify poor data quality in BIM models. A four-fold contribution is made in this research paper to define and improve the data quality of HVAC information by (1) extending the existing Flow Systems Ontology, (2) proposing the new Flow Properties Ontology, (3) proposing an HVAC rule set for compliance checking, and (4), moreover, we use Semantic Web technologies to demonstrate the benefits of efficient HVAC data management when sizing components. The demonstration case shows that we can represent the data model in a distributed way, validate it using 36 SHACL shapes and use SPARQL to determine the pressure and flow rate of fans and pumps.

Circular Economy in Architecture: Reducing Waste and Promoting Reuse in Construction

This paper explores the concept of circular economy within the Architecture, Engineering, and Construction (AEC) industries. It examines the evolution of the circular economy framework from the traditional 4R model to more expansive 9R and 10R iterations. The study investigates the challenges and opportunities in implementing circular economy principles in Nigeria's AEC sector, considering its significant contribution to the country's GDP and potential for sustainable economic development. By analysing the relationship between construction activities and economic growth, this research aims to provide insights into the transformative potential of circular economy practices in AEC industry and its broader implications for national development.

Big data analytics in the AEC industry: scientometric review and synthesis of research activities

Big data analytics in the AEC industry: scientometric review and synthesis of research activities

Digital Twin Technology in Built Environment: A Review of Applications, Capabilities and Challenges

Digital Twin (DT) technology is a pivotal innovation within the built environment industry, facilitating digital transformation through advanced data integration and analytics. DTs have demonstrated significant benefits in building design, construction, and asset management, including optimising lifecycle energy use, enhancing operational efficiency, enabling predictive maintenance, and improving user adaptability. By integrating real-time data from IoT sensors with advanced analytics, DTs provide dynamic and actionable insights for better decision-making and resource management. Despite these promising benefits, several challenges impede the widespread adoption of DT technology, such as technological integration, data consistency, organisational adaptation, and cybersecurity concerns. Addressing these challenges requires interdisciplinary collaboration, standardisation of data formats, and the development of universal design and development platforms for DTs. This paper provides a comprehensive review of DT definitions, applications, capabilities, and challenges within the Architecture, Engineering, and Construction (AEC) industries. This paper provides important insights for researchers and professionals, helping them gain a more comprehensive and detailed view of DT. The findings also demonstrate the significant impact that DTs can have on this sector, contributing to advancing DT implementations and promoting sustainable and efficient building management practices. Ultimately, DT technology is set to revolutionise the AEC industries by enabling autonomous, data-driven decision-making and optimising building operations for enhanced productivity and performance.

Exploring the barriers and enablers of industrial solutions in renovation projects: a mixed-methods study in the finnish AEC industry

Offsite construction is a major approach to promote industrialisation in construction. However, implementation of prevailing industrial solutions is often less adequate and unsatisfactory, especially in renovation projects. Thus, the overall objective of this study is to understand the reasons behind the poor performance in implementation of the industrial solutions. The specific objectives include identifying the prominent barriers and enablers of prefabricated products in renovation projects. This study employed exploratory sequential mixed method. The qualitative data were gathered via semi-structured interviews to collect experiences and perception of experts related to industrial solutions. This was followed by quantitative data collection via questionnaire survey using a seven-point Likert scale. The major barriers and enablers of industrial solutions in renovation projects have been ranked in this study. The findings reveal that immutability of heritage buildings, the tolerances of old buildings and insufficient spaces to ensure construction work ranked the top three barriers for implementing industrial solutions in renovation projects. Moreover, the study identifies the most significant enablers including shorter project schedules, quality improvement and work safety improvement. The novelty of the research lies in the comprehensive presentation of the barriers and enablers of industrial solutions in the renovation project context. Policymakers, designers, and contractors can utilize these findings as guiding principles to enhance decision-making processes and create viable solutions for the obstacles encountered in renovation projects. This study further represents a vital step towards the efficient and effective implementation of industrial solutions in renovation projects, resulting in more sustainable and cost-effective outcomes.

Gender Disparity and Self-Presentation on Social Media among AEC Industry Leaders

Gender Disparity and Self-Presentation on Social Media among AEC Industry Leaders

Explorando o potencial da gestão ágil na indústria da construção: uma revisão sistemática da literatura

To carry out more efficient and effective projects, those involved in project management in the construction industry seek alternatives to preserve projects' profit and value, manage change, improve communication with the client, and anticipate risks in the face of unforeseen events. In the face of uncertain and ever-changing scenarios, the Agile methodology has emerged to help the Architecture, Engineering, and Construction (AEC) sector face management challenges. This paper investigates the applicability of Agile methodology in construction project management. Insights from a state-of-the-art were mapped based on a systematic literature review and bibliometric analysis of 26 articles selected using criteria listed in the research protocol. A quantitative analysis of the distribution by year and country of publication and a qualitative analysis of the content were conducted, using codes managed by Atlas.ti software. The characterization of Agile management and the Scrum framework, the problems in construction projects, the application in the AEC industry and the conceptualization of the hybrid approach were analyzed. The authors discussed the main points surrounding the research and validated the benefits Agile adds to construction project management based on the literature.

BIM-Based Strategies for the Revitalization and Automated Management of Buildings: A Case Study

This study explores the transformative potential of integrating Building Information Modeling (BIM) and Generative Design methodologies in heritage conservation and building management. By utilizing BIM, detailed architectural, structural, and MEP models were created, facilitating precise design and effective stakeholder collaboration. Generative Design enabled the exploration of multiple design solutions, optimizing spatial layouts and structural integrity. The project also integrated automated management systems and IoT sensors to enhance real-time monitoring, energy efficiency, and user comfort through the development of a digital twin. Despite encountering challenges such as technical complexities and budget constraints, the project successfully preserved the cinema’s historical essence while incorporating modern functionalities. The findings highlight the contributions of BIM and Generative Design to the AEC industry, emphasizing their role in improving design accuracy, operational efficiency, and sustainability. This research provides valuable insights for future projects in heritage conservation, offering a blueprint for balancing historical preservation with contemporary needs. The revitalization of the “Ex Cinema Santa Barbara” in Paternò exemplifies these advancements, demonstrating how these technologies can restore and modernize culturally significant historical buildings effectively.

Mapping the global knowledge landscape of digital transformation in the AEC industry: a scientometric analysis

PurposeIn recent decades, interest in digital transformation (DX) within the architecture, engineering, and construction (AEC) industry has significantly increased. Despite the existence of several literature reviews on DX research, there remains a notable lack of systematic quantitative and visual investigations into the structure and evolution of this field. This study aims to address this gap by uncovering the current state, key topics, keywords, and emerging areas in DX research specific to the AEC sector.Design/methodology/approachEmploying a holistic review approach, this study undertook a thorough and systematic analysis of the literature concerning DX in the AEC industry. Utilizing a bibliometric analysis, 3,656 papers were retrieved from the Web of Science spanning the years 1990–2023. A scientometric analysis was then applied to these publications to discern patterns in publication years, geographical distribution, journals, authors, citations, and keywords.FindingsThe findings identify China, the USA, and England as the leading contributors in the field of DX in AEC sector. Prominent keywords include “building information modeling”, “design”, “system”, “framework”, “adoption”, “model”, “safety”, “internet of things”, and “innovation”. Emerging areas of interest are “deep learning”, “embodied energy”, and “machine learning”. A cluster analysis of keywords reveals key research themes such as “deep learning”, “smart buildings”, “virtual reality”, “augmented reality”, “smart contracts”, “sustainable development”, “building information modeling”, “big data”, and “3D printing”.Originality/valueThis study is among the earliest to provide a comprehensive scientometric mapping of the DX field. The findings presented here have significant implications for both industry practitioners and the scientific community, offering a thorough overview of the current state, prominent keywords, topics, and emerging areas within DX in the AEC industry. Additionally, this research serves as an invaluable reference and guideline for scholars interested in this subject.

Digital Evolution in AEC industry: Bridging BIM, Building Codes, and Future Technologies

Abstract In recent decades, the Architecture, Engineering, and Construction (AEC) industry has witnessed profound shifts driven by digital technologies. Central to this transformation is Building Information Modelling (BIM), which has offered a holistic approach to design, analysis, and documentation, yielding benefits in visualization, collaboration, simulation, and life-cycle management. However, the industry’s intricate regulatory landscape, primarily rooted in traditional text-heavy building codes, has lagged in digital adaptability. This paper explores the imperative to transition building codes and regulations into machine-friendly formats, capitalizing on structured databases, semantic annotations, and (Application Programming Interface) API-driven access. Such a transformation facilitates streamlined (Artificial Intelligence) AI-based compliance checks and augments the capabilities of BIM systems. Furthermore, the research delves into the convergence of BIM with other burgeoning technologies. Extended Reality (XR) promise enriched visualization and on-site integration. AI introduces automated analytics, optimization, and predictive facilities management. The integration of Internet of Things (IoT) proposes a real-time feedback loop into BIM, evolving towards dynamic Digital Twins. The discussion also touches upon the potential of XR technology use for enhanced workforce performance and quality control on the site. In conclusion, the AEC industry stands on the edge of a digital evolution, demanding integrated approaches to fully harness the potential of these technologies, ensuring not only efficient construction practices but also enhancing building safety and sustainability.