Construction of Intelligent Building Design System Based on BIM and AI

Zhang, Jianfeng; Yechao, Jiang; Liu, Fang

doi:10.1109/icsgea51094.2020.00066

Cited by 4 publications

(4 citation statements)

References 7 publications

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“…The results are contrasted with what was shown by previous reviews, such as references [36,37,84], showing that there is a growing trend of research on the subject. This review provides the classification of the articles found by PMI knowledge areas (Project Management Institute 2017), finding that the greatest interest of the academic community is in cost management [53,58,64,74,79], quality management [12,73,77], time management [57,60,62,82], and, finally, scope management [11,81,87]. There is a knowledge gap in the use of emerging technologies (big data, data science, and artificial intelligence) in the areas of stakeholder management, communications, and human resources, at least in the construction and civil works sector.…”

Section: Discussionmentioning

confidence: 99%

“…Project cost management (22 records) mainly features the use of emerging technologies to perform budget forecasting and projection [77,79,85], as well as the early detection of anomalies in financial and operational data [8,53,58]. Data science is also used to simulate different scenarios and assess the impact of decisions on the final project budget [64,68,74].…”

Section: Question 2-what Are the Most-used Methodological Routes And ...mentioning

confidence: 99%

“…About the analysis of quality management (19 articles) highlights the use of big data and data science as a strategy to collect data related to project quality to identify trends and areas for improvement. This involves the prediction, through artificial intelligence, of potential problems through analyzing historical and current data [4,10,12,77]. This allows taking preventive measures to avoid errors.…”

Section: Question 2-what Are the Most-used Methodological Routes And ...mentioning

confidence: 99%

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Big Data, Data Science, and Artificial Intelligence for Project Management in the Architecture, Engineering, and Construction Industry: A Systematic Review

Zabala-Vargas,

Jaimes-Quintanilla,

Jimenez-Barrera

2023

Buildings

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The high volume of information produced by project management and its quality have become a challenge for organizations. Due to this, emerging technologies such as big data, data science and artificial intelligence (ETs) have become an alternative in the project life cycle. This article aims to present a systematic review of the literature on the use of these technologies in the architecture, engineering, and construction industry. A methodology of collection, purification, evaluation, bibliometric, and categorical analysis was used. A total of 224 articles were found, which, using the PRISMA method, finally generated 57 articles. The categorical analysis focused on determining the technologies used, the most common methodologies, the most-discussed project management areas, and the contributions to the AEC industry. The review found that there is international leadership by China, the United States, and the United Kingdom. The type of research most used is quantitative. The areas of knowledge where ETs are most used are Cost, Quality, Time, and Scope. Finally, among the most outstanding contributions are as follows: prediction in the development of projects, the identification of critical factors, the detailed identification of risks, the optimization of planning, the automation of tasks, and the increase in efficiency; all of these to facilitate management decision making.

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Section: Discussionmentioning

confidence: 99%

Section: Question 2-what Are the Most-used Methodological Routes And ...mentioning

confidence: 99%

Section: Question 2-what Are the Most-used Methodological Routes And ...mentioning

confidence: 99%

See 1 more Smart Citation

Big Data, Data Science, and Artificial Intelligence for Project Management in the Architecture, Engineering, and Construction Industry: A Systematic Review

Zabala-Vargas,

Jaimes-Quintanilla,

Jimenez-Barrera

2023

Buildings

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“…The authors validated the system by using a BIM model of an 11-story residential tower. Jianfeng et al (2020) optimized the function and application process of an intelligent building through the combination of BIM and AI. By applying the scheme and implementation strategy to a pilot project, they showed that the system directly reduces workload and improves design efficiency and quality.…”

Section: Literature Reviewmentioning

confidence: 99%

Building information modeling as a tool for prevention of design defects

Koo

O’Connor

2021

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Purpose In recent decades, professionals in the architecture, engineering and construction industry have come to recognize building information modeling (BIM) as one of the most powerful technologies available to ensure successful project outcomes. The purpose of this paper is to explore the benefits of BIM on design defect prevention during the design phase of building projects. Design/methodology/approach The authors qualitatively analyzed 160 design defect leading indicators (LIs) to identify key themes for design defect prevention. Then, by matching appropriate BIM functionalities to each key LI theme, they identified BIM-supported key LI themes. Findings The result of this paper served as the foundation of a BIM-based key design processes framework, which identifies the necessary data, project parties, actions and applicable BIM functions for preventing particular design defects. In addition, the authors found that BIM implementation can benefit 71.2% of the LIs of the design defects associated with problematic deliverables. Originality/value This study establishes the current state of BIM use for design defect prevention and also gives practitioners precisely targeted guidelines for using BIM functions during the design phase for better quality management.

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