Application of Artificial Intelligence in Sustainable Building Design - Optimisation Methods

Gilner, Ewa; Gałuszka, Adam; Grychowski, Tomasz

doi:10.1109/mmar.2019.8864698

Cited by 7 publications

(6 citation statements)

References 13 publications

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“…By exploring the integration, benefits, limitations, application areas, and challenges, the study aims to bridge the gap between theoretical potential and practical implementation. The findings of the study will contribute to the existing knowledge base and provide valuable insights for practitioners and researchers to harness the full potential of AI in civil engineering, leading to more efficient, accurate, and sustainable civil engineering projects [12].…”

Section: -Study Problemmentioning

confidence: 92%

“…Classification: Classification algorithms, including decision trees, random forests, support vector machines (SVM), and neural networks, are used for categorizing data into different classes or categories. In civil engineering, classification models can be applied for soil classification, material identification, structural element recognition, and construction defect detection [12]. 3.…”

Section: Machine Learning Algorithms and Their Applicationsmentioning

confidence: 99%

“…Support Vector Machines (SVM): SVM is a supervised learning algorithm that is effective for both classification and regression tasks. In civil engineering, SVM can be used for soil classification, pavement condition assessment, fault detection in structures, and prediction of construction project delays or failures [12]. 6.…”

Section: Machine Learning Algorithms and Their Applicationsmentioning

confidence: 99%

“…Changes can be made effortlessly, and the impact of those changes can be visualized in real-time. This allows for faster design iterations, enabling engineers to explore multiple design alternatives, assess their feasibility, and optimize the design efficiently [12]. 4.…”

Section: Improved Accuracy and Efficiencymentioning

confidence: 99%

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The Role of Artificial Intelligence in Civil Engineering Applications and Programs

Alghurair,

Fahim

2023

Journal of Engineering Sciences and Information Technology

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The integration of artificial intelligence (AI) techniques in civil engineering programs and drawing techniques has the potential to revolutionize the industry. This study explores the benefits, challenges, and strategies for the effective utilization of AI in civil engineering. The research investigates the current state of AI integration, examines its applications in structural analysis, design, documentation, and project management, and identifies the barriers hindering widespread adoption. The study highlights the importance of data-driven decision-making, enhanced design visualization, improved accuracy and efficiency, streamlined documentation and communication, and enhanced project management and control. By addressing the challenges and providing insights into AI techniques, this study aims to bridge the gap between theoretical potential and practical implementation, paving the way for more sustainable and intelligent civil engineering projects.

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Section: -Study Problemmentioning

confidence: 92%

Section: Machine Learning Algorithms and Their Applicationsmentioning

confidence: 99%

Section: Machine Learning Algorithms and Their Applicationsmentioning

confidence: 99%

Section: Improved Accuracy and Efficiencymentioning

confidence: 99%

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The Role of Artificial Intelligence in Civil Engineering Applications and Programs

Alghurair,

Fahim

2023

Journal of Engineering Sciences and Information Technology

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“…The role of artificial intelligence in construction industry revolves around improving every design element to reduce the need of manual labor (Nasirian et al. , 2019), improving designs to be sustainable through all climates and using technology to better allocate resources and materials supply (Gilner et al. , 2019).…”

Section: Construction Technologies Influencing Labor Activitiesmentioning

confidence: 99%

A qualitative conceptual framework to tackle skill shortages in offsite construction industry: a scientometric approach

Saad

Alaloul

Ammad

et al. 2021

ECAM

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PurposeThis study assessed the key construction technology trends and tracked the impact of these developments on labor influencing factors in an effort to alleviate the limitations posed by skilled labor scarcity in offsite construction (OSC).Design/methodology/approachThe study followed systematic literature review to acquisition initial data sets. The data retrieved form identified databases was then subjected to scientometric analysis. In next stage, disruptive factors were identified to produce a conceptual framework followed by its practical application for an OSC firm.FindingsThis study identified seven construction technologies with a potential to disrupt OSC in future. The study also developed a conceptual framework as a benchmark to help establish further frameworks for policy interns in OSC.Research limitations/implicationsThe review conducted only takes into account the literature from 2009 to March 2021. Any prior to the date and unpublished studies were not included in study.Practical implicationsA proper utilization of conceptual framework can contribute to technological adoption significantly lowering the need of labor in OSC industry. Moreover, the established discussion on understanding the purpose of deploying latest technology may reduce additional costs, management, time and allocation of labor resources.Social implicationsThis study provides a mechanism to intern OSC policymakers to impartially incorporate the latest technology in OSC.Originality/valueThis study fulfilled an identified need to study latest technological trends in OSC by utilizing bibliometric tools with SLR. The disruptive categories and factors highlighted by the study were not identified in a systematic manner in previous studies, which could further enhance the implementation of latest construction technology in OSC.

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A systematic review on green practices in the Malaysian construction industry: Status, challenges, key motivations, rating systems and technology evolution

Masyhur,

Alias,

Haron

et al. 2024

Energy and Buildings

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Application of Artificial Intelligence in Sustainable Building Design - Optimisation Methods

Cited by 7 publications

References 13 publications

The Role of Artificial Intelligence in Civil Engineering Applications and Programs

The Role of Artificial Intelligence in Civil Engineering Applications and Programs

A qualitative conceptual framework to tackle skill shortages in offsite construction industry: a scientometric approach

A systematic review on green practices in the Malaysian construction industry: Status, challenges, key motivations, rating systems and technology evolution

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