Artificial Intelligence Based Methods for Retrofit Projects: A Review of Applications and Impacts

IF 9.7 2区 工程技术 Q1 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS Archives of Computational Methods in Engineering Pub Date : 2024-08-01 DOI:10.1007/s11831-024-10159-7
Nicoleta Bocaneala, Mohammad Mayouf, Edlira Vakaj, Mark Shelbourn
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Abstract

The Architecture, Engineering and Construction (AEC) sector faces severe sustainability and efficiency challenges. In recent years, various initiatives have demonstrated how artificial intelligence can effectively address these challenges and improve sustainability and efficiency in the sector. In the context of retrofit projects, there is a continual rising interest in the deployment of Artificial Intelligence (AI) techniques and applications, but the complex nature of such projects requires critical insight into data, processes, and applications so that value can be maximised. This study aims to review AI applications and techniques that have been used in the context of retrofit projects. A review of existing literature on the use of artificial intelligence in retrofit projects within the construction industry was carried out through a thematic analysis. The analysis revealed the potential advantages and difficulties associated with employing AI techniques in retrofit projects, and also identified the commonly utilised techniques, data sources, and processes involved. This study provides a pathway to realise the broad benefits of AI applications for retrofit projects. This study adds to the AI body of knowledge domain by synthesizing the state-of-the-art of AI applications for Retrofit and revealing future research opportunities in this field to enhance the sustainability and efficiency of the AEC sector.

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基于人工智能的改造项目方法:应用与影响综述
建筑、工程和施工(AEC)行业面临着严峻的可持续性和效率挑战。近年来,各种举措已经证明了人工智能如何有效应对这些挑战,并提高该行业的可持续性和效率。在改造项目中,人们对人工智能(AI)技术和应用的兴趣持续上升,但此类项目的复杂性要求对数据、流程和应用有关键的洞察力,这样才能实现价值最大化。本研究旨在回顾在改造项目中使用的人工智能应用和技术。通过专题分析,对建筑行业改造项目中人工智能应用的现有文献进行了回顾。该分析揭示了在改造项目中采用人工智能技术的潜在优势和困难,并确定了常用技术、数据来源和相关流程。这项研究为实现人工智能在改造项目中的广泛应用提供了一条途径。本研究综合了人工智能在改造项目中的最新应用,揭示了该领域未来的研究机会,为人工智能知识领域增添了新的内容,从而提高了 AEC 行业的可持续性和效率。
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来源期刊
CiteScore
19.80
自引率
4.10%
发文量
153
审稿时长
>12 weeks
期刊介绍: Archives of Computational Methods in Engineering Aim and Scope: Archives of Computational Methods in Engineering serves as an active forum for disseminating research and advanced practices in computational engineering, particularly focusing on mechanics and related fields. The journal emphasizes extended state-of-the-art reviews in selected areas, a unique feature of its publication. Review Format: Reviews published in the journal offer: A survey of current literature Critical exposition of topics in their full complexity By organizing the information in this manner, readers can quickly grasp the focus, coverage, and unique features of the Archives of Computational Methods in Engineering.
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