Artificial Intelligence Based Methods for Retrofit Projects: A Review of Applications and Impacts
Bocaneala, Nicoleta and Mayouf, Mohammad and Vakaj, Edlira and Shelbourn, Mark (2024) Artificial Intelligence Based Methods for Retrofit Projects: A Review of Applications and Impacts. Archives of Computational Methods in Engineering. ISSN 1134-3060
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AI_Based_Methods_for_Retrofit.pdf - Accepted Version Available under License Creative Commons Attribution. Download (1MB) |
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.
| Item Type: | Article | ||||||
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| Identification Number: | https://doi.org/10.1007/s11831-024-10159-7 | ||||||
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| Uncontrolled Keywords: | Artificial intelligence, Retrofit, Digital Twin, Sustainability, Construction Industry | ||||||
| Subjects: | CAH11 - computing > CAH11-01 - computing > CAH11-01-01 - computer science CAH13 - architecture, building and planning > CAH13-01 - architecture, building and planning > CAH13-01-02 - building |
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| Divisions: | Faculty of Computing, Engineering and the Built Environment > College of Built Environment Faculty of Computing, Engineering and the Built Environment > College of Computing |
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| Depositing User: | Gemma Tonks | ||||||
| Date Deposited: | 02 Jul 2024 14:41 | ||||||
| Last Modified: | 08 Aug 2024 13:43 | ||||||
| URI: | https://www.open-access.bcu.ac.uk/id/eprint/15633 |
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