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AI-Driven Approaches to Enhance Energy Efficiency in Heritage Architecture: A Review

1Suleyman Demirel University
✉ Corresponding author: Ali Berkay Avci · aliavci@sdu.edu.tr
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Abstract

This review explores the role of artificial intelligence (AI) in enhancing energy efficiency within heritage buildings, focusing on balancing sustainability goals with the preservation of historical and architectural integrity. AI technologies such as Building Energy Management Systems (BEMS), digital twins, and reinforcement learning provide innovative solutions to optimize energy use while minimizing physical interventions. Heritage buildings pose unique challenges for energy retrofits due to structural and regulatory constraints, but AI-driven tools offer non-invasive strategies that align with conservation principles. By predicting energy consumption patterns, facilitating adaptive climate control, and improving predictive maintenance, AI technologies can ensure that energy efficiency goals are met without compromising the building’s historical character. The review also addresses ethical considerations, such as data privacy and the cultural implications of AI interventions in heritage structures. This study highlights the potential for AI to revolutionize energy retrofitting in heritage architecture, providing a roadmap for future research on the integration of AI with sustainable building practices.

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Cite this article

Avci, A. B. (2024). AI-Driven Approaches to Enhance Energy Efficiency in Heritage Architecture: A Review. In 6th International Symposium on Innovation in Architecture, Planning and Design (pp. 37–41). SET Technology. https://doi.org/10.36287/setsci.20.5.037

Article History

Published
12 Dec 2024

License

© 2024 SET Technology. This article is distributed under the terms of the CC BY 4.0.

Research Contributions (2019+)Peer reviewed by at least two reviewers
Open AccessCC BY 4.0
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