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

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dc.creator Avci, Ali Berkay
dc.date 2024-11-19T00:00:00Z
dc.date.accessioned 2025-02-25T10:40:05Z
dc.date.available 2025-02-25T10:40:05Z
dc.identifier e225a9b3-bd9c-427e-9eb8-fa012dd89766
dc.identifier 10.36287/setsci.20.5.037
dc.identifier https://avesis.sdu.edu.tr/publication/details/e225a9b3-bd9c-427e-9eb8-fa012dd89766/oai
dc.identifier.uri http://acikerisim.sdu.edu.tr/xmlui/handle/123456789/101684
dc.description <p><span style="font-family: -apple-system, BlinkMacSystemFont, &quot;Segoe UI&quot;, Roboto, &quot;Helvetica Neue&quot;, Arial, &quot;Noto Sans&quot;, sans-serif, &quot;Apple Color Emoji&quot;, &quot;Segoe UI Emoji&quot;, &quot;Segoe UI Symbol&quot;, &quot;Noto Color Emoji&quot;; text-align: justify;">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.</span></p>
dc.language eng
dc.rights info:eu-repo/semantics/openAccess
dc.title AI-Driven Approaches to Enhance Energy Efficiency in Heritage Architecture: A Review
dc.type info:eu-repo/semantics/conferenceObject


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