An AI-Supported Framework for Enhancing Energy Resilience of Historical Buildings Under Future Climate Change
Year: 2025
Type: article
Abstract: Climate change threatens the sustainability of historic buildings with increasing extreme weather events, making energy resilience critical. However, studies on energy resilience often lack forward-looking, holistic approaches. This study aims to develop a conceptual framework that includes how Artificial Intelligence (AI) technologies can support energy resilience in historical buildings with data-driven prediction and analysis to increase energy resilience against climate change. This study applied a methodology with four-stage qualitative research techniques, including a systematic literature review (PRISMA method), content analysis, AI integration, and conceptual framework development processes, in the intersections of historical building, energy resilience, and climate change. The findings reveal a significant research gap in the predictive analysis of the resilience of historic buildings and the integration of AI-based tools in the context of climate change. The proposed framework outlines a multi-layered system that includes data collection, performance analysis, scenario-based prediction, and AI-assisted decision-making, aiming to enhance the resilience of the building (including building envelope, thermal, and lifecycle analysis). Consequently, this study provides a theoretical and methodological perspective and proposes a scientifically based and applicable roadmap. It also highlights the potential of AI as a bridge between energy resilience and historical buildings in the face of a rapidly changing climate.
Source: Architecture
Institutions: Selçuk University, Gazi University, Northumbria University
Language: English
Subfield: Building and Construction
Field: Engineering
Domain: Physical Sciences
Open Access status: gold
Estimated APC paid: $1,207
OpenAlex ID: W4413378245