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

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 anagement 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.