Application of Artificial Intelligence (AI) in the Lifecycle of Sustainable Buildings: An Exhaustive Literature Review

Abstract

With architectural structures accounting for significant share of global energy consumption and greenhouse gas emissions, the integration of Artificial Intelligence (AI) is a promising avenue for enhancing sustainability throughout the building lifecycle. This paper aims to investigate current insights regarding AI’s potential to improve energy efficiency and mitigate environmental impacts in building design, construction, and operational management. A comprehensive literature review and synthesis was conducted to identify relevant AI technologies that promote sustainable construction practices, assess their impacts, and examine challenges to effective real-world implementation. The review utilized rigorous search methodology with specific keywords related to AI applications in sustainable building design, construction, and operations. The findings reveal AI’s capabilities in optimizing energy efficiency through advanced control systems, improving predictive maintenance, and facilitating beneficial design simulations. Machine learning algorithms enable data-driven analytics and forecasting, while digital twin technologies offer real-time insights for strategic decision-making. The review identifies impediments to AI adoption, such as cost concerns, data security vulnerabilities, and challenges in implementing advanced systems. AI has transformative potential for enhancing sustainability in the built environment, providing innovative strategies for energy optimization and eco-friendly practices. Addressing technical and practical challenges is crucial for effective integration of AI into sustainable building methodologies.