Development of a Framework Using AI for Building Facade Optimization: An Application Focusing on Retrofitting NYCHA Midrise Housing in New York City

Artificial intelligence (AI) technology and the industrial revolution (4IR) have potential for the raid advancement of smart buildings, materials, and construction processes to achieve global decarbonization goals. There is a need to perform the assessment work quickly and thoroughly to design the most appropriate retrofit system. Current retrofit techniques can vary a lot in their methodology from place to place, but what most have in common is time contraints and the need to follow budgets often and show significant reductions in energy usage. The objective of this research is to develop a framework that optimizes the façade retrofitting process with the help of AI, bringing it in as a decision-making tool that also accounts for other parameters, but differently to traditional retrofit methodologies, where both the designer and the user are the judges. Thus, this research explores the possibilities of recent AI tools such as Midjourney to be used for problem-solving in retrofitting. This is done with a literature review of the application of AI in the architectural field for retrofits, façade optimization, and image generation. From there, the overall framework suggested is developed addressing materiality, high performance analysis, affordable costs, and user-experience inputs, aiming for a successful retrofit. Furthermore, this research contributes to the retrofit discussions by initiating steps on how available AI tools can add to the discussion, carving out a pathway on how AI can help in this process. The results show an improvement in the way retrofits are addressed with the help of AI, mainly on user-experience, with their integration in the decision-making process.