Investigating Contemporary AI Tools for Assessment of Thermal Efficiency in Architecture

This paper is based on the application of the latest artificial intelligence technologies to assess and improve the thermal performance of buildings.With the demand for optimizing the thermal performance of the built environment becomes more urgent due to reasons like climate change, growing energy costs, and sustainability goals.A wide literature review with examples during the research had outlined several recent advances in AI in architecture, such as in machine learning, deep learning, natural language processing and computer vision, and robotics, and will include a summary of the relevant research areas.The paper reviews recent approaches and challenges to the use of these technologies, including the diversity of AI technologies, lack of standardized evaluation criteria for assessing AI technologies in architecture, challenges to the integration of AI technologies as a part of a design workflow, the variability in the performance of AI tools, and a general lack of knowledge of AI amongst architectural practitioners.The purpose of the study is to develop a comparative analysis of selected AI tools for assessing thermal performance.Objectives are processed in including identifying selected contemporary AI tools, establishing evaluation criteria, performing an analysis and determining the potential applicability of the AI tool to various contexts.The method will involve a secondary literature review, identification of contemporary AI tools, the establishment and criteria for the evaluation of AI assessment tools, and a comparison of the identified AI tools for their potential applicability.The study found that the tools do significantly improve the design, construction and management of buildings with high thermal performance.Recommendations include suggestions for selecting and using AI tools to deliver high thermal performance, and in doing so, contributing to energy efficiency and sustainability goals in architecture.