AI application in architecture in UAE: Application of an advanced optimized shading structure as a retrofit strategy of a midrise residential building façade in downtown Abu Dhabi

Artificial intelligence is a phenomenon that influences every aspect of our lives. AI applications have already started to change the methods in different disciplines. Architecture is one of the disciplines that is highly affected by the developments of AI technologies. With the United Arab Emirates heading to employ new technology to lead the country and region development, it is important to explore and develop the application of AI in the strategic disciplines of the country in which the built environment is essential. This study aimed to develop and evaluate an advanced model script (to be used as a tool) using Artificial intelligence tools methods and platforms. This model is to be used to Optimize an X parametric shading structure (As a midrise building façade retrofitting strategy in Downtown Abu Dhabi) to reach the most energy-efficient design based on the building parameters. Mixed qualitative, quantitative, and experimental methods were applied in the different stages of this study. The study is divided into four stages: started with exploring AI progress in architecture to define the tools methods, and platforms used to develop the advanced model script, At the second stage the midrise building stock in downtown Abu Dhabi investigated to define the needed parameters, in addition to that, an energy simulation model including Energy plus engine created and validated, to be utilized on the optimization script evaluation. Also at this stage the variable parameter defined based on the related literature, the defied parameters are the perforation area and depth ratio. At the third stage the advanced model script was developed using the Grasshopper plug-in for Rhino software, which is based on Python language. Three trials for developing the optimization script were conducted to define the objective function of the optimization process. Finally, the tool was validated and tested using midrise building case studies, the energy consumption for the case study was reduced by 26.2 %–30 % when the generated optimum structure was applied as a shading structure to the southwest façade. An advanced tool that can be applied to different midrise buildings and automatically recognize its parameters and optimize a parametric shading structure for the building based on its parameter resulted from this study. The parametric pattern optimization process includes minimization of the total radiation on the building envelop cooling loads and increasing the energy efficiency, while ensuring adequate values for the daylighting and visual connection