Implementing Ai In Architecture: A Strategy For Seismic Resilience

Every year, earthquakes claim upwards to 40,000 lives, affecting millions (see fig. 1) primarily in developing countries with injuries and displacements. These regions need both new buildings and strengthening of existing structures but face challenges due to limited expertise, time, and financial resources. This research focuses on the identification of buildings that require strengthening measures by using machine learning to reach seismic resilience. Two existing AI models: The IC Assistant and Rapid Seismic Assessment model were analysed and utilized for a case study of an Istanbul apartment building along with a Geography Model that is in development by the authors. These models evaluate building safety on various factors like soil type, structural layout and building information. This three-model method aims to be the standard practice as current traditional on site analyses are not efficient and feasible for major cities like Istanbul which face fast approaching earthquake threats.