The objective of this project is to support research that looks to examine building design and operation during disasters, focusing on people who have navigational challenges that may adversely affect their evacuation. It provides new insights into building features from the perspective of those who rely on mobility aids. The outcomes potentially lead to responsible, resilient buildings and contribute to knowledge at the interaction of disasters, built environment, and populations. Additionally, this project promotes interdisciplinary education in engineering, humanities, and design through new course modules and outreach initiatives. Building designers and operators often overlook unique obstacles posed during disasters due to a lack of evaluation methods that can integrate architectural design principles, the needs of people with mobility support requirements, and disaster resilience goals. This gap is further rooted in the absence of voices from people who use mobility aids and efficient mechanisms to incorporate their needs into digital platforms. This project, by leveraging the power of foundation models, which are large deep learning models trained on extensive datasets of images and text, looks to automate extraction and analysis of key building features. Furthermore, value of the developed models will be evaluated by assessing how well such features align with need hierarchies derived from a curated database of lived experiences during past flood events. The findin