BRAILS is a new AI-enabled tool to assist regional-scale simulations.
BRAILS utilizes machine learning (ML) and deep learning (DL) to create enhanced building inventory databases of cities. Examples of its capabilities include: (a) The identification of roof shapes to improve the damage and loss calculations for the hurricane workflow. This implementation used data from open street map and images from Google Maps. (b) The identification of soft-story buildings to improve models in earthquake workflows. This implementation used engineering knowledge and a subset of images from Google Street View to train a neural network to automatically classify the remaining images.
"Regional-Level Building Inventory Generation for Natural Hazards Studies Using BRAILS"
Dr. Barbaros Cetiner, January 27, 2023
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How to cite:
Barbaros Cetiner, Charles Wang, Frank McKenna, Sascha Hornauer, & Yunhui Gao. (2022). NHERI-SimCenter/BRAILS: Release v3.0.0 (v3.0.0). Zenodo. https://doi.org/10.5281/zenodo.7132010