Software Open Access
Charles Wang; Qian Yu; Frank McKenna; Barbaros Cetiner; Stella X. Yu; Ertugrul Taciroglu; Kincho H. Law
Website: https://github.com/NHERI-SimCenter/BRAILS
BRAILS is the acronym for Building Recognition using AI at Large-Scale, which is an AI-Based pipeline for city-scale building information modeling (BIM).
BRAILS helps users create regional-scale database of building inventory, where buildings properties are extracted from satellite or street view images using deep learning.
BIM, as an efficient way for describing buildings, gives architecture, engineering, and construction (AEC) professionals the insight and tools to more efficiently plan, design, construct, and manage buildings and infrastructure.
Natural disasters cause losses to human society by damaging or destroying buildings, which consequently endangers lives and goods. Buildings are the major components of a human built environment, hence are of the major considerations in planning for, responding to and recovering from disasters. BIM contains information showing building geometry, components, material, usage, etc, which makes it an ideal source for generation and running of simulations of building behavior under both normal and emergency scenarios. For example, based on BIM, structure engineers can create numerical models for dynamic simulations of seismic loading conditions.
Name | Size | |
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NHERI-SimCenter/BRAILS-v0.1.1.zip
md5:48c7b20823fcc32d3662e01bdcd27084 |
34.8 MB | Download |
All versions | This version | |
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Views | 374 | 305 |
Downloads | 26 | 24 |
Data volume | 854.2 MB | 834.3 MB |
Unique views | 302 | 263 |
Unique downloads | 20 | 19 |