Excited to launch a new machine learning competition! The goal is to be able to a better job creating disaster response plans based on detailed maps of communities. In order to do this, we need to understand the risk to structures, which we can do by understanding what kind of roof a building has. Come use your machine learning skills for a good cause! Plus it's got interesting geo data, novel imagery, and the opportunity to develop new methods.

In areas like the Caribbean that face considerable risk from natural hazards like earthquakes, hurricanes, and floods, these forces of nature can have a devastating effect. This is especially true where houses and buildings are not up to modern construction standards, often in poor and informal settlements. While buildings can be retrofit to better prepare them for disaster, the traditional method for identifying high-risk buildings involves going door to door by foot, taking weeks if not months and costing millions of dollars. This is where AI can help. WeRobotics and the World Bank Global Program for Resilient Housing have teamed up to prepare aerial drone imagery of buildings across the Caribbean annotated with characteristics that matter to building inspectors.