Visuals are interesting here in the linked article below. Another example of where there needs to be strong, real-time collaboration with human interactions.
Disaster Relief Is Dangerously Broken. Can AI Fix It?
By Katharine Schwab in FastCompany
The use of artificial intelligence in disaster relief is gaining favor as weather-related catastrophes grow in frequency and severity. For example, a startup founded by Stanford University's Ahmad Wani has launched a machine learning platform to help cities respond to floods with specialized maps that update in real time so emergency crews can determine where aid is most needed. Wani said a key challenge was enabling rapid, city-wide analysis of structural engineering to better predict damage. The Flood Concern risk map was based on an earlier algorithm that digests building construction and retrofitting data, integrated with information on building materials and surrounding soil properties, to predict earthquake damage. Flood Concern crunches vast data volumes based on water-flow physics, previous flood data, and satellite imagery to approximate water depth, direction, and speed and localize areas at most risk; demographic data is layered atop the prediction so emergency planners can anticipate areas with the most likely at-risk residents. .... "
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