Disaster Response and Mitigation in an AI World

After the destructive California wildfires of 2019, the U.S. government put together a White House Executive forum to develop better ways of protecting the nation and key infrastructure, such as the power grid, from wildfires and other disasters. In 2020 alone, more than 10.3 million acres burned across the United States, a level three times higher than the 1990–2000 10-year average. Between fire suppression costs, direct and indirect costs, wildfires in 2020 cost the United States upwards of $170 billion. Add in floods, hurricanes, and other natural disasters, and the toll of disasters on the livelihoods of Americans is astronomical.

Andre Coleman and his team of researchers at Pacific Northwest National Laboratory (PNNL) are part of the First Five Consortium, a group of government, industry, and academia experts committed to lessening the impact of natural disasters using technology. Coleman and team are expanding PNNL’s operational Rapid Analytics for Disaster Response (RADR) image analytics and modeling suite to mitigate damage to key energy infrastructure. Using a combination of image capturing technology (satellite, airborne, and drone images), artificial intelligence (AI), and cloud computing, Coleman and the team work to not only assess damage but predict it as well.

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