Extreme weather events cause billions of dollars of damage every year. Response during storms and restoration of damaged infrastructure afterwards is a perennial problem in many sectors. In the immediate aftermath of an extreme weather event, obtaining accurate ground truth information about “what just happened” is often a time consuming and manual process. This leads to operational delays and inefficiencies, which in turn drive higher costs and poor customer satisfaction.
ACW Analytics is attempting to drastically shorten the post-storm damage assessment window by using AI to confidently estimate the impacts of events in real-time. We have developed an analytical system that applies machine learning algorithms to a blend of NOAA nowcasting, analysis, and observations (HRRR, RTMA, NEXRAD) together with infrastructural and environmental data to produce detailed estimates of the severity and location of storm damages. This information can help infrastructure managers gain the situational intelligence they need to quickly adapt to severe weather as it happens, and ensure a fast and efficient return to normal.
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