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Fire Risk Assessment
Real-time updates for the public and firefighters that highlight current and future high risk fire areas
Using historical data from NOAA (National Oceanic and Atmospheric Administration), Google Maps, Waze we can find early warning signs of potential fires to highlight high risk fire areas. To find these warning signs we will run ML models on past weather attributes (ex. temperature, precipitation, wind speed, etc.) and travel patterns (ex. people heading to risky fire starting areas like campgrounds) to highlight key attributes/patterns that best determine fire risk. We will apply this model to real-time streaming data from the same sources to determine high risk areas. This information will be available in two interfaces. One for the public which alerts travelers that they are heading to a high fire risk area and suggest other similar areas that have a lower fire risk. Another to be used by firefighters as a way to allocate manpower and resources to the appropriate areas before a fire starts.
ApplicationTraffic Analytics Platform (TAP)
Advanced analytics platform evaluating traffic patterns in real-time
A full service traffic analytics platform run on Google's Cloud Platform to measure traffic counts, classify vehicles, forecast speeds and car crashes, and visualize traffic patterns in new ways
Solution