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Use CaseGovernment & Public Sector / Government

Predict risk from natural disasters such as wildfires

Predict risk from natural causes such as wildfires, using data from a wide variety of sources such as satellites and environmental sensors and often building on other data models - for example likely weather patterns. Predicting likely wildfire movement for example can have huge impact on human safety and resource deployment.

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Risk reduction
Risk reduction - Reduce environmental physical risk
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Operational Support
Operational Support - Process visualisation
Description

Predict risk from natural disasters such as wildfires

Linked Case Studies
Case Study
One Concern
One concern optimises emergency crews distribution during natural disasters with machine learning
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Case Study
Harvard University
Harvard university seismologists developed a deep learning algorithm to predict the location of aftershocks with an AUC of .849
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Case Study
Google
Monta Vista High School students build a model to predict wildfires using Google Tensorflow
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Case Study
Los Alamos National Laboratory
Researchers at Los Alamos National Laboratory identified a sound pattern that indicates slippage and fault failure using machine learning
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Case Study
Technical University of Berlin
Researchers at Technical University of Berlin monitor 17 volcanoes worldwide using machine learning
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Case Study
Google
Google predicts river floods and their severity using AI based forecasting models
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Case Study
University of Bristol
University of Bristol Researchers detect possibility of volcanic eruption using neural networks
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