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article imageGoogle to use AI to predict natural disasters

By Tim Sandle     Sep 26, 2018 in Technology
Google has announced plans to work with the Central Water Commission of India. For this Google will use artificial intelligence to alert people in India about impending floods.
Google has provided a service for many years which provides alerts about natural disasters. This has been in the form of warnings provided by government agencies, which have been incorporated into its apps like Maps and Search. Google is now moving a stage beyond this regurgitation of information towards providing its own alerts based on its own analysis of climatic conditions.
As the first wave of Google's use of artificial intelligence to predict natural disasters, The Verge reports how the technology firm will be working with the Central Water Commission of India. The service will inform Google users about impending floods. The service will begin with providing prediction relating to the Patna region. If this is successful, the service will be rolled out to other parts of the country.
Patna is located in Bihar, which is India's most flood-prone State, with 76 percent of the population in the North Bihar living under the recurring threat of flood devastation. In August 2018, several villages in Rahui and Harnaut blocks were devastated by major flooding.
India's Central Water Commission has outlined how it will work with Google to share technical expertise in the fields of artificial intelligence, machine learning, geospatial mapping and analysis of hydrological observation data to improve flood prediction systems and to provide location-targeted, actionable flood warnings.
Discussing the new service on a Google blog post, Google’s engineering Vice-President Yossi Matias describes how the artificial intelligence will make the predictions. This is through a combination of machine learning, rainfall records, and flood simulations.
He writes: “A variety of elements — from historical events, to river level readings, to the terrain and elevation of a specific area — feed into our models. With this information, we’ve created river flood forecasting models that can more accurately predict not only when and where a flood might occur, but the severity of the event as well.”
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