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Save Lives in emergency situations where you don't know what to do, but machine learning does! #AndroidDevChallenge

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Save Lifes Now

Save Lifes Now AndroidDevChallenge

Have you ever thought that we don't know what to do in an emergency situation?

We don't know if we call the emergency first, or help the person, or if we signal the location, and we don't often know first aid needs to be done.

The Save Lifes Now app will work with machine learning, analyzing the scene, and telling the person the best way to handle the situation. For example:

  • If machine learning detects that you are on a highway and you have had an accident, it will first ask the person to flag the location so that no further accidents can happen, the app will automatically send traffic notifications to let other cars know that an accident has occurred.
  • If an accident has occurred and machine learning detects that there is too much smoke, it will ask them to move away because of the risk of explosion.
  • Or in a motorcycle accident for example. If machine learning detects that the person is still wearing a helmet, he or she will ask them to take off, and not move the person until the rescuers arrive.
  • If pointing the camera and machine learning detects that the person is bleeding a lot, he will ask you to waterproof, and will show you how to do it.
  • If machine learning detects that it has a storm in your location, it will show you step by step how to proceed. For example, staying in covered places, moving away from trees, metal fences, the beach, etc ...
  • And anothers situations...

We need an APP like that, because at the time of emergency we don't remember anything, and the phone is in our lives, and there's nothing like it yet.

Save Lifes Now AndroidDevChallenge

The project will be divided into three stages.

  1. Brienfing: Talk to teams of first responders, and see what key issues they need to solve, and decide all possible situations that machine learning can work.
  2. Data collection: Gather all the information for machine learning to be grounded in and to work in emergency situations.
  3. Final Test: Perform machine learning tests, and make adjustments before launching the beta. Scheduled for April 20, 2020

"I true believe that can make difference an app like that. Using machine learning for emergency situations and saving lives. I work with social projects for a while. Here in Brazil, I launched an app to find blood donors in seconds that are close to your localization, so just call and ask for their help" Brayon Pieske

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Save Lives in emergency situations where you don't know what to do, but machine learning does! #AndroidDevChallenge

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