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Simulate an autonomous drone that can avoid obstacles, detect and track wildfires using model-based design, AI, and image processing techniques.

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⭐ Please complete the prework below! Do not clone this repository directly. ⭐

Catching Fire: Autonomous Drones to Detect and Track Wildfires!

Hardware and Software Requirements

To participate in the workshop, you need:

  1. A laptop
  2. Google Chrome browser
  3. A MathWorks account

You will be provided with a temporary workshop license that will give you access to all products used in the workshop, as well as the workshop exercise files.

Step I. Set Up Your MathWorks Account

If you don’t have a MathWorks account, you need to create one to get access to MATLAB Online and the material for this event. You will need access to your email on the machine you are using to create the account.

  1. In Google Chrome, go to: https://www.mathworks.com/mwaccount/ and click 'Create one!' next to 'No Account?'
  2. Fill out the form and click Create. Follow the directions for verifying your email address.
  3. To complete your registration, click the link in the verification email and fill out the form. You must check the Online Services Agreement box. You may leave these fields blank: Activation Key or License Number, Sales rep contact, Associate with a license, Trial

Step II. Activate the Workshop License

The workshop uses MATLAB Online. You must activate this license to participate.

  1. Navigate to this address in Google Chrome. If you are not already logged in, do so:
    https://www.mathworks.com/licensecenter/classroom/3883400/

  2. Click Access MATLAB Online.

Step III. Access Exercise Files

Once you have access to MATLAB Online, to get access to the workshop files, use the following commands in the command window:

  1. mkdir WiDS_CatchingFire
  2. cd("/MATLAB Drive/WiDS_CatchingFire")
  3. unzip("https://github.com/shwetadotsingh/WiDS_CatchingFire/archive/refs/heads/main.zip")
  4. cd("WiDS_CatchingFire-main")

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Simulate an autonomous drone that can avoid obstacles, detect and track wildfires using model-based design, AI, and image processing techniques.

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