Blav is a tool for the blind to navigate around. It uses a Qualcomm Dragonboard 410c for sensors and other data.

How it was made

  • The dragonboard collects data like webcam, distance, etc. and determines which direction to walk in using Machine Learning and Image Processing.
  • The hasura backend is used to communicate between the dragonboard and the computer. It has a flask-restful api deployed.

How does it detect

  • Using image processing, we detect certain points on the 'sidewalks'.
  • Then, we run regression over it to get a polynomial.
  • The angle of intersection between these two polynomials determines which direction to turn in.

Difficulties we ran into

  • The dragonboard was a huge pain to get working as there isn't much documentation on it. The Hasura APIs had little to none documentation, which made it very hard to set up.
  • The biggest challenge we ran into was getting the dragonboard to output current through its GPIO pins. It sounds easy, but with almost no documentation about a certain include error, we took hours to resolve that. ## What's next We would love to get this out in the real world and make our algorithm much more reliable.

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