User input for controlling and adjusting lighting conditions is both tedious and inefficient. There is a need for automatic pipelines that can learn from the user's preferences.

What it does

We propose an artificially intelligent way to control lighting in a room that gradually learns to change the light color and intensity based on user's mood, preferences and environmental conditions. Advanced machine learning techniques based on artificial neural networks is employed.

How we built it

Machine was trained using different layers of neural networks so that they can able to recognize different user daily routine life patterns in room.

Challenges we ran into

  • Ideation
  • Gathering of resources
  • Coding

Accomplishments that we're proud of

We are able to make a intelligent machine by using the given set of data in a limited amount of time.

What we learned

Hard work and dedication pays of.

What's next for Helvar Who needs a light switch

More data means more intelligent lighting!

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