We're all from the Erie campus and the weather would get so crazy there sometimes. It would be warm when the temperature was low, solely because the sun was out or cold because it was windy that day. This gave us the idea of building a web app that would benefit the people living in that area by telling them what to wear based on Real Feel Temperature.

What it does

Based on Accuweather's Real Feel Temperature, which considers multiple factors including the temperature, humidity, cloud cover, sun intensity, and wind to generate the actual temperature that we feel when outside, the program comes with suggestions for what we should wear out that day. The minimum and maximum forecast also provides us with a gauge of whether or not to bring out an extra coat that day just in case.

How we built it

By screaming at our computers. That and the use of Brackets to code the HTML and CSS, and script in Javascript. Data provided by the Accuweather APIs extracted and implemented via Javascript as well.

Challenges we ran into

Initially we coded in C++ because that was what we were all more familiar with and was not able to integrate our C++ code with our HTML and CSS codes properly so we switch to Javascript, which was completely new to us. We had a hard time extracting the weather data results from the APIs and debugging was a big issue but with the kind advices from seniors and organizers, we managed to pull through.

Accomplishments that we're proud of

That we actually got this to work and not let it be a pile of broken garbage. Although it is really basic now, we see the potential in it to be further improved.

What we learned

  • Javascript, the parts we needed
  • How to implement APIs
  • How difficult it is to actualize a product from its idea form

What's next for Stylecast

  • The system can be further refined to give more personalized suggestions such as remembering a user's gender, details and preferences for clothing
  • Monthly forecast to give the user a sense of what they will be mostly wearing for those months so they can prepare ahead of time
  • Collaboration with clothing brands to suggest to users actual products that the user may like and would be suitable for the climate.

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