Every morning we stare a number that means little to us on our phone and are still at loss with what to wear. Even with all the information and data we have on the weather each day, we are still unclear on what outfit to wear. Somedays we spend the day freezing; others we spend sweating. It's a battle everyday to see if we can choose the correct outfit for the appropriate weather. WeatherWear solves this issue by helping users pick outfits based on personal preferences and weather.

What it does

WeatherWear relieves its users of the stress of deciding what to wear. It's simple user interface shows suggestions for what types of clothing to wear based on the weather. The user will then choose an outfit, take a picture of that outfit, and upload it into the app. We used Google's Vision API to analyze the picture and collect data on what kinds of clothes the user has chosen. At the end of the day, we ask the user to input some feedback and how they felt during the day, "too hot", "just right", or "too cold". We then take that feedback and input the datapoint into the system. The more the user uses the app, the more personalized the app becomes.

How we built it

First we brainstormed ideas and thoughts onto a google doc (link attached) and decided on exactly what the app will accomplish. Then we focused on what kinds of input and data that will go into the app and what output it will present the user. Next we prototyped the app design in Adobe Illustrator (link also attached). Lastly we sat down and coded the basic app idea in Android Studio and developed a working model of the app.

Challenges we ran into

The biggest challenge was coming up with an idea that we thought was both applicable to an API as well as being useful and practical in our daily lives. On a technical front, connecting the frontend and backend and parsing the data received from the API proved to be some of the biggest challenges.

Accomplishments that we're proud of

We have completed the basic functionality of our app. It uses the Google Vision API to take a picture and detect clothing articles, and based on user preferences, output clothing suggestions. We developed the idea and prototyped the product design in a relatively short amount of time which we are proud of. With more time, we could add more functionality and further improve the app’s ability to give clothing suggestions.

What we learned

We learned how to apply an API to create a useful and useable product, making extensive use of the internet to read documentation and figure out how to apply existing technologies to our project. We also learned how to divide up the work and maximize team efficiency. This project also taught us about coding workflow and the fast-forwarded life cycle of a project.

What's next for WeatherWear

After completing this mobile application, we want to integrate voice commands into the process in order to efficiently use the product. We would like the app to dictate the outfit suggestions to the user in the future. We would also want to advertise this product further in order to change lives..for the weather. :)

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