We wanted a way to bring the social media world to the real world while adding meaning to it.

How it works

Utilizing the Twitter API, EmoteAware will pull your current tweets or tweets @ you and parse them, analyzing the sentimental value of the message. We wrote our own parser and pseudo-sentiment analyzer in JavaScript to accomplish this. We used Node.js for the back-end, the Sparkcore wifi-capable processor, and the Sparkcore API for the bridge between Node and the LED lights in the scarf.

Challenges I ran into

We ran into many development challenges - pulse sensing hardware was unavailable, Sparkcore hardware was locked to other user accounts (an issue we could only resolve by contacting Sparkcore directly,) and the myriad of challenges that come with learning and utilizing a new API.

Accomplishments that I'm proud of

I'm proud of the outcome of one our first hardware hacks. The concept is beautiful and has incredible potential.

What I learned

I've learned many engineering concepts, how to use the Sparkcore device and API, CURL, and some Node.js

What's next for EmoteAware

There are many directions EmoteAware could possibly go in terms of what data we choose to analyze or extrapolate. We could perhaps analyze total trend of a hashtag, product, person, or idea. Additionally, EmoteAware can evolve to any piece of clothing or as an accessory.

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