I guess every one of these apps has to start with a tragic back story... Once upon a time Robert had a girlfriend. She was a real girl: hair, mouth, eyes...eyebrows... a likeable 3D girl. Despite his nerdy disposition and geeky personality, she somehow liked him. Perhaps he was attractive in her eyes, or maybe she was actually interested in his flawless coding skills. They had met through a hackathon in Iceland, but after returning to their homes far away from each other, to talk, they used a messaging app. However, Robert encountered a problem. One day, his girlfriend texted him,"Come back now". He couldn't tell her tone of urgency through text, and soon, he was without a girlfriend. Alone. His inability to react to body language and feelings through text caused him to lose his girl.

From Robert's depths of despair following his breakup came the birth of Rich Messaging System. With this app, Robert hopes that others will not suffer the same fate of miscommunication he did.

What it does

Rich Messaging System incorporates emotional tags such as sarcasm to better convey messages.

How we built it

We split into two teams: one on front-end development, the other on the back end. Our front-end team used Javascript, Cordova, CSS, and HTML

Challenges we ran into

Finicky languages that don't cooperate with us; Raspberry Pi didn't go as fast as we expected. Had to update the pi (hasn't been updated for 8 months).

Accomplishments that we're proud of

We're proud that we as a first time team have developed a complete hack, we're proud of being able to cooperate as a team to develop an application that we can work on after this hackathon.

What we learned

Javascript and CSS are finicky, and using a Raspberry Pi as a server isn't as easy as it sounds. Front end development is annoying. We learned that uniting hardware and software isn't easy either.

What's next for Rich Messaging System

We hope to incorporate human stimuli such as heart rate, breathing, body temperature, and tactile senses in order send messages more efficiently and accurately. We also hope to incorporate machine learning into our app to increase automation of certain input strings. For example, if a user always says a certain phase sarcastically, the app will make the sarcastic tag automatically.

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