RelationLIT

Using social media and IOT to further social interaction.

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What to expect

A sample of the real RGB LED functionality of the product

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Inspiration

Social media is unable to facilitate true social interaction among people. We believe that technology is meant to augment our social experiences. We looked to finding a solution that fit the theme that less technology deliveries a more meaningful and powerful user experience.

What it does

The user attaches the LED puck to the bottom of their plastic cup. A user authenticates into our ionic mobile application on their iOS or Android application. The user can now put their device back in a pocket, bag, or purse for the rest of the experience. We are now able to pull the user's Facebook likes as well as their top artists and music on Spotify. We then process those request in our C# .NET backend which then serves up a API endpoint for our python client to access. The python client is responsible for matching clients and their cups to each other and communicate to the NodeMCU IOT board. Once matched, the user will walk around until finding their matched cup based on LED color in the hand of another user.

How we built it (and how it works)

3D printed LED puck with RGB LED and NodeMCU IOT board. .NET and Python backend server. Ionic mobile application.

The mobile application allows a user to sign in with Facebook, taking a user's likes and profile information and sending it to the .NET and Python backend. Once in the backend, the user object is processed and users are matched based on the amalgamation of user data points. When signing in to RelationLIT, a user is instructed to take the cup with an ID matching their registration. The cups are matched server-side, but this information is not exposed to the users. The user will then actively seek out the guest with matching interests. The cups' RGB LED will change color as the user gets closer to their pre-determined match.

Landing Login Prompt User Page
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Technologies used

  • Python (backend): Crunches our user "likes" and Spotify genres to generate matches of attendees.
  • .NET (backend): Handles API requests from the mobile app with user data
  • Heroku: Hosts the server for cups to connect and receive information from the app
  • Ionic 2 (frontend): Allows the user to login and request their cup
  • Facebook and Spotify API (backend): Takes in user likes and Spotify activity to find people with mutual interests
  • Arduino and ESP8266 (hardware): Uses HTTP requests and an RGB led to exchange information with the server and other cups
  • 3D Printing (hardware): Houses the Arduino-based NodeMCU development kit attached to normal disposable "party cups"

Challenges we ran into

Integrating all of our services and clients. Seamless OAuth authentication flow with Facebook and Spotify API.

Accomplishments that we're proud of

Building a mesh-net with no prior experience and integrating many APIs and clients. As well as incorporating a high fidelity 3D printed model of the LED puck attached to a plastic solo cup.

What we learned

How to implement a mesh-net work architecture and design pattern.

What's next for RelationLIT

We look to seriously refining and developing our concept. Implement ML for more accurate personality matching and utilizing big data. Possible start-up? Hey Facebook, Tinder, and Google we're ready to sell.

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