Inspiration
Back in freshman year of college, we felt that one of the best ways to meet new people was to go to a dining hall and meet other students, but the COVID-19 pandemic has made this extremely difficult for students to do so. Now, people eat their lunch at home, and often without company. We wanted to create a product that reproduces these social interactions during lunch.
What it does
Lunchmeat is an online video-chatting platform for those who want to meet and chat with new people over a lunch. A user answers some basic questions, like how long their lunch break is, to help us match users together. Once we've found a match, the users will go into a 1-on-1 private voice chat where they can chat over lunch!
How I built it
We used Node.js, React.js, and Express.js for our technology stack, and the app is deployed on Heroku. Our front-end was styled using Sass and Material UI components and icons. The logos were designed in Adobe Illustrator. For sockets, we used socket.io integrated with Express.js. We used the Daily.co API for video chatting.
Challenges I ran into
We ran into some challenges in deploying our back-end application and front-end application on Heroku. Our biggest challenge was figuring out a CORS issue and secure communication between the two apps. We also had a few challenges with version control on Github.
Accomplishments that I'm proud of
Some accomplishments that we're proud of is building a fully functional MVP from start to finish. There have been a number of hackathons where we've started a project but haven't had the capacity to finish something and this shows that we were truly able to create something. The other was building out the sockets to handle real time communication between users who have connected.
What I learned
We learned about understanding how sockets worked, a better understanding of Figma, deploying frontend and backend, and Adobe Illustrator. We also had to learn how to use Daily.co for our video chatting feature.
What's next for Lunchmeat
A better matching algorithm (extending the matching algorithm to be more intelligent), better curated topics of interests, integrations with university, more than 1:1 calls (group calls), being able to see rooms that are being used, and potentially more ways to connect (adding social media handles)
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