just joe

Inspiration

As a college student, the idea of creating a crowd-sourced coffee study spot app is incredibly enticing to me. It's a project born out of my own deep-seated desire for the perfect study haven. I envision a vibrant community of students, united by a shared goal of making our campus life better. This endeavor isn't just about app development; it's a chance to immerse myself in entrepreneurship, meet the owners of local coffee shops, and build a network that could shape my future. Moreover, it's an opportunity to showcase my passion for technology and innovation, making it more than just a project, but a true labor of love. Most importantly, it's a chance to have a positive, lasting impact on my peers' academic and social experiences, and that's something I'm truly passionate about.

What it does

A crowd-sourced coffee study spot app is essential for students because it offers real-time, diverse, and community-driven insights. It provides up-to-date recommendations and diverse perspectives, creating a valuable resource for students with various study needs and habits. This approach encourages community engagement and peer recommendations, making it a powerful tool for enhancing students' study experiences.

How we built it

We designed the front-end using Figma and R for user interface and data visualization. For back-end, we used python and R to develop the logic to convert menu images to text, identify the prices for a user's usual order, and generate a map locating coffee shops that are best matched to a user's preferences as well as based on how busy it is.

Challenges we ran into

Though we developed the flow of the app, we were not able to create a working prototype as time did not permit. Additionally, finding unique traits about this app was difficult as it is closely related to Google Maps.

Accomplishments that we're proud of

We are proud of the creating a intriguing front end design as well as developing most of our back end logic, given our limited experience with mobile development.

What we learned

We learned how to use new libraries and tools in R and Python. We also created animations and components for the first time in Figma to replicate user interaction in a mobile app.

What's next for just joe

First, we would like to connect the front-end to the back-end as we really want to release this app for use. Next, in order to determine the ambience of a coffee shop, we would like to crowd source noise levels in order to share this information with users. Lastly, we want to implement a reward system to encourage users to fill out surveys.

Built With

• chatgpt
• figma
• firebase
• gif
• leaflet.js
• pil
• pytesseract
• python
• r