Stage

Hibernating

README

PhilaVibes Project

PhilaVibes is a map application that helps people in Philadelphia at point A with more time than they need to get to point B find a comfortable place to be between those spaces. The map will feature points surrounded by word clouds describing the spaces (and will show the name, address, etc, once the user clicks on that space). The user can see choose to see spaces around them, along their route, or around their destination.

Project Activity

Update #1

Launchpad 2023 Showcase

Our progress after 5 weeks

What we've decided

PhilaVibes is a map application that helps people in Philadelphia at point A with more time than they need to get to point B find a comfortable place to be between those spaces. The map will feature points surrounded by word clouds describing the spaces (and will show the name, address, etc, once the user clicks on that space). The user can see choose to see spaces around them, along their route, or around their destination.

What we've done so far

The team came together and built out a roadmap, wireframes, and even a clickable demo!

While the developers came together to build out a plan using user interviews and user testing, the development team chose a tech stack, built out boilerplate for that stack, began building our models and endpoints, and have begun to build out the frontend.

That tech stack

  • Frontend
    • React
    • Leaflet
  • Backend
    • Django & Django Rest Framework
    • PostgreSQL & PostGIS

Next steps

  • In future meetings, the team will continue to get the current build caught up with the current wireframes.
  • We will also build out a comprehensive way to programmatically pull qualitative data about the spaces we are trying to describe in the map.
  • The other large part is building out the behaviors in the map so that users can easily see the the word cloud without being overwhelmed, including adding filters for keywords or amenities like wifi etc.

What we need help with

  • We would love for more developers to join our team! Devs with geospatial and React experience especially though all are welcome to come learn with us!
  • We will need help creating an algorithm to initialize our data using Yelp reviews and pulling out descriptive words (we're starting with cafes but will expand once the algorithm is reliably scalable)
  • We will need help building out a user-feedback system (users will be able to "thumbs up" or "thumbs down" the qualities of a space based on if they agree that its "cozy", "kid-friendly", etc.