‘Q8TL’ - ’The A&W Runners’ - ‘BlockBuddy’

BlockBuddy lets residents capture and share neighbourhood complaints through text or camera, chat by area, and view complaint markers on a map based on their city/neighbourhood.

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‘Q8TL’ - ’The A&W Runners’ - ‘BlockBuddy’

Inspiration

  • Give residents a friendly way to flag neighborhood issues, talk to each other, and see community impact on a map.

What It Does

  • Publish complaints via text or camera (AI‑assisted summaries, severity, weather).
  • Show complaint markers on a map centered on the user’s neighborhood/city.
  • Chat privately, by neighborhood (city+neighborhood), or city forum threads.

How We Built It

  • Frontend: React + Vite + TypeScript
  • Backend: Node.js + Express
  • DB: MongoDB
  • Services: OpenWeather for weather and Gemini AI for camera analysis.

Challenges We Ran Into

  • Location UX: reliable Canada‑only autocomplete
  • Chat threading + privacy
  • Mongo schema modeling (messages/threads)

Accomplishments That We’re Proud Of

  • Analysis using text/camera to display on live map with severity + weather.
  • Neighborhood, city, and private chats

What We Learned

  • How to deploy frontend on AWS
  • How to use a MERN tech stack

What’s Next for BlockBuddy

  • Moderation tools, spam detection, and report verification workflows.
  • Add ability for adding media to chats and support for videos in compaints
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