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Main Landing Page
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Backend Code
Inspiration
Finding homes can be difficult for families. Realtors are not allowed to say if areas are “Safe”, or “have good schools”. How can a family plan for their future employment? Our App assists families to find the best city for them to live in!
What it does
User ranks importance of safety, school quality, employment in the area, and their budget for a home price
With an intuitive web application, displays the top cities recommended based on the preferences set
How we built it
Found datasets of school rankings, crime indexes, employability, and house prices in the state of Wisconsin, organizing by city Real Estate API to determine average house prices
Parsed datasets, combined three into a master dataset of data needed
React.js, Flask Server, and creation of algorithm for determining best-fit city
Challenges we ran into
Backend deployment
Co-op experience with Github (Merges, Pushes, Pulls)
Accomplishments that we're proud of
Successfully used Mapbox API to give users a custom map of Wisconsin, adding markers of the user's top-rated cities. Parsed large amounts of data, using an algorithm to determine the best fit for the user.
What we learned
Development in React.js
Learned uses of AWS Amplify
Intricacies of Frontend
Further understanding of roles for programmers (Frontend, Backend)
What's next for WiscHomeHelper
Utilize a database to collect and store user information and city information better (SQL)
Search for homes in the city according to the budget
Further expand filters to help families narrow selections Create a radius of interest
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