Inspiration
Struggle to find an visually appealing/easy to use interface to filter for suitable locations for housing
What it does
It curates ideal locations personalized with just a few inputs. We built it so that an end user would be able to get a quick idea of what areas would be suitable for one's lifestyle. To make this quick we implemented an algorithm that calculates the most optimal locations by simply adding a few factors like real estate prices, risk estimation (based on life expectancy and COVID 19), and scope of the search.
How we built it
For the frontend we used React.js (CRA) as our frontend web framework, Chakra UI for the styling of the UI components and Leaflet. For the backend MySQL for the database, Python+Flask for our REST API.
Challenges we ran into
A whole bunch ranging from initially hosting on a platform like heroku and github pages, confusing documentation on leaflet and having to use a webscrapping bot to gather data.
Accomplishments that we're proud of
Being able to deliver a product in such a tight deadline. Mobile responsive
What we learned
We learned a lot of things all across the board but I feel like deployment was something as a team we had to conquer.
What's next for mapM
More integration with other datasets and enhancing our algorithm to allow for greater visibility and user experience. Add in the following features: Education (School ratings) Crime rates Cost of living Income tax rate
Important Note
The deployment for the website is not yet fully done due to https security interfering with our REST api. Please use
yarn install
yarn start
to start the frontend.
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