Inspiration

With the housing market being as big as it is and rapidly expanding, it's becoming increasingly more difficult to keep track of everything. With so many different websites and sources for information, we wanted to make something that made the process of browsing the real estate market easy for beginners or anyone else who is looking to do so. One of our members was looking to buy a new house himself and was overwhelmed by barrier of entry. JProperty solves that problem.

What it does

JProperty is a real estate aggregator that complies housing listings displays all the information on one interface. For our testing purposes, we used local housing listings and global Airbnb listings. We took over 5000 worldwide airbnb listings and over 650 local property listings and created a database around them. JProperty allows you to search for properties by location and price, comprehensively overview the listing, read reviews associated with the listing, and save listings you like to a personal list.

How we built it

The JProperty frontend interface was made using Java Swing and the backend was made using MongoDB. Various APIs were used to bridge the gap between the client-side and server-side. Additionally, MapDB was used to design a heat map of the listings displayed. In order to get our Airbnb and local real estate listings, we had to scrape listings from the Airbnb website and over 20 local real estate websites.

Challenges we ran into

We ran into some challenges with networking and getting the client to easily access the MongoDB database. We also ran into some challenges with converting the street data into latitude and longitude that could be used for our heat map and also had challenges with layering images on top of text areas and other display items.

Accomplishments that we're proud of

One of the accomplishments that we're proud of is the working heat map. Generating accurate and displayable information from the only street names was very difficult but we were able to overcome it. Another accomplishment we are proud of is linking our program to MongoDB properly since we had minimal experience with the database beforehand.

What we learned

We learned how to leverage different APIs as well as networking and data scraping and wrangling.

What's next for JProperty

We hope to continue expanding our program to include a greater variety of listings, not just local housing and Airbnbs, so that it is more accessible and useful to more people. We also hope to add more features to our program, for example a function that allows the user to get in contact with the seller of the property and a global heat map instead of just a local Windsor one.

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