As a student at university, after first year it is very difficult to find all the information you need to find off campus living, we wanted to solve this problem to help students find the information that they need. There is no central website or collection of information that exists that can aid students with this problem, and thats where we come in!

What it does

Using a constantly updated database, we track what listings are available near the university for prospective housing options in a certain area. The results are then displayed in a meaningful and simple fashion providing the user with all the information required to make an informed decision, such as: relative location of housing to points of interest (i.e. University, Restaurants, Gyms, etc.), comparing houses by price and size, and providing a price average to give the user a point of reference when looking at house prices.

How we built it

Using various platforms and different languages, we built our website with many different moving parts. One collects data about available housing from the major landlords of the area and stores it into the data base. The second part takes the data from the database and intereprets it in a meaningful manner. That information is then taken and displayed in a sleek and elegant website which is accessible to the end user.

Challenges we ran into

Collecting data from websites despite varying HTML/Source Codes, CSS, using our data and applying it best for the consumer, interacting various API's, and gluing it all together.

Accomplishments that we're proud of

We are proud that we manage to collect 50 property listings which would effectively provide many students with ample choices in where to live, easing the process for them. We are also proud of how well worked together especially since most of our team members come from different Universities and had only met at the hackathon.

What we learned

We learned integral software design skills which we incorporated in our projects design. We also learned about different types of API's specifically the Google API and how to interact with them.

What's next for FindLiving.Space

We are going to scale it to incorporate data about listing in more cities to assist students, from other universities, facing similar difficulties finding affordable housings. We would also like to offer features which would benefit the landlords as well, giving them an estimate on their property's value based on the, hopefully, thousands of property listings on the site. We want to create the ideal solution the problem we are trying to solve.

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