Nest Finder

sign-in: access account through intuitive sign-in page
browse and filter page: find housing with browse and filter options, narrowing down price, type, and distance from UBC
homepage-bottom
house-listing: view house listings with photos, descriptions, price, and links to contact landlords to secure the nest
homepage-top: : showcases out branding, navigation bar, and introduction to help THUNDERBIRDS find their dream residence/nest.

The inspiration for Nest Finder came from the unique challenges students face when searching for affordable and convenient housing near their universities. Many students struggle to find reliable information on rental properties that suit their specific needs, such as proximity to campus, affordability, and access to public transportation. We aimed to create a platform that addresses these pain points by providing a centralized and student-focused housing search tool.

Nest Finder is a web application designed to help students find housing near their universities. It aggregates listings from various rental marketplaces and provides detailed information on each property, including rent prices, distance from campus, utilities, and amenities. The platform also offers filters tailored to students, such as budget ranges, room types, and lease terms, to simplify the search process.

A significant challenge we encountered was integrating APIs from different rental marketplaces. Each marketplace had its own API structure and data format, making it difficult to standardize the data for our platform. Additionally, some APIs had limitations on data retrieval rates, which required us to implement efficient caching and data synchronization mechanisms. Ensuring data consistency and handling errors from third-party APIs also posed considerable difficulties. We also struggled with making the login exclusive for UBC students as we didn't have access to active CWLs and passwords.

Even though we couldn't completely overcome the API integration challenges, we made substantial progress in standardizing the data we could access. We also succeeded in creating a user-friendly interface that allows students to search for and filter housing options efficiently. Our team's ability to work through complex data issues and maintain a functioning platform despite these obstacles is something we take pride in.

We learned a great deal about the complexities of API integration, especially when dealing with inconsistent data formats and limitations imposed by third-party services. This experience highlighted the importance of robust error handling, data normalization, and the need for clear communication with API providers. Additionally, we gained insights into the importance of flexibility in design to accommodate ongoing technical challenges.

Moving forward, we plan to focus on improving the API integration by exploring alternative data sources and potentially partnering directly with landlords or student housing providers to reduce dependency on external APIs. We will also work on enhancing the platform with additional features, such as user reviews and property alerts, to provide even more value to students. Continuous iteration and feedback will be essential as we refine the platform and address the remaining technical challenges.