Inspiration

The recent devastation caused by hurricanes like Hurricane Milton has highlighted the importance of informed decision-making for homeowners and buyers. Many people are unknowingly purchasing homes in areas at high risk for natural disasters, without fully understanding the long-term financial and personal impact.

Use Case

Haven helps users assess whether a property is worth buying by analyzing natural disaster risks in the area and comparing them with home prices. It provides a risk-to-price ratio, offering users an easy way to make informed decisions on real estate investments.

Development

We developed the frontend using React for dynamic user interaction and Flask for the backend to handle API requests. The app integrates Zillow’s property data with disaster-related datasets, ensuring real-time insights. Users can input property URLs, and Haven displays essential information like home price, ZIP code, and risk assessments.

Challenges

We encountered CORS issues during API integration and had to carefully manage data extraction from complex property URLs. Ensuring consistent and accurate data delivery was also challenging, especially when handling multiple data sources simultaneously.

Accomplishments

We’re proud of building a fully functional web app within a limited time, seamlessly integrating different APIs, and offering users a meaningful way to assess real estate risks. Overcoming technical challenges like CORS errors and refining the app's design were significant achievements.

Lessons

Through this project, we sharpened our skills in React, Flask, and API management. We also learned how to troubleshoot complex issues like preflight requests and how to work efficiently under tight deadlines, improving our collaboration and problem-solving abilities.

What's Next?

Our next steps include adding more data sources for enhanced accuracy, improving the user interface, and implementing machine learning models to predict future risks.

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