The Toyota Dream Car Finder

Recommendations based on algorithm
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Inspiration

Car shopping can be overwhelming, with dozens of models, trims, and options to consider. Many buyers struggle to find the right vehicle that fits their lifestyle, budget, and preferences. Our team wanted to simplify this process by creating a tool that combines user input with smart recommendations. Inspired by the desire to make car shopping more customizable and efficient, we built the Toyota Dream Car Finder to help users discover their ideal Toyota vehicle.

What it does

The Toyota Dream Car Finder helps users find the perfect Toyota vehicle based on their personal preferences. Users input details such as budget, vehicle size, speed preference, household needs, and commute distance. The app then uses a custom algorithm to match these preferences with the most suitable Toyota models. Users can explore recommended cars, compare options, and make decisions quickly, making the car shopping experience more personalized and efficient.

How we built it

We built the Toyota Dream Car Finder using a modern web stack. The frontend is powered by React with React Router, while the backend uses FastAPI (Python) to handle API requests and manage data efficiently. We store user inputs and car data securely in Firebase Firestore. A custom algorithm processes user preferences to recommend the most suitable Toyota models. CORS is configured to allow secure cross origin requests. This setup allows the app to deliver real-time, personalized car recommendations in a user friendly way.

Challenges we ran into

Challenges we ran into were developing the algorithm based on past datasets we could find. Finding datasets was very difficult. Additionally, integrating the frontend with the backend was another hurdle.

Accomplishments that we're proud of

We’re proud of the custom algorithm we developed. Additionally, the frontend provides a seamless and experience, allowing users to input their preferences and view recommendations effortlessly.