Car IQ

Car IQ empowers college students to confidently navigate car-related decisions independently, offering essential tools and streamlined learning to make informed choices.

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Inspiration

We wanted to help college students gain independence and make informed car-related decisions without relying on parents or guardians. Navigating the car-buying process can be overwhelming, with too many technical details and confusing options. This idea came from our own personal struggles to find a car that fit our lifestyle and needs, and we realized many students face the same challenge. That’s why we created Car IQ, to simplify the process and empower students to take control of their car-buying decisions.

What it does

Car IQ is a chatbot-based app that simplifies car-related decisions for our users. The chatbot can answer questions about Toyota cars, perform detailed data analysis, and offer personalized recommendations. It provides information on car models from 2021-2025, such as fuel efficiency, eco scores, and greenhouse gas emissions. Users can compare car models, analyze trends, or filter cars based on specific criteria. Additionally, the app includes a lifestyle quiz that recommends a car to the user based on their driving habits and preferences, such as their interest in electric vehicles and city versus highway driving.

How we built it

We used the storyboard feature within Xcode to design the app's layout and framework. From there, we connected the different elements of the framework to the Swift code editor. We further coded the chatbot to be able to remember the responses that the user is entering and create a level of interactivity within the different features of the app. We used Python for the back-end development and integrated SambaNova API for the AI chatbot feature. We created a function to read the file and then used the API key to call the AI model user activity. We used the SambaNova API to analyze data and return a detailed analytical response based on the data provided by Toyota whenever the user prompts a question. We then converted the Python code to Swift to ultimately have the whole app up and running.

Challenges we ran into

We faced several challenges during development, including connecting the front-end and back-end, working with the Sambranova API, setting up the Android emulator, and designing the app interface using Figma. This eventually led us to completely scrap working with ReactNative, Figma, and Andriod Studio and instead just focus our attention on programming in Swift within Xcode for the front-end design and Python with SambaNova API for the back-end code.

Accomplishments that we're proud of

We’re proud of designing a fully working app within 24 hours as first-time hackers. We were able to use Swift to create an interactive front-end and integrated Python with the SambaNova API for the back-end. We’re also proud of the idea behind Car IQ and all the features we came up with to make it helpful and unique for college students.

What we learned

We learned how to integrate APIs, design intuitive user interfaces, and connect front-end and back-end systems. We also gained experience using Android Studio, Figma, XCode, and Swift, as well as problem-solving skills when tackling technical challenges. We also learned to be resilient in the toughest of situations. We learned that things don't always have to work out the first time, and it's ok to start over and take a different direction than originally planned.

What's next for Car IQ

In the future, we plan to expand the chatbot to support more car brands, add real-time car maintenance alerts, and improve the recommendation survey with more detailed lifestyle questions. We also want to make the app’s data analysis even better, giving users deeper insights into different car models and trends to help them make more personalized, data-driven decisions.

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