Inspiration
Tracking calories on MyFitnessPal has been helpful, but since coming to university, carrying a food scale around has become impractical. This made it difficult to estimate portions accurately, leading to inconsistent tracking. Platemate was born out of the need for a more convenient way to log meals—one that relies on images rather than manual input.
What it does
Platemate allows users to take a picture of their meal, automatically analyzing the image to estimate calorie content and nutritional values. It simplifies food tracking by leveraging AI-powered image recognition and database lookups, reducing the need for manual portion estimations.
How we built it
We developed Platemate using a combination of computer vision and machine learning models to analyze food images. The backend relies on an SQL database to store nutritional data, while the frontend was built using a mobile-friendly framework to ensure smooth user interaction. We integrated a camera API to allow image capture and processing, making the tracking process seamless.
Challenges we ran into
One of the biggest challenges was getting the camera functionality to work reliably across different devices. Additionally, downloading and retrieving data from the SQL database presented unexpected difficulties, requiring optimization to ensure smooth performance.
Accomplishments that we're proud of
We successfully implemented an image-based calorie estimation system, significantly reducing the effort required for food logging. Overcoming technical hurdles related to database access and camera integration was another major achievement. Most importantly, we built a functional prototype that makes calorie tracking more accessible and user-friendly.
What we learned
Throughout the development process, we gained valuable insights into database management, mobile app optimization, and integrating AI-powered tools to enhance functionality. We also learned how to troubleshoot complex technical issues, improving our problem-solving skills along the way.
What's next for Platemate
Next, we plan to polish the app by refining its graphical elements and introducing additional features, such as more detailed nutritional breakdowns. We also aim to integrate a chatbot to assist users with food queries, add offline functionality for seamless tracking without internet access, and finalize the settings menu to give users more customization options.
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