Green Scan

Inspiration:

We wanted to explore how sustainability can be integrated into our everyday lives, especially in the way people consume food and reduce plastic waste. Many consumers want to make better choices but lack clear, accessible information about the environmental impact of the products they use daily and our goal was to solve this problem.

What it does:

Green Scan is a web-based platform that helps users make more sustainable consumption choices.

Users can scan the barcode of food items to receive a “green score” that reflects environmental impact and plastic usage.
We use Open Food Facts as a reliable data source to validate product information.
For items without barcodes, our AI-powered image recognition system identifies products and provides similar insights.
A daily streak system that encourages consistent engagement and accountability.
Our users receive alternative recommendations for products with low sustainability scores.
The platform tracks user activity and generates an overall sustainability score.
A recycling tracker rewards users with points for sustainable disposing and recycling habits.
Includes a dark/light mode toggle that is easily accessible and user preference.

How we built it:

We collaborated using GitHub, along with tools like Cursor and Google Stitch.
We worked on the frontend and backend development, and all other considerations we could miss simultaneously to maximize efficiency.
We integrated the Open Food Facts API as our primary data source.
Our barcode scanner was connected to an LLM-based system to match and verify product data.
We developed features like streak tracking and scoring systems that would be more user engaging and interactive.
We implemented a secure user authentication and data storage.
We also built an image recognition system for non-barcoded items.
Designed a flexible UI with a seamless dark mode toggle.
Simplified scoring rubric to make them more intuitive and user-friendly.

Challenges we ran into:

We had difficulty implementing accurate image recognition.
We encountered inconsistencies with dark mode functionality.
Initial issues with real-time data updates on the homepage about customer consumption.
A major site crash when integrating a vulnerability-checking feature.

Accomplishments that we're proud of

Successfully debugging and recovering from a website crash.
Building a functional AI image recognition system.
Fully realizing our original vision and upgrading it with all the key features implemented.
Our strong teamwork, communication, and collaborative problem-solving.

What we learned

How to rapidly develop and implement innovative ideas.
The importance of adaptability and problem-solving in real time.
How to collaborate efficiently as a team under time constraints.

What's next for Green Scan

Our next goal is to expand Green Scan into a mobile application, making it even more accessible for everyday use. We also plan to enhance and broaden our database to support more products globally helping more people make sustainable choices and help our environment. In addition, we aim to collaborate with external platforms, such as Noom and Weight Watchers, to integrate sustainability insights into popular calorie-counting and wellness apps, allowing us to expand our reach and impact.