Agricultural Sustainability Index Tool (ASIT)

Inspiration

Previous Computer Vision (CV) innovations promoting agricultural sustainability.

What it does

Provides an objective assessment on the carbon footprint of food products using common ingredients and their CO2 emissions equivalent, revealing a product's relative carbon footprint as an objective function of its makeup, to help consumers make climate-conscious choices.

How we built it

Using Tensor Flow and Android Studio, we aspired to create a mobile tool that scans image-to-text and isolates ingredients present to evaluate relative carbon footprint.

Challenges we ran into

As beginners navigating app development, and ultimately worked with a template for TensorFlow Lite OCR. Our goal from here was to integrate computer vision, a task which we aspired to achieve but ultimately did not include due to constraints on time.

Accomplishments that we're proud of

Learning about CV, wire-framing the prototypes, compiling data for CO2eq/g for different ingredients, and drafting an algorithm for ingredient assessment.