Crop Guard is a project that utilizes cutting edge computer vision technology to identify unhealthy crops, enabling farmers to focus on sustainable agriculture practices. As a 220 billion dollar industry, sustainable agriculture is in clear need of innovation.

Our goal is to provide actionable, data-centric feedback that enables farmers to minimize pesticide use and empowers them to focus on sustainable agriculture principles.

We utilized Next.js, Tailwind CSS, and TypeScript for our frontend, incorporating various UI frameworks. Our backend hosts a PyTorch ML model and stores data with PostgreSQL.