Inspiration
Plants can get sick without us noticing until the damage is already serious. We wanted to make plant care easier for everyone, especially people who don't know much about plant diseases.
That idea led us to build PlantDoctor — a simple AI-powered tool where anyone can upload a picture of a plant and get a quick diagnosis and helpful care suggestions.
What it does
PlantDoctor analyzes a photo of a plant and identifies possible diseases or problems. It then provides an easy-to-understand explanation and suggestions to help the user take better care of the plant.
The goal is simple: make plant diagnosis accessible to everyone, not just experts.
How we built it
We built the web application with a modern web interface and connected it to an AI model for image-based plant diagnosis. The AI runs securely on the server side, while the website provides a simple interface for users to upload a plant image and receive the result.
The project is deployed online so anyone can try it directly from a browser.
Challenges we faced
Getting the AI diagnosis working was the biggest challenge. We faced API and model compatibility issues during deployment and had to troubleshoot the AI provider, environment variables, and model configuration.
Solving those problems taught us a lot about connecting an AI service to a real web application and deploying it for actual users.
What we learned
This project helped us understand that building an AI project isn't only about the AI model. Connecting the model, handling images, securing API keys, creating a usable interface, and deploying the application are equally important.
Most importantly, we learned by actually building and fixing things instead of just reading about them.
What's next
In the future, we want to improve PlantDoctor with more accurate disease detection, more plant species, treatment recommendations, and possibly support for local languages so that more people can use it.
