Plant health is critical to food security, yet disease diagnosis remains a challenge for many farmers and learners due to limited access to expert agronomists. PlantAid solves this problem by using artificial intelligence to detect plant diseases from leaf images with impressive accuracy.

Access the tool here: https://plant-aid-client.vercel.app

How It Works

Users upload or capture a photo of a plant leaf through the PlantAid web app. Behind the scenes, a Convolutional Neural Network (CNN) model analyzes the image and predicts the disease type. The system then displays the diagnosis along with supportive guidance.

This seamless workflow turns a smartphone into a powerful diagnostic device, making advanced plant disease detection accessible without specialized equipment.

Impact & Use Cases

• Empowers small‑scale farmers: Provides near‑instant diagnostics, helping farmers take timely action to protect crops.
• Educational tool: Students and learners use PlantAid to understand plant pathology and machine learning in action.
• Research platform: Enables further experimentation and model improvements in plant health detection.

Outcomes

• Achieved high detection accuracy across diverse leaf disease datasets.
• Delivered a simple UX that doesn’t require technical expertise.
• Supported by a scalable backend that can expand with more plant classes over time.

Technology Stack

• AI / ML: Python, TensorFlow, Keras (CNN model)
• Frontend: Next.js
• Deployment: Vercel, Hugging Face
• Backend: FastApi

Future Potential

PlantAid sets the foundation for localized disease models, multilingual support, and field‑ready mobile integration. With community contributions and dataset expansion, it could become a staple tool in digital agriculture.