🌱 This project aims to automate plant health monitoring using computer vision and deep learning. It focuses on accurate disease detection and classification in plants through rigorous data preprocessing and robust model selection.

Monitoring Plant Health and Diseases for Sustainable Agriculture using CNN

Defra Digital: Plant Health Export Service

A lightweight Python deep learning framework for precision agriculture. It leverages a CNN autoencoder to detect mixed pixels in thermal images, enabling early crop disease detection with robust metrics (MPP, SSIM, MSE) and scalable design.

Deep learning model to detect plant diseases from leaf images using CNNs and the PlantVillage dataset. Helps improve early crop disease diagnosis for agriculture and sustainability.

Research about collective action problems in plant health

🌿 AgroMind - AI-Driven Plant Health Advisor A smart Flutter app that helps home gardeners detect plant diseases, receive AI-driven care tips, and engage in a community for plant enthusiasts.

Helping smallholder farmers make smarter fertilizer decisions through deep learning–based nutrient diagnosis.

This project was developed as part of an academic module, focusing on delivering an innovative solution to monitor plant health in real time. Leveraging IoT sensors, AI models, and a responsive Progressive Web App (PWA), the system provides users with insightful data on plant environments and directs them to nearby agricultural centers.