AgriViT-NLP: A Multi-Modal Framework for Plant Disease Detection and Farmer Query Understanding

Plant diseases pose a serious threat to global food security by reducing crop yield and quality. To improve detection, a multi-modal diagnostic framework is proposed that combines Vision Transformers (ViTs) for image-based disease classification with Natural Language Processing (NLP) for symptom description and treatment recommendations. The system supports multilingual interaction and generates automatic disease reports, making it accessible to diverse farming communities. By integrating ViT and NLP, the model offers higher diagnostic accuracy and interpretable, farmer-friendly support. Designed for real-world use, it can be deployed on mobile and IoT platforms, enabling smart, interactive decision-making in precision agriculture.