A Dual-Module Vision-Language AI Framework for Intelligent Decision Making in Smart Agriculture

Providing timely and correct agricultural support to the farmers remains a major problem since not many people can access qualified knowledge and early diagnosis of the crops. A smart agriculture assistant powered by AI can allow farmers to get access to insights by both text-based and image-based agricultural query in a single interface. Image preprocessing and visual analysis are automated to process plant or crop images that could contain evidence of potential disease or crop conditions, whereas text queries are read to detect intent by the farmer in terms of treatment, fertilization, and prevention. The knowledge and recommendation repository is centralized and provides crop specific, disease symptoms and advisory information to aid in informed decision making. The system combines visual and written know-how to come up with easy-to-understand and farmer-friendly explanations and recommendations that are actionable. This strategy enhances the accessibility of agricultural advice, early intervention and leads to increased productivity and sustainable agricultural activities.