Development and Evaluation of a Smart Agricultural Chatbot

This research presents the development and evaluation of a farmer focused chatbot that provides real-time assistance by leveraging data from various agricultural research institutions. Using natural language processing (NLP), similarity search, and Maximum Marginal Relevance (MMR), the chatbot delivers accurate and diverse responses. Evaluation metrics, including response accuracy, speed, user satisfaction, and query resolution, highlight its effectiveness. A case study with 50 farmers revealed significant improvements in decision-making and productivity, showcasing the chatbot’s potential to enhance agricultural practices through technology.