Implementing AI-Powered Chatbots in Agriculture for Optimization and Efficiency

Agriculture is critical to the global economy, therefore the introduction of automation in this field is now an essential and rising topic internationally. Demands for food and labor are rising at an exponential rate, outpacing the capabilities of conventional farming practices. A new age of revolutionary change has been caused by the incorporation of Artificial Intelligence (AI) into agriculture. This study focuses on the development of an AI-powered Chatbot that is customized for the agricultural sector, offering assistance with crop recommendation and disease detection. The two machine learning models used to handle crop suggestions are Gaussian Naive Bayes (GNB) and Support Vector Machine (SVM). Using the VGG-16 transfer learning model, disease predictions are made. The models are evaluated thoroughly, and as a result, GNB and VGG-16 are chosen to be a part of the Chatbot's architecture. Without the need for professional knowledge, the Chatbot can help farmers select crops that are suited for cultivation and evaluate the health of their crops. The designed Chatbot is confirmed to be reliable and effective after extensive testing of its performance through various queries. By utilizing AI, we made a smart tool for effective crop management and harvesting.