WISER- A CHATBOT FOR FARMERS IN KERALA

Abstract

Farmers face many challenges in managing their crops, including crop diseases, - and weather fluctuations. These challenges can result in significant losses and decreased produc tivity. The proposed project aims to develop a machine learning-based chatbot for farmers to provide them with assistance in crop management. The chatbot will be designed to answer questions related to crop diseases, fertilizers, pesticides, and other agriculture-related topics. The chatbot will be powered by deep learning algorithms that can understand and respond to natural language queries. By providing quick and personalized solutions to farmers’ queries, the chatbot will reduce the time and effort required to find relevant information, and help farmers to overcome the challenges they face in crop management. The chatbot system will be powered by a deep learning model that can understand and respond to natural language queries. The model will be trained on a large dataset of agriculture-related topics and will use techniques such as neural networks and natural language processing to understand and respond to farmers’ queries accurately. The model will continually learn from its interactions with farmers, improving its responses and recommendations over time. In conclusion, the proposed machine learning-based chatbot system aims to provide farmers with quick and personalized solutions to their crop management challenges. By reducing the time and effort required to find relevant information, the chatbot system can help farmers to make data-driven decisions and increase their productivity. The deep learning model used in the chatbot system can understand and respond to natural language queries accurately, enabling farmers to interact with the system easily. We believe that our proposed chatbot system will be a valuable tool for farmers and agricultural stakeholders, helping to address the challenges faced by the agriculture sector and sustainably feed our growing global population