Text based smart answering system in agriculture using RNN.
Abstract Agriculture is an important aspect of India's economy, and the country currently has one of the highest rates of farm producers in the world. The world of agriculture is becoming increasingly serious. Delivering a high-quality product is only part of the equation in today's industry. A chatbot is a tool or assistant that you may communicate with via instant messages. The chatbot understands what you're trying to say and responds with a sensible, relevant reply or just completes the best errand for you. The goal of this project is to create a Chatbot that uses natural language processing to promote remote interaction between users/farmers and the agriculture environment. A chatbot is being developed that can answer basic questions from farmers as well as give possible agricultural knowledge and solutions. This technology assists farmers in distant areas without internet access in better understanding the crop to be cultivated based on atmospheric conditions and answering fundamental agricultural concerns. In this project we have tried implementing Multi-Layer Perceptron model and Recurrent Neural Network models on the dataset. The accuracy given by RNN was 97.83% much better comparable to MLP.