Virtual Assistant for Farmers using Machine Learning

Abstract

Every one works hard just to earn some food and survive but these days it has been very hard to produce sufficient food for the mammoth population across the world. This was due to lack of knowledge about modern practices and technologies in agriculture which will boost the fertility of land and food production. The aim of the proposed method is to provide a virtual Assistant that enables the user to know about modern practices,efficient techniques and appropriate amount of fertilizers and water for a particular crop which functions either by text input or voice commands. The text or voice commands are converted to machine understandable language by semantic parsing technique later on the mechanism forwards to   similarity function which helps in finding out keywords and probability of them by Naive Bayes algorithm and gives the output in voice format. The proposed virtual assistant operates in regional language which stands apart from the existing models.