Price Prediction of Agriculture Commodities Using Machine Learning and NLP

Abstract

The advancement in communication technology helped a lot for people in rural India. People can access the information over internet and use the smart phone. Majority of the people in India employed with agriculture. But still the farmers are not aware or the technology development in agriculture domain. The major gap is farmers not able to get the details in their local language or the language they are able to understand. Another major issue is farmers are not getting the enough return or good price for the commodities what they produced. They are not having information about the market trend and inter market information. Due to lack of unknown future price, they are not able to take informed decision about when and here to sell their produce. In this paper we proposed a model for forecasting the commodities price using machine learning techniques such as ARIMA, SARIMA, RNN. Also, we proposed a model to build the conversation system, voice bot for Kannada a regional language of Karnataka. With this model farmers in Karnataka will get benefitted with forecasted commodity price and get the information in Kannada. To build the voice bot the Natural Language Processing techniques can be used.