Kisan Mitra: A Data Analytic Based Prototype for Avoiding Crops Price Crash

Abstract

Price crash is an imminent issue faced by farmers in our country.Farm crisis has been faced owing to worst price slumps in 18 years at a point in time the previous year. Analyzing the various factors affecting cultivation and price crash like previous trends in demand, supply, exports of various kinds of crops will help us forecast beforehand when can a price crash situation arise. This will help in alarming the farmers regarding the same so that they can cultivate the crops accordingly. In our work we have proposed to use machine learning to forecast price crash and display them in an explicitly understandable format which could help in the generation of doable preventive measures.There would be conception of clustering methodology along with machine learning algorithms. The Performance of each algorithm is analyzed and the best algorithm is found out which is having maximum accuracy of price crash forecasting. The basic aim is to provide with an online application the knowledge from where could be disseminated to help the farmers to understand the outer world of demand and supply of agricultural commodities which are domestically and internationally traded and thus prevent themselves from price crash situation.