Weather-Based Crop Prediction Using Big Data Analytics

Abstract

Weather forecasting is an important and indispensable procedure in peoples' day-to-day lives, it evaluates the alteration happening in the current condition of the atmosphere. The major goal of this project is to create a weather-based crop prediction system to predict the crops based on weather forecasting using big data analytics. In this project, the authors gather and analyze data based on temperature, rainfall, soil, seed, crop production, humidity, and wind speed to assist farmers in improving agricultural yields. The data is first preprocessed in a Python environment, and then the MapReduce framework is used to further analyze and process the massive amount of data. Second, based on MapReduce findings, k-means clustering algorithm is used to produce a mean result on the data in terms of accuracy. After that, the authors examine the link between crops, rainfall, temperature, soil, and seed type using bar graphs and scatter plots.