SMART AGRICULTURE MANAGEMENT SYSTEM USING MACHINE LEARNING CLASSIFICATION ALGORITHMS

Abstract

India being an agricultural country, the most part of economy is depends on yield growth.
Agriculture, is largely depends on rainwater, and also depends on diverse soil parameters namely
nitrogen, phosphorous, potassium and weather aspects like temperature, rainfall etc. The
technological growth in agriculture will increase the crop productivity. Remote sensing systems
like IOT systems are being more widely used in smart farming systems, these systems produce
generous amount of data. Machine learning is an emerging research filed to predict the crop based
on the patterns of the data. The proposed system will integrate the IOT sensors like Ph., Moisture,
Rainfall, Temperature and Humidity sensors observe the data from those sensors and applying
machine learning algorithms: Logistic Regression, Decision Trees, Random Forest, and GDBoost.
A prediction of most suitable crops according the current environmental is made. This work gives
a better prediction for the farmers to plant which kind of crops to their farm field based on above
mention parameters to improve the productivity of Smart Farming.