An automatic procedure for crop mapping using agricultural monitoring

Abstract

Abstract IoT and Machine Learning are emerging techniques used in existing days. Agriculture plays a vital role in human survival. Mapping crop according to the current environment is important to improve agriculture. pH sensors, dielectric soil moisture Sensors, mechanical sensors, optical sensors, electro-chemical sensors and air flow sensors are used in this proposed system to gather data about the soil and supervised Learning associated with Association algorithm are used to analyze and predict which crop maps to the soil in the present circumstances. Ensemble Technique is integrated to make accurate classification to select the type of crop. Technology combining both IoT and Machine learning are used to improve the production of the crop which proportionally helps to improve the agricultural yield.