A Novel Predictive Machine Learning Approach in Agricultural Field Monitoring

Abstract

Modern methods of farming are to increase the crop production through implementation of various sensors that help detecting the soil moisture, climatic conditions and effective utilization of water resources under limited and unforeseen conditions. The aim of this model is to focus on modernising the agricultural monitoring procedure by analysing the geographic conditions, implementing a low-cost device that requires no knowledge for the laymen farmers but yet increase their productivity and reduce the farming cost. The agricultural monitoring activities comprise of machine learning technique that accumulates data from sensors and can use for predictive analysis to perform field watering, remote motor on-off, detection of rainfall in the location site.