Smart Farming - A Flexible Approach to Improve Crop Yield and Profit using Machine Learning Techniques

A smart farming system is a farm managing mechanism, which significantly increases the yield of crops by incorporating new technologies in the field of agriculture. Here we present an overview of smart farming software solutions that are recently developed. The proposed methodology works on the data mining techniques and data extracted from satellite information, the Internet, and from soil testing reports fed in the existing databases. This methodology elegantly makes use of the supervised algorithms and regression model for making decisions based on the cognizance of weather changes, season, crop influence factors such as humidity, type of soil, crop type, etc., This system can increase the productivity of fields by managing farm operations smartly. It has emerged together with the Internet of things and high-performance computing to create new opportunities to quantify and understand data-intensive processes in agricultural operational environments. Descriptively, in this work, we analyze the pollutants that cause the crop damage from the year 1980 and forecasted the pollutant like Benzene, PM levels from 2021 to 2051 on different crops. The proposed model predicts the crop life based on pesticides and the dose quantity that is used. This paper draws attention to analyzing and moderating the pesticides dosage level and helps farmers to protect the crop by moderating the dosage and fertilizer levels.