System model for smart precision farming for high crop yielding

Abstract

The meticulous application of Sensing and Machine Learning technology in precision farming has optimized the irrigation resources, improved the quality of crops, minimizes the risk of diseases in fields and reduces the energy consumption. The proper crop management and proper placement of seeds also controls the crop diseases as well as reduces the expenses of irrigation and pesticides etc. The diseases that can be caused in various stages are monitored by proper visual identification of the disease and the precise amount and position of spraying medicine for that plant is calculated. There is a need to build the perfect plans for the water irrigation in order to save the water (around 60% to 70%). The goal is to build solution which would reduce the cost per hectare and could also increase the yields to make farming more profitable. The proposed Smart system optimizes the crop yield by providing, yield mapping, yield monitoring, weed mapping, variable rate fertilizer, variable spraying etc. The System uses drones to gather the information for calculating the crop patterns and analyzing the field so that more area can be captured for the crop plantation in later model.