AGRO-CROP PREDICTION AND IMAGE DETECTION USING AI AND ML

The crop prediction is a major factor for the improvement of profit in smart agricultural system. The explicit crop type according to cultivation land, weather condition and previous year profit prediction is being considered from the dataset. The dataset includes attributes such as tons of production in particular area and soil nutritious repository that are used to predict the exact crop which can be cultivated in that area. These observation gives best accuracy result using data analytics techniques which predict the most profitable crops using previous year cultivation, area and tons of production from the given dataset. The logistic regression algorithm helps in classifying the crop types to the farmers with the highest accuracy rate. The Open CV technique that detects the high dimensional image of the affected plants using Pi camera. The Rover includes motor that spray the pesticides automatically for the particular interval of time when the weed image of the plant is detected. These applications can evaluate crops for disease and also provide an opted treatment plan like suggesting pesticides for the individual plant diseases. These above-mentioned technologies help farmers with solutions related to their difficulties in the region of profitable crop suggestion and weed, disease detection. So that the farmers can increase their profitable margin over a long run of time.