AI Based Crop Recommendations for Intensive Farming using WSN

AI’s promise in the field of researching and implementing intelligence in agricultural automation using WDN data is becoming increasingly important for developing intelligent solutions. Based on the projected rainfall, the resilience of the soil, and the history of the crop planted, a MEA is utilised in the proposed study to predict the type of crops that can be cultivated to acquire the maximum yield. Farmers will be provided with a user-friendly AGILE FARM web application to aid them in determining the sort of crop that can be cultivated depending on the specified parameters. Farmers will be given ideas on alternate sorts of crops that can be grown as a substitute to prevent the anticipated problems. Farmers can make their option depending on the available seeds, fertilizer, and cultivation history because the advice is not with one alternate crop. In the farm field and water bodies, a Wireless Sensor Network with a painless Mesh Topology will be used to collect vital metrics, which will be processed utilizing OCC boards to make precise predictions, and these data sets will be used for future forecasting. The planned work will significantly lessen the farmers’ real-time issues. When compared to other methods, the random forest machine learning algorithm gives good evaluation metrics such as R2, RMSD, MSD, MAD of 0.99, 0.22, 0.24, 0.122 with 99 percent accuracy. The farmer can acquire a satisfactory yield by planning the required crop while taking seasonal risk into account.