Abstract
AbstractThe term “Smart Agriculture” is increasingly widespread by Machine Learning [ML] of simply apparent refractory to the digital technology. In the field of agriculture soil moisture, prediction is more beneficial to farmers. Health is analyzed by nutrients present in surface of soil. Nutrients are phosphorus, potassium, and nitrogen play an important role for productivity of crops. For crop yield, soil moisture is vital to grasp to influence hydrological and agricultural process to the interaction between the atmosphere and land. In this paper, distinctive machine learning techniques utilized in foreseeing the soil type and soil moisture parameters are examined. This study starting for exploiting and comparing from soil moisture parameters for crop harvest by various machine learning techniques to suggest which fertilizer and crop are suitable to invest. The novelty of this paper is based on various regression algorithms are giving accuracy for the nutrients present in soil for productivity.KeywordsSoil moistureParametersRegression
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