Prediction of crop yield using Machine Learning with integrated IoT

Abstract: One major economic force is agriculture. A healthy biosphere depends on it. Almost every area of human life is dependent on a variety of agricultural products. The needs for more food of a higher caliber are growing, and farmers must adapt to these changes. In order to increase yield in order to help with the decision of planting the appropriate crop under certain circumstances, farmers must be informed of the climatic conditions. By continuously monitoring the field, IoT-based smart farming enhances the agricultural system as a whole. It provides an extremely clear real-time observation while monitoring a number of variables, including temperature, humidity, soil, and so forth. Machine learning in agriculture is used to improve the productivity and quality of the crops in the agriculture sector. Use of appropriate algorithms on the sensed data can help in recommendation of suitable crop.

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