Abstract
Agriculture is a crucial profitable motorist. It is the main basis for the entire human life. Life cannot be imagined without agriculture. It is a source of livelihood. Everyone should pay attention to agriculture in the society. Agriculture plays an important role in improving the economy. With the rise in worldwide population farmers are facing problems in increasing the production of crops by choosing unsuitable crop for there field without knowing the field status. For increasing growth of crops IoT-smart agriculture improves the entire farming husbandry system by covering the field characteristics and weather conditions like soil moisture, temperature, humidity,electric conductivity etc. For getting more accurate results we need to train the dataset by taking the IoT results as an input and stored in the thing speak. But for analyzing the cloud data ML algorithms are required for tested data can help in choosing of a better crop. Based on these three algorithms such as random forest, Decision tree, KNN the better accuracy algorithm is choosen from percentage comparision of algorithms then the prediction of field status is acquired and makes the farmers to estimate their harvests, plan logistics and make decisions based on it. These proposed system can estimate the field characteristics to the farmers whether it is good or bad.
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