Crop and Fertilizer recommenndation system

Agriculture And Artificial Intelligence

The impact of climate change in India, most of the agricultural crops are being badly affected in terms of their performance over a period of the last two decades. Predicting the crop yield in advance of its harvest would help the policy makers and farmers for taking appropriate measures for marketing and storage. This project will help the farmers to know the yield of their crop before cultivating onto the agricultural field and thus help them to make the appropriate decisions. The results of the prediction will be made available to the farmer. Thus, for such kinds of data analytics in crop prediction, there are different techniques or algorithms, and with the help of those algorithms we can predict crop yield. Random forest algorithm is used. In India, there are many ways to increase the economic growth in the field of agriculture. Data mining is also useful for predicting crop yield production. Generally, data Mining is the process of analyzing data from various viewpoints and summarizing it into important information. Random forest is the most popular and powerful supervised machine learning algorithm capable of performing both classification and regression tasks, that operate by constructing a multitude of decision trees during training time and generating output of the class that is the mode of the classes (classification) or mean prediction (regression) of the individual trees. Agriculture is the backbone of the Indian economy. In India, agricultural yield primarily depends on weather conditions. Rice cultivation mainly depends on rainfall. Timely advice to predict the future crop productivity and an analysis is to be made in order to help the farmers to maximize the crop production of crops. Yield prediction is an important agricultural problem. In the past farmers used to predict their yield from previous year yield experiences. Thus, for this kind of data analytics in crop prediction, there are different techniques or algorithms, and with the help of those algorithms we can predict crop yield. Random forest algorithm is used. Using all these algorithms and with the help of inter-relation between them, there are a growing range of applications and the role of big data analytics techniques in agriculture. Since the creation of new innovative technologies and techniques The agriculture field is slowly degrading. Due to these inventions, people are concentrated on cultivating artificial products that are hybrid products, where they lead to an unhealthy life.

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