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Smart crop monitoring based on Machine Learning

Category: Embedded Projects

Price: ₹ 22880 ₹ 26000 12% OFF

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In this project, data has been collected from various sensors to propose an IoT-assisted hybrid machine learning approach for obtaining an effective crop monitoring system. Crop monitoring system here means predicting as well as detecting diseases of crops. This study is about leveraging existing data and applying regression analysis, and decision tree to predict crop diseases in diverse crops such as rice, ragi, gram, potato, and onion. Among the applied methods, SVM outperforms regression, DT methods. The training and testing accuracy of Gram has 96.29% and 95.67%, respectively.

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