July 30, 2025

An Autonomous Framework for Crop Monitoring and Management Using Machine Learning Techniques

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Random Forest achieved the highest accuracy at 91.2% for crop recommendations and disease prediction.
The study evaluated several machine learning algorithms for predicting crop health using diverse datasets.
An autonomous framework leverages IoT sensors and drone imagery to provide real-time insights to farmers.
Implementation focuses on enhancing agricultural sustainability by optimizing resource use and supporting decision-making.

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Analysis reveals improved crop management through machine learning, indicating better resource use in agriculture.

Lazaru et al. (2025) studied this question.

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