Revolutionizing Agriculture IoT and Random Forest Algorithm for Crop Monitoring and Disease Prediction

Abstract

This research about presents a groundbreaking approach to revolutionize farming through the integration of Web of Things (IoT) innovation and progressed machine learning calculations. Centering on the improvement and execution of an IoT-based edit checking framework coupled with the Random Forest calculation for malady expectation, the ponder points to improve agrarian hones and relieve trim misfortunes caused by infections and natural components. Real-time information collection from IoT sensors sent in rural areas empowers comprehensive checking of vital natural parameters such as temperature, mugginess, soil dampness, and light concentrated. The Random Forest calculation analyzes this information to precisely foresee trim maladies, giving ranchers with significant bits of knowledge for proactive illness administration. Test comes about illustrate the adequacy of the proposed approach, with the Random Forest show accomplishing an exactness of 92%, exactness of 93%, review of 91%, and F1-score of 92%. These comes almost defeat customary methodologies and existing explore works, highlighting the potential of IoT and machine learning for optimizing alter proficiency and ensuring around the world food security.