IoT Based Plant Disease Detection in Smart Farming with Machine Learning Approach: A Systematic Review

Main Article Content

Ms. Uma. R. Patil, Dr. V.M. Patil

Abstract

Nowadays plant Disease Detection and controlling at early stage are important for the prevention of plant disease efficiently and precisely in the complex environment for better yield and quality crops. Recently Machine learning and deep learning methods have obtained surprising results with IoT based technology to apply them for best recognizing of Plant diseases. This review paper presents existing approaches that have been used in IoT based Smart farming with IoT and ML separately. This paper proposes a different model for plant disease detection and recognition based on machine learning and deep learning, which improves accuracy and efficiency. This paper presents a review of the various Machine Learning, Deep Learning techniques to detect plant diseases using the Internet of Things approach. This survey is to taken for future research to understand the different machine learning and deep learning techniques for identifying plant diseases to improving system performance and accuracy.


 


 

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Author Biography

Ms. Uma. R. Patil, Dr. V.M. Patil