Machine Learning & Internet of Things in Plant Disease Detection: A comprehensive Review

Agriculture is crucial to the growth of every country's economy. Due to population growth, unpredictable weather, and a lack of available resources, meeting the world's food needs has become an increasingly challenging undertaking in recent years. There are a number of issues that threaten agriculture's long-term viability, but new technologies are providing farmers with a way to combat them. To effectively control agricultural productivity, it is essential to accurately diagnose plant diseases. The use of machine learning (ML) and the Internet of Things (IoT) is a relatively new development in the agricultural industry with the potential to improve crop management. Improved agricultural yields are possible with the integration of machine learning and other Internet of Thing's technologies. This study provides a comprehensive analysis of the ways in which ML and IoT have been used in the agricultural sector. Here, this study reviews IoT and ML-powered smart farming and agricultural strategies that have been tried and tested. This study suggests a new strategy for integrating ML and IoT in real-time environment.