<![CDATA[Crop diseases are one of the main problems facing the farming sector. Detecting plant diseases using some automatic techniques is advantageous because it recognizes problems early and eliminates a significant amount of monitoring effort on massive farms. Numerous investigators have created various metaheuristic optimizing and an innovative technique for deep learning to recognize and classify plant illnesses. This research analyzes many IoT-based methods for automated plant disease identification and detection. The automatic module for detecting plant diseases provides data to a sink node that the system maintains to facilitate IoT-based monitoring. Numerous methods based on plant disease and computer vision exist. Thirty three papers in all are examined here. This research also offers a thorough understanding of how to enhance IoT-integrated plant disease detection and identification capabilities. In addition to this, various problems and research gaps are noted along with potential research.]]>
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