Optimized Adaptive Fuzzy Expert System-Based Plant Leaf Disease Prediction Model Using Data Through Internet Of Things

Abstract

Agriculture serves as the fundamental backbone of a nation, accounting for almost 50% of the global economy. Precision agriculture is crucial for assessing the condition of crops in order to identify appropriate measures for plant care. The given text is incomplete and does not provide enough information to rewrite it in a straightforward and precise manner. Please provide more context or complete the sentence. The traditional approach of predicting leaf diseases lacks stability and only offers limited accuracy in its predictions.

This study focuses on creating an enhanced module for predicting leaf illnesses with high accuracy. The module utilizes a hybrid optimization guided adaptive fuzzy expert system for disease detection. The Internet of Things (IoT) is recognized for its ability to gather real-time data. The suggested model makes use of the data acquired via the IoT framework. The data is analyzed to identify the existence of diseases in the crop, facilitated by the suggested Cat swarm-based Harris Hawks (CSHH) optimization method. The CSHH optimization method will be created by integrating the key features of the cat swarm optimization (CSO) algorithm and the Harris Hawks optimization (HHO) algorithm.