Roaming the Coffee Plantations Using Grey Wolves Optimisation and the Restricted Boltzmann Machine to Predict Coffee Berry Disease

Everyone's daily regimen includes a cup of coffee. However, even tiny changes in the coffee cherries cause significant differences in coffee quality, aroma, and flavor. Deep learning is used in the suggested method to forecast Coffee Berry Disease (Colletotrichum kahawai) and increase accuracy by utilizing the coffee cherry stages dataset with parameters incorporated in the Restricted Boltzmann Machine improvement model. The Grey Wolf meta-heuristic optimization algorithm was applied in this proposed study, an optimization technique that simulates Grey Wolf hunting behavior. As a result, the efficiency of the hypothesized model will improve. Furthermore, research shows that the proposed strategy is feasible and would be used to detect and outperform existing methodologies efficiently.