Leveraging AI in cloud computing to enhance nano grid operations and performance in agriculture

Abstract

The agricultural industry is critical to guaranteeing food security and sustainability, yet technological improvements have created new opportunities for enhancing farming operations. Nano-grids, or small-scale decentralized energy systems, are a viable response to agriculture's energy challenges.This study aims to investigate the integration of AI technologies into cloud computing frameworks to empower agricultural nano-grids. We propose Dragon Fruit Fly Optimization algorithms (D-FF) for energy management in Nano-grids operations with sustainable farming technology.The proposed approach's efficacy is evaluated using simulations and real-world situations in agricultural environments.The results show that the nano-grid supports agricultural activities as well as improves Accuracy (96 %), F1-Score (93 %), Precision (91 %), and Recall (92 %) with less energy wasted along with lower operating expenses.By developing smart agriculture techniques, more dependable and effective energy management in the agricultural sector is made possible by the results.