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

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. • To enhance the energy management in agricultural nano-grids, the study investigates the combination of AI technologies with cloud computing. • The Dragon Fruit Fly Optimization (D-FF) method is utilised for enhancing energy efficiency in environmentally friendly farming operations. • The proposed system has 96 % of Accuracy, 93 % of F1-Score, 91 % of Precision, and 92 % of Recall shows an effectiveness of the strategy and actual agricultural scenarios. • The nano-grid system supports more dependable and effective for smart agriculture practices by minimising the energy waste and operating costs.