Renewable Energy in Agriculture: Enhancing Aquaculture and Post-Harvest Technologies with Solar and AI Integration

Abstract

Renewable energy, particularly solar energy, is an important component of sustainable agriculture because it provides energy-efficient and ecologically friendly alternatives to traditional techniques. AI reduced waste and produced predicted insights, improving agricultural operations. This review focuses on how solar energy and artificial intelligence are being used in aquaculture and post-harvest technologies. Aquaculture uses AI-driven systems to monitor real-time water quality and fish health, enhancing productivity by reducing mortality rates and minimizing environmental impact. AI algorithms optimize the utilization of sun dryers and cold storage units, reducing post-harvest losses by over 30% and ensuring high-quality produce by minimizing waste. The paper discusses the economic and environmental effects of various technologies, ranging from the high initial cost and existing constraints to the potential for decentralized energy networks and data-driven optimization. This analysis brings out the key trends, gaps, and future opportunities in integrating solar and artificial intelligence technologies for resilient, sustainable, and energy-efficient agriculture. The study establishes the groundwork for future developments in sustainable agriculture by highlighting the important implications for energy efficiency, climate resilience, and global food security.