AI and ML for Enhancing Crop Yield and Resource Efficiency in Agriculture

In this study, we investigate how AI and ML might revolutionize the agricultural industry, particularly with regard to increasing crop output while decreasing input costs. Applying AI and ML technology has promise in a society struggling with population increase, climate change, and resource constraints. This study highlights the practical advantages of AI and ML in agriculture via a well-crafted research process, including data gathering, model creation, and assessment. The results show that AI and ML models are useful for forecasting agricultural yields, identifying illnesses, allocating resources efficiently, and assisting farmers with decision-making based on empirical evidence. Results like this highlight the importance of these technologies in advancing goals of efficiency, sustainability, and food safety. Additionally, the study acknowledges the significance of addressing ethical problems in AI deployment, guaranteeing equal access to these advancements. We should expect to see more research into cutting-edge methods, Internet of Things (IoT) integration, and accessible tools for subsistence farmers as we go further in the use of AI and ML in the agricultural sector. The full promise of AI and ML in designing a resilient, productive, and sustainable agricultural future requires collaborative efforts across stakeholders. In the struggle to feed the globe while protecting its resources, this study shines a bright light of optimism.