Developing AI-powered Systems to Optimize Planting, Irrigation, and Harvest Processes for Increased Agricultural Productivity

Abstract

This study shows that implementing AI in farming technologies is a must-do, especially through its utilization in production, irrigation, and harvest processes. Crop production can be optimized through the use of AI-driven systems analyzing weather information, soil parameters, and historical yield data along with Smart Decisions making for improved profitability and sustainability in agriculture. The outcomes of experiments showed that irrigation, planting, and harvest functions were optimized, which caused the rise of yields, the reduction of wastage of resources, and the improvement of profit of the agricultural enterprise. Nevertheless, sector-wise obtaining and developing AI in agriculture poses challenges of accessibility and cost yet, upcoming research shall try to provide scalability and affordability innovations, which if successful with machine learning enhancement and sensor technos, bear promise of more advancement.