Optimizing Smart Agriculture: Integrating Queuing Theory and IoT for Enhanced Resource Management and Efficiency

This paper investigates the integration of queuing theory with smart agriculture, utilizing the Internet of Things (IoT) to refine resource management and improve efficiency. By applying queuing models, we tackle key agricultural issues, including scheduling irrigation to avoid system overloads, optimizing machinery and equipment use, and enhancing crop harvesting and processing. The study also demonstrates how queuing theory can prioritize livestock care, manage real-time data processing, and streamline supply chain logistics. We model smart agriculture processes using queuing theory and solve the corresponding systems with the Supplementary Variable Technique, deriving comprehensive performance measures. This approach not only reduces wait times and minimizes resource waste but also increases productivity and sustainability, providing a robust framework for modern farming practices while supporting environmental conservation.