Performance Analysis and Modeling of Monitoring Systems for Sustainable Agriculture

This study focuses on evaluating the performance of monitoring systems designed to address challenges in sustainable agriculture, emphasizing resource management and timely decision-making. The proposed model employs a queuing network framework to analyze system performance, identify bottlenecks, and enhance monitoring processes. By assessing resource requirements, the system is designed to meet strict Service Level Agreement (SLA) standards, particularly concerning response times, which are critical for agricultural efficiency. To validate the proposed model, discrete event simulation is conducted using the Java Modeling Tool (JMT), replicating real-world agricultural scenarios. These simulations provide insights into the system’s reliability, scalability, and operational effectiveness under varying conditions. This research aligns with environmental sustainability goals by enabling precise resource management and optimizing monitoring processes, which contribute to reduced waste and improved agricultural productivity. The model’s comprehensive evaluation ensures it can effectively support decision-making in dynamic agricultural environments. By addressing critical operational challenges, this study provides a roadmap for developing robust and efficient monitoring systems tailored to sustainable agriculture. The findings offer valuable insights for future advancements in monitoring technologies, contributing to enhanced productivity while mitigating environmental impacts in the agricultural sector.