Abstract
The term "smart agriculture" describes how farming is carried out in the modern day as technology develops. Application of diverse insect protection and agricultural production tactics is crucial for crop monitoring. The structure as it is now has problems. A particular core Graphical Processing Unit (GPU) is used to manage the numerous sensors connected for crop surveillance and pest management. A Parallel and Distributed Simulation Framework (PDSF) with the Internet of Things (IoT) is proposed for pest management and agricultural monitoring tools. It lessens the pressure on a certain GPU, evenly distributes the workload over all available GPUs at simultaneously, and delivers data to the dashboards even when it's broken. The procedure will decrease system performance. In the PDSF multi-threading paradigm, each GPU unit distributes workloads to specific additional cores. To carry out the various tasks, the four levels of this system—crop management, pest identification and control, output activities, and input functional areas—are distributed among them. The information is processed simultaneously and handled in an efficient and controlled manner. The proposed system improves the performance measures of 98.65%.
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