Distributed and Parallel simulation methods for pest control and crop monitoring with IoT assistance

Abstract

In today's world, Agriculture moves toward technological advancements termed as Modern Agriculture. The usage of multiple pest control and crop management frameworks plays a significant role in crop monitoring. The existing framework faces challenges. It uses a single core Graphical Processing Unit (GPU) to handle the various sensors attached for pest control and crop monitoring system. Therefore, Distributed and parallel simulation Framework (DPSF) with the Internet of Things (IoT) Assistance is proposed for pest control and crop monitoring system. It reduces the stress on a single GPU and shares the process equally and simultaneously to the available GPUs and views data on the dashboard without crashing. The Technique will reduce the execution time. DPSF uses multi-threading concept, in which each core in GPU shares tasks to other cores. This process is done in four layers; each layer is shared to handle the specific task– Crop management, Pest detection and control, Output functions and input functions. The data is processed simultaneously and managed in an optimised and controlled fashion. Simulation analysis shows that the DPSF with IoT Assistance can classify and control pest effectively with IoT assistance.