Enhance Rfid Network Planning By Combining Edge Detection With Pso Algorithm

Abstract

One of the key factors influencing the degree of production performance in terms of both quantity and quality is the control of material flow during the assembly process in factories. We have conducted all of this research to examine the locations for gathering and producing materials, organizing their data, and feeding it into an algorithm to ascertain the quantity of readers and the scope of coverage because there is no automated system that provides us with the best locations for the material transfer process. This research delineates the outcomes of a multi-objective function model for the placement of RFID readers across several large-scale scenarios, intended to assess the implications of network expansion. Four distinct techniques were analyzed using the identical dataset. The dataset aimed to organize 60 tags inside the facility design based on a designated clustered distribution. Simulation results indicated that E-PSO outperformed other methods in tackling particular RNP issues, achieving significant tag coverage in reader deployment. The findings underscored the applicability and robustness of the proposed method, with its characteristics retaining exceptional approximation capabilities even in factory designs utilizing RFID systems.