Enhancing Localization Accuracy in Industrial Indoor Environment using Metaheuristic Algorithm

In an indoor industrial setup, it is important to locate the sensors accurately but in the course of implementing, the expense of localizing the sensors concurrently escalate with it. In this paper, the authors proposed a deployment scheme for the active anchor ground nodes (AGrN DV-GCMBO) DV-hop based localization technique. The localization accuracy is enhanced using an evolutionary algorithm, monarch butterfly optimization with greedy strategy and crossover operator (GCMBO) which provided sub-optimal deployment position for the anchor nodes. The scheme is simulated using the radio irregularity model (RIM) sensing model to recreate the propagation of signal in an indoor industrial environment. The results validated that the proposed scheme outperformed the scheme using classic monarch butterfly optimization algorithm (MBO).