kumoh national institute of technology
Networked Systems Lab.

Danielle Jaye Agron, Jae-Min Lee, and Dong-Seong Kim, "Enhancing Localization Accuracy in Indoor Industrial Environment using Metaheuristic Algorithm" 2020 ICTC, Oct. 21 - 23, Jeju, Korea (N8) (A)
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Date : 2020-06-07
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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. So in this paper, the authors proposed a RSS localization technique optimized by the meta-heuristic Monarch Butterfly Optimization with greedy strategy and crossover operator (GCMBO) to probe the sub-optimal position of the beacon nodes while minimizing the localization error. The authors analyzed the the proposed idea in terms of the cost effectiveness by evaluating the ratio of anchor nodes in the area that produces the highest accuracy. The simulation results validated that the proposed scheme outperformed the existing schemes.