| Autor: |
Assayag, Yuri, Souto, Eduardo, Barreto, Raimundo, Carvalho, Moises, Pazzi, Richard, Fernandes, Horácio |
| Zdroj: |
Computing; Jan2025, Vol. 107 Issue 1, p1-22, 22p |
| Abstrakt: |
Global positioning systems have proven effective in outdoor environments, but encounter challenges in indoor applications due to the absence of direct line-of-sight with satellites. To address this limitation, novel methods are emerging to navigate obstacles in indoor settings, with a focus on achieving precise tracking at reduced costs. Indoor Positioning Systems (IPSs) based on Received Signal Strength Indicator (RSSI) are widely adopted because of their cost-effective implementation. This work introduces a new IPS that utilizes Bluetooth Low Energy (BLE) technology and RSSI in a log-distance signal propagation model optimized by a genetic algorithm to improve the positioning estimation of mobile devices. Real-time Genetic Algorithms (GA) are employed to dynamically adjust the parameters of the Signal Propagation (SP) model, taking into account the variable wave propagation characteristics in different indoor regions. This results in superior performance when compared to the traditional approach of using fixed values in the propagation model for the entire scenario. To assess the effectiveness of our Genetic Algorithm-based SP-IPS (GASP-IPS), we conducted experiments in a real indoor environment comprising multiple rooms. The results indicate that our solution can achieve 2.52 m average error, without the need for significant pre-deployment efforts. [ABSTRACT FROM AUTHOR] |
| Databáze: |
Complementary Index |
| Externí odkaz: |
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