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Indoor Positioning Systems (IPS) play a crucial role in various applications, including asset tracking, navigation, and context-aware services. They rely on technologies such as WiFi, Bluetooth, and Ultra-Wideband (UWB) to determine the location of devices within enclosed spaces. By leveraging Mobile Access Points (MAP) and innovative algorithms, this paper aims to overcome the limitations of traditional IPS methods, particularly in challenging environments with Non- Line of Sight (NLOS) conditions. Comparisons are made with existing approaches, including the fingerprinting technique for signal strength analysis. Results demonstrate the effectiveness of the proposed system, achieving an impressive RMSE of 0.26 m. This work contributes to bridging the gap between telecom and data processing elements, translating simulations into real-world experiences, and providing a comprehensive evaluation framework.
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DOI: 10.1109/unet62310.2024.10794712
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