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    ARTICLE

    Enhanced Fingerprinting Based Indoor Positioning Using Machine Learning

    Muhammad Waleed Pasha1, Mir Yasir Umair1, Alina Mirza1,*, Faizan Rao1, Abdul Wakeel1, Safia Akram1, Fazli Subhan2, Wazir Zada Khan3

    CMC-Computers, Materials & Continua, Vol.69, No.2, pp. 1631-1652, 2021, DOI:10.32604/cmc.2021.018205

    Abstract Due to the inability of the Global Positioning System (GPS) signals to penetrate through surfaces like roofs, walls, and other objects in indoor environments, numerous alternative methods for user positioning have been presented. Amongst those, the Wi-Fi fingerprinting method has gained considerable interest in Indoor Positioning Systems (IPS) as the need for line-of-sight measurements is minimal, and it achieves better efficiency in even complex indoor environments. Offline and online are the two phases of the fingerprinting method. Many researchers have highlighted the problems in the offline phase as it deals with huge datasets and validation of Fingerprints without pre-processing of… More >

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