Imran Ashraf, Soojung Hur, Yousaf Bin Zikria, Yongwan Park*
CMC-Computers, Materials & Continua, Vol.68, No.2, pp. 2597-2620, 2021, DOI:10.32604/cmc.2021.016214
Abstract Predominantly the localization accuracy of the magnetic field-based localization approaches is severed by two limiting factors: Smartphone heterogeneity and smaller data lengths. The use of multifarious smartphones cripples the performance of such approaches owing to the variability of the magnetic field data. In the same vein, smaller lengths of magnetic field data decrease the localization accuracy substantially. The current study proposes the use of multiple neural networks like deep neural network (DNN), long short term memory network (LSTM), and gated recurrent unit network (GRN) to perform indoor localization based on the embedded magnetic sensor of the smartphone. A voting scheme… More >
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