A hybrid indoor positioning solution based on Wi-Fi, magnetic field, and inertial navigation

2017 ◽  
Author(s):  
Ugur Bolat ◽  
Mehmet Akcakoca
Keyword(s):  
Magnetic Field ◽  
Inertial Navigation ◽  
Indoor Positioning

scholarly journals A Comprehensive Analysis of Magnetic Field Based Indoor Positioning With Smartphones: Opportunities, Challenges and Practical Limitations

IEEE Access ◽  
2020 ◽  
Vol 8 ◽  
pp. 228548-228571
Author(s):  
Imran Ashraf ◽  
Yousaf Bin Zikria ◽  
Soojung Hur ◽  
Yongwan Park
Keyword(s):  
Magnetic Field ◽  
Indoor Positioning ◽  
Comprehensive Analysis

scholarly journals An Infrastructure-Free Magnetic-Based Indoor Positioning System with Deep Learning

Sensors ◽  
2020 ◽  
Vol 20 (22) ◽  
pp. 6664
Author(s):  
Letícia Fernandes ◽  
Sara Santos ◽  
Marília Barandas ◽  
Duarte Folgado ◽  
Ricardo Leonardo ◽  
...  
Keyword(s):  
Magnetic Field ◽  
Indoor Positioning ◽  
Test Dataset ◽  
Magnetic Field Data ◽  
Positioning Systems ◽  
Additional Information ◽  
Information Layer ◽  
Wide Range ◽  
Indoor Positioning System ◽  
New Infrastructure

Infrastructure-free Indoor Positioning Systems (IPS) are becoming popular due to their scalability and a wide range of applications. Such systems often rely on deployed Wi-Fi networks. However, their usability may be compromised, either due to scanning restrictions from recent Android versions or the proliferation of 5G technology. This raises the need for new infrastructure-free IPS independent of Wi-Fi networks. In this paper, we propose the use of magnetic field data for IPS, through Deep Neural Networks (DNN). Firstly, a dataset of human indoor trajectories was collected with different smartphones. Afterwards, a magnetic fingerprint was constructed and relevant features were extracted to train a DNN that returns a probability map of a user’s location. Finally, two postprocessing methods were applied to obtain the most probable location regions. We asserted the performance of our solution against a test dataset, which produced a Success Rate of around 80%. We believe that these results are competitive for an IPS based on a single sensing source. Moreover, the magnetic field can be used as an additional information layer to increase the robustness and redundancy of current multi-source IPS.

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