Camera-aided region-based magnetic field indoor positioning

2016 ◽  
Author(s):  
Yichen Du ◽  
Tughrul Arslan ◽  
Arief Juri
Keyword(s):  
Magnetic Field ◽  
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.

scholarly journals THE DESIGN AND IMPLEMENTATION OF INDOOR LOCALIZATION SYSTEM USING MAGNETIC FIELD BASED ON SMARTPHONE

2017 ◽  
Vol XLII-2/W7 ◽  
pp. 379-383
Author(s):  
J. Liu ◽  
C. Jiang ◽  
Z. Shi
Keyword(s):  
Magnetic Field ◽  
Indoor Localization ◽  
Indoor Positioning ◽  
Positioning System ◽  
Localization Algorithm ◽  
External Device ◽  
Localization System ◽  
Filtering Algorithm ◽  
Coordinate Conversion ◽  
Indoor Positioning System

Sufficient signal nodes are mostly required to implement indoor localization in mainstream research. Magnetic field take advantage of high precision, stable and reliability, and the reception of magnetic field signals is reliable and uncomplicated, it could be realized by geomagnetic sensor on smartphone, without external device. After the study of indoor positioning technologies, choose the geomagnetic field data as fingerprints to design an indoor localization system based on smartphone. A localization algorithm that appropriate geomagnetic matching is designed, and present filtering algorithm and algorithm for coordinate conversion. With the implement of plot geomagnetic fingerprints, the indoor positioning of smartphone without depending on external devices can be achieved. Finally, an indoor positioning system which is based on Android platform is successfully designed, through the experiments, proved the capability and effectiveness of indoor localization algorithm.

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