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Related Experiment Video

Updated: Nov 28, 2025

Magnetic Levitation Coupled with Portable Imaging and Analysis for Disease Diagnostics

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Published on: February 19, 2017

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

Letícia Fernandes¹, Sara Santos¹, Marília Barandas^1,2

¹Associação Fraunhofer Portugal Research, Rua Alfredo Allen 455/461, 4200-135 Porto, Portugal.

Sensors (Basel, Switzerland)

|November 25, 2020

Summary

This summary is machine-generated.

This study introduces a new infrastructure-free indoor positioning system (IPS) using magnetic field data and deep neural networks (DNN). The system achieves an 80% success rate, offering a promising alternative to Wi-Fi-based solutions.

Keywords:

deep neural networks fingerprinting indoor positioning systems infrastructure-free magnetic field smartphones

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Area of Science:

Computer Science
Electrical Engineering
Geophysics

Background:

Infrastructure-free indoor positioning systems (IPS) are crucial for various applications.
Existing Wi-Fi-based IPS face challenges due to Android restrictions and 5G proliferation.
There is a need for novel, infrastructure-independent indoor positioning solutions.

Purpose of the Study:

To propose and evaluate an infrastructure-free indoor positioning system (IPS) utilizing magnetic field data.
To leverage Deep Neural Networks (DNN) for accurate indoor localization.
To demonstrate the viability of magnetic field data as a primary sensing source for IPS.

Main Methods:

Collected a dataset of indoor trajectories using various smartphones.
Constructed magnetic fingerprints and extracted relevant features.
Trained a Deep Neural Network (DNN) to generate location probability maps.
Applied postprocessing techniques to identify probable location regions.

Main Results:

Achieved a Success Rate of approximately 80% on a test dataset.
Demonstrated competitive performance for a single-source sensing IPS.
Showcased the potential of magnetic field data for indoor positioning.

Conclusions:

The proposed magnetic field-based IPS offers a viable alternative to Wi-Fi dependent systems.
Magnetic field data can enhance the robustness and redundancy of multi-source IPS.
This approach addresses limitations of current infrastructure-free indoor positioning technologies.