Next Article in Journal
Fuzzy Logic-Based Guaranteed Lifetime Protocol for Real-Time Wireless Sensor Networks
Next Article in Special Issue
Saliency-Guided Detection of Unknown Objects in RGB-D Indoor Scenes
Previous Article in Journal
An Autonomous Self-Aware and Adaptive Fault Tolerant Routing Technique for Wireless Sensor Networks
Previous Article in Special Issue
VisitSense: Sensing Place Visit Patterns from Ambient Radio on Smartphones for Targeted Mobile Ads in Shopping Malls
Article Menu

Export Article

Open AccessArticle
Sensors 2015, 15(8), 20355-20372; doi:10.3390/s150820355

Infrastructure-Less Indoor Localization Using the Microphone, Magnetometer and Light Sensor of a Smartphone

1
Programa de Ingeniería de Software, Unidad Académica de Ingeniería Eléctrica, Universidad Autónoma de Zacatecas, Ciudad Universitaria Siglo XXI, Edificio de Ingeniería de Software e Ingeniería en Computación, Zacatecas 98160, Mexico
2
School of Engineering, MyDCI, Autonomous University of Baja California (UABC), Mexicali 21100, Mexico
3
Ingeniería Robótica y Mecatrónica, Unidad Académica de Ingeniería Eléctrica, Universidad Autónoma de Zacatecas "Francisco Garcia Salinas", Zacatecas 98000, Mexico
4
Graduate School of Engineering and Science, Instituto Tecnológico de Monterrey, CETEC South, 5th Floor, Av. E. Garza Sada 2501, Monterrey, NL 64849, Mexico
*
Author to whom correspondence should be addressed.
Academic Editor: Kourosh Khoshelham
Received: 2 July 2015 / Revised: 7 August 2015 / Accepted: 11 August 2015 / Published: 18 August 2015
(This article belongs to the Special Issue Sensors for Indoor Mapping and Navigation)
View Full-Text   |   Download PDF [921 KB, uploaded 25 August 2015]   |  

Abstract

In this paper, we present the development of an infrastructure-less indoor location system (ILS), which relies on the use of a microphone, a magnetometer and a light sensor of a smartphone, all three of which are essentially passive sensors, relying on signals available practically in any building in the world, no matter how developed the region is. In our work, we merge the information from those sensors to estimate the user’s location in an indoor environment. A multivariate model is applied to find the user’s location, and we evaluate the quality of the resulting model in terms of sensitivity and specificity. Our experiments were carried out in an office environment during summer and winter, to take into account changes in light patterns, as well as changes in the Earth’s magnetic field irregularities. The experimental results clearly show the benefits of using the information fusion of multiple sensors when contrasted with the use of a single source of information. View Full-Text
Keywords: indoor location; information fusion; feature extraction; feature selection; genetic algorithms indoor location; information fusion; feature extraction; feature selection; genetic algorithms
Figures

Figure 1

This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

Scifeed alert for new publications

Never miss any articles matching your research from any publisher
  • Get alerts for new papers matching your research
  • Find out the new papers from selected authors
  • Updated daily for 49'000+ journals and 6000+ publishers
  • Define your Scifeed now

SciFeed Share & Cite This Article

MDPI and ACS Style

Galván-Tejada, C.E.; García-Vázquez, J.P.; Galván-Tejada, J.I.; Delgado-Contreras, J.R.; Brena, R.F. Infrastructure-Less Indoor Localization Using the Microphone, Magnetometer and Light Sensor of a Smartphone. Sensors 2015, 15, 20355-20372.

Show more citation formats Show less citations formats

Related Articles

Article Metrics

Article Access Statistics

1

Comments

[Return to top]
Sensors EISSN 1424-8220 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top