| Autor: |
Galván-Tejada CE; 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. ericgalvan@uaz.edu.mx., García-Vázquez JP; School of Engineering, MyDCI, Autonomous University of Baja California (UABC), Mexicali 21100, Mexico. pablo.garcia@uabc.edu.mx., Galván-Tejada JI; Ingeniería Robótica y Mecatrónica, Unidad Académica de Ingeniería Eléctrica, Universidad Autónoma de Zacatecas 'Francisco Garcia Salinas', Zacatecas 98000, Mexico. gatejo@gmail.com., Delgado-Contreras JR; Graduate School of Engineering and Science, Instituto Tecnológico de Monterrey, CETEC South, 5th Floor, Av. E. Garza Sada 2501, Monterrey, NL 64849, Mexico. ruben.dc@gmail.com., Brena RF; Graduate School of Engineering and Science, Instituto Tecnológico de Monterrey, CETEC South, 5th Floor, Av. E. Garza Sada 2501, Monterrey, NL 64849, Mexico. ramon.brena@itesm.mx. |
| Abstrakt: |
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. |
