RT Journal Article
T1 Continuous Space Estimation: Increasing WiFi-Based Indoor Localization Resolution without Increasing the Site-Survey Effort
A1 Hernández, Noelia
A1 Ocaña, Manuel
A1 Alonso Moral, José María
A1 Kim, Euntai
K1 WiFi indoor localization
K1 Fingerprinting
K1 Continuous space estimation
K1 Machine learning
K1 Location-based services
AB AbstractAlthough much research has taken place in WiFi indoor localization systems, their accuracy can still be improved. When designing this kind of system, fingerprint-based methods are a common choice. The problem with fingerprint-based methods comes with the need of site surveying the environment, which is effort consuming. In this work, we propose an approach, based on support vector regression, to estimate the received signal strength at non-site-surveyed positions of the environment. Experiments, performed in a real environment, show that the proposed method could be used to improve the resolution of fingerprint-based indoor WiFi localization systems without increasing the site survey effort
PB MDPI
YR 2017
FD 2017
LK http://hdl.handle.net/10347/17711
UL http://hdl.handle.net/10347/17711
LA eng
NO Hernández, N.; Ocaña, M.; Alonso, J.M.; Kim, E.	Continuous Space Estimation: Increasing WiFi-Based Indoor Localization Resolution without Increasing the Site-Survey Effort. Sensors 2017, 17, 147
NO This work has been funded by TIN2014-56633-C3-3-R (ABS4SOWproject) from the Ministerio de Economía y Competitividad and the University of Alcalá Postdoctoral Research program (30400M000.541A.640.17)
DS Minerva
RD 24 abr 2026