Utiliza este identificador para citar o vincular este elemento: http://hdl.handle.net/10553/15152
Títulos: A low complexity system based on multiple weighted decision trees for indoor localization
Autores/as: Sanchez-Rodriguez, David 
Hernández-Morera, Pablo
Quinteiro, José Mª
Alonso-González, Itziar G.
Clasificación UNESCO: 3325 Tecnología de las telecomunicaciones
Palabras clave: WLAN indoor localization
Weighted decision trees
Received signal strength
Orientation
Sensor fusion
Fecha de publicación: 2015
Revistas: Sensors 
Resumen: Indoor position estimation has become an attractive research topic due to growing interest in location-aware services. Nevertheless, satisfying solutions have not been found with the considerations of both accuracy and system complexity. From the perspective of lightweight mobile devices, they are extremely important characteristics, because both the processor power and energy availability are limited. Hence, an indoor localization system with high computational complexity can cause complete battery drain within a few hours. In our research, we use a data mining technique named boosting to develop a localization system based on multiple weighted decision trees to predict the device location, since it has high accuracy and low computational complexity.
URI: http://hdl.handle.net/10553/15152
ISSN: 1424-8220
DOI: 10.3390/s150614809
Aparece en la colección:Artículos

Archivos en este elemento:
Archivo Descripción TamañoFormato 
sensors-15-14809.pdfArtículo principal1,13 MBAdobe PDFObserva/Abre
Muestra el registro completo del elemento

Citas SCOPUSTM   

15
actualizado el 21-feb-2019

Citas de WEB OF SCIENCETM
Citations

15
actualizado el 20-feb-2019

Vista de página(s) 50

28
actualizado el 21-mar-2019

Descargar(s) 50

3
actualizado el 21-mar-2019

Google ScholarTM

Verifica

Altmetric


Este elemento está sujeto a una licencia Licencia Creative Commons Creative Commons