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: Sánchez-Rodríguez, 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
Proyectos: http://www.mdpi.com/1424-8220/15/6/14809 
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
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