Por favor, use este identificador para citar o enlazar este ítem: https://doi.org/10.1016/j.future.2017.09.022

Registro completo de metadatos
Campo DCValorLengua/Idioma
dc.contributor.authorLopez-de-Teruel, Pedro E.-
dc.contributor.authorGarcia, Félix J.-
dc.contributor.authorCánovas, Óscar-
dc.date.accessioned2024-01-28T09:16:27Z-
dc.date.available2024-01-28T09:16:27Z-
dc.date.issued2020-06-
dc.identifier.citationFuture Generation Computer Systems, Volume 107, June 2020es
dc.identifier.urihttp://hdl.handle.net/10201/137867-
dc.description©2020. This document is the Published, version of a Published Work that appeared in final form in Future Generation Computer Systems. To access the final edited and published work see https://doi.org/10.1016/j.future.2017.09.022es
dc.description.abstractOccupancy is relevant information about key aspects, such as energy consumption or comfort management. Energy-saving and environmental quality strategies can be carried out in response to real-time facility occupancy. Some relevant solutions to measure and monitor occupancy information leverage radio-based indoor localization systems and employ Received Signal Strength (RSS) as the main source of data for location determination. However, those approaches usually require a previous training and calibration stage that involves a time-consuming and labor intensive site survey process, and which is also readily affected by environmental dynamics. In this paper, we propose a practical passive localization system for fast deployment of occupancy services able to track unmodified and heterogeneous devices after a quick and straightforward training phase. We present an experimental validation of the system that was conducted for 9 months in a lecture building of 6000 square meters with 20 classrooms and 4000 frequent users, where the existing teaching computers themselves were used as monitors to capture 802.11 traffic. In this environment, we test different representations and metrics to process the RSSI information and perform a thorough analysis of some important design parameters, which have a direct impact on both accuracy and time granularity of the localization system.es
dc.formatapplication/pdfes
dc.format.extent13es
dc.languageenges
dc.publisherElsevieres
dc.relationThis work was supported by the Spanish MINECO, as well as by European Commission FEDER funds, under grant TIN2015-66972-C5-3-Res
dc.relation.ispartofTÉCNICAS PARA LA MEJORA DE PRESTACIONES, FIABILIDAD Y CONSUMO DE ENERGÍA DE LOS SERVIDORES. OPTIMIZACIÓN DE APLICACIONES CIENTÍFICAS, MÉDICAS Y DE VISIÓN ARTIFICIAL.es
dc.rightsinfo:eu-repo/semantics/embargoedAccesses
dc.subjectBuilding occupancyes
dc.subjectWiFi signalses
dc.subjectPassive localizationes
dc.subjectHeterogeneous deviceses
dc.subjectMachine learninges
dc.titlePractical passive localization system based on wireless signals for fast deployment of occupancy serviceses
dc.typeinfo:eu-repo/semantics/articlees
dc.relation.publisherversionhttps://www.sciencedirect.com/science/article/pii/S0167739X17320083es
dc.embargo.termsSi-
dc.identifier.doihttps://doi.org/10.1016/j.future.2017.09.022-
dc.contributor.departmentIngeniería y Tecnología de Computadores-
Aparece en las colecciones:Artículos

Ficheros en este ítem:
Fichero Descripción TamañoFormato 
1-s2.0-S0167739X17320083-main.pdf3,73 MBAdobe PDFVista previa
Visualizar/Abrir    Solicitar una copia


Los ítems de Digitum están protegidos por copyright, con todos los derechos reservados, a menos que se indique lo contrario.