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Título: Practical passive localization system based on wireless signals for fast deployment of occupancy services
Fecha de publicación: jun-2020
Editorial: Elsevier
Cita bibliográfica: Future Generation Computer Systems, Volume 107, June 2020
Palabras clave: Building occupancy
WiFi signals
Passive localization
Heterogeneous devices
Machine learning
Resumen: Occupancy 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.
Autor/es principal/es: Lopez-de-Teruel, Pedro E.
Garcia, Félix J.
Cánovas, Óscar
Facultad/Departamentos/Servicios: Facultades, Departamentos, Servicios y Escuelas::Departamentos de la UMU::Ingeniería y Tecnología de Computadores
Forma parte de: TÉCNICAS PARA LA MEJORA DE PRESTACIONES, FIABILIDAD Y CONSUMO DE ENERGÍA DE LOS SERVIDORES. OPTIMIZACIÓN DE APLICACIONES CIENTÍFICAS, MÉDICAS Y DE VISIÓN ARTIFICIAL.
Versión del editor: https://www.sciencedirect.com/science/article/pii/S0167739X17320083
URI: http://hdl.handle.net/10201/137867
DOI: https://doi.org/10.1016/j.future.2017.09.022
Tipo de documento: info:eu-repo/semantics/article
Número páginas / Extensión: 13
Derechos: info:eu-repo/semantics/embargoedAccess
Descripción: ©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.2017.09.022
Aparece en las colecciones:Artículos: Ingeniería y Tecnología de Computadores

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