2016
Mendoza-Silva, Germán Martín; Rodríguez-Pupo, Luis Enrique; Torres-Sospedra, Joaquín; Huerta-Guijarro, Joaquín
Solutions for signal mapping campaigns of Wi-Fi networks Proceedings
JIIDE 2016 Barcelona (27-30/09/2016), 2016.
Abstract | Links | BibTeX | Tags: Citizen Science, Data Infrastructures, Mobile apps, Web, Wi-Fi, Wi-Fi mapping
@proceedings{mendozasolutions,
title = {Solutions for signal mapping campaigns of Wi-Fi networks},
author = {Germán Martín Mendoza-Silva and Luis Enrique Rodríguez-Pupo and Joaquín Torres-Sospedra and Joaquín Huerta-Guijarro},
url = {http://www.idee.es/resources/presentaciones/JIIDE16/2016/34_art_2_UJI_SolucionesMapeadoWiFi.pdf},
year = {2016},
date = {2016-09-27},
publisher = {JIIDE 2016 Barcelona (27-30/09/2016)},
abstract = {The boom of smart mobile devices with several types of sensors has enabled applications that engage people in collecting information about their surroundings so that they can contribute to citizen science projects. In this paper, we
address a set of software solutions that aim to enable the general public to participate in WiFi signal samples collection campaigns. We expect these solutions to be appealing for researchers working in WiFi-based indoor positioning due to the widespread presence of WiFi antennas, the popularity of smartphone able to connect to those antennas, and because it is usually required to create a WiFi fingerprint database, which is a very time-consuming activity. The solutions set addresses three step in the WiFi signal samples database creation process: The campaign planning, the WiFi signal collection and the database construction and sharing. By the end of the process, the research community is provided with sets of geo-located points whose attributes include the signal intensities of the detected WiFi access points. The solutions set that we described in this paper can be extended to include campaigns focused on measuring other physical phenomena by using other sensors found in mobile devices.
},
keywords = {Citizen Science, Data Infrastructures, Mobile apps, Web, Wi-Fi, Wi-Fi mapping},
pubstate = {published},
tppubtype = {proceedings}
}
The boom of smart mobile devices with several types of sensors has enabled applications that engage people in collecting information about their surroundings so that they can contribute to citizen science projects. In this paper, we
address a set of software solutions that aim to enable the general public to participate in WiFi signal samples collection campaigns. We expect these solutions to be appealing for researchers working in WiFi-based indoor positioning due to the widespread presence of WiFi antennas, the popularity of smartphone able to connect to those antennas, and because it is usually required to create a WiFi fingerprint database, which is a very time-consuming activity. The solutions set addresses three step in the WiFi signal samples database creation process: The campaign planning, the WiFi signal collection and the database construction and sharing. By the end of the process, the research community is provided with sets of geo-located points whose attributes include the signal intensities of the detected WiFi access points. The solutions set that we described in this paper can be extended to include campaigns focused on measuring other physical phenomena by using other sensors found in mobile devices.
address a set of software solutions that aim to enable the general public to participate in WiFi signal samples collection campaigns. We expect these solutions to be appealing for researchers working in WiFi-based indoor positioning due to the widespread presence of WiFi antennas, the popularity of smartphone able to connect to those antennas, and because it is usually required to create a WiFi fingerprint database, which is a very time-consuming activity. The solutions set addresses three step in the WiFi signal samples database creation process: The campaign planning, the WiFi signal collection and the database construction and sharing. By the end of the process, the research community is provided with sets of geo-located points whose attributes include the signal intensities of the detected WiFi access points. The solutions set that we described in this paper can be extended to include campaigns focused on measuring other physical phenomena by using other sensors found in mobile devices.