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Energy-Efficient Indoor Localization WiFi-Fingerprint System: An Experimental Study
In order to apply indoor localization systems in real environments it is necessary to provide an accurate location without implying a high impact on the user’s normal behaviour. To achieve this goal, in this paper, a combination of battery saving techniques with a system based on WiFi fingerprinting is proposed. This is done by transferring the location calculation workload to the server, leaving user’s mobile devices the only responsibility of making periodic WiFi network scans at dynamic intervals based on user activity, through an application running on background. There are not many studies analyzing energy consumption of existing localization systems, even though it is an important factor in real applications. In this paper, both energy consumption and accuracy are analyzed, having an energy consumption of only 0.8 Wh (having a 3.7 V battery) during a 24-hour cycle and an average localization error of 4.51 meters. Worth to mention that as computation is done on server side the system can be expanded to multiple buildings and floors. Finally, the dataset used in this paper has been published making possible to test new algorithms in the same environment. ; This work was supported in part by the Spanish Ministry of Economy and Competitiveness through the VICTORY Project under Grant TIN2017-82113-C2-1-R MINECO/FEDER R&D, UE, and in part by the Spanish Ministry of Science, Innovation, and Universities through the MICROCEBUS Project under Grant RTI2018-095168-B-C55 MCIU/AEI/FEDER,UE. ; Peer reviewed
Energy-Efficient Indoor Localization WiFi-Fingerprint System: An Experimental Study
In order to apply indoor localization systems in real environments it is necessary to provide an accurate location without implying a high impact on the user’s normal behaviour. To achieve this goal, in this paper, a combination of battery saving techniques with a system based on WiFi fingerprinting is proposed. This is done by transferring the location calculation workload to the server, leaving user’s mobile devices the only responsibility of making periodic WiFi network scans at dynamic intervals based on user activity, through an application running on background. There are not many studies analyzing energy consumption of existing localization systems, even though it is an important factor in real applications. In this paper, both energy consumption and accuracy are analyzed, having an energy consumption of only 0.8 Wh (having a 3.7 V battery) during a 24-hour cycle and an average localization error of 4.51 meters. Worth to mention that as computation is done on server side the system can be expanded to multiple buildings and floors. Finally, the dataset used in this paper has been published making possible to test new algorithms in the same environment. ; This work was supported in part by the Spanish Ministry of Economy and Competitiveness through the VICTORY Project under Grant TIN2017-82113-C2-1-R MINECO/FEDER R&D, UE, and in part by the Spanish Ministry of Science, Innovation, and Universities through the MICROCEBUS Project under Grant RTI2018-095168-B-C55 MCIU/AEI/FEDER,UE. ; Peer reviewed
Energy-Efficient Indoor Localization WiFi-Fingerprint System: An Experimental Study
Salazar González, Jose L. (author) / Soria Morillo, Luis Miguel (author) / Álvarez-García, Juan A. (author) / Enríquez de Salamanca Ros, Fernando (author) / Jiménez Ruiz, Antonio R. (author) / Ministerio de Economía y Competitividad (España) / Ministerio de Ciencia, Innovación y Universidades (España) / Salazar González, Jose L. 0000-0002-4823-3749 / Soria Morillo, Luis Miguel 0000-0002-6794-9179 / Álvarez-García, Juan A. 0000-0002-4106-6044
2019-11-07
Article (Journal)
Electronic Resource
English
DDC:
690
Energy-Efficient Indoor Localization WiFi-Fingerprint System: An Experimental Study
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