2023
DOI: 10.3390/data8010014
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UTMInDualSymFi: A Dual-Band Wi-Fi Dataset for Fingerprinting Positioning in Symmetric Indoor Environments

Abstract: Recent studies on indoor positioning using Wi-Fi fingerprinting are motivated by the ubiquity of Wi-Fi networks and their promising positioning accuracy. Machine learning algorithms are commonly leveraged in indoor positioning works. The performance of machine learning based solutions are dependent on the availability, volume, quality, and diversity of related data. Several public datasets have been published in order to foster advancements in Wi-Fi based fingerprinting indoor positioning solutions. These data… Show more

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Cited by 8 publications
(2 citation statements)
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“…Compared to the other indoor positioning, fingerprinting datasets utilized in e.g. [3] , [4] , [5] , [6] , the TUJI1 dataset is unique in two main aspects: It considers very fine measurement granularity, with data points spaced less than 45 cm apart, enabling studying the impact of data density on the positioning performance. It investigates effects of device heterogeneity, while utilizing 5 distinct devices for data acquisition.…”
Section: Value Of the Datamentioning
confidence: 99%
“…Compared to the other indoor positioning, fingerprinting datasets utilized in e.g. [3] , [4] , [5] , [6] , the TUJI1 dataset is unique in two main aspects: It considers very fine measurement granularity, with data points spaced less than 45 cm apart, enabling studying the impact of data density on the positioning performance. It investigates effects of device heterogeneity, while utilizing 5 distinct devices for data acquisition.…”
Section: Value Of the Datamentioning
confidence: 99%
“…Compared to the other indoor positioning, fingerprinting datasets utilized in e.g. [3][4][5][6] , the TUJI1 dataset is unique in two main aspects:…”
Section: Value Of the Datamentioning
confidence: 99%