Literature DB >> 33627669

OutFin, a multi-device and multi-modal dataset for outdoor localization based on the fingerprinting approach.

Fahad Alhomayani1, Mohammad H Mahoor2.   

Abstract

In recent years, fingerprint-based positioning has gained researchers' attention since it is a promising alternative to the Global Navigation Satellite System and cellular network-based localization in urban areas. Despite this, the lack of publicly available datasets that researchers can use to develop, evaluate, and compare fingerprint-based positioning solutions constitutes a high entry barrier for studies. As an effort to overcome this barrier and foster new research efforts, this paper presents OutFin, a novel dataset of outdoor location fingerprints that were collected using two different smartphones. OutFin is comprised of diverse data types such as WiFi, Bluetooth, and cellular signal strengths, in addition to measurements from various sensors including the magnetometer, accelerometer, gyroscope, barometer, and ambient light sensor. The collection area spanned four dispersed sites with a total of 122 reference points. Each site is different in terms of its visibility to the Global Navigation Satellite System and reference points' number, arrangement, and spacing. Before OutFin was made available to the public, several experiments were conducted to validate its technical quality.

Entities:  

Year:  2021        PMID: 33627669     DOI: 10.1038/s41597-021-00832-y

Source DB:  PubMed          Journal:  Sci Data        ISSN: 2052-4463            Impact factor:   6.444


  1 in total

1.  A multidevice and multimodal dataset for human energy expenditure estimation using wearable devices.

Authors:  Shkurta Gashi; Chulhong Min; Alessandro Montanari; Silvia Santini; Fahim Kawsar
Journal:  Sci Data       Date:  2022-09-01       Impact factor: 8.501

  1 in total

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