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

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