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

OutFin is a novel dataset of outdoor location fingerprints, collected using two different smartphones. It comprises 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 unique in terms of its reference points' number, arrangement, and spacing. A thorough description of the collection environment is provided in the form of an interactive map, that display information, such as RP coordinates (both ground truth and smartphone estimated), pictures of the collection sites, and building height and ground elevation. (A paper describing the dataset in detail will soon be available.)(The python scripts used to validate the dataset can also be obtained from GitHub: https://github.com/alhomayani/OutFin)

OutFin是一款新型室外位置指纹数据集，采用两款不同智能手机采集获取。该数据集涵盖多种数据类型：WiFi、蓝牙（Bluetooth）与蜂窝信号强度，此外还包含磁力计（magnetometer）、加速度计（accelerometer）、陀螺仪（gyroscope）、气压计（barometer）以及环境光传感器（ambient light sensor）等各类传感器的测量数据。采集区域覆盖4个分散站点，共计122个参考点（reference points）。每个站点的参考点数量、布设方式与间距均各不相同。采集环境的详细说明以交互式地图的形式提供，该地图可展示各类信息，例如参考点坐标（包含地面真值坐标与智能手机估算坐标）、采集站点实拍照片，以及建筑高度与地面海拔数据。（详细介绍该数据集的学术论文即将发表。）（用于验证该数据集的Python脚本可从GitHub获取：https://github.com/alhomayani/OutFin）