Crowdsourced WiFi database and benchmark software for indoor positioning

This dataset contains two Wi-Fi databases (one for training and one for test/estimation purposes in indoor positioning applications), collected in a crowdsourced mode (i.e., via 21 different devices and different users), together with a benchmarking utility software (in Matlab and Python) to illustrate various algorithms of indoor positioning based solely on WiFi information (MAC addresses and RSS values). The data was collected in a 4-floor university building in Tampere, Finland, during Jan-Aug 2017 and it comprises 687 training fingerprints and 3951 test or estimation fingerprints. 13.10.2017: Version 2 uploaded; the revised version contains improved readme files and improved Python SW. The dataset and/or the associated software are to be cited as follows: E.S. Lohan, J. Torres-Sospedra, P. Richter, H. Leppäkoski, J. Huerta, A. Cramariuc, “Crowdsourced WiFi-fingerprinting database and benchmark software for indoor positioning”, Zenodo repository, DOI 10.5281/zenodo.889798本数据集包含两份无线保真（Wi-Fi）数据库（一份用于室内定位应用的模型训练，另一份用于测试与评估用途），采用众包模式采集完成——即通过21台不同设备、由多位不同用户完成数据采集；同时附带一款支持Matlab与Python环境的基准测试工具软件，用于演示仅基于媒体访问控制（Media Access Control, MAC）地址与接收信号强度（Received Signal Strength, RSS）值的各类室内定位算法。该数据集于2017年1月至8月间，在芬兰坦佩雷的一栋4层大学建筑内采集，共包含687条训练指纹与3951条测试/评估指纹。2017年10月13日，该数据集发布版本2，修订版包含优化后的说明文档与Python工具软件。本数据集及/或其配套软件需按如下方式引用：E.S. Lohan、J. Torres-Sospedra、P. Richter、H. Leppäkoski、J. Huerta、A. Cramariuc，《面向室内定位的众包Wi-Fi指纹数据库与基准测试软件》，Zenodo仓储，DOI：10.5281/zenodo.889798