Wi-Fi RSSI fingerprint dataset from two malls with validation routes in a shop-level for indoor positioning

The dataset is composed of the RSSI fingerprinting calibration of two malls employing four different smartphones with the random walking survey method.  Moreover, the dataset includes validation routes performed with ten smartphones from various brands and labeled with the code of the shops where they were registered. For evaluation purposes, together with the samples, information related to the shopping center like the Euclidean distance between shops is provided. The files are described as follows:

building.csv’: two rows with the id of mall 1 and mall 2.

‘floor.csv’: there is a row for each of the floors of the two malls. Three floors for mall 1 and two floors for mall 2 

‘zones.csv’: for each zone is indicated the id of the mall and the id floor. There are 69 zones from mall 1 and 124 for mall 2 

‘training.csv’: in this file are registered the ids and the description of the five different calibrations performed (one per smartphone) in each of the malls. 

‘training_sample.csv’: each row of the file has the RSSI in dBm recorded during the off-line calibration phase together with the timestamp, channel, and MAC of the AP.

‘route.csv’: the id’s and the description of each of the validation routes are recorded in this file. 

‘route_sample.csv’: with a similar structure than the training_sample.csv, the RSSI, timestamp, channel, and MAC acquired during the validation routes are stored in this file.

‘euclidea_distance.csv”: to evaluate the error of the different algorithms, this file recorded the euclidean distance from the center of a shop to each other in meters.

The dataset is to be cited as follows:
J. A. López-Pastor, A.J. Ruiz-Ruiz, A.J. García-Sánchez, J.L. Gómez-Tornero. Wi-Fi RSSI fingerprint dataset from two malls with validation routes in a shop-level for indoor positioning. Zenodo repository. DOI: 10.5281/zenodo.3698238

本数据集包含两家购物中心的接收信号强度指示（Received Signal Strength Indicator, RSSI）指纹校准数据，采集时采用随机步行勘测法，使用了四款不同品牌的智能手机。此外，数据集还包含使用十款不同品牌智能手机完成的验证路线数据，这些数据均标注了其采集时所在商铺的编码。为便于模型评估，除样本数据外，本数据集还提供了与购物中心相关的附加信息，例如商铺间的欧氏距离。各文件说明如下：
1. building.csv：仅包含两行数据，分别对应两家购物中心的唯一标识。
2. floor.csv：每一行对应两家购物中心的一层楼，其中购物中心1设有三层楼，购物中心2设有两层楼。
3. zones.csv：每条数据均标注了所属购物中心的标识及楼层标识，本数据集共包含69个区域（来自购物中心1）与124个区域（来自购物中心2）。
4. training.csv：记录了两家购物中心各自开展的五次不同校准（每款智能手机对应一次校准）的唯一标识与相关描述。
5. training_sample.csv：文件中每一行数据均包含离线校准阶段采集的接收信号强度指示（RSSI，单位为dBm），以及时间戳、无线访问接入点（Access Point, AP）的信道与MAC地址。
6. route.csv：记录了每条验证路线的唯一标识与相关描述。
7. route_sample.csv：其数据结构与training_sample.csv类似，存储了验证路线采集过程中得到的RSSI、时间戳、信道及AP的MAC地址。
8. euclidea_distance.csv：为评估不同算法的定位误差，本文件记录了各商铺中心点之间的欧氏距离，单位为米。

本数据集的引用格式如下：
J. A. López-Pastor、A.J. Ruiz-Ruiz、A.J. García-Sánchez、J.L. Gómez-Tornero. 面向室内定位的两家购物中心商铺级验证路线Wi-Fi RSSI指纹数据集.Zenodo知识库.DOI: 10.5281/zenodo.3698238