CSIDA

The dataset is for Wi-Fi-based human activity recognition. The dataset is comprised of six experiments performed by 5 different subjects in five different locations in two different indoor environments. Each subject performed 20 trials for each of the experiments which makes the overall number of recorded trials in the dataset equals to 3000 trials (6 experiments × 5 subjects × 5 locations × 20 times). To record the data, we used the channel state information (CSI) tool to capture the exchanged Wi-Fi packets between a Wi-Fi transmitter and receiver. The utilized transmitter and receiver are retrofitted with the Intel 5300 network interface card which enabled us to capture the CSI values that are contained in the recorded transmissions. The related articles is "WiFi-based Cross-Domain Gesture Recognition via Modified Prototypical Networks" , whose url is https://github.com/Zhang-xie/WiGr. For storage space reasons, the data is uploaded in two parts. The first part includes the final data and its label, and the second part includes the raw data. The dataset folder contained seven sub-directories, which were the original data, the data with random phase offset removed, the data with noise removed, the action gesture label, the environment label, the location label, and the person label. This data was stored in zarr data format and needed to be read using python's zarr library. Zarr saved data in blocks. Frankly speaking, it was to divide a block of data into sub-blocks of the same size. Each sub-block was saved into a file named *.. The advantage of such processing was that it was very friendly to large scale data.

本数据集面向基于Wi-Fi的人体活动识别任务。该数据集包含由5名不同受试者在2种不同室内环境下的5个不同地点开展的6组实验。每名受试者针对每组实验完成20次重复试验，因此数据集总记录试验次数为3000次（6组实验 ×5名受试者 ×5个地点 ×20次重复）。为采集数据，本研究采用信道状态信息（Channel State Information, CSI）工具捕获Wi-Fi发射机与接收机之间交互的Wi-Fi数据包。所使用的发射机与接收机均加装Intel 5300网络接口卡，借此可捕获记录传输中包含的CSI数值。相关研究论文为《WiFi-based Cross-Domain Gesture Recognition via Modified Prototypical Networks》，其开源地址为https://github.com/Zhang-xie/WiGr。受存储空间限制，本数据集分两部分上传：第一部分包含最终数据及其标签，第二部分包含原始数据。数据集根目录包含7个子目录，分别为原始数据、去除随机相位偏移后的数据、去除噪声后的数据、动作手势标签、环境标签、地点标签以及受试者标签。本数据集采用zarr数据格式存储，需使用Python的zarr库进行读取。Zarr采用分块存储机制，简言之，即将整块数据划分为若干尺寸一致的子块，每个子块保存为一个命名为*的文件。该处理方式的优势在于对大规模数据十分友好。

搜集汇总

背景与挑战

背景概述

CSIDA是一个用于Wi-Fi人类活动识别的数据集，包含3000次试验记录，涵盖多种实验条件和环境。数据以zarr格式存储，包含处理后的数据和原始数据两部分，适用于大规模数据分析。