WiFi CSI-Based Long-Range Through-Wall Human Activity Recognition with the ESP32

WiFi CSI-Based Long-Range Through-Wall Human Activity Recognition with the ESP32 This repository contains the WiFi CSI human presence detection and activity recognition datasets proposed in [1]. Datasets DP_LOS - Line-of-sight (LOS) presence detection dataset, comprised of 392 CSI amplitude spectrograms. DP_NLOS - Non-line-of-sight (NLOS) presence detection dataset, comprised of 384 CSI amplitude spectrograms. DA_LOS - LOS activity recognition dataset, comprised of 392 CSI amplitude spectrograms. DA_NLOS - NLOS activity recognition dataset, comprised of 384 CSI amplitude spectrograms. Table 1: Characteristics of presence detection and activity recognition datasets. Dataset Scenario #Rooms #Persons #Classes Packet Sending Rate Interval #Spectrograms DP_LOS LOS 1 1 6 100Hz 4s (400 packets) 392 DP_NLOS NLOS 5 1 6 100Hz 4s (400 packets) 384 DA_LOS LOS 1 1 3 100Hz 4s (400 packets) 392 DA_NLOS NLOS 5 1 3 100Hz 4s (400 packets) 384 Data Format Each dataset employs an 8:1:1 training-validation-test split, defined in the provided label files trainLabels.csv, validationLabels.csv, and testLabels.csv. Label files use the sample format [i c], with i corresponding to the spectrogram index (i.png) and c corresponding to the class. For presence detection datasets (DP_LOS , DP_NLOS), c in {0 = "no presence", 1 = "presence in room 1", ..., 5 = "presence in room 5"}. For activity recognition datasets (DA_LOS , DA_NLOS), c in {0="no activity", 1="walking", and 2="walking + arm-waving"}. Furthermore, the mean and standard deviation of a given dataset are provided in meanStd.csv. Download and UseThis data may be used for non-commercial research purposes only. If you publish material based on this data, we request that you include a reference to our paper [1]. [1] Strohmayer, Julian, and Martin Kampel. "WiFi CSI-Based Long-Range Through-Wall Human Activity Recognition with the ESP32" International Conference on Computer Vision Systems. Cham: Springer Nature Switzerland, 2023. BibTeX citation: @inproceedings{strohmayer2023wifi, title={WiFi CSI-Based Long-Range Through-Wall Human Activity Recognition with the ESP32}, author={Strohmayer, Julian and Kampel, Martin}, booktitle={International Conference on Computer Vision Systems}, pages={41--50}, year={2023}, organization={Springer} }