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}
}