A dataset for Wi-Fi-based human-to-human interaction recognition

Published: 19 May 2020| Version 1 | DOI: 10.17632/3dhn4xnjxw.1
Contributors:
Rami Alazrai,
Ali Awad,
Baha' Alsaify,
Mohammad Hababeh,
Mohammad I. Daoud

Description

This dataset contains Wi-Fi signals that were recorded from 40 different pairs of subjects while performing twelve different human-to-human interactions in an indoor environment. Each pair of subjects performed ten trials of each of the twelve interactions and the total number of trials recorded in our dataset for all the 40 pairs of subjects is 4800 trials (i.e., 40 pairs of subjects × 12 interactions × 10 trials). The publicly available CSI tool is used to record the Wi-Fi signals transmitted from a commercial off-the-shelf access point, namely the Sagemcom 2704 access point, to a desktop computer that is equipped with an Intel 5300 network interface card. The recorded Wi-Fi signals consist of the Received Signal Strength Indicator (RSSI) values and the Channel State Information (CSI) values.

Files

Institutions

German Jordanian University, Jordan University of Science and Technology

Categories

Signal Processing, Wireless Computing, Activity Recognition, Machine Learning

License