channel-state-information

A list of awesome papers and cool resources on WiFi CSI sensing.

The python library for the ESPARGOS WiFi antenna array

Extract Channel State Information from WiFi-enabled ESP32 Microcontroller. Active and Passive modes available. (https://stevenmhernandez.github.io/ESP32-CSI-Tool/)

Human Activity Recognition based on WiFi Channel State Information

Human Activity Recognition using Channel State Information

Detect motion, presence and breathing through walls with ordinary WiFi. ESP32-S3 captures 802.11 CSI, a Raspberry Pi 4 runs the DSP, a browser dashboard shows it live.

Sign Language Recognition using WiFi and Convolutional Neural Networks

802.11n CSI Tool based on iwlwifi and Linux

Channel State Information for Raspberry Pi. Use the pi-5.10.92 branch.

An implementation for our paper: CsiGAN: Robust Channel State Information-based Activity Recognition with GANs (IEEE Internet of Things Journal, 2019), which is the semi-supervised Generative Adversarial Network (GAN) for Channel State Information (CSI) -based activity recognition.

This is a data-set for Human Activities & Gestures Recognition (HAGR) using the Channel State information (CSI) of IEEE 802.11n devices

Uncertainty-Aware Dimensionality Reduction for Channel Charting with Geodesic Loss

WiFi CSI-based human presence, occupancy, zone, and activity detection dashboard.

Realtime Wi-Fi CSI based Human Activity Recognition on a Raspberry Pi Zero + ESP32 setup

📊 Wi-Fi Channel State Information(CSI) visualization with python

Local WiFi CSI sensing for presence, occupancy, zone, and activity detection with a live Flask dashboard and optional Groq narration.

Gait Based User Recognition from Channel State Information(CSI) collected from WiFi Data

Source code related to the paper "Passive Channel Charting: Locating Passive Targets using Wi-Fi Channel State Information"

rvCSI — edge RF sensing runtime: normalize WiFi CSI from Nexmon/ESP32/Intel/Atheros/file/replay into one validated CsiFrame schema, run reusable DSP, emit typed confidence-scored events, bridge to RuVector. Rust + @ruv/rvcsi (npm) + rvcsi CLI + a Claude Code plugin.

Baha’ A. Alsaify, Mahmoud M. Almazari, Rami Alazrai, Mohammad I. Daoud, A dataset for Wi-Fi-based human activity recognition in line-of-sight and non-line-of-sight indoor environments, Data in Brief, Volume 33, 2020, 106534, ISSN 2352-3409, https://doi.org/10.1016/j.dib.2020.106534.