A Short Overview of Multi-Modal Wi-Fi Sensing
- URL: http://arxiv.org/abs/2505.06682v1
- Date: Sat, 10 May 2025 16:12:56 GMT
- Title: A Short Overview of Multi-Modal Wi-Fi Sensing
- Authors: Zijian Zhao,
- Abstract summary: Wi-Fi sensing has emerged as a significant technology in wireless sensing and Integrated Sensing and Communication (ISAC)<n>Wi-Fi sensing also faces challenges, such as low robustness and difficulties in data collection.
- Score: 2.61072980439312
- License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
- Abstract: Wi-Fi sensing has emerged as a significant technology in wireless sensing and Integrated Sensing and Communication (ISAC), offering benefits such as low cost, high penetration, and enhanced privacy. Currently, it is widely utilized in various applications, including action recognition, human localization, and crowd counting. However, Wi-Fi sensing also faces challenges, such as low robustness and difficulties in data collection. Recently, there has been an increasing focus on multi-modal Wi-Fi sensing, where other modalities can act as teachers, providing ground truth or robust features for Wi-Fi sensing models to learn from, or can be directly fused with Wi-Fi for enhanced sensing capabilities. Although these methods have demonstrated promising results and substantial value in practical applications, there is a lack of comprehensive surveys reviewing them. To address this gap, this paper reviews the multi-modal Wi-Fi sensing literature \textbf{from the past 24 months} and highlights the current limitations, challenges and future directions in this field.
Related papers
- Talk is Not Always Cheap: Promoting Wireless Sensing Models with Text Prompts [14.801020598640191]
We propose an innovative text-enhanced wireless sensing framework, WiTalk, that seamlessly integrates semantic knowledge through three prompt strategies-label-only, brief description, and detailed action description.<n>We rigorously validate this framework across three public benchmark datasets: XRF55 for human action recognition (HAR), WiFiTAL and XRFV2 for WiFi temporal action localization.
arXiv Detail & Related papers (2025-04-20T13:58:35Z) - A Survey on Wi-Fi Sensing Generalizability: Taxonomy, Techniques, Datasets, and Future Research Prospects [12.268939893726293]
In this survey, we review over 200 studies on Wi-Fi sensing generalization.<n>We analyze state-of-the-art techniques, which are employed to mitigate the adverse effects of environmental variability.<n>We discuss emerging research directions, such as multimodal approaches and the integration of large language models.
arXiv Detail & Related papers (2025-03-11T03:18:20Z) - WiMANS: A Benchmark Dataset for WiFi-based Multi-user Activity Sensing [8.143761572557539]
WiMANS is the first dataset for multi-user sensing based on WiFi.
We exploit WiMANS to benchmark the performance of state-of-the-art WiFi-based human sensing models and video-based models.
arXiv Detail & Related papers (2024-01-24T16:10:14Z) - Exposing the CSI: A Systematic Investigation of CSI-based Wi-Fi Sensing
Capabilities and Limitations [16.819111460629397]
This work aims to shed light on the impact of Wi-Fi 6 features on the sensing performance and to create a benchmark for future research on Wi-Fi sensing.
We perform an extensive CSI data collection campaign involving 3 individuals, 3 environments, and 12 activities, using Wi-Fi 6 signals.
An anonymized ground truth obtained through video recording accompanies our 80-GB dataset, which contains almost two hours of CSI data from three collectors.
arXiv Detail & Related papers (2023-02-02T10:21:00Z) - DensePose From WiFi [86.61881052177228]
We develop a deep neural network that maps the phase and amplitude of WiFi signals to UV coordinates within 24 human regions.
Our model can estimate the dense pose of multiple subjects, with comparable performance to image-based approaches.
arXiv Detail & Related papers (2022-12-31T16:48:43Z) - WiFi-based Spatiotemporal Human Action Perception [53.41825941088989]
An end-to-end WiFi signal neural network (SNN) is proposed to enable WiFi-only sensing in both line-of-sight and non-line-of-sight scenarios.
Especially, the 3D convolution module is able to explore thetemporal continuity of WiFi signals, and the feature self-attention module can explicitly maintain dominant features.
arXiv Detail & Related papers (2022-06-20T16:03:45Z) - Hands-on Wireless Sensing with Wi-Fi: A Tutorial [7.8774878397748065]
This tutorial takes Wi-Fi sensing as an example.
It introduces both the theoretical principles and the code implementation of data collection, signal processing, features extraction, and model design.
arXiv Detail & Related papers (2022-06-20T01:53:35Z) - A Wireless-Vision Dataset for Privacy Preserving Human Activity
Recognition [53.41825941088989]
A new WiFi-based and video-based neural network (WiNN) is proposed to improve the robustness of activity recognition.
Our results show that WiVi data set satisfies the primary demand and all three branches in the proposed pipeline keep more than $80%$ of activity recognition accuracy.
arXiv Detail & Related papers (2022-05-24T10:49:11Z) - GraSens: A Gabor Residual Anti-aliasing Sensing Framework for Action
Recognition using WiFi [52.530330427538885]
WiFi-based human action recognition (HAR) has been regarded as a promising solution in applications such as smart living and remote monitoring.
We propose an end-to-end Gabor residual anti-aliasing sensing network (GraSens) to directly recognize the actions using the WiFi signals from the wireless devices in diverse scenarios.
arXiv Detail & Related papers (2022-05-24T10:20:16Z) - EfficientFi: Towards Large-Scale Lightweight WiFi Sensing via CSI
Compression [28.383494189730268]
EfficientFi is first IoT-cloud-enabled WiFi sensing framework.
It compresses CSI data from 1.368Mb/s to 0.768Kb/s with extremely low error of data reconstruction.
It achieves over 98% accuracy for human activity recognition.
arXiv Detail & Related papers (2022-04-08T15:48:41Z) - Transfer Learning for Future Wireless Networks: A Comprehensive Survey [49.746711269488515]
This article aims to provide a comprehensive survey on applications of Transfer Learning in wireless networks.
We first provide an overview of TL including formal definitions, classification, and various types of TL techniques.
We then discuss diverse TL approaches proposed to address emerging issues in wireless networks.
arXiv Detail & Related papers (2021-02-15T14:19:55Z) - Wireless for Machine Learning [91.13476340719087]
We give an exhaustive review of the state-of-the-art wireless methods that are specifically designed to support machine learning services over distributed datasets.
There are two clear themes within the literature, analog over-the-air computation and digital radio resource management optimized for ML.
This survey gives a comprehensive introduction to these methods, reviews the most important works, highlights open problems, and discusses application scenarios.
arXiv Detail & Related papers (2020-08-31T11:09:49Z)
This list is automatically generated from the titles and abstracts of the papers in this site.
This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.