Paper Info
Title
Deep AI Enabled Ubiquitous Wireless Sensing: A Survey
Abstract
AbstractWith the development of the Internet of Things (IoT), many kinds of wireless signals (e.g., Wi-Fi, LoRa, RFID) are filling our living and working spaces nowadays. Beyond communication, wireless signals can sense the status of surrounding objects, known as wireless sensing, with their reflection, scattering, and refraction while propagating in space. In the last decade, many sophisticated wireless sensing techniques and systems were widely studied for various applications (e.g., gesture recognition, localization, and object imaging). Recently, deep Artificial Intelligence (AI), also known as Deep Learning (DL), has shown great success in computer vision. And some works have initially proved that deep AI can benefit wireless sensing as well, leading to a brand-new step toward ubiquitous sensing. In this survey, we focus on the evolution of wireless sensing enhanced by deep AI techniques. We first present a general workflow of Wireless Sensing Systems (WSSs) which consists of signal pre-processing, high-level feature, and sensing model formulation. For each module, existing deep AI-based techniques are summarized, further compared with traditional approaches. Then, we provide a view of issues and challenges induced by combining deep AI and wireless sensing together. Finally, we discuss the future trends of deep AI to enable ubiquitous wireless sensing.
Year
DOI
Venue
2021
10.1145/3436729
ACM Computing Surveys
Keywords
DocType
Volume
Wireless sensing, AI, deep learning, deep neural network, Wi-Fi, acoustic, LoRa, activity recognition, human localization, pose estimation
Journal
54
Issue
ISSN
Citations 
2
0360-0300
5
PageRank 
References 
Authors
0.39
0
3
Name
Order
Citations
PageRank
Chenning Li150.39
Zhichao Cao217223.04
Yunhao Liu38810486.66