A Framework for Human Activity Recognition Based on WiFi CSI Signal Enhancement

Jieming Yang,Yuehua Yang,Zhiying Liu,Yun Wu,Yanming Liu,Tianyang Li,Raffaele Solimene

doi:10.1155/2021/6654752

Abstract

With the advancement of wireless technologies and sensing methodologies, many studies have shown that wireless signals can sense human behaviors. Human activity recognition using channel state information (CSI) in commercial WiFi devices plays an important role in many applications. In this paper, a framework for human activity recognition was constructed based on WiFi CSI signal enhancement. Firstly, the sensitivity of different antennas to human activity was studied. An antenna selection algorithm was proposed, which can make a choice of the antenna automatically based on their sensitivity in accordance with different activities. Secondly, two signal enhancement approaches, which can strengthen the active signals and weaken the inactive signals, were proposed to extract the active interval caused by human activity. Finally, an activity segmentation algorithm was proposed to detect the start and end time of activity. In order to verify and evaluate the methods, extensive experiments have been conducted in real indoor environments. The experimental results have demonstrated that our solutions can eliminate a large number of redundant information brought by insensitive and inactive signals. Our research results can be put into use to improve recognition accuracy significantly and decrease the cost of recognition time.

Highlights

Nowadays, WiFi signals cover almost every corner of people’s lives, such as houses, schools, shopping malls, and buildings
Human activity recognition based on WiFi signals will achieve “one thing with multiple uses”; WiFi can silently perceive every action in the physical world while completing data transmission tasks
According to the background mentioned above, we have explored three issues of human activity recognition and put forward some novel proposals in this paper. e contributions of our work are summarized as follows: (i) Based on the sensitivity of different antennas to actions, an active antenna selection approach, which makes a choice of antennas automatically, is proposed to reduce the amount of data required for subsequent calculation and analysis

Summary

Introduction

WiFi signals cover almost every corner of people’s lives, such as houses, schools, shopping malls, and buildings. If WiFi is regarded as a sensor in a sense, WiFi-based perception systems act as the world’s largest sensor network which covers all areas around us and monitors people’s behaviors. Human activity recognition based on WiFi signals will achieve “one thing with multiple uses”; WiFi can silently perceive every action in the physical world while completing data transmission tasks. Wireless sensing technology based on WiFi signals has become an important hub linking the physical world and the information world. It has become a research hotspot in the fields of gesture recognition [1], localization [2], and even identification [3]

Objectives

Discussion

Conclusion