Abstract

Human motion detection and activity recognition are becoming vital for the applications in smart homes. Traditional Human Activity Recognition (HAR) mechanisms use special devices to track human motions, such as cameras (vision-based) and various types of sensors (sensor-based). These mechanisms are applied in different applications, such as home security, Human–Computer Interaction (HCI), gaming, and healthcare. However, traditional HAR methods require heavy installation, and can only work under strict conditions. Recently, wireless signals have been utilized to track human motion and HAR in indoor environments. The motion of an object in the test environment causes fluctuations and changes in the Wi-Fi signal reflections at the receiver, which result in variations in received signals. These fluctuations can be used to track object (i.e., a human) motion in indoor environments. This phenomenon can be improved and leveraged in the future to improve the internet of things (IoT) and smart home devices. The main Wi-Fi sensing methods can be broadly categorized as Received Signal Strength Indicator (RSSI), Wi-Fi radar (by using Software Defined Radio (SDR)) and Channel State Information (CSI). CSI and RSSI can be considered as device-free mechanisms because they do not require cumbersome installation, whereas the Wi-Fi radar mechanism requires special devices (i.e., Universal Software Radio Peripheral (USRP)). Recent studies demonstrate that CSI outperforms RSSI in sensing accuracy due to its stability and rich information. This paper presents a comprehensive survey of recent advances in the CSI-based sensing mechanism and illustrates the drawbacks, discusses challenges, and presents some suggestions for the future of device-free sensing technology.

Highlights

  • Human localization, human motion detection, and Human Activity Recognition (HAR) have gained more attention due to rapid advancements in the fields of computing and sensing techniques that can be applied in different applications, such as Human–Computer Interaction (HCI), e-gaming, gesture recognition, and surveillance, etc

  • We address the current advances in device-free Channel State Information (CSI)-based sensing techniques, summarize previous studies, highlight possible applications, and show achieved results

  • Received Signal Strength Indicator (RSSI) has been leveraged in vast device-free approaches, since RSSI features are available in almost wireless devices

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Summary

Introduction

Human localization, human motion detection, and Human Activity Recognition (HAR) have gained more attention due to rapid advancements in the fields of computing and sensing techniques that can be applied in different applications, such as Human–Computer Interaction (HCI), e-gaming, gesture recognition, and surveillance, etc. [1]. Human localization, human motion detection, and Human Activity Recognition (HAR) have gained more attention due to rapid advancements in the fields of computing and sensing techniques that can be applied in different applications, such as Human–Computer Interaction (HCI), e-gaming, gesture recognition, and surveillance, etc. Is a field of computing research associated with human motion and activities in a controlled environment. Vision-based methods often require installing monitoring cameras in the field of interest to capture human activities. Sensor-based techniques require burdensome installation in the perceived environments or on the target human bodies

Literature
Previous Wi-Fi-Based Sensing Mechanisms
RSSI-Based Localization and Motion Detection
RSSI-Based Macro-Activity Recognition
RSSI-Based Micro-Activity Recognition
Wi-Fi Radar
CSI-Based Localization and Motion Detection
CSI-Based Macro-Activity Recognition
CSI-Based Micro-Activity Recognition
CSI Methodology
Preprocessing
Feature Extraction
Classification
Test Scenario
Limitations and Challenges
Findings
Conclusions

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