On Robustness of IEEE 802.11 WLAN-based Human Activity Recognition

Research output: Chapter in Book/Conference proceedingConference contributionpeer-review

Abstract

Contact-less or Device-less Human Activity Recognition (HAR) using IEEE 802.11 Wireless Local Area Network (WLAN) has garnered significant interest due to its ubiquitous coverage, convenience, and privacy compared to wearable and vision-based approaches. However, maintaining the accuracy of HAR in varying environments, ranges, and time periods remains a challenge. This work proposes a robust scheme using threshold segmentation, auto-correlation function (ACF), and a lightweight fully connected neural network (FCNN), which can maintain the HAR accuracy across different environments without the need to retrain the model. The proposed scheme is also evaluated across different transceivers' ranges to understand its deployment constraints. The results demonstrate that the proposed scheme delivers consistent performance across different environments, ranges, and days, achieving an average HAR accuracy of over 97.25% without retraining. This greatly reduces the deployment complexity and enhances its practicality.

Original languageEnglish
Title of host publication2023 IEEE Conference on Standards for Communications and Networking, CSCN 2023
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages417-422
Number of pages6
ISBN (Electronic)9798350395389
DOIs
Publication statusPublished - 2023
Event2023 IEEE Conference on Standards for Communications and Networking, CSCN 2023 - Munich, Germany
Duration: 6 Nov 20238 Nov 2023

Publication series

Name2023 IEEE Conference on Standards for Communications and Networking, CSCN 2023

Conference

Conference2023 IEEE Conference on Standards for Communications and Networking, CSCN 2023
Country/TerritoryGermany
CityMunich
Period6/11/238/11/23

Keywords

  • auto-correlation function
  • human activity recognition
  • IEEE 802.11 WLAN/Wi-Fi sensing
  • lightweight FCNN

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Hardware and Architecture
  • Safety, Risk, Reliability and Quality

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