research-article

: Towards Collaborative and Cross-Domain Wi-Fi Sensing: A Case Study for Human Activity Recognition<sc/>

Authors:

Xiaojiang Chen,

Zheng WangAuthors Info & Claims

IEEE Transactions on Mobile Computing, Volume 23, Issue 2

Pages 1674 - 1688

https://doi.org/10.1109/TMC.2023.3242324

Published: 06 February 2023 Publication History

Abstract

The quality of a learning-based Wi-Fi sensing system is bounded by the quantity and quality of training data. However, obtaining sufficient and high-quality data across different domains is difficult due to extensive user involvement. We present CARING, a federated-learning-based framework to support collaborative and cross-domain Wi-Fi sensing. A key challenge of CARING is to allow the effective exchange and learning of knowledge across local models that are derived from heterogeneous data sources with uneven data distributions. We overcome this challenge by first extracting the activity-related representation to train local models. The shared global model aggregates received local model parameters and sends them back to individual devices for fine-tuning locally in the deployed environment. By leveraging the crowdsourced knowledge, CARING allows local models to quickly adapt to domain changes using just a few samples seen at test time. We demonstrate the benefit of CARING by applying it to activity recognition across three public datasets collected from 5 environments, 7 deployments, 31 users, and 29 activities. Experimental results show that CARING is highly effective and robust, improving the alternative approach for using single-sourced training data by up to 47%, giving an accuracy of over 80% (up to 100%) for various cross-domain scenarios.

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Cited By

Jin CMeng XLi XWang JPan MFang Y(2024)Rodar: Robust Gesture Recognition Based on mmWave Radar Under Human Activity InterferenceIEEE Transactions on Mobile Computing10.1109/TMC.2024.340235623:12(11735-11749)Online publication date: 1-Dec-2024
https://dl.acm.org/doi/10.1109/TMC.2024.3402356
Peng CGui LSheng BGuo ZXiao F(2023)RoSeFi: A Robust Sedentary Behavior Monitoring System With Commodity WiFi DevicesIEEE Transactions on Mobile Computing10.1109/TMC.2023.332130623:5(6470-6489)Online publication date: 2-Oct-2023
https://dl.acm.org/doi/10.1109/TMC.2023.3321306

Index Terms

: Towards Collaborative and Cross-Domain Wi-Fi Sensing: A Case Study for Human Activity Recognition
1. Computing methodologies
  1. Machine learning
2. Human-centered computing

Index terms have been assigned to the content through auto-classification.

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cover image IEEE Transactions on Mobile Computing

IEEE Transactions on Mobile Computing Volume 23, Issue 2

Feb. 2024

1002 pages

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1536-1233 © 2023 IEEE. Personal use is permitted, but republication/redistribution requires IEEE permission. See https://www.ieee.org/publications/rights/index.html for more information.

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Published: 06 February 2023

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Cited By

Jin CMeng XLi XWang JPan MFang Y(2024)Rodar: Robust Gesture Recognition Based on mmWave Radar Under Human Activity InterferenceIEEE Transactions on Mobile Computing10.1109/TMC.2024.340235623:12(11735-11749)Online publication date: 1-Dec-2024
https://dl.acm.org/doi/10.1109/TMC.2024.3402356
Peng CGui LSheng BGuo ZXiao F(2023)RoSeFi: A Robust Sedentary Behavior Monitoring System With Commodity WiFi DevicesIEEE Transactions on Mobile Computing10.1109/TMC.2023.332130623:5(6470-6489)Online publication date: 2-Oct-2023
https://dl.acm.org/doi/10.1109/TMC.2023.3321306

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