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[Poster] You Only Sense Once: Unified Localization and Activity Recognition of Multiple Persons

Published: 04 June 2024 Publication History

Abstract

WiFi-based human sensing has exhibited remarkable potential to analyze user behaviors in a non-intrusive and device-free manner. However, most previous works focus on single-user sensing, which has limited practicability in scenarios involving multiple users. In this paper, we introduce YOSO a novel system employing a multi-label multi-view Transformer-based architecture to address these issues, enabling simultaneous localization and activity recognition. By applying advanced preprocessing techniques and utilizing the Transformer's self-attention mechanism, our system effectively learns high-dimensional representations of human activities and locations from CSI data. This approach overcomes traditional sequential data processing limitations, offering precise activity recognition and localization in multiperson environments. Our experimental results showcase superior performance in both localization and activity recognition tasks, surpassing existing methods. The real-time processing capability of our system paves the way for applications in smart environments, security, and healthcare monitoring, providing an efficient tool for situational awareness and advancing wireless sensing technology.

References

[1]
Zhenghua et. al. Chen. 2018. WiFi CSI based passive human activity recognition using attention based BLSTM. Transactions on Mobile Computing 18, 11 (2018).
[2]
Shuokang Huang, Kaihan Li, Di You, Yichong Chen, Arvin Lin, Siying Liu, Xiaohui Li, and Julie A McCann. 2024. WiMANS: A Benchmark Dataset for WiFi-based Multi-user Activity Sensing. arXiv preprint arXiv:2402.09430 (2024).
[3]
Hyunggeun Mo and Seungku Kim. 2021. A deep learning-based human identification system with wi-fi csi data augmentation. IEEE Access 9 (2021), 91913--91920.
[4]
Hamada Rizk, Akira Uchiyama, and Hirozumi Yamaguchi. 2024. Adaptability Matters: Heterogeneous Graphs for Agile Indoor Positioning in Cluttered Environments. In MDM. IEEE.
[5]
Hamada et. al. Rizk. 2023. Indoor Localization System for Seamless Tracking Across Buildings and Network Configurations. In GLOBECOM 2023-2023 IEEE Global Communications Conference. IEEE, 776--782.
[6]
Yu Sugimoto, Hamada Rizk, Akira Uchiyama, and Hirozumi Yamaguchi. 2023. Towards Environment-Independent Activity Recognition Using Wi-Fi CSI with an Encoder-Decoder Network. In the Workshop on Body-Centric Computing Systems. ACM.

Cited By

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  • (2024)RISense: 6G-Enhanced Human Activity Recognition System with RIS and Deep LDA2024 25th IEEE International Conference on Mobile Data Management (MDM)10.1109/MDM61037.2024.00035(119-128)Online publication date: 24-Jun-2024

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  1. [Poster] You Only Sense Once: Unified Localization and Activity Recognition of Multiple Persons

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    cover image ACM Conferences
    MOBISYS '24: Proceedings of the 22nd Annual International Conference on Mobile Systems, Applications and Services
    June 2024
    778 pages
    ISBN:9798400705816
    DOI:10.1145/3643832
    Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

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    New York, NY, United States

    Publication History

    Published: 04 June 2024

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    Author Tags

    1. wireless sensing
    2. activity recognition
    3. localization

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    • JST

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    • (2024)RISense: 6G-Enhanced Human Activity Recognition System with RIS and Deep LDA2024 25th IEEE International Conference on Mobile Data Management (MDM)10.1109/MDM61037.2024.00035(119-128)Online publication date: 24-Jun-2024

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