WiRIM: Resolution Improving Mechanism for Human Sensing With Commodity Wi-Fi
The growing physical (PHY) layer capabilities of Wi-Fi have made it possible to use Wi-Fi signals for both communication and human sensing. Wi-Fi channel state information (CSI) in PHY layer can be obtained from commodity Wi-Fi devices. As CSI can detect the minute environment changes that alter sig...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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IEEE
2019-01-01
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| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/8907825/ |
| _version_ | 1818621710534967296 |
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| author | Xinbin Shen Lingchao Guo Zhaoming Lu Xiangming Wen Zhihong He |
| author_facet | Xinbin Shen Lingchao Guo Zhaoming Lu Xiangming Wen Zhihong He |
| author_sort | Xinbin Shen |
| collection | DOAJ |
| description | The growing physical (PHY) layer capabilities of Wi-Fi have made it possible to use Wi-Fi signals for both communication and human sensing. Wi-Fi channel state information (CSI) in PHY layer can be obtained from commodity Wi-Fi devices. As CSI can detect the minute environment changes that alter signal propagation, it is thus capable of capturing the subtle human activities to provide cost-effective and easy-to-use human sensing. However, the limited bandwidth of each individual Wi-Fi channel fundamentally constrains the resolution of signals, resulting in poor performance of human sensing. In this paper, we present WiRIM, a resolution improving mechanism for Wi-Fi based human sensing. We design a channel switching and aggregation algorithm to extend the effective bandwidth of commodity Wi-Fi signals and improve the performance and efficiency of human sensing applications. With aggregated CSI, WiRIM constructs feature images which contain rich frequency, temporal and spatial characteristics, and then uses a deep learning method to process the extracted features. We propose a cross-location human activity recognition (CLHAR) scenario as a case study. The CLHAR scenario requires a high enough resolution of the Wi-Fi signals to accurately recognize different activities under the interference of tiny changes in human location. The experiments demonstrate the generality and effectiveness of the proposed mechanism. |
| first_indexed | 2024-12-16T18:13:36Z |
| format | Article |
| id | doaj.art-32a9907b39894202b3fd062df12f2f33 |
| institution | Directory Open Access Journal |
| issn | 2169-3536 |
| language | English |
| last_indexed | 2024-12-16T18:13:36Z |
| publishDate | 2019-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj.art-32a9907b39894202b3fd062df12f2f332022-12-21T22:21:43ZengIEEEIEEE Access2169-35362019-01-01716835716837010.1109/ACCESS.2019.29546518907825WiRIM: Resolution Improving Mechanism for Human Sensing With Commodity Wi-FiXinbin Shen0https://orcid.org/0000-0002-2195-5194Lingchao Guo1https://orcid.org/0000-0003-1319-6674Zhaoming Lu2https://orcid.org/0000-0002-6041-0031Xiangming Wen3https://orcid.org/0000-0003-2793-6696Zhihong He4https://orcid.org/0000-0002-4509-8166Beijing Key Laboratory of Network System Architecture and Convergence, Beijing University of Posts and Telecommunications, Beijing, ChinaBeijing Key Laboratory of Network System Architecture and Convergence, Beijing University of Posts and Telecommunications, Beijing, ChinaBeijing Key Laboratory of Network System Architecture and Convergence, Beijing University of Posts and Telecommunications, Beijing, ChinaBeijing Key Laboratory of Network System Architecture and Convergence, Beijing University of Posts and Telecommunications, Beijing, ChinaBeijing Key Laboratory of Network System Architecture and Convergence, Beijing University of Posts and Telecommunications, Beijing, ChinaThe growing physical (PHY) layer capabilities of Wi-Fi have made it possible to use Wi-Fi signals for both communication and human sensing. Wi-Fi channel state information (CSI) in PHY layer can be obtained from commodity Wi-Fi devices. As CSI can detect the minute environment changes that alter signal propagation, it is thus capable of capturing the subtle human activities to provide cost-effective and easy-to-use human sensing. However, the limited bandwidth of each individual Wi-Fi channel fundamentally constrains the resolution of signals, resulting in poor performance of human sensing. In this paper, we present WiRIM, a resolution improving mechanism for Wi-Fi based human sensing. We design a channel switching and aggregation algorithm to extend the effective bandwidth of commodity Wi-Fi signals and improve the performance and efficiency of human sensing applications. With aggregated CSI, WiRIM constructs feature images which contain rich frequency, temporal and spatial characteristics, and then uses a deep learning method to process the extracted features. We propose a cross-location human activity recognition (CLHAR) scenario as a case study. The CLHAR scenario requires a high enough resolution of the Wi-Fi signals to accurately recognize different activities under the interference of tiny changes in human location. The experiments demonstrate the generality and effectiveness of the proposed mechanism.https://ieeexplore.ieee.org/document/8907825/Human sensingresolution improvementWi-FiCSIcross-location human activity recognition |
| spellingShingle | Xinbin Shen Lingchao Guo Zhaoming Lu Xiangming Wen Zhihong He WiRIM: Resolution Improving Mechanism for Human Sensing With Commodity Wi-Fi IEEE Access Human sensing resolution improvement Wi-Fi CSI cross-location human activity recognition |
| title | WiRIM: Resolution Improving Mechanism for Human Sensing With Commodity Wi-Fi |
| title_full | WiRIM: Resolution Improving Mechanism for Human Sensing With Commodity Wi-Fi |
| title_fullStr | WiRIM: Resolution Improving Mechanism for Human Sensing With Commodity Wi-Fi |
| title_full_unstemmed | WiRIM: Resolution Improving Mechanism for Human Sensing With Commodity Wi-Fi |
| title_short | WiRIM: Resolution Improving Mechanism for Human Sensing With Commodity Wi-Fi |
| title_sort | wirim resolution improving mechanism for human sensing with commodity wi fi |
| topic | Human sensing resolution improvement Wi-Fi CSI cross-location human activity recognition |
| url | https://ieeexplore.ieee.org/document/8907825/ |
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