WPTrack: A Wi-Fi and Pressure Insole Fusion System for Single Target Tracking
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arXiv
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| Format: | Preprint |
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2025
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| _version_ | 1866909735212548096 |
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| author | Guo, Wei Yamagishi, Shunsei Jing, Lei |
| author_facet | Guo, Wei Yamagishi, Shunsei Jing, Lei |
| contents | As the Internet of Things (IoT) continues to evolve, indoor location has become a critical element for enabling smart homes, behavioral monitoring, and elderly care. Existing WiFi-based human tracking solutions typically require specialized equipment or multiple Wi-Fi links, a limitation in most indoor settings where only a single pair of Wi-Fi devices is usually available. However, despite efforts to implement human tracking using one Wi-Fi link, significant challenges remain, such as difficulties in acquiring initial positions and blind spots in DFS estimation of tangent direction. To address these challenges, this paper proposes WPTrack, the first Wi-Fi and Pressure Insoles Fusion System for Single Target Tracking. WPTrack collects Channel State Information (CSI) from a single Wi-Fi link and pressure data from 90 insole sensors. The phase difference and Doppler velocity are computed from the CSI, while the pressure sensor data is used to calculate walking velocity. Then, we propose the CSI-pressure fusion model, integrating CSI and pressure data to accurately determine initial positions and facilitate precise human tracking. The simulation results show that the initial position localization accuracy ranges from 0.02 cm to 42.55 cm. The trajectory tracking results obtained from experimental data collected in a real-world environment closely align with the actual trajectory. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2508_09166 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | WPTrack: A Wi-Fi and Pressure Insole Fusion System for Single Target Tracking Guo, Wei Yamagishi, Shunsei Jing, Lei Networking and Internet Architecture Human-Computer Interaction As the Internet of Things (IoT) continues to evolve, indoor location has become a critical element for enabling smart homes, behavioral monitoring, and elderly care. Existing WiFi-based human tracking solutions typically require specialized equipment or multiple Wi-Fi links, a limitation in most indoor settings where only a single pair of Wi-Fi devices is usually available. However, despite efforts to implement human tracking using one Wi-Fi link, significant challenges remain, such as difficulties in acquiring initial positions and blind spots in DFS estimation of tangent direction. To address these challenges, this paper proposes WPTrack, the first Wi-Fi and Pressure Insoles Fusion System for Single Target Tracking. WPTrack collects Channel State Information (CSI) from a single Wi-Fi link and pressure data from 90 insole sensors. The phase difference and Doppler velocity are computed from the CSI, while the pressure sensor data is used to calculate walking velocity. Then, we propose the CSI-pressure fusion model, integrating CSI and pressure data to accurately determine initial positions and facilitate precise human tracking. The simulation results show that the initial position localization accuracy ranges from 0.02 cm to 42.55 cm. The trajectory tracking results obtained from experimental data collected in a real-world environment closely align with the actual trajectory. |
| title | WPTrack: A Wi-Fi and Pressure Insole Fusion System for Single Target Tracking |
| topic | Networking and Internet Architecture Human-Computer Interaction |
| url | https://arxiv.org/abs/2508.09166 |