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| Main Authors: | , , , , , , , |
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| Format: | Preprint |
| Published: |
2024
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2409.00086 |
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| _version_ | 1866914931577716736 |
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| author | Ni, Tao Sun, Zehua Han, Mingda Lan, Guohao Xie, Yaxiong Li, Zhenjiang Gu, Tao Xu, Weitao |
| author_facet | Ni, Tao Sun, Zehua Han, Mingda Lan, Guohao Xie, Yaxiong Li, Zhenjiang Gu, Tao Xu, Weitao |
| contents | Diverse Wi-Fi-based wireless applications have been proposed, ranging from daily activity recognition to vital sign monitoring. Despite their remarkable sensing accuracy, the high energy consumption and the requirement for customized hardware modification hinder the wide deployment of the existing sensing solutions. In this paper, we propose REHSense, an energy-efficient wireless sensing solution based on Radio-Frequency (RF) energy harvesting. Instead of relying on a power-hungry Wi-Fi receiver, REHSense leverages an RF energy harvester as the sensor and utilizes the voltage signals harvested from the ambient Wi-Fi signals to enable simultaneous context sensing and energy harvesting. We design and implement REHSense using a commercial-off-the-shelf (COTS) RF energy harvester. Extensive evaluation of three fine-grained wireless sensing tasks (i.e., respiration monitoring, human activity, and hand gesture recognition) shows that REHSense can achieve comparable sensing accuracy with conventional Wi-Fi-based solutions while adapting to different sensing environments, reducing the power consumption by 98.7% and harvesting up to 4.5mW of power from RF energy. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2409_00086 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Towards Battery-Free Wireless Sensing via Radio-Frequency Energy Harvesting Ni, Tao Sun, Zehua Han, Mingda Lan, Guohao Xie, Yaxiong Li, Zhenjiang Gu, Tao Xu, Weitao Networking and Internet Architecture Hardware Architecture Human-Computer Interaction Machine Learning Systems and Control Diverse Wi-Fi-based wireless applications have been proposed, ranging from daily activity recognition to vital sign monitoring. Despite their remarkable sensing accuracy, the high energy consumption and the requirement for customized hardware modification hinder the wide deployment of the existing sensing solutions. In this paper, we propose REHSense, an energy-efficient wireless sensing solution based on Radio-Frequency (RF) energy harvesting. Instead of relying on a power-hungry Wi-Fi receiver, REHSense leverages an RF energy harvester as the sensor and utilizes the voltage signals harvested from the ambient Wi-Fi signals to enable simultaneous context sensing and energy harvesting. We design and implement REHSense using a commercial-off-the-shelf (COTS) RF energy harvester. Extensive evaluation of three fine-grained wireless sensing tasks (i.e., respiration monitoring, human activity, and hand gesture recognition) shows that REHSense can achieve comparable sensing accuracy with conventional Wi-Fi-based solutions while adapting to different sensing environments, reducing the power consumption by 98.7% and harvesting up to 4.5mW of power from RF energy. |
| title | Towards Battery-Free Wireless Sensing via Radio-Frequency Energy Harvesting |
| topic | Networking and Internet Architecture Hardware Architecture Human-Computer Interaction Machine Learning Systems and Control |
| url | https://arxiv.org/abs/2409.00086 |