Chen, L, Chen, K, Xiong, J et al. (7 more authors) (2023) Towards Wide-Area Contactless Wireless Sensing. IEEE/ACM Transactions on Networking, 31 (2). pp. 590-605. ISSN 1063-6692
Abstract
Contactless wireless sensing without attaching a device to the target has achieved promising progress in recent years. However, one severe limitation is the small sensing range. This paper presents to realize wide-area sensing with only one transceiver pair. utilizes the LoRa signal to achieve a larger range of sensing and further incorporates drone’s mobility to broaden the sensing area. presents solutions across software and hardware to overcome two aspects of challenges for wide-range contactless sensing: (i) the interference brought by device mobility and LoRa’s high sensitivity; and (ii) the ambiguous target information such as location when employing just a single pair of transceivers for sensing. We have developed a working prototype of for human target detection and localization that are especially useful in emergency scenarios such as rescue search, and evaluated with both controlled experiments and the field study in a high-rise building. Extensive experiments demonstrate the great potential of for wide-area contactless sensing with a single LoRa transceiver pair hosted on a drone.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2022 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. |
Keywords: | Wide-area , wireless sensing , LoRa , mobility |
Dates: |
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Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Engineering & Physical Sciences (Leeds) > School of Computing (Leeds) |
Depositing User: | Symplectic Publications |
Date Deposited: | 04 Aug 2022 15:46 |
Last Modified: | 23 May 2024 14:49 |
Status: | Published |
Publisher: | Association for Computing Machinery (ACM) |
Identification Number: | 10.1109/TNET.2022.3196744 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:189686 |