Chen, L, Xiong, J, Chen, X et al. (6 more authors) (2019) WideSee: towards wide-area contactless wireless sensing. In: Proceedings of the 17th Conference on Embedded Networked Sensor Systems. 17th ACM Conference on Embedded Networked Sensor Systems (SenSys 2019), 10-13 Nov 2019, New York, NY, USA. ACM Digital Library , pp. 258-270. ISBN 978-1-4503-6950-3
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 WideSee to realize wide-area sensing with only one transceiver pair. WideSee utilizes the LoRa signal to achieve a larger range of sensing and further incorporates drone's mobility to broaden the sensing area. WideSee presents solutions across software and hardware to overcome two aspects of challenges for wide-range contactless sensing: (i) the interference brought by the device mobility and LoRa's high sensitivity; and (ii) the ambiguous target information such as location when employing just a single pair of transceivers. We have developed a working prototype of WideSee for human target detection and localization that are especially useful in emergency scenarios such as rescue search, and evaluated WideSee with both controlled experiments and the field study in a high-rise building. Extensive experiments demonstrate the great potential of WideSee for wide-area contactless sensing with a single LoRa transceiver pair hosted on a drone.
Metadata
Item Type: | Proceedings Paper |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2019 Association for Computing Machinery. This is an author produced version of a paper published in Proceedings of the 17th Conference on Embedded Networked Sensor Systems. Uploaded in accordance with the publisher's self-archiving policy. |
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: | 15 Aug 2019 11:08 |
Last Modified: | 02 Dec 2019 15:35 |
Status: | Published |
Publisher: | ACM Digital Library |
Identification Number: | 10.1145/3356250.3360031 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:149652 |