Towards omnidirectional passive human detection
Passive human detection and localization serve as key enablers for various pervasive applications such as smart space, human-computer interaction and asset security. The primary concern in devising scenario-tailored detecting systems is the coverage of their monitoring units. In conventional radio-b...
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sg-smu-ink.sis_research-57602020-01-16T10:30:34Z Towards omnidirectional passive human detection ZHOU, Zimu YANG, Zheng WU, Chenshu SHANGGUAN, Longfei LIU, Yunhao Passive human detection and localization serve as key enablers for various pervasive applications such as smart space, human-computer interaction and asset security. The primary concern in devising scenario-tailored detecting systems is the coverage of their monitoring units. In conventional radio-based schemes, the basic unit tends to demonstrate a directional coverage, even if the underlying devices are all equipped with omnidirectional antennas. Such an inconsistency stems from the link-centric architecture, creating an anisotropic wireless propagating environment. To achieve an omnidirectional coverage while retaining the link-centric architecture, we propose the concept of Omnidirectional Passive Human Detection, and investigate to harness the PHY layer features to virtually tune the shape of the unit coverage by fingerprinting approaches, which is previously prohibited with mere MAC layer RSSI. We design the scheme with ubiquitously deployed WiFi infrastructure and evaluate it in typical multipath-rich indoor scenarios. Experimental results show that our scheme achieves an average false positive of 8% and an average false negative of 7% in detecting human presence in 4 directions. 2013-04-01T07:00:00Z text application/pdf https://ink.library.smu.edu.sg/sis_research/4757 info:doi/10.1109/INFCOM.2013.6567118 https://ink.library.smu.edu.sg/context/sis_research/article/5760/viewcontent/10.1109_INFCOM.2013.6567118.pdf http://creativecommons.org/licenses/by-nc-nd/4.0/ Research Collection School Of Computing and Information Systems eng Institutional Knowledge at Singapore Management University Software Engineering |
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Software Engineering ZHOU, Zimu YANG, Zheng WU, Chenshu SHANGGUAN, Longfei LIU, Yunhao Towards omnidirectional passive human detection |
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Passive human detection and localization serve as key enablers for various pervasive applications such as smart space, human-computer interaction and asset security. The primary concern in devising scenario-tailored detecting systems is the coverage of their monitoring units. In conventional radio-based schemes, the basic unit tends to demonstrate a directional coverage, even if the underlying devices are all equipped with omnidirectional antennas. Such an inconsistency stems from the link-centric architecture, creating an anisotropic wireless propagating environment. To achieve an omnidirectional coverage while retaining the link-centric architecture, we propose the concept of Omnidirectional Passive Human Detection, and investigate to harness the PHY layer features to virtually tune the shape of the unit coverage by fingerprinting approaches, which is previously prohibited with mere MAC layer RSSI. We design the scheme with ubiquitously deployed WiFi infrastructure and evaluate it in typical multipath-rich indoor scenarios. Experimental results show that our scheme achieves an average false positive of 8% and an average false negative of 7% in detecting human presence in 4 directions. |
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text |
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ZHOU, Zimu YANG, Zheng WU, Chenshu SHANGGUAN, Longfei LIU, Yunhao |
author_facet |
ZHOU, Zimu YANG, Zheng WU, Chenshu SHANGGUAN, Longfei LIU, Yunhao |
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ZHOU, Zimu |
title |
Towards omnidirectional passive human detection |
title_short |
Towards omnidirectional passive human detection |
title_full |
Towards omnidirectional passive human detection |
title_fullStr |
Towards omnidirectional passive human detection |
title_full_unstemmed |
Towards omnidirectional passive human detection |
title_sort |
towards omnidirectional passive human detection |
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Institutional Knowledge at Singapore Management University |
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2013 |
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https://ink.library.smu.edu.sg/sis_research/4757 https://ink.library.smu.edu.sg/context/sis_research/article/5760/viewcontent/10.1109_INFCOM.2013.6567118.pdf |
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