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Zhang Y, Wang X, Wen J, Zhu X. WiFi-based non-contact human presence detection technology. Sci Rep 2024; 14:3605. [PMID: 38351067 PMCID: PMC10864388 DOI: 10.1038/s41598-024-54077-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/23/2023] [Accepted: 02/08/2024] [Indexed: 02/16/2024] Open
Abstract
In the swiftly evolving landscape of Internet of Things (IoT) technology, the demand for adaptive non-contact sensing has seen a considerable surge. Traditional human perception technologies, such as vision-based approaches, often grapple with problems including lack of sensor versatility and sub-optimal accuracy. To address these issues, this paper introduces a novel, non-contact method for human presence perception, relying on WiFi. This innovative approach involves a sequential process, beginning with the pre-processing of collected Channel State Information (CSI), followed by feature extraction, and finally, classification. By establishing signal models that correspond to varying states, this method enables the accurate perception and recognition of human presence. Remarkably, this technique exhibits a high level of precision, with sensing accuracy reaching up to 99[Formula: see text]. The potential applications of this approach are extensive, proving to be particularly beneficial in contexts such as smart homes and healthcare, amongst various other everyday scenarios. This underscores the significant role this novel method could play in enhancing the sophistication and effectiveness of human presence detection and recognition systems in the IoT era.
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Affiliation(s)
- Yang Zhang
- School of Economics and Management, Shanghai Polytechnic University, Shanghai, 201209, China.
| | - Xuechun Wang
- School of Electrical and Electronic Engineering, Hubei University of Technology, Wuhan, 430068, China
| | - Jinghao Wen
- School of Computer Science, Central China Normal University, Wuhan, 430079, China
| | - Xianxun Zhu
- School of Communication and Information Engineering, Shanghai University, Shanghai, 200444, China
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2
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Eliezer Y, Rührmair U, Wisiol N, Bittner S, Cao H. Tunable nonlinear optical mapping in a multiple-scattering cavity. Proc Natl Acad Sci U S A 2023; 120:e2305027120. [PMID: 37490539 PMCID: PMC10401015 DOI: 10.1073/pnas.2305027120] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/28/2023] [Accepted: 06/18/2023] [Indexed: 07/27/2023] Open
Abstract
Nonlinear disordered systems are not only a model system for fundamental studies but also in high demand for practical applications. However, optical nonlinearity based on intrinsic material response is weak in random scattering systems. Here, we propose and experimentally realize a highly nonlinear mapping between the scattering potential and the emerging light of a reconfigurable multiple-scattering cavity. A quantitative analysis of the degree of nonlinearity reveals its dependence on the number of scattering events. The effective order of nonlinear mapping can be tuned over a wide range at low optical lower. The strong nonlinear mapping enhances output intensity fluctuations and long-range correlations. The flexibility, robustness, and energy efficiency of our approach provides a versatile platform for exploring such nonlinear mappings for various applications.
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Affiliation(s)
- Yaniv Eliezer
- Department of Applied Physics, Yale University, New Haven, CT06520
| | - Ulrich Rührmair
- Electrical and Computer Engineering Department, University of Connecticut, Storrs, CT06249
- Institute for Computer Science, Ludwig Maximilian University of Munich, 80538München, Germany
| | - Nils Wisiol
- Security in Telecommunications, Department of Software Engineering and Theoretical Computer Science, Technische Universität Berlin, Berlin, Germany
| | - Stefan Bittner
- Chair in Photonics, CentraleSupélec, Optical Materials, Photonics and Systems Laboratory, Metz57070, France
- Université de Lorraine, Chair in Photonics, CentraleSupélec, Optical Materials, Photonics and Systems Laboratory, Metz57070, France
| | - Hui Cao
- Department of Applied Physics, Yale University, New Haven, CT06520
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3
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Davy M, Besnier P, Del Hougne P, de Rosny J, Richalot E, Sarrazin F, Savin DV, Mortessagne F, Kuhl U, Legrand O. Diffuse field cross-correlations: Scattering theory and electromagnetic experiments. Phys Rev E 2021; 104:044204. [PMID: 34781571 DOI: 10.1103/physreve.104.044204] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/02/2021] [Accepted: 09/23/2021] [Indexed: 11/07/2022]
Abstract
The passive estimation of impulse responses from ambient noise correlations arouses increasing interest in seismology, acoustics, optics, and electromagnetism. Assuming the equipartition of the noise field, the cross-correlation function measured with noninvasive receiving probes converges towards the difference of the causal and anticausal Green's functions. Here, we consider the case when the receiving field probes are antennas which are well coupled to a complex medium-a scenario of practical relevance in electromagnetism. We propose a general approach based on the scattering matrix formalism to explore the convergence of the cross-correlation function. The analytically derived theoretical results for chaotic systems are confirmed in microwave measurements within a mode-stirred reverberation chamber. This study provides fundamental insight into the Green's function retrieval technique and paves the way for a new technique to characterize electromagnetic antennas.
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Affiliation(s)
- Matthieu Davy
- Univ Rennes, INSA Rennes, CNRS, IETR - UMR 6164, F-35000 Rennes, France
| | - Philippe Besnier
- Univ Rennes, INSA Rennes, CNRS, IETR - UMR 6164, F-35000 Rennes, France
| | - Philipp Del Hougne
- Univ Rennes, INSA Rennes, CNRS, IETR - UMR 6164, F-35000 Rennes, France.,Université Côte d'Azur, CNRS, Institut de Physique de Nice, UMR 7010, 06108 Nice, France
| | - Julien de Rosny
- ESPCI Paris, PSL Research University, Institut Langevin, F-75005 Paris, France
| | - Elodie Richalot
- ESYCOM lab, Univ Gustave Eiffel, CNRS, F-77454 Marne-la-Vallée, France
| | - François Sarrazin
- ESYCOM lab, Univ Gustave Eiffel, CNRS, F-77454 Marne-la-Vallée, France
| | - Dmitry V Savin
- Department of Mathematics, Brunel University London, Uxbridge UB8 3PH, United Kingdom
| | - Fabrice Mortessagne
- Université Côte d'Azur, CNRS, Institut de Physique de Nice, UMR 7010, 06108 Nice, France
| | - Ulrich Kuhl
- Université Côte d'Azur, CNRS, Institut de Physique de Nice, UMR 7010, 06108 Nice, France
| | - Olivier Legrand
- Université Côte d'Azur, CNRS, Institut de Physique de Nice, UMR 7010, 06108 Nice, France
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4
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Peng Z, Jian J, Wen H, Gribok A, Wang M, Liu H, Huang S, Mao ZH, Chen KP. Distributed fiber sensor and machine learning data analytics for pipeline protection against extrinsic intrusions and intrinsic corrosions. OPTICS EXPRESS 2020; 28:27277-27292. [PMID: 32988024 DOI: 10.1364/oe.397509] [Citation(s) in RCA: 18] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/12/2020] [Accepted: 08/19/2020] [Indexed: 06/11/2023]
Abstract
This paper presents an integrated technical framework to protect pipelines against both malicious intrusions and piping degradation using a distributed fiber sensing technology and artificial intelligence. A distributed acoustic sensing (DAS) system based on phase-sensitive optical time-domain reflectometry (φ-OTDR) was used to detect acoustic wave propagation and scattering along pipeline structures consisting of straight piping and sharp bend elbow. Signal to noise ratio of the DAS system was enhanced by femtosecond induced artificial Rayleigh scattering centers. Data harnessed by the DAS system were analyzed by neural network-based machine learning algorithms. The system identified with over 85% accuracy in various external impact events, and over 94% accuracy for defect identification through supervised learning and 71% accuracy through unsupervised learning.
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5
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Del Hougne P, Savin DV, Legrand O, Kuhl U. Implementing nonuniversal features with a random matrix theory approach: Application to space-to-configuration multiplexing. Phys Rev E 2020; 102:010201. [PMID: 32795053 DOI: 10.1103/physreve.102.010201] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/10/2020] [Accepted: 07/16/2020] [Indexed: 11/07/2022]
Abstract
We consider the efficiency of multiplexing spatially encoded information across random configurations of a metasurface-programmable chaotic cavity in the microwave domain. The distribution of the effective rank of the channel matrix is studied to quantify the channel diversity and to assess a specific system's performance. System-specific features such as unstirred field components give rise to nontrivial interchannel correlations and need to be properly accounted for in modeling based on random matrix theory. To address this challenge, we propose a two-step hybrid approach. Based on an ensemble of experimentally measured scattering matrices for different random metasurface configurations, we first learn a system-specific pair of coupling matrix and unstirred contribution to the Hamiltonian, and then add an appropriately weighted stirred contribution. We verify that our method is capable of reproducing the experimentally found distribution of the effective rank with good accuracy. The approach can also be applied to other wave phenomena in complex media.
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Affiliation(s)
- Philipp Del Hougne
- Institut de Physique de Nice, CNRS UMR 7010, Université Côte d'Azur, 06108 Nice, France
| | - Dmitry V Savin
- Department of Mathematics, Brunel University London, Uxbridge UB8 3PH, United Kingdom
| | - Olivier Legrand
- Institut de Physique de Nice, CNRS UMR 7010, Université Côte d'Azur, 06108 Nice, France
| | - Ulrich Kuhl
- Institut de Physique de Nice, CNRS UMR 7010, Université Côte d'Azur, 06108 Nice, France
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6
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Ma S, Xiao B, Drikas Z, Addissie B, Hong R, Antonsen TM, Ott E, Anlage SM. Wave scattering properties of multiple weakly coupled complex systems. Phys Rev E 2020; 101:022201. [PMID: 32168697 DOI: 10.1103/physreve.101.022201] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/06/2019] [Accepted: 12/19/2019] [Indexed: 11/07/2022]
Abstract
The statistics of the scattering of waves inside single ray-chaotic enclosures have been successfully described by the random coupling model (RCM). We expand the RCM to systems consisting of multiple complex ray-chaotic enclosures with various coupling scenarios. The statistical properties of the model-generated quantities are tested against measured data of electrically large multicavity systems of various designs. The statistics of model-generated transimpedance and induced voltages on a load impedance agree well with the experimental results. The RCM coupled chaotic enclosure model is general and can be applied to other physical systems, including coupled quantum dots, disordered nanowires, and short-wavelength electromagnetic and acoustic propagation through rooms in buildings, aircraft, and ships.
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Affiliation(s)
- Shukai Ma
- Quantum Materials Center and Department of Physics, University of Maryland, College Park, Maryland 20742-4111, USA
| | - Bo Xiao
- Department of Electrical and Computer Engineering, University of Maryland, College Park, Maryland 20742-3285, USA
| | - Zachary Drikas
- U.S. Naval Research Laboratory, Washington, DC 20375, USA
| | | | - Ronald Hong
- U.S. Naval Research Laboratory, Washington, DC 20375, USA
| | - Thomas M Antonsen
- Department of Electrical and Computer Engineering, University of Maryland, College Park, Maryland 20742-3285, USA.,Department of Physics, University of Maryland, College Park, Maryland 20742-4111, USA
| | - Edward Ott
- Department of Electrical and Computer Engineering, University of Maryland, College Park, Maryland 20742-3285, USA.,Department of Physics, University of Maryland, College Park, Maryland 20742-4111, USA
| | - Steven M Anlage
- Quantum Materials Center and Department of Physics, University of Maryland, College Park, Maryland 20742-4111, USA.,Department of Electrical and Computer Engineering, University of Maryland, College Park, Maryland 20742-3285, USA
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7
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Del Hougne P, Imani MF, Fink M, Smith DR, Lerosey G. Precise Localization of Multiple Noncooperative Objects in a Disordered Cavity by Wave Front Shaping. PHYSICAL REVIEW LETTERS 2018; 121:063901. [PMID: 30141669 DOI: 10.1103/physrevlett.121.063901] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/31/2018] [Indexed: 05/13/2023]
Abstract
Complicated multipath trajectories of waves in disordered cavities cause object localization to be very challenging with traditional ray-tracing approaches. Yet it is known that information about the object position is encoded in the Green's function. After a calibration step, traditional time-reversal approaches retrieve a source's location from a broadband impulse response measurement. Here, we show that a nonemitting object's scattering contribution to a reverberant medium suffices to localize the object. We demonstrate our finding in the microwave domain. Then, we further simplify the scheme by replacing the temporal degrees of freedom (d.o.f.) of the broadband measurement with spatial d.o.f. obtained from wave front shaping. A simple electronically reconfigurable reflectarray inside the cavity dynamically modulates parts of the cavity boundaries, thereby providing spatial d.o.f. The demonstrated ability to localize multiple noncooperative objects with a single-frequency scheme may have important applications for sensors in smart homes.
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Affiliation(s)
- Philipp Del Hougne
- Institut Langevin, CNRS UMR 7587, ESPCI Paris, PSL Research University, 1 rue Jussieu, 75005 Paris, France
- Department of Electrical and Computer Engineering, Center for Metamaterials and Integrated Plasmonics, Duke University, Durham, North Carolina 27708, USA
| | - Mohammadreza F Imani
- Department of Electrical and Computer Engineering, Center for Metamaterials and Integrated Plasmonics, Duke University, Durham, North Carolina 27708, USA
| | - Mathias Fink
- Institut Langevin, CNRS UMR 7587, ESPCI Paris, PSL Research University, 1 rue Jussieu, 75005 Paris, France
| | - David R Smith
- Department of Electrical and Computer Engineering, Center for Metamaterials and Integrated Plasmonics, Duke University, Durham, North Carolina 27708, USA
| | - Geoffroy Lerosey
- Greenerwave, ESPCI Paris Incubator PC'up, 6 rue Jean Calvin, 75005 Paris, France
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