0000000000331216

AUTHOR

Muhammad Muaaz

0000-0001-5225-1926

showing 10 related works from this author

The Transfer Function of Non-Stationary Indoor Channels and its Relationship to System Functions of LFMCW Radars

2021

This paper studies the relationship between the time-variant (TV) channel transfer function (CTF) of non-stationary indoor channels and the system functions of linear frequency modulated continuous waves (LFMCW) radars. To do so, we consider a moving person/object in indoor environments, which is modelled by a cluster of moving point scatterers. It is shown that the TVCTF can be obtained from the beat signal of LFMCW radar systems. Analytical expressions are derived for the TV demodulated radar response, the complex channel gain, and the TV Doppler-delay profile. A relationship between the presented results and existing non-stationary indoor channel models assuming pulsed wave systems is al…

Analytical expressionslawComputer scienceAcousticsBeat (acoustics)ComputerSystemsOrganization_SPECIAL-PURPOSEANDAPPLICATION-BASEDSYSTEMSPoint (geometry)RadarChannel modelsRadar systemsTransfer functionSignallaw.invention
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CORMORANT

2019

People own and carry an increasing number of ubiquitous mobile devices, such as smartphones, tablets, and notebooks. Being small and mobile, those devices have a high propensity to become lost or stolen. Since mobile devices provide access to their owners' digital lives, strong authentication is vital to protect sensitive information and services against unauthorized access. However, at least one in three devices is unprotected, with inconvenience of traditional authentication being the paramount reason. We present the concept of CORMORANT, an approach to significantly reduce the manual burden of mobile user verification through risk-aware, multi-modal biometric, cross-device authentication…

PasswordAuthenticationBiometricsComputer Networks and CommunicationsEvent (computing)Computer science020206 networking & telecommunications02 engineering and technologyComputer securitycomputer.software_genreHuman-Computer InteractionInformation sensitivityKeystroke dynamicsHardware and Architecture0202 electrical engineering electronic engineering information engineeringStrong authentication020201 artificial intelligence & image processingcomputerMobile deviceProceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies
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A Trajectory-Driven 3D Non-Stationary mm-Wave MIMO Channel Model for a Single Moving Point Scatterer

2021

This paper proposes a new non-stationary three-dimensional (3D) channel model for a physical millimeter wave (mm-Wave) multiple-input multiple-output (MIMO) channel. This MIMO channel model is driven by the trajectory of a moving point scatterer, which allows us to investigate the impact of a single moving point scatterer on the propagation characteristics in an indoor environment. Starting from the time-variant (TV) channel transfer function, the temporal behavior of the proposed non-stationary channel model has been analyzed by studying the TV micro-Doppler characteristics and the TV mean Doppler shift. The proposed channel model has been validated by measurements performed in an indoor e…

General Computer ScienceComputer scienceAcousticsMIMOData_CODINGANDINFORMATIONTHEORYMotion capturesymbols.namesakemm-Wave channelsInertial measurement unitGeneral Materials Sciencemean Doppler shiftVDP::Teknologi: 500::Informasjons- og kommunikasjonsteknologi: 550Computer Science::Information Theorymultipath propagationGeneral EngineeringPendulumnon-stationary channelsTK1-9971MIMO channelTrajectorysymbolsSpectrogramElectrical engineering. Electronics. Nuclear engineeringchannel measurementsDoppler effectCommunication channelIEEE Access
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ActRec: A Wi-Fi-Based Human Activity Recognition System

2020

In this paper, we develop a Wi-Fi-based activity recognition system called ActRec, which can be used for the remote monitoring of elderly. ActRec comprises two parts: radio-frequency (RF) sensing and machine learning. In the RF sensing part, two laptops act as transmitter and receiver to record the channel transfer function of an indoor environment. This RF data is collected in the presence of seven human participants performing three activities: walking, falling, and sitting. The RF data containing the fingerprints of user activity is then pre-processed with various signal processing algorithms to reduce noise effects and to estimate the mean Doppler shift (MDS) of each data sample. We pro…

Activity recognitionNaive Bayes classifierStatistical classificationComputer sciencebusiness.industryFeature vectorDecision treePattern recognitionArtificial intelligencebusiness2020 IEEE International Conference on Communications Workshops (ICC Workshops)
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Wi-Sense: a passive human activity recognition system using Wi-Fi and convolutional neural network and its integration in health information systems

2021

AbstractA human activity recognition (HAR) system acts as the backbone of many human-centric applications, such as active assisted living and in-home monitoring for elderly and physically impaired people. Although existing Wi-Fi-based human activity recognition methods report good results, their performance is affected by the changes in the ambient environment. In this work, we present Wi-Sense—a human activity recognition system that uses a convolutional neural network (CNN) to recognize human activities based on the environment-independent fingerprints extracted from the Wi-Fi channel state information (CSI). First, Wi-Sense captures the CSI by using a standard Wi-Fi network interface car…

Computer sciencebusiness.industry010401 analytical chemistry020206 networking & telecommunicationsPattern recognition02 engineering and technology01 natural sciencesConvolutional neural network0104 chemical sciencesActivity recognitionData setNetwork interface controllerChannel state informationVDP::Teknologi: 500::Medisinsk teknologi: 620Principal component analysis0202 electrical engineering electronic engineering information engineeringSpectrogramNoise (video)Artificial intelligenceElectrical and Electronic Engineeringbusiness
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On the Estimation of the Radial Distance of a Moving Person in Indoor Environments from the Demodulated Response of LFMCW Radars

2021

Estimationbusiness.industryComputer scienceComputer visionArtificial intelligencebusiness2021 17th International Conference on Wireless and Mobile Computing, Networking and Communications (WiMob)
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WiWeHAR: Multimodal Human Activity Recognition Using Wi-Fi and Wearable Sensing Modalities

2020

Robust and accurate human activity recognition (HAR) systems are essential to many human-centric services within active assisted living and healthcare facilities. Traditional HAR systems mostly leverage a single sensing modality (e.g., either wearable, vision, or radio frequency sensing) combined with machine learning techniques to recognize human activities. Such unimodal HAR systems do not cope well with real-time changes in the environment. To overcome this limitation, new HAR systems that incorporate multiple sensing modalities are needed. Multiple diverse sensors can provide more accurate and complete information resulting in better recognition of the performed activities. This article…

General Computer ScienceComputer scienceFeature extractionPrincipal component analysisComputació centrada en humansWearable computer02 engineering and technologyDoppler EfecteAccelerometerRadio frequency sensinglaw.inventionActivity recognitionlawInertial measurement unitMachine learning0202 electrical engineering electronic engineering information engineeringfeature fusionGeneral Materials ScienceComputer visionReconeixement de formes (Informàtica)VDP::Teknologi: 500::Informasjons- og kommunikasjonsteknologi: 550Feature fusionModality (human–computer interaction)business.industryfeature extractionSupervised learningGeneral Engineering:Enginyeria de la telecomunicació::Processament del senyal::Reconeixement de formes [Àrees temàtiques de la UPC]020206 networking & telecommunicationsGyroscopemicro-Doppler signatureDoppler effectWearable sensingmachine learningHuman-centered computingActivity recognitionFeature extractionMicro-Doppler signature020201 artificial intelligence & image processing:Informàtica::Intel·ligència artificial [Àrees temàtiques de la UPC]Artificial intelligencelcsh:Electrical engineering. Electronics. Nuclear engineeringHuman activity recognitionbusinesslcsh:TK1-9971
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The Influence of Human Walking Activities on the Doppler Characteristics of Non-stationary Indoor Channel Models

2019

This paper analyzes the time-variant (TV) Doppler power spectral density of a 3D non-stationary fixed-to-fixed indoor channel simulator after feeding it with realistic trajectories of a walking person. The trajectories of the walking person are obtained by simulating a full body musculoskeletal model in OpenSim. We provide expressions of the TV Doppler frequencies caused by these trajectories. Then, we present the complex channel gain consisting of fixed scatterers and a cluster of moving scatterers. After that, we use the concept of the spectrogram to analyze the TV Doppler power spectral density of the complex channel gain. Finally, we present expressions of the TV mean Doppler shift and …

Computer scienceAcoustics0206 medical engineeringWork (physics)Spectral density020206 networking & telecommunications02 engineering and technologyChannel models020601 biomedical engineeringActivity recognitionDynamic simulationsymbols.namesakeChannel simulator0202 electrical engineering electronic engineering information engineeringsymbolsSpectrogramDoppler effect
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Human Activity Signatures Captured under Different Directions Using SISO and MIMO Radar Systems

2022

In this paper, we highlight and resolve the shortcomings of single-input single-output (SISO) millimeter wave (mm-Wave) radar systems for human activity recognition (HAR). A 2×2 distributed multiple-input multiple-output (MIMO) radar framework is presented to capture human activity signatures under realistic conditions in indoor environments. We propose to distribute the two pairs of collocated transmitter–receiver antennas in order to illuminate the indoor environment from different perspectives. For the proposed MIMO system, we measure the time-variant (TV) radial velocity distribution and TV mean radial velocity to observe the signatures of human activities. We deploy the Anc…

direction-independent human activity recognition; fall detection; distributed MIMO; FMCW radar; micro-Doppler signatures; aspect angle; multistatic radar systems; passive step counter; DTW; velocity estimationFluid Flow and Transfer ProcessesProcess Chemistry and TechnologyGeneral EngineeringVDP::Medisinske Fag: 700General Materials ScienceVDP::Matematikk og Naturvitenskap: 400InstrumentationComputer Science::Information TheoryComputer Science ApplicationsApplied Sciences
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WiHAR : From Wi-Fi Channel State Information to Unobtrusive Human Activity Recognition

2020

A robust and unobtrusive human activity recognition system is essential to a multitude of applications, such as health care, active assisted living, robotics, sports, and tele-immersion. Existing well-performing activity recognition methods are either vision- or wearable sensor-based. However, they are not fully passive. In this paper, we develop WiHAR—an unobtrusive Wi-Fi-based activity recognition system. WiHAR uses the Wi-Fi network interface card to capture the channel state information (CSI) data. These CSI data are effectively processed, and then amplitude and phase information is used to obtain the spectrogram. In the subsequent step, the time-variant mean Doppler shift (MDS) caused …

business.industryComputer science05 social sciencesDecision treeWearable computer050801 communication & media studies020206 networking & telecommunicationsComputingMilieux_LEGALASPECTSOFCOMPUTING02 engineering and technologyLinear discriminant analysisActivity recognitionSupport vector machine0508 media and communicationsChannel state information0202 electrical engineering electronic engineering information engineeringSpectrogramComputer visionArtificial intelligencebusinessVDP::Teknologi: 500::Informasjons- og kommunikasjonsteknologi: 550
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