Is there a relationship between footstep-impact locations and measured signal characteristics?

Pai, Sai Ganesh Sarvotham; Reuland, Yves; Drira, Slah; Smith, Ian F. C.

doi:10.1145/3360773.3360888

Cited by 8 publications

(4 citation statements)

References 3 publications

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“…N s denotes the size of the impact signal, S s,f . Standard deviation (σ) values are well-suited to evaluate the impact signals since they are correlated to the impact force induced by footsteps as analyzed in detail by Pai et al (2019). Other metrics including maximum difference in amplitudes and root-mean square (RMS) of processed footstep-impact signals are also evaluated in this study.…”

Section: Influence Of Structural Behavior On Floor Vibrationsmentioning

confidence: 99%

“…An inversely proportional decay between distance from footstep-impact to a sensor location and impulse energy was shown by Pan et al (2014). However, it has been shown by Drira et al (2019b) and Pai et al (2019) this relationship is not always observable due to the presence of support conditions such as columns and walls leading to varying rigidity of floors.…”

Section: Introductionmentioning

confidence: 99%

“…Preliminary analysis by Pai et al (2019) has shown that due to the influence of structural behavior on floor vibrations, there is a need for model-based approaches for occupant localization. In addition, a sensitivity analysis over several signal characteristics was carried out to find suitable metrics for model-based occupant localization.…”

Section: Introductionmentioning

confidence: 99%

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Uncertainties in Structural Behavior for Model-Based Occupant Localization Using Floor Vibrations

Drira

Pai

Smith

2021

Front. Built Environ.

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In sensed buildings, information related to occupant movement helps optimize functions such as security, energy management, and caregiving. Due to privacy needs, non-intrusive sensing approaches for tracking occupants inside buildings, such as vibration sensors, are often preferred over intrusive strategies that involve use of cameras and wearable devices. Current sensor-based occupant-localization approaches are data-driven techniques that do not account for structural behavior and limited to slabs on grade. Varying-rigidity floors and inherent variability in walking gaits lead to ambiguous interpretations of floor vibrations when performing model-free occupant localization. In this paper, an extensive analysis of vibrations induced by a range of occupants is described. Firstly, the need for a structural-behavior model for occupant localization is assessed using two full-scale case studies. Structural behavior is found to significantly influence floor vibrations induced by footstep impacts. Since a simple relationship between distances from footstep-impact to sensor locations cannot be assured, the use of physics-based models is necessary for accurate occupant localization. Secondly, measured data are interpreted using physics-based models and information related to uncertainties from multiple sources. There are two types of uncertainties: modelling uncertainties and measurement uncertainties, including variability in walking gaits. Error-domain model falsification (EDMF) and residual minimization (RM) are model-based approaches for data interpretation. Unlike RM, EDMF explicitly accounts for the presence of systematic errors in parameters and overall model bias. In this paper, model-based occupant localization is carried out using EDMF and RM on a full-scale case study. By explicitly accounting for the presence of uncertainties and the influence of structural behavior, EDMF, unlike RM, accurately reveals possible occupant locations on floor slabs.

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Section: Influence Of Structural Behavior On Floor Vibrationsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Uncertainties in Structural Behavior for Model-Based Occupant Localization Using Floor Vibrations

Drira

Pai

Smith

2021

Front. Built Environ.

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“…Alajlouni et al [39], for instance, showed their hypothesis of an energy-decay model (energy logarithmically decays with propagation distance) as a localization model. In their work, Pai et al [40] analyzed whether a relationship exists between the occupant's footfall patterns and the measured signal characteristics in an empirical case study. In light of their work, the authors assert that there is no evidence of a monotonic relationship between the amplitude or kurtosis of the measured signal and the propagation distance.…”

Section: Introductionmentioning

confidence: 99%

A Multi-Sensor Stochastic Energy-Based Vibro-Localization Technique with Byzantine Sensor Elimination

Ambarkutuk,

Alajlouni,

Tarazaga

et al. 2023

Sensors

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This paper presents an occupant localization technique that determines the location of individuals in indoor environments by analyzing the structural vibrations of the floor caused by their footsteps. Structural vibration waves are difficult to measure as they are influenced by various factors, including the complex nature of wave propagation in heterogeneous and dispersive media (such as the floor) as well as the inherent noise characteristics of sensors observing the vibration wavefronts. The proposed vibration-based occupant localization technique minimizes the errors that occur during the signal acquisition time. In this process, the likelihood function of each sensor—representing where the occupant likely resides in the environment—is fused to obtain a consensual localization result in a collective manner. In this work, it becomes evident that the above sources of uncertainties can render certain sensors deceptive, commonly referred to as “Byzantines.” Because the ratio of Byzantines among the set sensors defines the success of the collective localization results, this paper introduces a Byzantine sensor elimination (BSE) algorithm to prevent the unreliable information of Byzantine sensors from affecting the location estimations. This algorithm identifies and eliminates sensors that generate erroneous estimates, preventing the influence of these sensors on the overall consensus. To validate and benchmark the proposed technique, a set of previously conducted controlled experiments was employed. The empirical results demonstrate the proposed technique’s significant improvement (3~0%) over the baseline approach in terms of both accuracy and precision.

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Using footstep-induced vibrations for occupant detection and recognition in buildings

Drira

Pai

Reuland

et al. 2021

Advanced Engineering Informatics

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Is there a relationship between footstep-impact locations and measured signal characteristics?

Cited by 8 publications

References 3 publications

Uncertainties in Structural Behavior for Model-Based Occupant Localization Using Floor Vibrations

Uncertainties in Structural Behavior for Model-Based Occupant Localization Using Floor Vibrations

A Multi-Sensor Stochastic Energy-Based Vibro-Localization Technique with Byzantine Sensor Elimination

Using footstep-induced vibrations for occupant detection and recognition in buildings

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