Abstract
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.
Highlights
Sensed buildings increasingly incorporate sophisticated technology to track occupants to provide services that enhance safety (Song et al, 2008), caregiving (Cully et al, 2011; Cully et al, 2012) and comfort (Erickson et al, 2013) of inhabitants
Radio-frequency identification devices including portable sensors (Fierro et al, 2012; Lazik et al, 2015), embedded Wi-Fi (Zeng et al, 2016; Lee et al, 2020) and Bluetooth beacons (Feldmann et al, 2003; Lazik et al, 2015) have been used for occupant localization. These sensing techniques require clear spaces and a dense deployment of sensors to provide accurate localization of occupants and above all undermine the privacy of building occupants (Tekler et al, 2020)
This paper describes occupant detection and localization carried out using sensors measuring floor vibrations induced by human footsteps
Summary
Sensed buildings increasingly incorporate sophisticated technology to track occupants to provide services that enhance safety (Song et al, 2008), caregiving (Cully et al, 2011; Cully et al, 2012) and comfort (Erickson et al, 2013) of inhabitants. Comparing event signals induced by footsteps at locations #1, #2 and #3 and recorded by sensors S5 and S7, standard deviation (σ) values present a significant discrepancy in magnitudes while these impact locations are at equal distances to sensors (see Figure 3) This disparity in magnitudes between sensors S5 and S7 arises from the varying rigidity of the floor slab between the corridor and the offices due to difference in boundary conditions and presence of separation walls (see Figure 1). RM, which does not take into account uncertainties from multiple sources explicitly, provides inaccurate occupant localization
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