Model-Based Occupant Tracking Using Slab-Vibration Measurements

Sensor-based occupant tracking has the potential to enhance knowledge of the utilization of buildings. Occupancy-tracking strategies using footstep-induced floor vibrations may be beneficial for thermal-load prediction, security enhancement, and care-giving without undermining privacy. Current floor-vibration-based occupant-tracking methodologies are based on data-driven techniques that do not include a physics-based model of the structural behavior of the floor slab. These techniques suffer from ambiguous interpretations when signals are affected by complex configurations of structural and non-structural elements such as beams and walls. Using a physics-based model for data-interpretation enables deployment of sparse number of sensors in contexts of non-uniform structural configurations. In this paper, an application of physics-based data interpretation using error-domain model falsification (EDMF) is presented to track an occupant within an office environment through footstep-induced floor vibrations. EDMF is a population-based approach that incorporates various sources of uncertainty, including bias, arising from measurements and modeling. EDMF involves the rejection of simulated model responses that contradict footstep-induced floor vibration measurements. Thus, EDMF provides a set of candidate locations from an initial population of possible occupant locations. A sequential analysis that accommodates information from previous footsteps is then used to enhance candidate locations and identify trajectories among candidates. In this way, incorporating structural behavior in interpreting vibration measurements induced by occupant footsteps has the potential to identify accurately the trajectory of an occupant in buildings with complex configurations, thereby providing tracking information without undermining privacy

Model-Based Occupant Tracking Using Slab-Vibration Measurements

Sensor-based occupant tracking has the potential to enhance knowledge of the utilization of buildings. Occupancy-tracking strategies using footstep-induced floor vibrations may be beneficial for thermal-load prediction, security enhancement, and care-giving without undermining privacy. Current floor-vibration-based occupant-tracking methodologies are based on data-driven techniques that do not include a physics-based model of the structural behavior of the floor slab. These techniques suffer from ambiguous interpretations when signals are affected by complex configurations of structural and non-structural elements such as beams and walls. Using a physics-based model for data-interpretation enables deployment of sparse number of sensors in contexts of non-uniform structural configurations. In this paper, an application of physics-based data interpretation using error-domain model falsification (EDMF) is presented to track an occupant within an office environment through footstep-induced floor vibrations. EDMF is a population-based approach that incorporates various sources of uncertainty, including bias, arising from measurements and modeling. EDMF involves the rejection of simulated model responses that contradict footstep-induced floor vibration measurements. Thus, EDMF provides a set of candidate locations from an initial population of possible occupant locations. A sequential analysis that accommodates information from previous footsteps is then used to enhance candidate locations and identify trajectories among candidates. In this way, incorporating structural behavior in interpreting vibration measurements induced by occupant footsteps has the potential to identify accurately the trajectory of an occupant in buildings with complex configurations, thereby providing tracking information without undermining privacy

LOCALIZATION OF STATIONARY SOURCE OF FLOOR VIBRATION USING THE STEERED RESPONSE POWER METHOD

If the generated vibration in a building exceeds the acceptable limit design for a floor system, it is necessary to identify the source of vibration, a process known as localization. The objective of this study is the localization of stationary vibration sources, and the approach used is the steered response power (SRP) method. This method has already been shown to work well for wireless and acoustical applications to locate transmitter and sound sources, respectively. To the writer’s knowledge, this study is the first application of the SRP method to locate vibration sources using floor vibration measurements. However, because waves behave differently when propagated through a concrete floor as opposed to the air, this method has been significantly modified for the application presented herein. The key and prerequisite parameter for most vibration-sensing-localization approaches is wave propagation speed (WPS). The accuracy of these approaches therefore depends on the accuracy of the WPS estimate. The WPS of a concrete floor system is a function of parameters with high variability due to the mechanical and dynamic properties of the floor. This makes the task of vibration-sensing-localization challenging for the aforementioned approaches. The SRP method has been employed because it is based on an algorithm to post-process all received signals together and such structural variability is less likely to affect the accuracy; therefore, the SRP method is more robust. Most localization approaches are based on ideal wave propagation, e.g., constant propagation speed in all directions and vibration energy decreasing predictably as the source-sensor distance increases. However, such ideal propagation does not occur in many real-world structural systems such as a concrete floor. In this study, the WPS was estimated empirically in orthogonal directions using the cross-correlation function. The SRP method used herein was adopted to use the estimated WPS in orthogonal directions as an input parameter and then automatically interpolating the corresponding propagation speed for all other directions. This is another advantage of this method over existing methods. The experiment was conducted on the second floor of a full-scale, concrete-framed building at the University of Kentucky. The WPS was estimated in orthogonal directions using an electrodynamic shaker and seven accelerometers. The shaker applied an excitation force and acted as the source of vibration, and the accelerometers were put in various locations on the floor and measured the response. Using the estimated WPS and corresponding measurement data, the SRP method was able to locate the vibration source within 2.0 m in a floor approximately 13.4 m by 8.4 m in size

Device-free indoor localisation with non-wireless sensing techniques : a thesis by publications presented in partial fulfilment of the requirements for the degree of Doctor of Philosophy in Electronics and Computer Engineering, Massey University, Albany, New Zealand

Global Navigation Satellite Systems provide accurate and reliable outdoor positioning to support a large number of applications across many sectors. Unfortunately, such systems do not operate reliably inside buildings due to the signal degradation caused by the absence of a clear line of sight with the satellites. The past two decades have therefore seen intensive research into the development of Indoor Positioning System (IPS). While considerable progress has been made in the indoor localisation discipline, there is still no widely adopted solution. The proliferation of Internet of Things (IoT) devices within the modern built environment provides an opportunity to localise human subjects by utilising such ubiquitous networked devices. This thesis presents the development, implementation and evaluation of several passive indoor positioning systems using ambient Visible Light Positioning (VLP), capacitive-flooring, and thermopile sensors (low-resolution thermal cameras). These systems position the human subject in a device-free manner (i.e., the subject is not required to be instrumented). The developed systems improve upon the state-of-the-art solutions by offering superior position accuracy whilst also using more robust and generalised test setups. The developed passive VLP system is one of the first reported solutions making use of ambient light to position a moving human subject. The capacitive-floor based system improves upon the accuracy of existing flooring solutions as well as demonstrates the potential for automated fall detection. The system also requires very little calibration, i.e., variations of the environment or subject have very little impact upon it. The thermopile positioning system is also shown to be robust to changes in the environment and subjects. Improvements are made over the current literature by testing across multiple environments and subjects whilst using a robust ground truth system. Finally, advanced machine learning methods were implemented and benchmarked against a thermopile dataset which has been made available for other researchers to use

Biomechanical Locomotion Heterogeneity in Synthetic Crowds

Synthetic crowd simulation combines rule sets at different conceptual layers to represent the dynamic nature of crowds while adhering to basic principles of human steering, such as collision avoidance and goal completion. In this dissertation, I explore synthetic crowd simulation at the steering layer using a critical approach to define the central theme of the work, the impact of model representation and agent diversity in crowds. At the steering layer, simulated agents make regular decisions, or actions, related to steering which are often responsible for the emergent behaviours found in the macro-scale crowd. Because of this bottom-up impact of a steering model's defining rule-set, I postulate that biomechanics and diverse biomechanics may alter the outcomes of dynamic synthetic-crowds-based outcomes. This would mean that an assumption of normativity and/or homogeneity among simulated agents and their mobility would provide an inaccurate representation of a scenario. If these results are then used to make real world decisions, say via policy or design, then those populations not represented in the simulated scenario may experience a lack of representation in the actualization of those decisions. A focused literature review shows that applications of both biomechanics and diverse locomotion representation at this layer of modelling are very narrow and often not present. I respond to the narrowness of this representation by addressing both biomechanics and heterogeneity separately. To address the question of performance and importance of locomotion biomechanics in crowd simulation, I use a large scale comparative approach. The industry standard synthetic crowd models are tested under a battery of benchmarks derived from prior work in comparative analysis of synthetic crowds as well as new scenarios derived from built environments. To address the question of the importance of heterogeneity in locomotion biomechanics, I define tiers of impact in the multi-agent crowds model at the steering layer--from the action space, to the agent space, to the crowds space. To this end, additional models and layers are developed to address the modelling and application of heterogeneous locomotion biomechanics in synthetic crowds. The results of both studies form a research arc which shows that the biomechanics in steering models provides important fidelity in several applications and that heterogeneity in the model of locomotion biomechanics directly impacts both qualitative and quantitative synthetic crowds outcomes. As well, systems, approaches, and pitfalls regarding the analysis of steering model and human mobility diversity are described

The Yoga Analogy: Scaling-Up the U.S.’s Renewable Energy Sector Mindfully with New Technologies, Evolving Standards, Public Buy-In, Data Sharing, and Innovation Clusters

This paper focuses on innovative renewable energy devices, exploring how scientifically-based industry standards that continuously evolve with engineering design technology, the public’s buy-in and feeling of connectedness with groundbreaking devices, and innovation clusters that accelerate device development through data sharing and public-private partnerships can all help advance the U.S.’s domestic renewable energy industry. Part I analyzes challenges inherent to scaling- up novel renewable energy technologies while simultaneously developing the industry standards regulating them. Part II uses the Block Island Wind Farm, an offshore wind demonstration project, and Pavegen’s globally-deployed arrays of piezoelectric smart flooring tiles as examples illustrating the importance connectedness and engagement play in garnering public buy-in during a cutting-edge renewable energy device’s roll-out. Part III discusses private investors’ critical role in bearing financial risks associated with backing experimental technologies, promoting aesthetically unusual device designs, and integrating novel devices into the built environment. Part IV explores the advantages that data anonymization and data sharing within a data trust construct can produce for constituents in an innovation cluster, particularly those functioning together within a public-private partnership. Part V explores the benefits of introducing a renewable energy device prototype in an innovation cluster, where the government, academia, and industry collaborate and share data through public-private partnerships in an engaged, supportive, and technologically savvy community focused on accelerating the development of a particular industry. This paper concludes that by setting industry standards that continuously evolve in tandem with technologies they aim to regulate, having businesses’ investment-backed expectations remain a key driving force in renewable energy device development, and deploying government funding through innovation clusters that support data sharing and public-private partnerships in a particular industry, the U.S. can strike a desired balance and mindfully scale-up its nascent renewable energy industry

Soundscape in Times of Change: Case Study of a City Neighbourhood During the COVID-19 Lockdown

The coronavirus disease 2019 (COVID-19) lockdown meant a greatly reduced social and economic activity. Sound is of major importance to people's perception of the environment, and some remarked that the soundscape was changing for the better. But are these anecdotal reports based in truth? Has traffic noise from cars and airplanes really gone down, so that more birdsong can be heard? Have socially distanced people quietened down? This article presents a case study of the human perception of environmental sounds in an urban neighborhood in the Basque Country between 15 March and 25 May 2020. The social restrictions imposed through national legislation divided the 69-day period into three phases. We collected observations, field audio recordings, photography, and diary notes on 50 days. Experts in soundscape and architecture were presented with the recordings, in randomized order, and made two separate perceptual analyses. One group (N = 11) rated the recordings for pleasantness and eventfulness using an adapted version of the Swedish Soundscape Quality Protocol, and a partly overlapping group (N = 12) annotated perceived sound events with free-form semantic labels. The labels were systematically classified into a four-level Taxonomy of Sound Sources, allowing an estimation of the relative amounts of Natural, Human, and Technological sounds. Loudness and three descriptors developed for bioacoustics were extracted computationally. Analysis showed that Eventfulness, Acoustic Complexity, and Acoustic Richness increased significantly over the time period, while the amount of Technological sounds decreased. These observations were interpreted as reflecting changes in people's outdoor activities and behavior over the whole 69-day period, evidenced in an increased presence of Human sounds of voices and walking, and a significant shift from motorized vehicles toward personal mobility devices, again evidenced by perceived sounds. Quantitative results provided a backdrop against which qualitative analyses of diary notes and observations were interpreted in relation to the restrictions and the architectural specifics of the site. An integrated analysis of all sources pointed at the temporary suspension of human outdoor activity as the main reason for such a change. In the third phase, the progressive return of street life and the usage of personal mobility vehicles seemed to be responsible for a clear increase in Eventfulness and Loudness even in the context of an overall decrease of Technological sounds. Indoor human activity shared through open windows and an increased presence of birdsong emerge as a novel characteristic element of the local urban soundscape. We discuss how such changes in the acoustic environment of the site, in acoustic measurements and as perceived by humans, point toward the soundscape being a crucial component of a comprehensive urban design strategy that aims to improve health and quality of life for increasingly large and dense populations in the future.This research was conducted with funding from Politcnico di Milano - Design (Lenzi), EKOPOL (Sábada), and CityU StUp Grant 7200671 (Lindborg)