The Impact of Spatial Resolution and Representation on Human Mobility Predictability

The study of human mobility patterns is important for both understanding human behaviour, a social phenomenon and to simulate infection transmission. Factors such as geometry representation, granularity, missing data and data noise affect the reliability, validity, and credibility of human mobility data, and any models drawn from this data. This thesis discusses the impact of spatial representations of human mobility patterns through a series of analyses using entropy and trip-length distributions as evaluation criteria, Voronoi decomposition and square grid decomposition as alternative geometry representations. I further examine a spectrum of spatial granularity, from dimensions associated with social interaction, to city, and provincial scale, and toggle analysis between raw data and post-processed data to understand the impact of noisy data and missing data influence estimation. A dataset I was involved with collecting – SHED1 – featuring multi-sensor data collection over 5 weeks among 39 participants – has been used for the experiments. An analysis of the results further strengthens the findings of Song et al., and demonstrates comparability in predictability of human mobility through geometric representation between Voronoi decomposition and square grid decompositions, suggesting a scale dependence of human mobility analysis, and demonstrating the value of using missing data analysis throughout the study

Object Localization and Tracking in 3D

The field of Computer Vision has repeatedly been recognized as an intellectual frontier whose boundaries of applicability are yet to be stipulated. The work attempts to demonstrate that vision can achieve an automatic localization and tracking of targets in a 3D space. Localization of targets has gained importance in the recent past due to the myriad of applications it plays a significant role in. It is analogous to detection of objects in a video sequence in the image processing domain. This work aims to localize a target based on range measurements obtained using a network of sensors scattered in the 3D continuum. To this end, the use of the biologically inspired particle swarm optimization(PSO) algorithm is motivated. In this context, a novel modification of PSO algorithm is proposed that leads to faster convergence, and eliminates the ip ambiguity encountered by coplanar sensors. The initial results over several simulation runs highlight the accuracy and speed of the proposed approach

Mobile Robots Navigation

Mobile robots navigation includes different interrelated activities: (i) perception, as obtaining and interpreting sensory information; (ii) exploration, as the strategy that guides the robot to select the next direction to go; (iii) mapping, involving the construction of a spatial representation by using the sensory information perceived; (iv) localization, as the strategy to estimate the robot position within the spatial map; (v) path planning, as the strategy to find a path towards a goal location being optimal or not; and (vi) path execution, where motor actions are determined and adapted to environmental changes. The book addresses those activities by integrating results from the research work of several authors all over the world. Research cases are documented in 32 chapters organized within 7 categories next described

Recent Advances in Indoor Localization Systems and Technologies

Despite the enormous technical progress seen in the past few years, the maturity of indoor localization technologies has not yet reached the level of GNSS solutions. The 23 selected papers in this book present the recent advances and new developments in indoor localization systems and technologies, propose novel or improved methods with increased performance, provide insight into various aspects of quality control, and also introduce some unorthodox positioning methods

Position estimation error performance model for a minimum configuration 3-D multilateration

A multilateration system estimates the position of emitter using time difference of arrival (TDOA) measurements with a lateration algorithm. It involves solving a set of hyperbolic plane equations to determine the position of the emitter given the TDOA measurements that corresponds to the path difference (PD) measurement in distance. A performance model is developed using the relative maximum error bound (RMEB) which relates the plane equation condition number, the relative ground receiving station (GRS) geometry and the PD measurement error to estimate the position estimation (PE) error. By using air traffic monitoring for civil aviation as an application, Monte Carlo simulation verifies the PE error of the performance model for a square GRS configuration. The coverage assumed a 3600 bearing, a range of up to 200 km and a maximum altitude of 15 km. Simulation results also show that the performance model estimates the horizontal position error with a maximum absolute error of 0.1 km up to a range of 200 km at an altitude of 15 km and a minimum absolute error of 0.2 km at an altitude of 15 km

Optimization of anchor nodes placement in wireless localization networks

This work focuses on optimizing node placement for time-of-flight-based wireless localization networks. Main motivation are critical safety applications. The first part of my thesis is an experimental study on in-tunnel vehicle localization. In- tunnel localization of vehicles is crucial for emergency management, especially for large trucks transporting dangerous goods such as inflammable chemicals. Compared to open roads, evacuation in tunnels is much more difficult, so that fire or other accidents can cause much more damage. We provide distance measurement error characterization inside road tunnels focusing on time of flight measurements. We design a complete system for in-tunnel radio frequency time-of- flight-based localization and show that such a system is feasible and accurate, and that few nodes are sufficient to cover the entire tunnel. The second part of my work focuses on anchor nodes placement optimization for time-of-flight-based localization networks where multilateration is used to obtain the target position based on its distances from fixed and known anchors. Our main motivation are safety at work applications, in particular, environments such as factory halls. Our goal is to minimize the number of anchors needed to localize the target while keeping the localization uncertainty lower than a given threshold in an area of arbitrary shape with obstacles. Our propagation model accounts for the presence of line of sight between nodes, while geometric dilution of precision is used to express the localization error introduced by multilateration. We propose several integer linear programming formulations for this problem that can be used to obtain optimal solutions to instances of reasonable sizes and compare them in terms of execution times by simulation experiments. We extend our approach to address fault tolerance, ensuring that the target can still be localized after any one of the nodes fails. Two dimensional localization is sufficient for most indoor applications. However, for those industrial environments where the ceiling is very high and the worker might be climbing or be lifted from the ground, or if very high localization precision is needed, three-dimensional localization may be required. Therefore, we extend our approach to three-dimensional localization. We derive the expression for geometric dilution of precision for 3D multilateration and give its geometric interpretation. To tackle problem instances of large size, we propose two novel heuristics: greedy placement with pruning, and its improved version, greedy placement with iterative pruning. We create a simulator to test and compare all our proposed approaches by generating multiple test instances. For anchor placement for multilateration-based localization, we obtain solutions with below 2% anchors overhead with respect to the optimum on average, with around 5s average execution time for 130 candidate positions. For the fault-tolerant version of the same problem, we obtain solutions of around 1% number of anchors overhead with respect to the optimum on average, with 0.4s execution time for 65 candidate positions, by using greedy heuristic with pruning. For 3D placement, the greedy heuristic with iterative pruning produced results of 0.05% of optimum on average, with average execution time of around 6s for 250 candidate positions, for the problem instances we tested

1-D broadside-radiating leaky-wave antenna based on a numerically synthesized impedance surface

A newly-developed deterministic numerical technique for the automated design of metasurface antennas is applied here for the first time to the design of a 1-D printed Leaky-Wave Antenna (LWA) for broadside radiation. The surface impedance synthesis process does not require any a priori knowledge on the impedance pattern, and starts from a mask constraint on the desired far-field and practical bounds on the unit cell impedance values. The designed reactance surface for broadside radiation exhibits a non conventional patterning; this highlights the merit of using an automated design process for a design well known to be challenging for analytical methods. The antenna is physically implemented with an array of metal strips with varying gap widths and simulation results show very good agreement with the predicted performance

Beam scanning by liquid-crystal biasing in a modified SIW structure

A fixed-frequency beam-scanning 1D antenna based on Liquid Crystals (LCs) is designed for application in 2D scanning with lateral alignment. The 2D array environment imposes full decoupling of adjacent 1D antennas, which often conflicts with the LC requirement of DC biasing: the proposed design accommodates both. The LC medium is placed inside a Substrate Integrated Waveguide (SIW) modified to work as a Groove Gap Waveguide, with radiating slots etched on the upper broad wall, that radiates as a Leaky-Wave Antenna (LWA). This allows effective application of the DC bias voltage needed for tuning the LCs. At the same time, the RF field remains laterally confined, enabling the possibility to lay several antennas in parallel and achieve 2D beam scanning. The design is validated by simulation employing the actual properties of a commercial LC medium