Indoor Mapping and Reconstruction with Mobile Augmented Reality Sensor Systems

Augmented Reality (AR) ermöglicht es, virtuelle, dreidimensionale Inhalte direkt innerhalb der realen Umgebung darzustellen. Anstatt jedoch beliebige virtuelle Objekte an einem willkürlichen Ort anzuzeigen, kann AR Technologie auch genutzt werden, um Geodaten in situ an jenem Ort darzustellen, auf den sich die Daten beziehen. Damit eröffnet AR die Möglichkeit, die reale Welt durch virtuelle, ortbezogene Informationen anzureichern. Im Rahmen der vorliegenen Arbeit wird diese Spielart von AR als "Fused Reality" definiert und eingehend diskutiert. Der praktische Mehrwert, den dieses Konzept der Fused Reality bietet, lässt sich gut am Beispiel seiner Anwendung im Zusammenhang mit digitalen Gebäudemodellen demonstrieren, wo sich gebäudespezifische Informationen - beispielsweise der Verlauf von Leitungen und Kabeln innerhalb der Wände - lagegerecht am realen Objekt darstellen lassen. Um das skizzierte Konzept einer Indoor Fused Reality Anwendung realisieren zu können, müssen einige grundlegende Bedingungen erfüllt sein. So kann ein bestimmtes Gebäude nur dann mit ortsbezogenen Informationen augmentiert werden, wenn von diesem Gebäude ein digitales Modell verfügbar ist. Zwar werden größere Bauprojekt heutzutage oft unter Zuhilfename von Building Information Modelling (BIM) geplant und durchgeführt, sodass ein digitales Modell direkt zusammen mit dem realen Gebäude ensteht, jedoch sind im Falle älterer Bestandsgebäude digitale Modelle meist nicht verfügbar. Ein digitales Modell eines bestehenden Gebäudes manuell zu erstellen, ist zwar möglich, jedoch mit großem Aufwand verbunden. Ist ein passendes Gebäudemodell vorhanden, muss ein AR Gerät außerdem in der Lage sein, die eigene Position und Orientierung im Gebäude relativ zu diesem Modell bestimmen zu können, um Augmentierungen lagegerecht anzeigen zu können. Im Rahmen dieser Arbeit werden diverse Aspekte der angesprochenen Problematik untersucht und diskutiert. Dabei werden zunächst verschiedene Möglichkeiten diskutiert, Indoor-Gebäudegeometrie mittels Sensorsystemen zu erfassen. Anschließend wird eine Untersuchung präsentiert, inwiefern moderne AR Geräte, die in der Regel ebenfalls über eine Vielzahl an Sensoren verfügen, ebenfalls geeignet sind, als Indoor-Mapping-Systeme eingesetzt zu werden. Die resultierenden Indoor Mapping Datensätze können daraufhin genutzt werden, um automatisiert Gebäudemodelle zu rekonstruieren. Zu diesem Zweck wird ein automatisiertes, voxel-basiertes Indoor-Rekonstruktionsverfahren vorgestellt. Dieses wird außerdem auf der Grundlage vierer zu diesem Zweck erfasster Datensätze mit zugehörigen Referenzdaten quantitativ evaluiert. Desweiteren werden verschiedene Möglichkeiten diskutiert, mobile AR Geräte innerhalb eines Gebäudes und des zugehörigen Gebäudemodells zu lokalisieren. In diesem Kontext wird außerdem auch die Evaluierung einer Marker-basierten Indoor-Lokalisierungsmethode präsentiert. Abschließend wird zudem ein neuer Ansatz, Indoor-Mapping Datensätze an den Achsen des Koordinatensystems auszurichten, vorgestellt

Earth observation-based operational estimation of soil moisture and evapotranspiration for agricultural crops in support of sustainable water management

Global information on the spatio-temporal variation of parameters driving the Earth’s terrestrial water and energy cycles, such as evapotranspiration (ET) rates and surface soil moisture (SSM), is of key significance. The water and energy cycles underpin global food and water security and need to be fully understood as the climate changes. In the last few decades, Earth Observation (EO) technology has played an increasingly important role in determining both ET and SSM. This paper reviews the state of the art in the use specifically of operational EO of both ET and SSM estimates. We discuss the key technical and operational considerations to derive accurate estimates of those parameters from space. The review suggests significant progress has been made in the recent years in retrieving ET and SSM operationally; yet, further work is required to optimize parameter accuracy and to improve the operational capability of services developed using EO data. Emerging applications on which ET/SSM operational products may be included in the context specifically in relation to agriculture are also highlighted; the operational use of those operational products in such applications remains to be seen

Smart Urban Water Networks

This book presents the paper form of the Special Issue (SI) on Smart Urban Water Networks. The number and topics of the papers in the SI confirm the growing interest of operators and researchers for the new paradigm of smart networks, as part of the more general smart city. The SI showed that digital information and communication technology (ICT), with the implementation of smart meters and other digital devices, can significantly improve the modelling and the management of urban water networks, contributing to a radical transformation of the traditional paradigm of water utilities. The paper collection in this SI includes different crucial topics such as the reliability, resilience, and performance of water networks, innovative demand management, and the novel challenge of real-time control and operation, along with their implications for cyber-security. The SI collected fourteen papers that provide a wide perspective of solutions, trends, and challenges in the contest of smart urban water networks. Some solutions have already been implemented in pilot sites (i.e., for water network partitioning, cyber-security, and water demand disaggregation and forecasting), while further investigations are required for other methods, e.g., the data-driven approaches for real time control. In all cases, a new deal between academia, industry, and governments must be embraced to start the new era of smart urban water systems

A Network Science Approach to Understanding and Generating Ship Arrangements in Early-Stage Design.

In recent years, automated approaches for creating ship general arrangements in early-stage design have been developed. These approaches seek to avoid “black box” implementations by keeping the designer involved in the layout generation and selection process, but they do not avoid it entirely. Existing methods first generate layouts, next evaluate each layout’s quality, and subsequently filter out poor designs in an iterative process. In addition, desires to move toward full distributed system layouts in early-stage design have only led to more highly-refined CAD-style implementations requiring extensive modeling and computation time. This dissertation asserts that there is a need to shift away from the current trajectory toward higher-fidelity three-dimensional layout models and re-vector toward a perspective that focuses on understanding and inherently respects the fundamental underlying relationships among elements within those models. The research offered in this thesis uses network science to envision the layout problem from a new perspective. In this view, design relationships are information inputs into layout-related analyses rather than only post-processors for evaluating layouts. This is consistent with existing design processes in which human designers attempt to keep relevant relationships in the back of their mind at all times to inform decisions. Network nodes represent ship compartments and edges correspond to design constraints forming a relationship network. First, network concepts of centrality and hierarchy are used to highlight and rank the embedded drivers of an early-stage arrangement prior to developing spatial layouts by directly analyzing the relationship network in a methodical and holistic manner. The obscured design intent of a notional WWII naval vessel is exposed using the hierarchical approach. Second, a network partitioning method is used to cluster shipboard elements into communities of mutually-compatible elements to minimize the degradation of other items located in the same region of the ship. These communities can form the basis of functional zone definitions. Varying the number of partitions reveals a multi-scale depiction of the relationship network. Third, the communities are assigned to structural zones based on cumulative zone preference values. Finally, two new visualization techniques help designers establish connections between the network of inter-element relationships and spatial ship arrangements.PHDNaval Architecture & Marine EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/96126/1/justinwg_1.pd

Improving the matching of registered unemployed to job offers through machine learning algorithms

Dissertation presented as the partial requirement for obtaining a Master's degree in Information Management, specialization in Knowledge Management and Business IntelligenceDue to the existence of a double-sided asymmetric information problem on the labour market characterized by a mutual lack of trust by employers and unemployed people, not enough job matches are facilitated by public employment services (PES), which seem to be caught in a low-end equilibrium. In order to act as a reliable third party, PES need to build a good and solid reputation among their main clients by offering better and less time consuming pre-selection services. The use of machine-learning, data-driven relevancy algorithms that calculate the viability of a specific candidate for a particular job opening is becoming increasingly popular in this field. Based on the Portuguese PES databases (CVs, vacancies, pre-selection and matching results), complemented by relevant external data published by Statistics Portugal and the European Classification of Skills/Competences, Qualifications and Occupations (ESCO), the current thesis evaluates the potential application of models such as Random Forests, Gradient Boosting, Support Vector Machines, Neural Networks Ensembles and other tree-based ensembles to the job matching activities that are carried out by the Portuguese PES, in order to understand the extent to which the latter can be improved through the adoption of automated processes. The obtained results seem promising and point to the possible use of robust algorithms such as Random Forests within the pre-selection of suitable candidates, due to their advantages at various levels, namely in terms of accuracy, capacity to handle large datasets with thousands of variables, including badly unbalanced ones, as well as extensive missing values and many-valued categorical variables

Decision-Support System for LID Footprint Planning and Urban Runoff Mitigation in the Lower Rio Grande Valley of South Texas

To address regional flooding in the United States, federal and state agencies are adopting strict drainage policies in any large-scale commercial development within the watershed boundary. The conventional approach of implementing a wet detention pond (WP) reduces the land cover and causes operation and maintenance challenges eventually. The present study developed a decision-support system (DSS) in the Lower Rio Grande Valley region of South Texas for optimal selection of Best Management Practices (BMPs) by substituting a portion of the WP footprint with three regionally promising low-impact development practices, namely, porous concrete pavement (PCP), bioretention (BR), and bioswale (BS). Source Load Assessment and Management Model for Windows (WinSLAMM) was used as the foundation for the DSS database and algorithm development. This tool suggested that the implementation of bioswale alone can considerably reduce the footprint and construction cost. Less than 0.95 ha of installation of BR and BS can mitigate 79–91% of runoff from a maximum of 5 ha of commercial development. A combination of BR, BS, and WP was found to reduce runoff significantly (~100%), which suggests that the successful adoption of DSS might support better planning of the urban stormwater management in the Lower Rio Grande Valley (LRGV)

FLASH 1.0: A Software Framework for Rapid Parallel Deployment and Enhancing Host Code Portability in Heterogeneous Computing

In this paper, we present FLASH 1.0, a C++-based software framework for rapid parallel deployment and enhancing host code portability in heterogeneous computing. FLASH takes a novel approach in describing kernels and dynamically dispatching them in a hardware-agnostic manner. FLASH features truly hardware-agnostic frontend interfaces, which not only unify the compile-time control flow but also enforces a portability-optimized code organization that imposes a demarcation between computational (performance-critical) and functional (non-performance-critical) codes as well as the separation of hardware-specific and hardware-agnostic codes in the host application. We use static code analysis to measure the hardware independence ratio of popular HPC applications and show that up to 99.72% code portability can be achieved with FLASH. Similarly, we measure the complexity of state-of-the-art portable programming models and show that a code reduction of up to 2.2x can be achieved for two common HPC kernels while maintaining 100% code portability with a normalized framework overhead between 1% - 13% of the total kernel runtime. The codes are available at https://github.com/PSCLab-ASU/FLASH.Comment: 12 page

Doctor of Philosophy

dissertationNetwork emulation has become an indispensable tool for the conduct of research in networking and distributed systems. It offers more realism than simulation and more control and repeatability than experimentation on a live network. However, emulation testbeds face a number of challenges, most prominently realism and scale. Because emulation allows the creation of arbitrary networks exhibiting a wide range of conditions, there is no guarantee that emulated topologies reflect real networks; the burden of selecting parameters to create a realistic environment is on the experimenter. While there are a number of techniques for measuring the end-to-end properties of real networks, directly importing such properties into an emulation has been a challenge. Similarly, while there exist numerous models for creating realistic network topologies, the lack of addresses on these generated topologies has been a barrier to using them in emulators. Once an experimenter obtains a suitable topology, that topology must be mapped onto the physical resources of the testbed so that it can be instantiated. A number of restrictions make this an interesting problem: testbeds typically have heterogeneous hardware, scarce resources which must be conserved, and bottlenecks that must not be overused. User requests for particular types of nodes or links must also be met. In light of these constraints, the network testbed mapping problem is NP-hard. Though the complexity of the problem increases rapidly with the size of the experimenter's topology and the size of the physical network, the runtime of the mapper must not; long mapping times can hinder the usability of the testbed. This dissertation makes three contributions towards improving realism and scale in emulation testbeds. First, it meets the need for realistic network conditions by creating Flexlab, a hybrid environment that couples an emulation testbed with a live-network testbed, inheriting strengths from each. Second, it attends to the need for realistic topologies by presenting a set of algorithms for automatically annotating generated topologies with realistic IP addresses. Third, it presents a mapper, assign, that is capable of assigning experimenters' requested topologies to testbeds' physical resources in a manner that scales well enough to handle large environments