Collaborative geographic visualization

Dissertação apresentada na Faculdade de Ciências e Tecnologia da Universidade Nova de Lisboa para a obtenção do grau de Mestre em Engenharia do Ambiente, perfil Gestão e Sistemas AmbientaisThe present document is a revision of essential references to take into account when developing ubiquitous Geographical Information Systems (GIS) with collaborative visualization purposes. Its chapters focus, respectively, on general principles of GIS, its multimedia components and ubiquitous practices; geo-referenced information visualization and its graphical components of virtual and augmented reality; collaborative environments, its technological requirements, architectural specificities, and models for collective information management; and some final considerations about the future and challenges of collaborative visualization of GIS in ubiquitous environment

Ontology based data warehousing for mining of heterogeneous and multidimensional data sources

Heterogeneous and multidimensional big-data sources are virtually prevalent in all business environments. System and data analysts are unable to fast-track and access big-data sources. A robust and versatile data warehousing system is developed, integrating domain ontologies from multidimensional data sources. For example, petroleum digital ecosystems and digital oil field solutions, derived from big-data petroleum (information) systems, are in increasing demand in multibillion dollar resource businesses worldwide. This work is recognized by Industrial Electronic Society of IEEE and appeared in more than 50 international conference proceedings and journals

Tangible user interfaces : past, present and future directions

In the last two decades, Tangible User Interfaces (TUIs) have emerged as a new interface type that interlinks the digital and physical worlds. Drawing upon users' knowledge and skills of interaction with the real non-digital world, TUIs show a potential to enhance the way in which people interact with and leverage digital information. However, TUI research is still in its infancy and extensive research is required in or- der to fully understand the implications of tangible user interfaces, to develop technologies that further bridge the digital and the physical, and to guide TUI design with empirical knowledge. This paper examines the existing body of work on Tangible User In- terfaces. We start by sketching the history of tangible user interfaces, examining the intellectual origins of this field. We then present TUIs in a broader context, survey application domains, and review frame- works and taxonomies. We also discuss conceptual foundations of TUIs including perspectives from cognitive sciences, phycology, and philoso- phy. Methods and technologies for designing, building, and evaluating TUIs are also addressed. Finally, we discuss the strengths and limita- tions of TUIs and chart directions for future research

Hybrid intelligent decision support system for distributed detection based on ad hoc integrated WSN & RFID

This thesis was submitted for the award of Doctor of Philosophy and was awarded by Brunel University LondonThe real time monitoring of environment context aware activities, based on distributed detection, is becoming a standard in public safety and service delivery in a wide range of domains (child and elderly care and supervision, logistics, circulation, and other). The safety of people, goods and premises depends on the prompt immediate reaction to potential hazards identified in real time, at an early stage to engage appropriate control actions. Effective emergency response can be supported only by available and acquired expertise or elaborate collaborative knowledge in the domain of distributed detection that include indoor sensing, tracking and localizing. This research proposes a hybrid conceptual multi-agent framework for the acquisition of collaborative knowledge in dynamic complex context aware environments for distributed detection. This framework has been applied for the design and development of a hybrid intelligent multi-agent decision system (HIDSS) that supports a decentralized active sensing, tracking and localizing strategy, and the deployment and configuration of smart detection devices associated to active sensor nodes wirelessly connected in a network topology to configure, deploy and control ad hoc wireless sensor networks (WSNs). This system, which is based on the interactive use of data, models and knowledge base, has been implemented to support fire detection and control access fusion functions aimed at elaborating: An integrated data model, grouping the building information data and WSN-RFID database, composed of the network configuration and captured data, A virtual layout configuration of the controlled premises, based on using a building information model, A knowledge-based support for the design of generic detection devices, A multi-criteria decision making model for generic detection devices distribution, ad hoc WSNs configuration, clustering and deployment, and Predictive data models for evacuation planning, and fire and evacuation simulation. An evaluation of the system prototype has been carried out to enrich information and knowledge fusion requirements and show the scope of the concepts used in data and process modelling. It has shown the practicability of hybrid solutions grouping generic homogeneous smart detection devices enhanced by heterogeneous support devices in their deployment, forming ad hoc networks that integrate WSNs and radio frequency identification (RFID) technology. The novelty in this work is the web-based support system architecture proposed in this framework that is based on the use of intelligent agent modelling and multi-agent systems, and the decoupling of the processes supporting the multi-sensor data fusion from those supporting different context applications. Although this decoupling is essential to appropriately distribute the different fusion functions, the integration of several dimensions of policy settings for the modelling of knowledge processes, and intelligent and pro-active decision making activities, requires the organisation of interactive fusion functions deployed upstream to a safety and emergency response.Saudi government, represented by the Ministry of Interior and General Directorate of Civil Defenc

A Learning Health System for Radiation Oncology

The proposed research aims to address the challenges faced by clinical data science researchers in radiation oncology accessing, integrating, and analyzing heterogeneous data from various sources. The research presents a scalable intelligent infrastructure, called the Health Information Gateway and Exchange (HINGE), which captures and structures data from multiple sources into a knowledge base with semantically interlinked entities. This infrastructure enables researchers to mine novel associations and gather relevant knowledge for personalized clinical outcomes. The dissertation discusses the design framework and implementation of HINGE, which abstracts structured data from treatment planning systems, treatment management systems, and electronic health records. It utilizes disease-specific smart templates for capturing clinical information in a discrete manner. HINGE performs data extraction, aggregation, and quality and outcome assessment functions automatically, connecting seamlessly with local IT/medical infrastructure. Furthermore, the research presents a knowledge graph-based approach to map radiotherapy data to an ontology-based data repository using FAIR (Findable, Accessible, Interoperable, Reusable) concepts. This approach ensures that the data is easily discoverable and accessible for clinical decision support systems. The dissertation explores the ETL (Extract, Transform, Load) process, data model frameworks, ontologies, and provides a real-world clinical use case for this data mapping. To improve the efficiency of retrieving information from large clinical datasets, a search engine based on ontology-based keyword searching and synonym-based term matching tool was developed. The hierarchical nature of ontologies is leveraged to retrieve patient records based on parent and children classes. Additionally, patient similarity analysis is conducted using vector embedding models (Word2Vec, Doc2Vec, GloVe, and FastText) to identify similar patients based on text corpus creation methods. Results from the analysis using these models are presented. The implementation of a learning health system for predicting radiation pneumonitis following stereotactic body radiotherapy is also discussed. 3D convolutional neural networks (CNNs) are utilized with radiographic and dosimetric datasets to predict the likelihood of radiation pneumonitis. DenseNet-121 and ResNet-50 models are employed for this study, along with integrated gradient techniques to identify salient regions within the input 3D image dataset. The predictive performance of the 3D CNN models is evaluated based on clinical outcomes. Overall, the proposed Learning Health System provides a comprehensive solution for capturing, integrating, and analyzing heterogeneous data in a knowledge base. It offers researchers the ability to extract valuable insights and associations from diverse sources, ultimately leading to improved clinical outcomes. This work can serve as a model for implementing LHS in other medical specialties, advancing personalized and data-driven medicine

Towards BIM/GIS interoperability: A theoretical framework and practical generation of spaces to support infrastructure Asset Management

The past ten years have seen the widespread adoption of Building Information Modelling (BIM) among both the Architectural, Engineering and Construction (AEC) and the Asset Management/ Facilities Management (AM/FM) communities. This has been driven by the use of digital information to support collaborative working and a vision for more efficient reuse of data. Within this context, spatial information is either held in a Geographic Information Systems (GIS) or as Computer-Aided Design (CAD) models in a Common Data Environment (CDE). However, these being heterogeneous systems, there are inevitable interoperability issues that result in poor integration. For this thesis, the interoperability challenges were investigated within a case study to ask: Can a better understanding of the conceptual and technical challenges to the integration of BIM and GIS provide improved support for the management of asset information in the context of a major infrastructure project? Within their respective fields, the terms BIM and GIS have acquired a range of accepted meanings, that do not align well with each other. A seven-level socio-technical framework is developed to harmonise concepts in spatial information systems. This framework is used to explore the interoperability gaps that must be resolved to enable design and construction information to be joined up with operational asset information. The Crossrail GIS and BIM systems were used to investigate some of the interoperability challenges that arise during the design, construction and operation of an infrastructure asset. One particular challenge concerns a missing link between AM-based information and CAD-based geometry which hinders engineering assets from being located within the geometric model and preventing geospatial analysis. A process is developed to link these CAD-based elements with AM-based assets using defined 3D spaces to locate assets. However, other interoperability challenges must first be overcome; firstly, the extraction, transformation and loading of geometry from CAD to GIS; secondly, the creation of an explicit representation of each 3D space from the implicit enclosing geometry. This thesis develops an implementation of the watershed transform algorithm to use real-world Crossrail geometry to generate voxelated interior spaces that can then be converted into a B-Rep mesh for use in 3D GIS. The issues faced at the technical level in this case study provide insight into the differences that must also be addressed at the conceptual level. With this in mind, this thesis develops a Spatial Information System Framework to classify the nature of differences between BIM, GIS and other spatial information systems

SOLAP+: extending the interaction model

Thesis submitted to Faculdade de Ciências e Tecnologia of the Universidade Nova de Lisboa, in partial fulfillment of the requirements for the degree of Master in Computer ScienceDecision making is a crucial process that can dictate success or failure in today’s businesses and organizations. Decision Support Systems (DSS) are designed in order to help human users with decision making activities. Inside the big family of DSSs there is OnLine Analytical Processing (OLAP) - an approach to answer multidimensional queries quickly and effectively. Even though OLAP is recognized as an efficient technique and widely used in mostly every area, it does not offer spatial analysis, spatial data visualization nor exploration. Geographic Information Systems (GIS) had a huge growth in the last years and acquiring and storing spatial data is easier than ever. In order to explore this potential and include spatial data and spatial analysis features to OLAP, Bédard introduced Spatial OLAP (SOLAP). Although it is a relatively new area, many proposals towards SOLAP’s standardization and consolidation have been made,as well as functional tools for different application areas. There are however many issues and topics in SOLAP that are either not covered or with incompatible/non general proposals. We propose to define a generic model for SOLAP interaction based on previous works, extending it to include new visualization options,components and cases; create and present a component-driven architecture proposal for such a tool, including descriptive metamodels, aggregate navigator to increase perfomance and a communication protocol; finally, develop an example prototype that partially implements the proposed interaction features, taking into consideration guidelines for a user friendly, yet powerful and flexible application

Spatial consensus-building through access to web-based GIS : an online planning tool for Leipzig

Thesis (M.C.P.)--Massachusetts Institute of Technology, Dept. of Urban Studies and Planning, 1997.Includes bibliographical references (p. 143-149).by Matthias Baxmann.M.C.P