A Big Data perspective on Cyber-Physical Systems for Industry 4.0: modernizing and scaling complex event processing

Doctoral program in Advanced Engineering Systems for IndustryNowadays, the whole industry makes efforts to find the most productive ways of working and it already understood that using the data that is being produced inside and outside the factories is a way to improve the business performance. A set of modern technologies combined with sensor-based communication create the possibility to act according to our needs, precisely at the moment when the data is being produced and processed. Considering the diversity of processes existing in a factory, all of them producing data, Complex Event Processing (CEP) with the capabilities to process that amount of data is needed in the daily work of a factory, to process different types of events and find patterns between them. Although the integration of the Big Data and Complex Event Processing topics is already present in the literature, open challenges in this area were identified, hence the reason for the contribution presented in this thesis. Thereby, this doctoral thesis proposes a system architecture that integrates the CEP concept with a rulebased approach in the Big Data context: the Intelligent Event Broker (IEB). This architecture proposes the use of adequate Big Data technologies in its several components. At the same time, some of the gaps identified in this area were fulfilled, complementing Event Processing with the possibility to use Machine Learning Models that can be integrated in the rules' verification, and also proposing an innovative monitoring system with an immersive visualization component to monitor the IEB and prevent its uncontrolled growth, since there are always several processes inside a factory that can be integrated in the system. The proposed architecture was validated with a demonstration case using, as an example, the Active Lot Release Bosch's system. This demonstration case revealed that it is feasible to implement the proposed architecture and proved the adequate functioning of the IEB system to process Bosch's business processes data and also to monitor its components and the events flowing through those components.Hoje em dia as indústrias esforçam-se para encontrar formas de serem mais produtivas. A utilização dos dados que são produzidos dentro e fora das fábricas já foi identificada como uma forma de melhorar o desempenho do negócio. Um conjunto de tecnologias atuais combinado com a comunicação baseada em sensores cria a possibilidade de se atuar precisamente no momento em que os dados estão a ser produzidos e processados, assegurando resposta às necessidades do negócio. Considerando a diversidade de processos que existem e produzem dados numa fábrica, as capacidades do Processamento de Eventos Complexos (CEP) revelam-se necessárias no quotidiano de uma fábrica, processando diferentes tipos de eventos e encontrando padrões entre os mesmos. Apesar da integração do conceito CEP na era de Big Data ser um tópico já presente na literatura, existem ainda desafios nesta área que foram identificados e que dão origem às contribuições presentes nesta tese. Assim, esta tese de doutoramento propõe uma arquitetura para um sistema que integre o conceito de CEP na era do Big Data, seguindo uma abordagem baseada em regras: o Intelligent Event Broker (IEB). Esta arquitetura propõe a utilização de tecnologias de Big Data que sejam adequadas aos seus diversos componentes. As lacunas identificadas na literatura foram consideradas, complementando o processamento de eventos com a possibilidade de utilizar modelos de Machine Learning com vista a serem integrados na verificação das regras, propondo também um sistema de monitorização inovador composto por um componente de visualização imersiva que permite monitorizar o IEB e prevenir o seu crescimento descontrolado, o que pode acontecer devido à integração do conjunto significativo de processos existentes numa fábrica. A arquitetura proposta foi validada através de um caso de demonstração que usou os dados do Active Lot Release, um sistema da Bosch. Os resultados revelaram a viabilidade da implementação da arquitetura e comprovaram o adequado funcionamento do sistema no que diz respeito ao processamento dos dados dos processos de negócio da Bosch e à monitorização dos componentes do IEB e eventos que fluem através desses.This work has been supported by FCT – Fundação para a Ciência e Tecnologia within the R&D Units Project Scope: UIDB/00319/2020, the Doctoral scholarship PD/BDE/135101/2017 and by European Structural and Investment Funds in the FEDER component, through the Operational Competitiveness and Internationalization Programme (COMPETE 2020) [Project nº 039479; Funding Reference: POCI-01- 0247-FEDER-039479]

INFORMATION TECHNOLOGY FOR NEXT-GENERATION OF SURGICAL ENVIRONMENTS

Minimally invasive surgeries (MIS) are fundamentally constrained by image quality,access to the operative field, and the visualization environment on which thesurgeon relies for real-time information. Although invasive access benefits the patient,it also leads to more challenging procedures, which require better skills andtraining. Endoscopic surgeries rely heavily on 2D interfaces, introducing additionalchallenges due to the loss of depth perception, the lack of 3-Dimensional imaging,and the reduction of degrees of freedom.By using state-of-the-art technology within a distributed computational architecture,it is possible to incorporate multiple sensors, hybrid display devices, and3D visualization algorithms within a exible surgical environment. Such environmentscan assist the surgeon with valuable information that goes far beyond what iscurrently available. In this thesis, we will discuss how 3D visualization and reconstruction,stereo displays, high-resolution display devices, and tracking techniques arekey elements in the next-generation of surgical environments

Molecular simulations and visualization: introduction and overview

Here we provide an introduction and overview of current progress in the field of molecular simulation and visualization, touching on the following topics: (1) virtual and augmented reality for immersive molecular simulations; (2) advanced visualization and visual analytic techniques; (3) new developments in high performance computing; and (4) applications and model building

Optimization of Display-Wall Aware Applications on Cluster Based Systems

Actualment, els sistemes d'informació i comunicació que treballen amb grans volums de dades requereixen l'ús de plataformes que permetin una representació entenible des del punt de vista de l'usuari. En aquesta tesi s'analitzen les plataformes Cluster Display Wall, usades per a la visualització de dades massives, i es treballa concretament amb la plataforma Liquid Galaxy, desenvolupada per Google. Mitjançant la plataforma Liquid Galaxy, es realitza un estudi de rendiment d'aplicacions de visualització representatives, identificant els aspectes de rendiment més rellevants i els possibles colls d'ampolla. De forma específica, s'estudia amb major profunditat un cas representatiu d'aplicació de visualització, el Google Earth. El comportament del sistema executant Google Earth s'analitza mitjançant diferents tipus de test amb usuaris reals. Per a aquest fi, es defineix una nova mètrica de rendiment, basada en la ratio de visualització, i es valora la usabilitat del sistema mitjançant els atributs tradicionals d'efectivitat, eficiència i satisfacció. Adicionalment, el rendiment del sistema es modela analíticament i es prova la precisió del model comparant-ho amb resultats reals.Nowadays, information and communication systems that work with a high volume of data require infrastructures that allow an understandable representation of it from the user's point of view. This thesis analyzes the Cluster Display Wall platforms, used to visualized massive amounts of data, and specifically studies the Liquid Galaxy platform, developed by Google. Using the Liquid Galaxy platform, a performance study of representative visualization applications was performed, identifying the most relevant aspects of performance and possible bottlenecks. Specifically, we study in greater depth a representative case of visualization application, Google Earth. The system behavior while running Google Earth was analyzed through different kinds of tests with real users. For this, a new performance metric was defined, based on the visualization ratio, and the usability of the system was assessed through the traditional attributes of effectiveness, efficiency and satisfaction. Additionally, the system performance was analytically modeled and the accuracy of the model was tested by comparing it with actual results.Actualmente, los sistemas de información y comunicación que trabajan con grandes volúmenes de datos requieren el uso de plataformas que permitan una representación entendible desde el punto de vista del usuario. En esta tesis se analizan las plataformas Cluster Display Wall, usadas para la visualización de datos masivos, y se trabaja en concreto con la plataforma Liquid Galaxy, desarrollada por Google. Mediante la plataforma Liquid Galaxy, se realiza un estudio de rendimiento de aplicaciones de visualización representativas, identificando los aspectos de rendimiento más relevantes y los posibles cuellos de botella. De forma específica, se estudia en mayor profundidad un caso representativo de aplicación de visualización, el Google Earth. El comportamiento del sistema ejecutando Google Earth se analiza mediante diferentes tipos de test con usuarios reales. Para ello se define una nueva métrica de rendimiento, basada en el ratio de visualización, y se valora la usabilidad del sistema mediante los atributos tradicionales de efectividad, eficiencia y satisfacción. Adicionalmente, el rendimiento del sistema se modela analíticamente y se prueba la precisión del modelo comparándolo con resultados reales

Optimization of VR application in texturing cultural heritage

The research question underlying this short essay refers to the possibility of realizing through a well-established workflow a high level of immersivity in the VR representation of Cultural Heritage to be used as a working tool by architects and renovators as well as heritage scholars. At present active or passive 3D scanning techniques are a known reality where the choice of data acquisition system depends both on the final purpose and characteristics of the object to be surveyed. With the maturity achieved in point cloud acquisition, post processing phases and the development of BIM-based systems, the model has given the possibility to become a repository of information related to the existing, to be used for maintenance or renovation processes. If the model can represent the existing with a certain level of detail, it can be assumed that a differentiated Level of Immersivity can be organized depending on the specific needs it intends to fulfil. In the context of renovation or preservation of Cultural Heritage, the potential offered by VR becomes more interesting when it can provide a realistic portrait not only of the geometry, but also of the materiality and state of preservation of the buildings. This research opens new possibilities to develop tools to aid designers and renovators in degradation analysis, intervention projects, and scheduled maintenance. The research question starts analyzing the possibility of creating photorealistic immersive environments that are easy to access, organized based on surveys of existing heritage buildings using specific datasets

Immersive Insights: A Hybrid Analytics System for Collaborative Exploratory Data Analysis

In the past few years, augmented reality (AR) and virtual reality (VR) technologies have experienced terrific improvements in both accessibility and hardware capabilities, encouraging the application of these devices across various domains. While researchers have demonstrated the possible advantages of AR and VR for certain data science tasks, it is still unclear how these technologies would perform in the context of exploratory data analysis (EDA) at large. In particular, we believe it is important to better understand which level of immersion EDA would concretely benefit from, and to quantify the contribution of AR and VR with respect to standard analysis workflows. In this work, we leverage a Dataspace reconfigurable hybrid reality environment to study how data scientists might perform EDA in a co-located, collaborative context. Specifically, we propose the design and implementation of Immersive Insights, a hybrid analytics system combining high-resolution displays, table projections, and augmented reality (AR) visualizations of the data. We conducted a two-part user study with twelve data scientists, in which we evaluated how different levels of data immersion affect the EDA process and compared the performance of Immersive Insights with a state-of-the-art, non-immersive data analysis system.Comment: VRST 201