SDK development for bridging heterogeneous data sources through connect bridge platform

Nesta dissertação apresentou-se um SDK para a criação de conectores a integrar com o CB Server, que pretende: acelerar o desenvolvimento, garantir melhores práticas e simplificar as diversas atividades e tarefas no processo de desenvolvimento. O SDK fornece uma API pública e simples, suportada por um conjunto de ferramentas, que facilitam o processo de desenvolvimento, explorando as facilidades disponibilizadas através da API. Para analisar a exatidão, viabilidade, integridade e acessibilidade da solução apresentam-se dois exemplos e casos de estudo. Através dos casos de estudo foi possível identificar uma lista de problemas, de pontos sensíveis e melhorias na solução proposta. Para avaliar a usabilidade da API, uma metodologia baseada em vários métodos de avaliação de usabilidade foi estabelecida. O múltiplo caso de estudo funciona como o principal método de avaliação, combinando vários métodos de pesquisa. O caso de estudo consiste em três fases de avaliação: um workshop, uma avaliação heurística e uma análise subjetiva. O caso de estudo envolveu três engenheiros de software (incluindo programadores e avaliadores). A metodologia aplicada gerou resultados com base num método de inspeção, testes de utilizador e entrevistas. Identificou-se não só pontos sensíveis e falhas no código-fonte, mas também problemas estruturais, de documentação e em tempo de execução, bem como problemas relacionados com a experiência do utilizador. O contexto do estudo é apresentado de modo a tirar conclusões acerca dos resultados obtidos. O trabalho futuro incluirá o desenvolvimento de novas funcionalidades. Adicionalmente, pretende-se resolver problemas encontrados na metodologia aplicada para avaliar a usabilidade da API, nomeadamente problemas e falhas no código fonte (por exemplo, validações) e problemas estruturais.In this dissertation, we present an SDK for the creation of connectors to integrate with CB Server which accelerates deployment, ensures best practices and simplifies the various activities and tasks in the development process. The SDK provides a public and simple API leveraged by a set of tools around the API developed which facilitate the development process by exploiting the API facilities. To analyse the correctness, feasibility, completeness, and accessibility of our solution, we presented two examples and case studies. From the case studies, we derived a list of issues found in our solution and a set of proposals for improvement. To evaluate the usability of the API, a methodology based on several usability evaluation methods has been established. Multiple case study works as the main evaluation method, combining several research methods. The case study consists of three evaluation phases – a hands-on workshop, a heuristic evaluation and subjective analysis. The case study involved three computer science engineers (including novice and expert developers and evaluators). The applied methodology generated insights based on an inspection method, a user test, and interviews. We identify not only problems and flaws in the source code, but also runtime, structural and documentation problems, as well as problems related to user experience. To help us draw conclusion from the results, we point out the context of the study. Future work will include the development of new functionalities. Additionally, we aim to solve problems found in the applied methodology to evaluate the usability of the API, namely problems and flaws in the source code (e.g. validations) and structural problems

Proceedings of the 4th Workshop of the MPM4CPS COST Action

Proceedings of the 4th Workshop of the MPM4CPS COST Action with the presentations delivered during the workshop and papers with extended versions of some of them

An Information Exchange Framework For BIM, BAS, And IoT Data Using Semantic Web Technologies

With digital technologies like Building Information Modeling (BIM), Internet of Things (IoT), and Building Automation System (BAS), an increasing amount of data is being created. Data silos in Architecture Engineering and Construction (AEC) industry emerged. The isolation between BIM-based building contextual information, IoT devices’ time-series data, and BAS metadata still exist. This research aims to develop a framework to facilitate information exchange between BIM-based building contextual data, IoT devices’ time-series data, and BAS metadata using Semantic Web technology. This research: i) conducts a comprehensive literature review on BIM and IoT integration based on domains of application and integration methods to summarized an optimal current approach; ii) proposes a framework which enables information exchange among semantically described building contextual data, BAS metadata, and time-series data; iii) the proposed framework uses BOT and BRICK schema to describe building contextual data and BAS metadata; iv) creates an MVD for BIM assisted BAS design and information exchange using BACnet and IFC use case; v) validates the framework with the use case and data from Georgia Tech campus buildings.Ph.D

Development of semantic data models to support data interoperability in the rail industry

Railways are large, complex systems that comprise many heterogeneous subsystems and parts. As the railway industry continues to enjoy increasing passenger and freight custom, ways of deriving greater value from the knowledge within these subsystems are increasingly sought. Interfaces to and between systems are rare, making data sharing and analysis difficult. Semantic data modelling provides a method of integrating data from disparate sources by encoding knowledge about a problem domain or world into machine-interpretable logic and using this knowledge to encode and infer data context and meaning. The uptake of this technique in the Semantic Web and Linked Data movements in recent years has provided a mature set of techniques and toolsets for designing and implementing ontologies and linked data applications. This thesis demonstrates ways in which semantic data models and OWL ontologies can be used to foster data exchange across the railway industry. It sets out a novel methodology for the creation of industrial semantic models, and presents a new set of railway domain ontologies to facilitate integration of infrastructure-centric railway data. Finally, the design and implementation of two prototype systems is described, each of which use the techniques and ontologies in solving a known problem

Contelog: A Formal Declarative Framework for Contextual Knowledge Representation and Reasoning

Context-awareness is at the core of providing timely adaptations in safety-critical secure applications of pervasive computing and Artificial Intelligence (AI) domains. In the current AI and application context-aware frameworks, the distinction between knowledge and context are blurred and not formally integrated. As a result, adaptation behaviors based on contextual reasoning cannot be formally derived and reasoned about. Also, in many smart systems such as automated manufacturing, decision making, and healthcare, it is essential for context-awareness units to synchronize with contextual reasoning modules to derive new knowledge in order to adapt, alert, and predict. A rigorous formalism is therefore essential to (1) represent contextual domain knowledge as well as application rules, and (2) efficiently and effectively reason to draw contextual conclusions. This thesis is a contribution in this direction. The thesis introduces first a formal context representation and a context calculus used to build context models for applications. Then, it introduces query processing and optimization techniques to perform context-based reasoning. The formal framework that achieves these two tasks is called Contelog Framework, obtained by a conservative extension of the syntax and semantics of Datalog. It models contextual knowledge and infers new knowledge. In its design, contextual knowledge and contextual reasoning are loosely coupled, and hence contextual knowledge is reusable on its own. The significance is that by fixing the contextual knowledge, rules in the program and/or query may be changed. Contelog provides a theory of context, in a way that is independent of the application logic rules. The context calculus developed in this thesis allows exporting knowledge inferred in one context to be used in another context. Following the idea of Magic sets from Datalog, Magic Contexts together with query rewriting algorithms are introduced to optimize bottom-up query evaluation of Contelog programs. A Book of Examples has been compiled for Contelog, and these examples are implemented to showcase a proof of concept for the generality, expressiveness, and rigor of the proposed Contelog framework. A variety of experiments that compare the performance of Contelog with earlier Datalog implementations reveal a significant improvement and bring out practical merits of current stage of Contelog and its potential for future extensions in context representation and reasoning of emerging applications of context-aware computing

Geomatics for Mobility Management. A comprehensive database model for Mobility Management

In urban and metropolitan context, Traffic Operations Centres (TOCs) use technologies as Geographic Information Systems (GIS) and Intelligent Transport Systems (ITS) to tackling urban mobility issue. Usually in TOCs, various isolated systems are maintained in parallel (stored in different databases), and data comes from different sources: a challenge in transport management is to transfer disparate data into a unified data management system that preserves access to legacy data, allowing multi-thematic analysis. This need of integration between systems is important for a wise policy decisions. This study aims to design a comprehensive and general spatial data model that could allow the integration and visualization of traffic components and measures. The activity is focused on the case study of 5T Agency in Turin, a TOC that manages traffic regulation, public transit fleets and information to users, in the metropolitan area of Turin and Piedmont Region. In particular, the agency has set up during years a wide system of ITS technologies that acquires continuously measures and traffic information, which are used to deploy information services to citizens and public administrations. However, the spatial nature of these data is not fully considered in the daily operational activity, with the result of difficulties in information integration. Indeed the agency lacks of a complete GIS that includes all the management information in an organized spatial and “horizontal” vision. The main research question concerns the integration of different kind of data in a unique GIS spatial data model. Spatial data interoperability is critical and particularly challenging because geographic data definition in legacy database can vary widely: different data format and standards, data inconsistencies, different spatial and temporal granularities, different methods and enforcing rules that relates measures, events and physical infrastructures. The idea is not to replace the existing implemented and efficient system, but to built-up on these systems a GIS that overpass the different software and DBMS platforms and that can demonstrate how a spatial and horizontal vision in tackling urban mobility issues may be useful for policy and strategies decisions. The modelling activity take reference from a transport standards review and results in database general schema, which can be reused by other TOCs in their activities, helping the integration and coordination between different TOCs. The final output of the research is an ArcGIS geodatabase, tailored on 5T data requirements, which enable the customised representation of private traffic elements and measures. Specific custom scripts have been developed to allow the extraction and the temporal aggregation of traffic measures and events. The solution proposed allows the reuse of data and measures for custom purposes, without the need to deeply know the entire ITS environment system. In addition, The proposed ArcGIS geodatabase solution is optimised for limited power-computing environment. A case study has been deepened in order to evaluate the suitability of the database: a confrontation between damages, detected by Emergency Mapping Services (EMS), and Traffic Message Channel traffic events, has been conducted, evaluating the utility of 5T historical information of traffic events of the Piedmont floods of November 2016 for EMS services

Safe Programming Over Distributed Streams

The sheer scale of today\u27s data processing needs has led to a new paradigm of software systems centered around requirements for high-throughput, distributed, low-latency computation.Despite their widespread adoption, existing solutions have yet to provide a programming model with safe semantics -- and they disagree on basic design choices, in particular with their approach to parallelism. As a result, naive programmers are easily led to introduce correctness and performance bugs. This work proposes a reliable programming model for modern distributed stream processing, founded in a type system for partially ordered data streams. On top of the core type system, we propose language abstractions for working with streams -- mechanisms to build stream operators with (1) type-safe compositionality, (2) deterministic distribution, (3) run-time testing, and (4) static performance bounds. Our thesis is that viewing streams as partially ordered conveniently exposes parallelism without compromising safety or determinism. The ideas contained in this work are implemented in a series of open source software projects, including the Flumina, DiffStream, and Data Transducers libraries

BIM in the construction industry

En las últimas décadas, el término modelado de información de construcción (BIM) se ha mencionado en una amplia gama de esfuerzos de investigación de la construcción. BIM es una nueva solución para la recesión sin precedentes en la industria de la construcción, es decir, pérdida de productividad, escasez de mano de obra, sobrecostos y competitividad severa. La tecnología BIM proporciona muchos beneficios: detección rápida de conflictos de diseño, regulación automática de diseño algoritmo de verificación, visualización de realidad virtual/aumentada y entorno de trabajo de colaboración. BIM los expertos, así como los profesionales de la industria, enfatizan la importancia de las aplicaciones BIM en el campo de construcción. Dado el rápido desarrollo y adopción de BIM en la arquitectura, ingeniería, y construcción (AEC), están surgiendo nuevas tendencias relevantes para la investigación de BIM, siendo sumamente útil no sólo para los académicos sino también para los profesionales.In recent decades, the term building information modeling (BIM) has been mentioned in a wide range of construction research endeavors. BIM is a new solution for unprecedented recession in the construction industry, i.e., productivity loss, labor shortage, cost overrun, and severe competitiveness. BIM technology provides many benefits: prompt design clash detection, automatic deign regulatory check algorithm, augmented/virtual reality visualization, and collaboration work environment. BIM experts as well as industry practitioners are stressing the importance of BIM applications in the field of construction. Given the rapid development and adoption of BIM in the architecture, engineering, and construction (AEC) industry, new trends relevant to the research of BIM are emerging, being exceedingly helpful not only for academics but also for practitioners