Internet of things

Manual of Digital Earth / Editors: Huadong Guo, Michael F. Goodchild, Alessandro Annoni .- Springer, 2020 .- ISBN: 978-981-32-9915-3Digital Earth was born with the aim of replicating the real world within the digital world. Many efforts have been made to observe and sense the Earth, both from space (remote sensing) and by using in situ sensors. Focusing on the latter, advances in Digital Earth have established vital bridges to exploit these sensors and their networks by taking location as a key element. The current era of connectivity envisions that everything is connected to everything. The concept of the Internet of Things(IoT)emergedasaholisticproposaltoenableanecosystemofvaried,heterogeneous networked objects and devices to speak to and interact with each other. To make the IoT ecosystem a reality, it is necessary to understand the electronic components, communication protocols, real-time analysis techniques, and the location of the objects and devices. The IoT ecosystem and the Digital Earth (DE) jointly form interrelated infrastructures for addressing today’s pressing issues and complex challenges. In this chapter, we explore the synergies and frictions in establishing an efficient and permanent collaboration between the two infrastructures, in order to adequately address multidisciplinary and increasingly complex real-world problems. Although there are still some pending issues, the identified synergies generate optimism for a true collaboration between the Internet of Things and the Digital Earth

Towards a Reference Architecture with Modular Design for Large-scale Genotyping and Phenotyping Data Analysis: A Case Study with Image Data

With the rapid advancement of computing technologies, various scientific research communities have been extensively using cloud-based software tools or applications. Cloud-based applications allow users to access software applications from web browsers while relieving them from the installation of any software applications in their desktop environment. For example, Galaxy, GenAP, and iPlant Colaborative are popular cloud-based systems for scientific workflow analysis in the domain of plant Genotyping and Phenotyping. These systems are being used for conducting research, devising new techniques, and sharing the computer assisted analysis results among collaborators. Researchers need to integrate their new workflows/pipelines, tools or techniques with the base system over time. Moreover, large scale data need to be processed within the time-line for more effective analysis. Recently, Big Data technologies are emerging for facilitating large scale data processing with commodity hardware. Among the above-mentioned systems, GenAp is utilizing the Big Data technologies for specific cases only. The structure of such a cloud-based system is highly variable and complex in nature. Software architects and developers need to consider totally different properties and challenges during the development and maintenance phases compared to the traditional business/service oriented systems. Recent studies report that software engineers and data engineers confront challenges to develop analytic tools for supporting large scale and heterogeneous data analysis. Unfortunately, less focus has been given by the software researchers to devise a well-defined methodology and frameworks for flexible design of a cloud system for the Genotyping and Phenotyping domain. To that end, more effective design methodologies and frameworks are an urgent need for cloud based Genotyping and Phenotyping analysis system development that also supports large scale data processing. In our thesis, we conduct a few studies in order to devise a stable reference architecture and modularity model for the software developers and data engineers in the domain of Genotyping and Phenotyping. In the first study, we analyze the architectural changes of existing candidate systems to find out the stability issues. Then, we extract architectural patterns of the candidate systems and propose a conceptual reference architectural model. Finally, we present a case study on the modularity of computation-intensive tasks as an extension of the data-centric development. We show that the data-centric modularity model is at the core of the flexible development of a Genotyping and Phenotyping analysis system. Our proposed model and case study with thousands of images provide a useful knowledge-base for software researchers, developers, and data engineers for cloud based Genotyping and Phenotyping analysis system development

Proactive services ecosystem framework

Dissertation presented to obtain the degree of Doctor in Electrical and Computer Engineering, specialization on Collaborative Enterprise NetworksCollaborative-Networks (CN) have experienced a fast evolution in the last two decades. The collaboration among independent entities or professionals supported by Information and Communication Technology (ICT) has attracted the research community to establish the conceptual basis for this scientific discipline. Service Orientation has been one of the key selected paradigms for that conceptual basis. Nevertheless, the service concept itself does not have a common understanding in the Business and ICT worlds. In the former, client satisfaction, resources management and business process models are some example concerns, whilst the later deals with interoperability, remote function calling or communication protocols. If for example an enterprise provides some service, it may hire specialists to wrap such service into web-services, expecting to reach worldwide potential new clients. In fact, nowadays Web Services and Service Oriented Architectures (SOA) are the technological elements most commonly used. However, these are passive elements in the sense they do not perform any action towards pursuing business interests, which constitute a limiting factor from a business perspective. Another approach for the above mentioned enterprise is to follow the Multi-Agent Systems (MAS) approach, as the pro-activity is a keyword in such contexts. Nevertheless, as MAS approaches are not so commonly used and not so robust yet, the worldwide potential set of new clients is reduced; which also constitutes an inhibitor factor from the business perspective. This dissertation proposes a Pro-Active Services Ecosystem Framework, gathering inspiration from both the SOA and MAS research areas, trying to bridge the business and ICT worlds through the base concepts for the creation of a Services’ Ecosystem where business services are represented in a pro-active manner towards pursuing business interests, like finding collaboration opportunities or improving the chances each CN member has to see its services selected among competitors, for example. This work also includes a prototype system applied / validated in the area of a Professional Virtual Community of Senior Professionals

Integrating Internet of Things, Provenance and Blockchain to Enhance Trust in Last Mile Food Deliveries

Engineering and Physical Sciences Research Council - The work presented here was supported by an award made by the UKRI, EPSRC funded Internet of Food Things Network+ grant EP/R045127/1. FUNDING: The work presented here was supported by an award made by the UKRI, EPSRC funded Internet of Food Things Network+ grant EP/R045127/1. ACKNOWLEDGMENTS: We would like to thank G. McWilliam and Aberdeen University Services for their cooperation during the pilot deployments of the PROoFD-IT system. We would also like to thank Food Standards Scotland and the Semantic Web Company GmbH for their valuable comments on the project.Peer reviewedPublisher PD

Architecture for orchestration of M2M services

The past few years, miniaturization has allowed usto imbue computers into everyday devices. This in turn hasenabled these devices to communicate with each other, and in doing so, allows us to collect a wealth of information, moreaccurately and with greater availability than ever before. Thisphenomenon is known as the Internet of Things. It allows smart environments to truly behave in an intelligent manner by using information collected from the devices mentioned above. However, it’s necessary to model how the gathered data will influence the behavior of a smart environment. This open problem can be approached as a machine to machine (M2M) orchestration.In this paper we present a new architecture for M2Morchestration. This new architecture will be based around aplatform that creates orchestration processes through a graphical interface. Through this interface a business process execution language (BPEL) service will be made and deployed on an enterprise service bus (ESB). Alongside this, we are also developing a collection of services that will be used for the purposes of implementing a smart environment

A abordagem POESIA para a integração de dados e serviços na Web semantica

Orientador: Claudia Bauzer MedeirosTese (doutorado) - Universidade Estadual de Campinas, Instituto de ComputaçãoResumo: POESIA (Processes for Open-Ended Systems for lnformation Analysis), a abordagem proposta neste trabalho, visa a construção de processos complexos envolvendo integração e análise de dados de diversas fontes, particularmente em aplicações científicas. A abordagem é centrada em dois tipos de mecanismos da Web semântica: workflows científicos, para especificar e compor serviços Web; e ontologias de domínio, para viabilizar a interoperabilidade e o gerenciamento semânticos dos dados e processos. As principais contribuições desta tese são: (i) um arcabouço teórico para a descrição, localização e composição de dados e serviços na Web, com regras para verificar a consistência semântica de composições desses recursos; (ii) métodos baseados em ontologias de domínio para auxiliar a integração de dados e estimar a proveniência de dados em processos cooperativos na Web; (iii) implementação e validação parcial das propostas, em urna aplicação real no domínio de planejamento agrícola, analisando os benefícios e as limitações de eficiência e escalabilidade da tecnologia atual da Web semântica, face a grandes volumes de dadosAbstract: POESIA (Processes for Open-Ended Systems for Information Analysis), the approach proposed in this work, supports the construction of complex processes that involve the integration and analysis of data from several sources, particularly in scientific applications. This approach is centered in two types of semantic Web mechanisms: scientific workflows, to specify and compose Web services; and domain ontologies, to enable semantic interoperability and management of data and processes. The main contributions of this thesis are: (i) a theoretical framework to describe, discover and compose data and services on the Web, inc1uding mIes to check the semantic consistency of resource compositions; (ii) ontology-based methods to help data integration and estimate data provenance in cooperative processes on the Web; (iii) partial implementation and validation of the proposal, in a real application for the domain of agricultural planning, analyzing the benefits and scalability problems of the current semantic Web technology, when faced with large volumes of dataDoutoradoCiência da ComputaçãoDoutor em Ciência da Computaçã