Advancing IoT Platforms Interoperability

The IoT European Platforms Initiative (IoT-EPI) projects are addressing the topic of Internet of Things and Platforms for Connected Smart Objects and aim to deliver an IoT extended into a web of platforms for connected devices and objects that supports smart environments, businesses, services and persons with dynamic and adaptive configuration capabilities. The specific areas of focus of the research activities are architectures and semantic interoperability, which reliably cover multiple use cases. The goal is to deliver dynamically-configured infrastructure and integration platforms for connected smart objects covering multiple technologies and multiple intelligent artefacts. The IoT-EPI ecosystem has been created with the objective of increasing the impact of the IoT-related European research and innovation, including seven European promising projects on IoT platforms: AGILE, BIG IoT, INTER-IoT, VICINITY, SymbIoTe, bIoTope, and TagItSmart.This white paper provides an insight regarding interoperability in the IoT platforms and ecosystems created and used by IoT-EPI. The scope of this document covers the interoperability aspects, challenges and approaches that cope with interoperability in the current existing IoT platforms and presents some insights regarding the future of interoperability in this context. It presents possible solutions, and a possible IoT interoperability platform architecture

Advancing IoT Platforms Interoperability

The IoT European Platforms Initiative (IoT-EPI) projects are addressing the topic of Internet of Things and Platforms for Connected Smart Objects and aim to deliver an IoT extended into a web of platforms for connected devices and objects that supports smart environments, businesses, services and persons with dynamic and adaptive configuration capabilities. The specific areas of focus of the research activities are architectures and semantic interoperability, which reliably cover multiple use cases. The goal is to deliver dynamically-configured infrastructure and integration platforms for connected smart objects covering multiple technologies and multiple intelligent artefacts. The IoT-EPI ecosystem has been created with the objective of increasing the impact of the IoT-related European research and innovation, including seven European promising projects on IoT platforms: AGILE, BIG IoT, INTER-IoT, VICINITY, SymbIoTe, bIoTope, and TagItSmart.This white paper provides an insight regarding interoperability in the IoT platforms and ecosystems created and used by IoT-EPI. The scope of this document covers the interoperability aspects, challenges and approaches that cope with interoperability in the current existing IoT platforms and presents some insights regarding the future of interoperability in this context. It presents possible solutions, and a possible IoT interoperability platform architecture

Fostering IoT service replicability in interoperable urban ecosystems

Worldwide cities are involved in a digital transformation phase specially focused on sustainability and improving citizen's quality of life. However, such objectives are hard to achieve if the migration of the urban processes are not performed following a common approach. Under the paradigm of smart city, different Information and Communication Technologies (ICT) have been deployed over urban environments to enable such digital transformation. However, actual implementations differ from one city to another, and even between services within the same city. As a consequence, the deployment of urban services is hindered, since they need to be tailored to each city. In addition, the isolation of urban services obstructs its optimization, since it cannot harness contextual information coming from other services. All in all, it is necessary to implement tools and mechanisms that allow us to ensure that city solutions and their vertical services are interoperable. In order to tackle this issue, different initiatives have proposed architectures that homogenize the interaction with smart cities from different angles. However, so far the compliance with such architectures has not been assessed. Having this in mind, in this work we present a validation framework, developed under the umbrella of the SynchroniCity project, which aims to verify that interfaces and data exposed by cities are aligned with the adopted standards and data models. In this regard, the validation framework presented here is the technical enabler for the creation of an interoperability certi cate for smart cities. To assess the bene ts of the validation framework, we have used it to check the interoperability of 21 smart city deployments worldwide that adhered the SynchroniCity guidelines. Afterwards, during an open call a total number of 37 services have been deployed over such SynchroniCity instances, thus con rming the goodness of uniform and validated smart cities to foster service replicability.This work was supported in part by the European Union’s Horizon 2020 Programme [SynchroniCity (Delivering an IoT enabled Digital Single Market for Europe and Beyond)] under Grant 732240, and in part by the Spanish Government (Ministerio de Economía y Competitividad, Fondo Europeo de Desarrollo Regional, MINECO-FEDER) through the project FIERCE: Future Internet Enabled Resilient smart CitiEs under Grant RTI2018-093475-AI00

Ontology-based Consistent Specification and Scalable Execution of Sensor Data Acquisition Plans in Cross-Domain loT Platforms

Nowadays there is an increased number of vertical Internet of Things (IoT) applications that have been developed within IoT Platforms that often do not interact with each other because of the adoption of different standards and formats. Several efforts are devoted to the construction of software infrastructures that facilitate the interoperability among heterogeneous cross-domain IoT platforms for the realization of horizontal applications. Even if their realization poses different challenges across all layers of the network stack, in this thesis we focus on the interoperability issues that arise at the data management layer. Starting from a flexible multi-granular Spatio-Temporal-Thematic data model according to which events generated by different kinds of sensors can be represented, we propose a Semantic Virtualization approach according to which the sensors belonging to different IoT platforms and the schema of the produced event streams are described in a Domain Ontology, obtained through the extension of the well-known ontologies (SSN and IoT-Lite ontologies) to the needs of a specific domain. Then, these sensors can be exploited for the creation of Data Acquisition Plans (DAPs) by means of which the streams of events can be filtered, merged, and aggregated in a meaningful way. Notions of soundness and consistency are introduced to bind the output streams of the services contained in the DAP with the Domain Ontology for providing a semantic description of its final output. The facilities of the \streamLoader prototype are finally presented for supporting the domain experts in the Semantic Virtualization of the sensors and for the construction of meaningful DAPs. Different graphical facilities have been developed for supporting domain experts in the development of complex DAPs. The system provides also facilities for their syntax-based translations in the Apache Spark Streaming language and execution in real time in a distributed cluster of machines

An interoperability framework for pervasive computing systems

Communication and interaction between smart devices is the foundation for pervasive computing and the Internet of Things. Pervasive platforms, that support developers in building new services and applications, have been extensively researched in the past. Nowadays, a multitude of heterogeneous pervasive platforms exist. In real-world deployments, this leads to the formation of platform-specific silos. Therefore, the need for interoperability between such platforms arises. This thesis presents a framework which addresses all elaborated issues preventing co-operation between different platforms and allows for extension and customisation of different aspects, including platforms and transformation mechanisms. The framework bases on uniform abstractions that support translations of different features. The transformation model provides an automatic as well as a manual transformation mechanism. For evaluation, a prototype is implemented and assessed, providing support for six distinct platforms. Particularly, the framework’s feasibility is demonstrated with three realistic scenario implementations, an effort evaluation, and a cost evaluation

Towards Interoperability of Smart City Data Platforms

We present a comprehensive analysis of the literature on interoperability of smart city data platforms in an attempt to conceptualize interoperability approaches. To this end, we propose a taxonomy of said approaches based on four dimensions with three characteristics each. The taxonomy can be used to classify interoperability approaches. We discuss implications for theory and practice and conclude with a first assessment of individual approaches towards their prospect of success

Prototyping and Evaluation of Sensor Data Integration in Cloud Platforms

The SFI Smart Ocean centre has initiated a long-running project which consists of developing a wireless and autonomous marine observation system for monitoring of underwater environments and structures. The increasing popularity of integrating the Internet of Things (IoT) with Cloud Computing has led to promising infrastructures that could realize Smart Ocean's goals. The project will utilize underwater wireless sensor networks (UWSNs) for collecting data in the marine environments and develop a cloud-based platform for retrieving, processing, and storing all the sensor data. Currently, the project is in its early stages and the collaborating partners are researching approaches and technologies that can potentially be utilized. This thesis contributes to the centre's ongoing research, focusing on the aspect of how sensor data can be integrated into three different cloud platforms: Microsoft Azure, Amazon Web Services, and the Google Cloud Platform. The goals were to develop prototypes that could successfully send data to the chosen cloud platforms and evaluate their applicability in context of the Smart Ocean project. In order to determine the most suitable option, each platform was evaluated based on set of defined criteria, focusing on their sensor data integration capabilities. The thesis has also investigated the cloud platforms' supported protocol bindings, as well as several candidate technologies for metadata standards and compared them in surveys. Our evaluation results shows that all three cloud platforms handle sensor data integration in very similar ways, offering a set of cloud services relevant for creating diverse IoT solutions. However, the Google Cloud Platform ranks at the bottom due to the lack of IoT focus on their platform, with less service options, features, and capabilities compared to the other two. Both Microsoft Azure and Amazon Web Services rank very close to each other, as they provide many of the same sensor data integration capabilities, making them the most applicable options.Masteroppgave i Programutvikling samarbeid med HVLPROG399MAMN-PRO

A Semantic Interoperability Model Based on the IEEE 1451 Family of Standards Applied to the Industry 4.0

The Internet of Things (IoT) has been growing recently. It is a concept for connecting billions of smart devices through the Internet in different scenarios. One area being developed inside the IoT in industrial automation, which covers Machine-to-Machine (M2M) and industrial communications with an automatic process, emerging the Industrial Internet of Things (IIoT) concept. Inside the IIoT is developing the concept of Industry 4.0 (I4.0). That represents the fourth industrial revolution and addresses the use of Internet technologies to improve the production efficiency of intelligent services in smart factories. I4.0 is composed of a combination of objects from the physical world and the digital world that offers dedicated functionality and flexibility inside and outside of an I4.0 network. The I4.0 is composed mainly of Cyber-Physical Systems (CPS). The CPS is the integration of the physical world and its digital world, i.e., the Digital Twin (DT). It is responsible for realising the intelligent cross-link application, which operates in a self-organised and decentralised manner, used by smart factories for value creation. An area where the CPS can be implemented in manufacturing production is developing the Cyber-Physical Production System (CPPS) concept. CPPS is the implementation of Industry 4.0 and CPS in manufacturing and production, crossing all levels of production between the autonomous and cooperative elements and sub-systems. It is responsible for connecting the virtual space with the physical world, allowing the smart factories to be more intelligent, resulting in better and smart production conditions, increasing productivity, production efficiency, and product quality. The big issue is connecting smart devices with different standards and protocols. About 40% of the benefits of the IoT cannot be achieved without interoperability. This thesis is focused on promoting the interoperability of smart devices (sensors and actuators) inside the IIoT under the I4.0 context. The IEEE 1451 is a family of standards developed to manage transducers. This standard reaches the syntactic level of interoperability inside Industry 4.0. However, Industry 4.0 requires a semantic level of communication not to exchange data ambiguously. A new semantic layer is proposed in this thesis allowing the IEEE 1451 standard to be a complete framework for communication inside the Industry 4.0 to provide an interoperable network interface with users and applications to collect and share the data from the industry field.A Internet das Coisas tem vindo a crescer recentemente. É um conceito que permite conectar bilhões de dispositivos inteligentes através da Internet em diferentes cenários. Uma área que está sendo desenvolvida dentro da Internet das Coisas é a automação industrial, que abrange a comunicação máquina com máquina no processo industrial de forma automática. Essa interligação, representa o conceito da Internet das Coisas Industrial. Dentro da Internet das Coisas Industrial está a desenvolver o conceito de Indústria 4.0 (I4.0). Isso representa a quarta revolução industrial que aborda o uso de tecnologias utilizadas na Internet para melhorar a eficiência da produção de serviços em fábricas inteligentes. A Indústria 4.0 é composta por uma combinação de objetos do mundo físico e do mundo da digital que oferece funcionalidade dedicada e flexibilidade dentro e fora de uma rede da Indústria 4.0. O I4.0 é composto principalmente por Sistemas Ciberfísicos. Os Sistemas Ciberfísicos permitem a integração do mundo físico com seu representante no mundo digital, por meio do Gémeo Digital. Sistemas Ciberfísicos são responsáveis por realizar a aplicação inteligente da ligação cruzada, que opera de forma auto-organizada e descentralizada, utilizada por fábricas inteligentes para criação de valor. Uma área em que o Sistema Ciberfísicos pode ser implementado na produção manufatureira, isso representa o desenvolvimento do conceito Sistemas de Produção Ciberfísicos. Esse sistema é a implementação da Indústria 4.0 e Sistema Ciberfísicos na fabricação e produção. A cruzar todos os níveis desde a produção entre os elementos e subsistemas autónomos e cooperativos. Ele é responsável por conectar o espaço virtual com o mundo físico, permitindo que as fábricas inteligentes sejam mais inteligentes, resultando em condições de produção melhores e inteligentes, aumentando a produtividade, a eficiência da produção e a qualidade do produto. A grande questão é como conectar dispositivos inteligentes com diferentes normas e protocolos. Cerca de 40% dos benefícios da Internet das Coisas não podem ser alcançados sem interoperabilidade. Esta tese está focada em promover a interoperabilidade de dispositivos inteligentes (sensores e atuadores) dentro da Internet das Coisas Industrial no contexto da Indústria 4.0. O IEEE 1451 é uma família de normas desenvolvidos para gerenciar transdutores. Esta norma alcança o nível sintático de interoperabilidade dentro de uma indústria 4.0. No entanto, a Indústria 4.0 requer um nível semântico de comunicação para não haver a trocar dados de forma ambígua. Uma nova camada semântica é proposta nesta tese permitindo que a família de normas IEEE 1451 seja um framework completo para comunicação dentro da Indústria 4.0. Permitindo fornecer uma interface de rede interoperável com utilizadores e aplicações para recolher e compartilhar os dados dentro de um ambiente industrial.This thesis was developed at the Measurement and Instrumentation Laboratory (IML) in the University of Beira Interior and supported by the portuguese project INDTECH 4.0 – Novas tecnologias para fabricação, que tem como objetivo geral a conceção e desenvolvimento de tecnologias inovadoras no contexto da Indústria 4.0/Factories of the Future (FoF), under the number POCI-01-0247-FEDER-026653

PIS: IoT & Industry 4.0 Challenges

International audienceIn the era of Industry 4.0, digital manufacturing is evolving into smart manufacturing. This evolution impacts companies in three main areas: organization, people, and technologies. This chapter analyzes the Internet of Things (IoT) and Cyber-Physical Systems (CPS)—key technologies transforming the physical world into a digitalized physical world. IoT and CPS provide factories with sensing capabilities, perform data and context capture and allow them to act/react to optimize the value chain. We survey the recent state-of-the-art development of the Industrial Internet of Things (IIoT)—also known as IoT and CPS in the context of Industry 4.0, from a protocol, architecture, and standard point-of-view. We also explore key challenges and future research directions for extensive industrial adoption of these technologies

Next Generation Internet of Things – Distributed Intelligence at the Edge and Human-Machine Interactions

This book provides an overview of the next generation Internet of Things (IoT), ranging from research, innovation, development priorities, to enabling technologies in a global context. It is intended as a standalone in a series covering the activities of the Internet of Things European Research Cluster (IERC), including research, technological innovation, validation, and deployment.The following chapters build on the ideas put forward by the European Research Cluster, the IoT European Platform Initiative (IoT–EPI), the IoT European Large-Scale Pilots Programme and the IoT European Security and Privacy Projects, presenting global views and state-of-the-art results regarding the next generation of IoT research, innovation, development, and deployment.The IoT and Industrial Internet of Things (IIoT) are evolving towards the next generation of Tactile IoT/IIoT, bringing together hyperconnectivity (5G and beyond), edge computing, Distributed Ledger Technologies (DLTs), virtual/ andaugmented reality (VR/AR), and artificial intelligence (AI) transformation.Following the wider adoption of consumer IoT, the next generation of IoT/IIoT innovation for business is driven by industries, addressing interoperability issues and providing new end-to-end security solutions to face continuous treats.The advances of AI technology in vision, speech recognition, natural language processing and dialog are enabling the development of end-to-end intelligent systems encapsulating multiple technologies, delivering services in real-time using limited resources. These developments are focusing on designing and delivering embedded and hierarchical AI solutions in IoT/IIoT, edge computing, using distributed architectures, DLTs platforms and distributed end-to-end security, which provide real-time decisions using less data and computational resources, while accessing each type of resource in a way that enhances the accuracy and performance of models in the various IoT/IIoT applications.The convergence and combination of IoT, AI and other related technologies to derive insights, decisions and revenue from sensor data provide new business models and sources of monetization. Meanwhile, scalable, IoT-enabled applications have become part of larger business objectives, enabling digital transformation with a focus on new services and applications.Serving the next generation of Tactile IoT/IIoT real-time use cases over 5G and Network Slicing technology is essential for consumer and industrial applications and support reducing operational costs, increasing efficiency and leveraging additional capabilities for real-time autonomous systems.New IoT distributed architectures, combined with system-level architectures for edge/fog computing, are evolving IoT platforms, including AI and DLTs, with embedded intelligence into the hyperconnectivity infrastructure.The next generation of IoT/IIoT technologies are highly transformational, enabling innovation at scale, and autonomous decision-making in various application domains such as healthcare, smart homes, smart buildings, smart cities, energy, agriculture, transportation and autonomous vehicles, the military, logistics and supply chain, retail and wholesale, manufacturing, mining and oil and gas