Mapping the NGSI-LD Context Model on Top of a SPARQL Event Processing Architecture: Implementation Guidelines

NGSI-LD is an open specification released by ETSI which proposes an information model and an API for an easy to use and standard management of context information. The NGSI-LD information model is framed within an ontology and adopts JSON-LD as serialization format for context information. This paper presents an approach to the implementation of the NGSI-LD specification over a SPARQL Event Processing Architecture. This work is being developed within the European-Brasilian H2020 SWAMP project focused on implementing an Internet of Things platform providing services for smart water management in agriculture

From Heterogeneous Sensor Networks to Integrated Software Services: Design and Implementation of a Semantic Architecture for the Internet of Things at ARCES@UNIBO

The Internet of Things (IoTs) is growing fast both in terms of number of devices connected and of complexity of deployments and applications. Several research studies an- alyzing the economical impact of the IoT worldwide identify the interoperability as one of the main boosting factor for its growth, thanks to the possibility to unlock novel commercial opportunities derived from the integration of heterogeneous systems which are currently not interconnected. However, at present, interoperability constitutes a relevant practical issue on any IoT deployments that is composed of sensor platforms mapped on different wireless technologies, network protocols or data formats. The paper addresses such issue, and investigates how to achieve effective data interoperability and data reuse on complex IoT deployments, where multiple users/applications need to consume sensor data produced by heterogeneous sensor networks. We propose a generic three-tier IoT architecture, which decouples the sensor data producers from the sensor data consumers, thanks to the intermediation of a semantic broker which is in charge of translating the sensor data into a shared ontology, and of providing publish-subscribe facilities to the producers/consumers. Then, we describe the real-world implementation of such architecture devised at the Advanced Research Center on Electronic System (ARCES) of the University of Bologna. The actual system collects the data produced by three different sensor networks, integrates them through a SPARQL Event Processing Architecture (SEPA), and supports two front- end applications for the data access, i.e. a web dashboard and an Amazon Alexa voice service

Semantic Web and the Web of Things: concept, platform and applications

The ubiquitous presence of devices with computational resources and connectivity is fostering the diffusion of the Internet of Things (IoT), where smart objects interoperate and react to the available information providing services to the users. The pervasiveness of the IoT across many different areas proves the worldwide interest of researchers from academic and enterprises worlds. This Research has brought to new technologies and protocols addressing different needs of emerging scenarios, making difficult to develop interoperable applications. The Web of Things is born to address this problem through the standard protocols responsible for the success of the Web. But a greater contribution can be provided by standards of the Semantic Web. Semantic Web protocols grant univocal identification of resources and representation of data in a way that information is machine understandable and computable and such that information from different sources can be easily aggregated. Semantic Web technologies are then interoperability enablers for the IoT. This Thesis investigates how to employ Semantic Web protocols in the IoT, to realize the Semantic Web of Things (SWoT) vision of an interoperable network of applications. Part I introduces the IoT, Part II investigates the algorithms to efficiently support the publish/subscribe paradigm in semantic brokers for the SWoT and their implementation in Smart-M3 and SEPA. The preliminary work toward the first benchmark for SWoT applications is presented. Part IV describes the Research activity aimed at applying the developed semantic infrastructures in real life scenarios (electro-mobility, home automation, semantic audio and Internet of Musical Things). Part V presents the conclusions. A lack of effective ways to explore and debug Semantic Web datasets emerged during these activities. Part III describes a second Research aimed at devising of a novel way to visualize semantic datasets, based on graphs and the new concept of Semantic Planes.La presenza massiva di dispositivi dotati di capacità computazionale e connettività sta alimentando la diffusione di un nuovo paradigma nell'ICT, conosciuto come Internet of Things. L'IoT è caratterizzato dai cosiddetti smart object che interagiscono, cooperano e reagiscono alle informazioni a loro disponibili per fornire servizi agli utenti. La diffusione dell'IoT su così tante aree è la testimonianza di un interesse mondiale da parte di ricercatori appartenenti sia al mondo accademico che a quello industriale. La Ricerca ha portato alla nascita di tecnologie e protocolli progettati per rispondere ai diversi bisogni degli scenari emergenti, rendendo difficile sviluppare applicazioni interoperabili. Il Web of Things (WoT) è nato per rispondere a questi problemi tramite l'adozione degli standard che hanno favorito il successo del Web. Ma un contributo maggiore può venire dal Semantic Web of Things (SWoT). Infatti, i protocolli del Semantic Web permettono identificazione univoca delle risorse e una rappresentazione dei dati tale che le informazioni siano computabili e l'informazione di differenti fonti facilmente aggregabile. Le tecnologie del Semantic Web sono quindi degli interoperability enabler per l'IoT. Questa Tesi analizza come adottare le tecnologie del Semantic Web nell'IoT per realizzare la visione del SWoT di una rete di applicazioni interoperabile. Part I introduce l'IoT, Part II analizza gli algoritmi per supportare il publish-subscribe nei broker semantici e la loro implementazione in Smart-M3 e SEPA. Inoltre, viene presentato il lavoro preliminare verso il primo benchmark per applicazioni SWoT. Part IV discute l'applicazione dei risultati a diversi domini applicativi (mobilità elettrica, domotica, semantic audio ed Internet of Musical Things). Part V presenta le conclusioni sul lavoro svolto. La Ricerca su applicazioni semantiche ha evidenziato carenze negli attuali software di visualizzazione. Quindi, Part III presenta un nuovo metodo di rappresentazione delle basi di conoscenza semantiche basato sull’approccio a grafo che introduce il concetto di Semantic Plane

A Semantic Approach for Big Data Exploration in Industry 4.0

The growing trends in automation, Internet of Things, big data and cloud computing technologies have led to the fourth industrial revolution (Industry 4.0), where it is possible to visualize and identify patterns and insights, which results in a better understanding of the data and can improve the manufacturing process. However, many times, the task of data exploration results difficult for manufacturing experts because they might be interested in analyzing also data that does not appear in pre-designed visualizations and therefore they must be assisted by Information Technology experts. In this paper, we present a proposal materialized in a semantic-based visual query system developed for a real Industry 4.0 scenario that allows domain experts to explore and visualize data in a friendly way. The main novelty of the system is the combined use that it makes of captured data that are semantically annotated first, and a 2D customized digital representation of a machine that is also linked with semantic descriptions. Those descriptions are expressed using terms of an ontology, where, among others, the sensors that are used to capture indicators about the performance of a machine that belongs to a Industry 4.0 scenario have been modeled. Moreover, this semantic description allows to: formulate queries at a higher level of abstraction, provide customized graphical visualizations of the results based on the format and nature of the data, and download enriched data enabling further types of analysis.This research was funded by the Spanish Ministry of Economy and Competitiveness under Grant No. FEDER/TIN2016-78011-C4-2-R and the Basque Government under Grant No. IT1330-19. The work of Víctor Julio Ramírez is funded by the Spanish Ministry of Economy and Competitiveness under contract with reference BES-2017-081193

Exploring the adoption of precision agriculture for irrigation in the context of agriculture 4.0: The key role of internet of things

In recent years, the concept of Agriculture 4.0 has emerged as an evolution of precision agriculture (PA) through the diffusion of the Internet of things (IoT). There is a perception that the PA adoption is occurring at a slower pace than expected. Little research has been carried out about Agriculture 4.0, as well as to farmer behavior and operations management. This work explores what drives the adoption of PA in the Agriculture 4.0 context, focusing on farmer behavior and operations management. As a result of a multimethod approach, the factors explaining the PA adoption in the Agriculture 4.0 context and a model of irrigation operations management are proposed. Six simulation scenarios are performed to study the relationships among the factors involved in irrigation planning. Empirical findings contribute to a better understanding of what Agriculture 4.0 is and to expand the possibilities of IoT in the PA domain. This work also contributes to the discussion on Agriculture 4.0, thanks to multidisciplinary research bringing together the different perspectives of PA, IoT and operations management. Moreover, this research highlights the key role of IoT, considering the farmer’s possible choice to adopt several IoT sensing technologies for data collection

Semantic traffic sensor data: The TRAFAIR experience

Modern cities face pressing problems with transportation systems including, but not limited to, traffic congestion, safety, health, and pollution. To tackle them, public administrations have implemented roadside infrastructures such as cameras and sensors to collect data about environmental and traffic conditions. In the case of traffic sensor data not only the real-time data are essential, but also historical values need to be preserved and published. When real-time and historical data of smart cities become available, everyone can join an evidence-based debate on the city''s future evolution. The TRAFAIR (Understanding Traffic Flows to Improve Air Quality) project seeks to understand how traffic affects urban air quality. The project develops a platform to provide real-time and predicted values on air quality in several cities in Europe, encompassing tasks such as the deployment of low-cost air quality sensors, data collection and integration, modeling and prediction, the publication of open data, and the development of applications for end-users and public administrations. This paper explicitly focuses on the modeling and semantic annotation of traffic data. We present the tools and techniques used in the project and validate our strategies for data modeling and its semantic enrichment over two cities: Modena (Italy) and Zaragoza (Spain). An experimental evaluation shows that our approach to publish Linked Data is effective

Semantic Traffic Sensor Data: The TRAFAIR Experience

Modern cities face pressing problems with transportation systems including, but not limited to, traffic congestion, safety, health, and pollution. To tackle them, public administrations have implemented roadside infrastructures such as cameras and sensors to collect data about environmental and traffic conditions. In the case of traffic sensor data not only the real-time data are essential, but also historical values need to be preserved and published. When real-time and historical data of smart cities become available, everyone can join an evidence-based debate on the city’s future evolution. The TRAFAIR (Understanding Traffic Flows to Improve Air Quality) project seeks to understand how traffic affects urban air quality. The project develops a platform to provide real-time and predicted values on air quality in several cities in Europe, encompassing tasks such as the deployment of low-cost air quality sensors, data collection and integration, modeling and prediction, the publication of open data, and the development of applications for end-users and public administrations. This paper explicitly focuses on the modeling and semantic annotation of traffic data. We present the tools and techniques used in the project and validate our strategies for data modeling and its semantic enrichment over two cities: Modena (Italy) and Zaragoza (Spain). An experimental evaluation shows that our approach to publish Linked Data is effective

A Presence- and Performance-Driven Framework to Investigate Interactive Networked Music Learning Scenarios

Cooperative music making in networked environments has been subject of extensive research, scientific and artistic. Networked music performance (NMP) is attracting renewed interest thanks to the growing availability of effective technology and tools for computer-based communications, especially in the area of distance and blended learning applications. We propose a conceptual framework for NMP research and design in the context of classical chamber music practice and learning: presence-related constructs and objective quality metrics are used to problematize and systematize the many factors affecting the experience of studying and practicing music in a networked environment. To this end, a preliminary NMP experiment on the effect of latency on chamber music duos experience and quality of the performance is introduced. The degree of involvement, perceived coherence, and immersion of the NMP environment are here combined with measures on the networked performance, including tempo trends and misalignments from the shared score. Early results on the impact of temporal factors on NMP musical interaction are outlined, and their methodological implications for the design of pedagogical applications are discussed

Applying Hypervisor-Based Fault Tolerance Techniques to Safety-Critical Embedded Systems

This document details the work conducted through the development of this thesis, and it is structured as follows: • Chapter 1, Introduction, has briefly presented the motivation, objectives, and contributions of this thesis. • Chapter 2, Fundamentals, exposes a series of concepts that are necessary to correctly understand the information presented in the rest of the thesis, such as the concepts of virtualization, hypervisors, or software-based fault tolerance. In addition, this chapter includes an exhaustive review and comparison between the different hypervisors used in scientific studies dealing with safety-critical systems, and a brief review of some works that try to improve fault tolerance in the hypervisor itself, an area of research that is outside the scope of this work, but that complements the mechanism presented and could be established as a line of future work. • Chapter 3, Problem Statement and Related Work, explains the main reasons why the concept of Hypervisor-Based Fault Tolerance was born and reviews the main articles and research papers on the subject. This review includes both papers related to safety-critical embedded systems (such as the research carried out in this thesis) and papers related to cloud servers and cluster computing that, although not directly applicable to embedded systems, may raise useful concepts that make our solution more complete or allow us to establish future lines of work. • Chapter 4, Proposed Solution, begins with a brief comparison of the work presented in Chapter 3 to establish the requirements that our solution must meet in order to be as complete and innovative as possible. It then sets out the architecture of the proposed solution and explains in detail the two main elements of the solution: the Voter and the Health Monitoring partition. • Chapter 5, Prototype, explains in detail the prototyping of the proposed solution, including the choice of the hypervisor, the processing board, and the critical functionality to be redundant. With respect to the voter, it includes prototypes for both the software version (the voter is implemented in a virtual machine) and the hardware version (the voter is implemented as IP cores on the FPGA). • Chapter 6, Evaluation, includes the evaluation of the prototype developed in Chapter 5. As a preliminary step and given that there is no evidence in this regard, an exercise is carried out to measure the overhead involved in using the XtratuM hypervisor versus not using it. Subsequently, qualitative tests are carried out to check that Health Monitoring is working as expected and a fault injection campaign is carried out to check the error detection and correction rate of our solution. Finally, a comparison is made between the performance of the hardware and software versions of Voter. • Chapter 7, Conclusions and Future Work, is dedicated to collect the conclusions obtained and the contributions made during the research (in the form of articles in journals, conferences and contributions to projects and proposals in the industry). In addition, it establishes some lines of future work that could complete and extend the research carried out during this doctoral thesis.Programa de Doctorado en Ciencia y Tecnología Informática por la Universidad Carlos III de MadridPresidente: Katzalin Olcoz Herrero.- Secretario: Félix García Carballeira.- Vocal: Santiago Rodríguez de la Fuent