Integration of Novel Sensors and Machine Learning for Predictive Maintenance in Medium Voltage Switchgear to Enable the Energy and Mobility Revolutions

The development of renewable energies and smart mobility has profoundly impacted the future of the distribution grid. An increasing bidirectional energy flow stresses the assets of the distribution grid, especially medium voltage switchgear. This calls for improved maintenance strategies to prevent critical failures. Predictive maintenance, a maintenance strategy relying on current condition data of assets, serves as a guideline. Novel sensors covering thermal, mechanical, and partial discharge aspects of switchgear, enable continuous condition monitoring of some of the most critical assets of the distribution grid. Combined with machine learning algorithms, the demands put on the distribution grid by the energy and mobility revolutions can be handled. In this paper, we review the current state-of-the-art of all aspects of condition monitoring for medium voltage switchgear. Furthermore, we present an approach to develop a predictive maintenance system based on novel sensors and machine learning. We show how the existing medium voltage grid infrastructure can adapt these new needs on an economic scale

Extensibility of Enterprise Modelling Languages

Die Arbeit adressiert insgesamt drei Forschungsschwerpunkte. Der erste Schwerpunkt setzt sich mit zu entwickelnden BPMN-Erweiterungen auseinander und stellt deren methodische Implikationen im Rahmen der bestehenden Sprachstandards dar. Dies umfasst zum einen ganz konkrete Spracherweiterungen wie z. B. BPMN4CP, eine BPMN-Erweiterung zur multi-perspektivischen Modellierung von klinischen Behandlungspfaden. Zum anderen betrifft dieser Teil auch modellierungsmethodische Konsequenzen, um parallel sowohl die zugrunde liegende Sprache (d. h. das BPMN-Metamodell) als auch die Methode zur Erweiterungsentwicklung zu verbessern und somit den festgestellten Unzulänglichkeiten zu begegnen. Der zweite Schwerpunkt adressiert die Untersuchung von sprachunabhängigen Fragen der Erweiterbarkeit, welche sich entweder während der Bearbeitung des ersten Teils ergeben haben oder aus dessen Ergebnissen induktiv geschlossen wurden. Der Forschungsschwerpunkt fokussiert dabei insbesondere eine Konsolidierung bestehender Terminologien, die Beschreibung generisch anwendbarer Erweiterungsmechanismen sowie die nutzerorientierte Analyse eines potentiellen Erweiterungsbedarfs. Dieser Teil bereitet somit die Entwicklung einer generischen Erweiterungsmethode grundlegend vor. Hierzu zählt auch die fundamentale Auseinandersetzung mit Unternehmensmodellierungssprachen generell, da nur eine ganzheitliche, widerspruchsfreie und integrierte Sprachdefinition Erweiterungen überhaupt ermöglichen und gelingen lassen kann. Dies betrifft beispielsweise die Spezifikation der intendierten Semantik einer Sprache

Fuzzy-based user modelling for motivation assessment in programming learning adaptive web-based education systems

Learning programming is not an easy task and students often find this subject difficult to understand and pass. One way to improve students’ knowledge in programming is by using Intelligent Tutoring System (ITS) through Adaptive Web-Based Education Systems (AWBESs). The objective of ITS is to provide a personalized tutoring that is tailored to the student’s needs. User modelling is one of the key factors that can meet the ITS intended objectives. From the literature, it was discovered that motivation stands out as one of the critical students’ characteristics that need to be considered when designing a user model. However, from the previous studies, it was discovered that almost all the researchers and educators constructed the user model based on knowledge and skills as students’ characteristics. Thus, the aim of this study is to develop a user model based on students’ motivation known as the Motivation Assessment Model. This is a model that is able to assess students’ motivation level and deliver tutorial materials accordingly. The Motivation Assessment Model was developed based on Self-Efficacy theory that contributes to the fundamental motivation factor which influences students’ motivation during the learning process. Furthermore, to assess the motivation level, fuzzy logic technique was applied. A tutoring system was then developed based on the proposed model using ITS architecture and ADDIE instructional design model. In order to determine students’ knowledge level after using the tutoring system, pre- and post-tests were conducted on the controlled group and experimental group (30 and 31 students). The learning achievements between experimental group (mean = 3.00) and control group (mean = 2.00) indicated that the tutoring system is significantly more effective in improving students’ knowledge level compared to the traditional approach. A usability evaluation was also conducted whereby the effectiveness was evaluated at the number of errors (7.5%) and completion rate (86.5%); efficiency (mean = 4.85); satisfaction evaluated at task level (mean = 6.77) and test level (mean = 83.55). As a conclusion, the overall tutoring system usability results are accepted by students in the experimental group. The research contribution to knowledge is the development of the proposed Motivation Assessment Model for ITS

IT Leadership in Transition - The Impact of Digitalization on Finnish Organizations

Digitalization is transforming business models across industries. As information technology (IT) is becoming embedded in products and services, IT leadership has an increasingly dualistic role in supporting the organization and also serving its customers' changing needs. The ACIO research program studied how Finnish industry and public sector organizations utilize information technology in developing and managing critical business capabilities. The focus was on understanding and analyzing contemporary approaches to IT leadership. This research report summarizes some of the key research findings, providing scholars and practitioners with insights into and understanding of digitalization and changes in IT leadership in Finnish informationintensive organizations

Developing innovation competences in engineering education through project-based and challenge-based learning

There is a gap between industry needs and engineering graduates’ competences that since the past two decades has been under discussion. Engineering graduates are perceived as “too theoretical” by the industry and face difficulties when adapting to the practical working context. This gap is being mostly tackled by project-based courses. Furthermore, the expected competences of the future engineers go beyond the purely technical skills. Competences like creativity, innovativeness, business skills, sense of responsibility, problem-based thinking, collaboration, ability to communicate and effectively dealing with stress and uncertainty, among others, will be increasingly important in the future. Innovation competences in particular are key to tackle current societal challenges, but there is limited understanding about what innovation competences are developed through different types of project-based courses. An education that remains only in the scope of technical skills traditionally expected from engineers will eventually limit the capabilities of the engineers to influence strategy and management decisions, as well as concept definition for new products and services. Institutions like ABET, CDIO and ENAEE – EUR-ACE®, highlight these demands for future engineers’ competences. Ultimately, the more engineers master the innovation process beyond the technical aspects, the more impact they can have in shaping the society of the future, and the greater chances they have to position themselves as decision makers. This study discusses what are the innovation competences needed for engineering students and pedagogical approaches to develop those competences, with the aim of understanding how to better design educational strategies to improve innovation competences in future engineering graduates. A broad literature review was developed on existing innovation competences models and pedagogical approaches to develop innovation competences, going from problem-based to project-based learning to challenge-based education, from New Product Development to Design Thinking, and through different strategies to measure innovation competences. Through a mixed method approach, combining quantitative analysis of surveys and qualitative content analysis of project results, we compared two experiential learning courses developed at the UPC Telecom school: a project-based course and a challenge- based course. We compared self-perception on innovation competences using the INCODE (Innovation Competences Development) Barometer and we developed a qualitative content analysis of project results and self-reflection documents of two groups of engineering students from Telecom Engineering school from UPC going through CBI (Challenge Based Innovation) course versus PDP (Product Development Project) course. CBI is an innovative learning experience carried out by three institutions: Telecom Engineering School of UPC, ESADE Business School and IED Instituto Europeo di Design in collaboration with CERN, where mixed teams of students from the three institutions face open innovation challenges through Design Thinking, with the objective of designing solutions to complex societal problems, considering the use of CERN technologies if suitable. PDP is the “standard” capstone course taken by Telecom engineering students following a classical project management approach based on the CDIO framework. Results shows that experiential learning approaches like project-based and challenge-based education are good educational strategies for developing competences and, explicitly, innovation competences in engineering education, but each strategy emphasizes some competences more than others. Project-based courses demonstrates better results in Planning and Managing Projects. Creativity, Leadership and Entrepreneurship are more developed through a challenge-based approach combined with Design Thinking.Existe una brecha entre las necesidades de la industria y las competencias de los graduados en ingeniería que se ha estado debatiendo desde las últimas dos décadas. Los graduados en ingeniería son percibidos como "demasiado teóricos" por la industria y encuentran dificultades para adaptarse al contexto laboral real. Esta brecha se aborda principalmente mediante cursos basados en proyectos, desarrollando las competencias esperadas de los futuros ingenieros, que van más allá de las habilidades puramente técnicas. Competencias como la creatividad, la innovación, las habilidades empresariales, el sentido de la responsabilidad, el pensamiento basado en problemas, la colaboración, la capacidad para comunicarse y afrontar eficazmente el estrés y la incertidumbre, entre otras, serán cada vez más importantes en el futuro. Las competencias de innovación en particular son clave para abordar los desafíos sociales actuales. Pero hay una comprensión limitada sobre qué competencias de innovación se desarrollan a través de diferentes tipos de cursos basados en proyectos. Instituciones como ABET, CDIO y ENAEE - EUR-ACE®, destacan estas demandas de competencias de los futuros ingenieros. Este estudio analiza cuáles son las competencias de innovación necesarias para los estudiantes de ingeniería y los enfoques pedagógicos para desarrollar estas competencias, con el objetivo de comprender cómo diseñar mejores estrategias educativas para el desarrollo de competencias de innovación en los futuros graduados en ingeniería. Se desarrolló una extensa revisión de la literatura incluyendo modelos de competencias de innovación y enfoques pedagógicos existentes para desarrollar competencias de innovación, pasando del aprendizaje basado en problemas al aprendizaje basado en proyectos y la educación basada en retos. También se estudió el desarrollo de nuevos productos (NPD) y el pensamiento de diseño (Design Thinking), así como diferentes estrategias para medir competencias de innovación. A través de un enfoque de métodos mixto, combinando el análisis cuantitativo de encuestas y el análisis de contenido cualitativo de resultados de proyectos, se compararon dos cursos de aprendizaje experiencial desarrollados en la escuela Telecomunicaciones de la UPC: un curso basado en proyectos PDP (Proyecto de desarrollo de producto) y un curso basado en retos (CBI-Challenge Based Innovation). Se analizó la autopercepción sobre competencias de innovación utilizando el Barómetro INCODE (Innovation Competences Development), y se desarrolló un análisis de contenido cualitativo de los resultados de proyectos y documentos de autorreflexión. CBI es una experiencia de aprendizaje innovadora llevada a cabo por tres instituciones: Escuela de Ingeniería de Telecomunicaciones de la UPC, ESADE Business School e IED Istituto Europeo di Design en colaboración con CERN, donde equipos mixtos de estudiantes de las tres instituciones enfrentan desafíos de innovación abierta a través del Design Thinking, con el objetivo de diseñar soluciones a problemas sociales complejos, considerando el uso de tecnologías CERN (si es apropiado). PDP es el curso final ¿estándar¿ que toman los estudiantes de ingeniería de telecomunicaciones siguiendo un enfoque clásico de gestión de proyectos basado en el marco CDIO. Los resultados muestran que los enfoques de aprendizaje experiencial como la educación basada en proyectos y la educación basada en retos son buenas estrategias educativas para desarrollar competencias y, específicamente, competencias de innovación en la educación en ingeniería. Pero cada estrategia enfatiza algunas competencias más que otras. Los cursos basados en proyectos demuestran mejores resultados en la planificación y gestión de proyectos. La creatividad, el liderazgo y el espíritu empresarial se desarrollan más a través de un enfoque basado en retos combinado con Design Thinking.Postprint (published version

IoT and Sensor Networks in Industry and Society

The exponential progress of Information and Communication Technology (ICT) is one of the main elements that fueled the acceleration of the globalization pace. Internet of Things (IoT), Artificial Intelligence (AI) and big data analytics are some of the key players of the digital transformation that is affecting every aspect of human's daily life, from environmental monitoring to healthcare systems, from production processes to social interactions. In less than 20 years, people's everyday life has been revolutionized, and concepts such as Smart Home, Smart Grid and Smart City have become familiar also to non-technical users. The integration of embedded systems, ubiquitous Internet access, and Machine-to-Machine (M2M) communications have paved the way for paradigms such as IoT and Cyber Physical Systems (CPS) to be also introduced in high-requirement environments such as those related to industrial processes, under the forms of Industrial Internet of Things (IIoT or I2oT) and Cyber-Physical Production Systems (CPPS). As a consequence, in 2011 the German High-Tech Strategy 2020 Action Plan for Germany first envisioned the concept of Industry 4.0, which is rapidly reshaping traditional industrial processes. The term refers to the promise to be the fourth industrial revolution. Indeed, the first industrial revolution was triggered by water and steam power. Electricity and assembly lines enabled mass production in the second industrial revolution. In the third industrial revolution, the introduction of control automation and Programmable Logic Controllers (PLCs) gave a boost to factory production. As opposed to the previous revolutions, Industry 4.0 takes advantage of Internet access, M2M communications, and deep learning not only to improve production efficiency but also to enable the so-called mass customization, i.e. the mass production of personalized products by means of modularized product design and flexible processes. Less than five years later, in January 2016, the Japanese 5th Science and Technology Basic Plan took a further step by introducing the concept of Super Smart Society or Society 5.0. According to this vision, in the upcoming future, scientific and technological innovation will guide our society into the next social revolution after the hunter-gatherer, agrarian, industrial, and information eras, which respectively represented the previous social revolutions. Society 5.0 is a human-centered society that fosters the simultaneous achievement of economic, environmental and social objectives, to ensure a high quality of life to all citizens. This information-enabled revolution aims to tackle today’s major challenges such as an ageing population, social inequalities, depopulation and constraints related to energy and the environment. Accordingly, the citizens will be experiencing impressive transformations into every aspect of their daily lives. This book offers an insight into the key technologies that are going to shape the future of industry and society. It is subdivided into five parts: the I Part presents a horizontal view of the main enabling technologies, whereas the II-V Parts offer a vertical perspective on four different environments. The I Part, dedicated to IoT and Sensor Network architectures, encompasses three Chapters. In Chapter 1, Peruzzi and Pozzebon analyse the literature on the subject of energy harvesting solutions for IoT monitoring systems and architectures based on Low-Power Wireless Area Networks (LPWAN). The Chapter does not limit the discussion to Long Range Wise Area Network (LoRaWAN), SigFox and Narrowband-IoT (NB-IoT) communication protocols, but it also includes other relevant solutions such as DASH7 and Long Term Evolution MAchine Type Communication (LTE-M). In Chapter 2, Hussein et al. discuss the development of an Internet of Things message protocol that supports multi-topic messaging. The Chapter further presents the implementation of a platform, which integrates the proposed communication protocol, based on Real Time Operating System. In Chapter 3, Li et al. investigate the heterogeneous task scheduling problem for data-intensive scenarios, to reduce the global task execution time, and consequently reducing data centers' energy consumption. The proposed approach aims to maximize the efficiency by comparing the cost between remote task execution and data migration. The II Part is dedicated to Industry 4.0, and includes two Chapters. In Chapter 4, Grecuccio et al. propose a solution to integrate IoT devices by leveraging a blockchain-enabled gateway based on Ethereum, so that they do not need to rely on centralized intermediaries and third-party services. As it is better explained in the paper, where the performance is evaluated in a food-chain traceability application, this solution is particularly beneficial in Industry 4.0 domains. Chapter 5, by De Fazio et al., addresses the issue of safety in workplaces by presenting a smart garment that integrates several low-power sensors to monitor environmental and biophysical parameters. This enables the detection of dangerous situations, so as to prevent or at least reduce the consequences of workers accidents. The III Part is made of two Chapters based on the topic of Smart Buildings. In Chapter 6, Petroșanu et al. review the literature about recent developments in the smart building sector, related to the use of supervised and unsupervised machine learning models of sensory data. The Chapter poses particular attention on enhanced sensing, energy efficiency, and optimal building management. In Chapter 7, Oh examines how much the education of prosumers about their energy consumption habits affects power consumption reduction and encourages energy conservation, sustainable living, and behavioral change, in residential environments. In this Chapter, energy consumption monitoring is made possible thanks to the use of smart plugs. Smart Transport is the subject of the IV Part, including three Chapters. In Chapter 8, Roveri et al. propose an approach that leverages the small world theory to control swarms of vehicles connected through Vehicle-to-Vehicle (V2V) communication protocols. Indeed, considering a queue dominated by short-range car-following dynamics, the Chapter demonstrates that safety and security are increased by the introduction of a few selected random long-range communications. In Chapter 9, Nitti et al. present a real time system to observe and analyze public transport passengers' mobility by tracking them throughout their journey on public transport vehicles. The system is based on the detection of the active Wi-Fi interfaces, through the analysis of Wi-Fi probe requests. In Chapter 10, Miler et al. discuss the development of a tool for the analysis and comparison of efficiency indicated by the integrated IT systems in the operational activities undertaken by Road Transport Enterprises (RTEs). The authors of this Chapter further provide a holistic evaluation of efficiency of telematics systems in RTE operational management. The book ends with the two Chapters of the V Part on Smart Environmental Monitoring. In Chapter 11, He et al. propose a Sea Surface Temperature Prediction (SSTP) model based on time-series similarity measure, multiple pattern learning and parameter optimization. In this strategy, the optimal parameters are determined by means of an improved Particle Swarm Optimization method. In Chapter 12, Tsipis et al. present a low-cost, WSN-based IoT system that seamlessly embeds a three-layered cloud/fog computing architecture, suitable for facilitating smart agricultural applications, especially those related to wildfire monitoring. We wish to thank all the authors that contributed to this book for their efforts. We express our gratitude to all reviewers for the volunteering support and precious feedback during the review process. We hope that this book provides valuable information and spurs meaningful discussion among researchers, engineers, businesspeople, and other experts about the role of new technologies into industry and society

ICSEA 2021: the sixteenth international conference on software engineering advances

The Sixteenth International Conference on Software Engineering Advances (ICSEA 2021), held on October 3 - 7, 2021 in Barcelona, Spain, continued a series of events covering a broad spectrum of software-related topics. The conference covered fundamentals on designing, implementing, testing, validating and maintaining various kinds of software. The tracks treated the topics from theory to practice, in terms of methodologies, design, implementation, testing, use cases, tools, and lessons learnt. The conference topics covered classical and advanced methodologies, open source, agile software, as well as software deployment and software economics and education. The conference had the following tracks: Advances in fundamentals for software development Advanced mechanisms for software development Advanced design tools for developing software Software engineering for service computing (SOA and Cloud) Advanced facilities for accessing software Software performance Software security, privacy, safeness Advances in software testing Specialized software advanced applications Web Accessibility Open source software Agile and Lean approaches in software engineering Software deployment and maintenance Software engineering techniques, metrics, and formalisms Software economics, adoption, and education Business technology Improving productivity in research on software engineering Trends and achievements Similar to the previous edition, this event continued to be very competitive in its selection process and very well perceived by the international software engineering community. As such, it is attracting excellent contributions and active participation from all over the world. We were very pleased to receive a large amount of top quality contributions. We take here the opportunity to warmly thank all the members of the ICSEA 2021 technical program committee as well as the numerous reviewers. The creation of such a broad and high quality conference program would not have been possible without their involvement. We also kindly thank all the authors that dedicated much of their time and efforts to contribute to the ICSEA 2021. We truly believe that thanks to all these efforts, the final conference program consists of top quality contributions. This event could also not have been a reality without the support of many individuals, organizations and sponsors. We also gratefully thank the members of the ICSEA 2021 organizing committee for their help in handling the logistics and for their work that is making this professional meeting a success. We hope the ICSEA 2021 was a successful international forum for the exchange of ideas and results between academia and industry and to promote further progress in software engineering research

ERP implementation methodologies and frameworks: a literature review

Enterprise Resource Planning (ERP) implementation is a complex and vibrant process, one that involves a combination of technological and organizational interactions. Often an ERP implementation project is the single largest IT project that an organization has ever launched and requires a mutual fit of system and organization. Also the concept of an ERP implementation supporting business processes across many different departments is not a generic, rigid and uniform concept and depends on variety of factors. As a result, the issues addressing the ERP implementation process have been one of the major concerns in industry. Therefore ERP implementation receives attention from practitioners and scholars and both, business as well as academic literature is abundant and not always very conclusive or coherent. However, research on ERP systems so far has been mainly focused on diffusion, use and impact issues. Less attention has been given to the methods used during the configuration and the implementation of ERP systems, even though they are commonly used in practice, they still remain largely unexplored and undocumented in Information Systems research. So, the academic relevance of this research is the contribution to the existing body of scientific knowledge. An annotated brief literature review is done in order to evaluate the current state of the existing academic literature. The purpose is to present a systematic overview of relevant ERP implementation methodologies and frameworks as a desire for achieving a better taxonomy of ERP implementation methodologies. This paper is useful to researchers who are interested in ERP implementation methodologies and frameworks. Results will serve as an input for a classification of the existing ERP implementation methodologies and frameworks. Also, this paper aims also at the professional ERP community involved in the process of ERP implementation by promoting a better understanding of ERP implementation methodologies and frameworks, its variety and history