Teaching And Learning Advances On Sensors For Iot

This book focuses on all the technologies involved in improving the teaching and learning process of some of the sensor-based IoT topics, such as virtual sensors, simulated data acquisition, virtual and remote labs for IoT sensing, gamification experiences and innovative teaching materials, among others. In particular, the articles inside the book show excellent works about hot topics, such as: - Remote labs for IoT teaching, including the full development cycle. - Practical guides for IoT cybersecurity. - Innovative multimodal learning analytics architecture that builds on software-defined networks and network function virtualization principles. - Problem-based learning experiences using designed complex sensor-based IoT ecosystems with sensors, actuators, microcontrollers, plants, soils and irrigation systems. - Block-based programming extensions to facilitate the creation of mobile apps for smart learning experiences. The articles published in this book present only some of the most important topics about sensor-based IoT learning and teaching. However, the selected papers offer significant studies and promising environments.

This book focuses on all the technologies involved in improving the teaching and learning process of some of the sensor-based IoT topics, such as virtual sensors, simulated data acquisition, virtual and remote labs for IoT sensing, gamification experiences and innovative teaching materials, among others. In particular, the articles inside the book show excellent works about hot topics, such as: - Remote labs for IoT teaching, including the full development cycle. - Practical guides for IoT cybersecurity. - Innovative multimodal learning analytics architecture that builds on software-defined networks and network function virtualization principles. - Problem-based learning experiences using designed complex sensor-based IoT ecosystems with sensors, actuators, microcontrollers, plants, soils and irrigation systems. - Block-based programming extensions to facilitate the creation of mobile apps for smart learning experiences. The articles published in this book present only some of the most important topics about sensor-based IoT learning and teaching. However, the selected papers offer significant studies and promising environments.

Academics 4.0 has become increasingly crucial in recent times due to the impact of Industry 4.0 on various fields. The emergence of disruptive technologies and the cyber-physical world has underscored the need for experts in these areas, which requires proper training of students from an early stage. Education 4.0 is essential in preparing faculties and students adequately for this purpose. This approach shifts the focus from teaching to learning and employs blended learning, MOOC courses, and flipped classrooms to achieve better understanding and application of knowledge. The practical aspect of the subject is discussed in the classroom, while the theoretical aspect is taught outside the class. The book, Architecture and Technological Advancements of Education 4.0, aims to explain the rationale, advantages, and features of Academics 4.0, explore assessment tools and techniques, and describe the national policy for bringing change in education. It also covers blended learning, MOOC courses, virtual labs, and mobile learning, with a focus on their benefits. The book will be useful for universities and educational entities that aim to follow Academics 4.0 in the education system, serve as a reference manual for research articles, and be helpful to faculties and academicians who wish to implement and assess online techniques. Additionally, it will be an excellent learning platform for providers and users of relevant domains, with a broad range of topics covering its impact on the education system, students, and workforce.

This book presents the proceedings of four conferences: The 16th International Conference on Frontiers in Education: Computer Science and Computer Engineering + STEM (FECS'20), The 16th International Conference on Foundations of Computer Science (FCS'20), The 18th International Conference on Software Engineering Research and Practice (SERP'20), and The 19th International Conference on e-Learning, e-Business, Enterprise Information Systems, & e-Government (EEE'20). The conferences took place in Las Vegas, NV, USA, July 27-30, 2020 as part of the larger 2020 World Congress in Computer Science, Computer Engineering, & Applied Computing (CSCE'20), which features 20 major tracks. Authors include academics, researchers, professionals, and students. This book contains an open access chapter entitled, "Advances in Software Engineering, Education, and e-Learning". Presents the proceedings of four conferences as part of the 2020 World Congress in Computer Science, Computer Engineering, & Applied Computing (CSCE'20); Includes the tracks Computer Engineering + STEM, Foundations of Computer Science, Software Engineering Research, and e-Learning, e-Business, Enterprise Information Systems, & e-Government; Features papers from FECS'20, FCS'20, SERP'20, EEE'20, including one open access chapter.

In the dynamic landscape of higher education, institutions face a myriad of challenges that threaten to inhibit their ability to nurture the leaders of tomorrow effectively. Academia is navigating new challenges, including the pressures of globalization, the complexities of digital transformation and the imperative of fostering diversity and inclusion. The need for innovative solutions and strategic approaches to these challenges has never been more pressing. Building Resiliency in Higher Education: Globalization, Digital Skills, and Student Wellness offers a comprehensive exploration of these critical issues, providing educators, administrators, policymakers, and researchers with a roadmap for navigating the complexities of the modern educational landscape. The book equips readers with the knowledge and insights needed to address these challenges head-on by delving into topics such as internationalization, innovation, and sustainability. This valuable resource aids understanding and responsiveness to the trends shaping higher education today through in-depth analysis and an interdisciplinary approach.

The book Advances in Distance Learning in Times of Pandemic is devoted to the issues and challenges faced by universities in the field of distance learning in COVID-19 times. It covers both the theoretical and practical aspects connected to distance education. It elaborates on issues regarding distance learning, its challenges, assessment by students and their expectations, the use of tools to improve distance learning, and the functioning of e-learning in the industry 4.0 and society 5.0 eras. The book also devotes a lot of space to the issues of Web 3.0 in university e-learning, quality assurance, and knowledge management. The aim and scope of this book is to draw a holistic picture of ongoing online teaching-activities before and during the lockdown period and present the meaning and future of e-learning from students’ points of view, taking into consideration their attitudes and expectations as well as industry 4.0 and society 5.0 aspects. The book presents the approach to distance learning and how it has changed, especially during a pandemic that revolutionized education. It highlights • the function of online education and how that has changed before and during the pandemic. • how e-learning is beneficial in promoting digital citizenship. • distance learning characteristic in the era of industry 4.0 and society 5.0. • how the era of industry 4.0 treats distance learning as a desirable form of education. The book covers both scientific and educational aspects and can be useful for university-level undergraduate, postgraduate and research-grade courses and can be referred to by anyone interested in exploring the diverse aspects of distance learning.

Machine learning (ML) and the internet of things (IoT) are the top technologies used by businesses to increase efficiency, productivity, and competitiveness in this fast-paced digital era transformation. ML is the key tool for fast processing and decision making applied to smart city applications and next-generation IoT devices, which require ML to satisfy their working objective. IoT technology has proven efficient in solving many real-world problems, and ML algorithms combined with IoT means the fusion of product and intelligence to achieve better automation, efficiency, productivity, and connectivity. The Handbook of Research on Machine Learning-Enabled IoT for Smart Applications Across Industries highlights the importance of ML for IoT’s success and diverse ML-powered IoT applications. This book addresses the problems and challenges in energy, industry, and healthcare and solutions proposed for ML-enabled IoT and new algorithms in ML. It further addresses their accuracy for existing real-time applications. Covering topics such as agriculture, pattern recognition, and smart applications, this premier reference source is an essential resource for engineers, scientists, educators, students, researchers, and academicians.

The application of internet of things (IoT) technologies and artificial intelligence (AI)-enabled IoT solutions has gradually become accepted by business and production organizations as an effective tool for automating several activities effectively and efficiently and developing and distributing products to the global market. Within this book, the reader will learn how to implement IoT devices, IoT-equipped machines, and AI-equipped IoT applications using models and methodologies along with an array of case studies. Advanced IoT Technologies and Applications in the Industry 4.0 Digital Economy covers the basics of IoT-equipped machines in developing and managing various activities in many industries. It discusses all of the key points of an AI-enabled IoT solution, which includes predictive analytics, robotic process automation, predictive maintenance, automated processes, IoT technologies and IoT-equipped sensors related to machines and processes, production testing systems, and product assessment processes in the production environment. The book presents the concepts and interactive methods using datasets, processing workflow charts, and architectural diagrams along with additional real-time systems for easy and fast understanding of the application of IoT-equipped machines and AI-enabled solutions in organizations and includes many case studies throughout the book to enforce reader comprehension. This book is an ideal read for industry specialists, practitioners, researchers, scientists, and engineers working or involved in the fields of Robotics, IT, Computer Science, Soft Computing, IoT, AL/ML/DL, Data Science, the Semantic Web, Knowledge Engineering, and other related fields.