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.

In today's rapidly evolving higher education landscape, educators face the daunting challenge of providing meaningful and compelling learning experiences to diverse students. The integration of technology, the shift towards student-centered learning, and the imperative to foster inclusive environments all contribute to the complexity of this task. Traditional teaching methods are needed to meet these demands, requiring educators to adapt and innovate in their approaches. Adaptive Learning Technologies for Higher Education offers a comprehensive solution to these challenges. By focusing on specific learning experiences and a variety of methodologies, including online platforms and gamification, the book provides practical techniques to enhance classroom environments. It also emphasizes technology integration, skills-based learning programs, and inclusivity, addressing critical areas of concern for educators seeking to improve student engagement and outcomes.

The agricultural sector can benefit immensely from developments in the field of smart farming. However, this research area focuses on providing specific fixes to particular situations and falls short on implementing data-driven frameworks that provide large-scale benefits to the industry as a whole. Using deep learning can bring immense data and improve our understanding of various earth sciences and improve farm services to yield better crop production and profit. Smart Agricultural Services Using Deep Learning, Big Data, and IoT is an essential publication that focuses on the application of deep learning to agriculture. While highlighting a broad range of topics including crop models, cybersecurity, and sustainable agriculture, this book is ideally designed for engineers, programmers, software developers, agriculturalists, farmers, policymakers, researchers, academicians, and students.

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.

This book is about the Internet of Things in the field of education. Specifically, it focuses on two major topics: IoT (Internet of Things) solutions to support distance education and new pedagogical approaches to support development of computational thinking with educational devices possessing the characteristics of IoT. As the educational landscape has dramatically changed in times of global pandemic, online resources and media, such as IoT, have become increasingly important. This situation compels all educational scholars, researchers and practitioners to search for new solutions, new educational pathways and new agents for knowledge development to support learning. This book presents the possibilities of IoT as both a catalyst and performance tool for education. The convergence of multiple technologies, real-time analytics, machine learning, commodity sensors, and embedded systems can serve as tools for learning support and this book details exactly how these powerful tools can be utilized to best effect.

With near-universal internet access and ever-advancing electronic devices, the ability to facilitate interactions between various hardware and software provides endless possibilities. Though internet of things (IoT) technology is becoming more popular among individual users and companies, more potential applications of this technology are being sought every day. There is a need for studies and reviews that discuss the methodologies, concepts, and possible problems of a technology that requires little or no human interaction between systems. The Handbook of Research on the Internet of Things Applications in Robotics and Automation is a pivotal reference source on the methods and uses of advancing IoT technology. While highlighting topics including traffic information systems, home security, and automatic parking, this book is ideally designed for network analysts, telecommunication system designers, engineers, academicians, technology specialists, practitioners, researchers, students, and software developers seeking current research on the trends and functions of this life-changing technology.

In the rapidly evolving landscape of education, technology continues to play a pivotal role in shaping the way we teach and learn. Among the many innovations transforming educational environments, the Internet of Things (IoT) stands out as a groundbreaking development with the potential to revolutionize traditional practices and open new avenues for personalized, data-driven education. "Integrating IoT in Education: Transforming Learning Through Smart Technologies" aims to provide a comprehensive examination of how IoT can be effectively utilized to enhance educational experiences. This book is born out of the recognition that while the integration of IoT in education offers immense opportunities, it also presents a unique set of challenges and considerations that must be addressed to fully realize its potential. Throughout this book, we explore the fundamental concepts of IoT, including its architecture, components, and communication protocols, and we delve into its practical applications within educational contexts. By analyzing successful case studies and best practices, we offer valuable insights into the implementation of IoT technologies in educational institutions. Our goal is to equip educators, administrators, and policymakers with the knowledge and tools needed to leverage IoT for improved teaching and learning outcomes.

Advances in web technology and the proliferation of sensors and mobile devices connected to the internet have resulted in the generation of immense data sets available on the web that need to be represented, saved, and exchanged. Massive data can be managed effectively and efficiently to support various problem-solving and decision-making techniques. Emerging Technologies and Applications in Data Processing and Management is a critical scholarly publication that examines the importance of data management strategies that coincide with advancements in web technologies. Highlighting topics such as geospatial coverages, data analysis, and keyword query, this book is ideal for professionals, researchers, academicians, data analysts, web developers, and web engineers.

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.

MACHINE LEARNING APPROACHES FOR CONVERGENCE OF IOT AND BLOCKCHAIN The unique aspect of this book is that its focus is the convergence of machine learning, IoT, and blockchain in a single publication. Blockchain technology and the Internet of Things (IoT) are two of the most impactful trends to have emerged in the field of machine learning. Although there are a number of books available solely on the subjects of machine learning, IoT and blockchain technology, no such book has been available which focuses on machine learning techniques for IoT and blockchain convergence until now. Thus, this book is unique in terms of the topics it covers. Designed as an essential guide for all academicians, researchers, and those in industry who are working in related fields, this book will provide insights into the convergence of blockchain technology and the IoT with machine learning. Highlights of the book include: Examines many industries such as agriculture, manufacturing, food production, healthcare, the military, and IT Security of the Internet of Things using blockchain and AI Developing smart cities and transportation systems using machine learning and IoT Audience The target audience of this book is professionals and researchers (artificial intelligence specialists, systems engineers, information technologists) in the fields of machine learning, IoT, and blockchain technology.