Recently, the internet of things (IoT) has brought the vision of a smarter world into reality with a massive amount of data and numerous services. With the outbreak of the COVID-19 pandemic, artificial intelligence (AI) has gained significant attention by utilizing its machine learning algorithms for quality patient care. The integration of IoT with AI may open new possibilities for both technologies and can play a big part in smart healthcare by providing improved insight into healthcare data and allowing for more inexpensive personalized care. The Handbook of Research on Advancements in AI and IoT Convergence Technologies considers recent advancements in AI and IoT convergence technologies with a focus on state-of-the-art approaches, methodologies, and systems for the design, development, deployment, and innovative use of those convergence technologies. It also provides insight into how to develop AI and IoT convergence techniques to meet industrial demands and covers the emerging research topics that are going to define the future of AI and IoT convergence technology development. Covering key topics such as diseases, smart healthcare, social distance monitoring, and security, this major reference work is ideal for industry professionals, nurses, healthcare workers, computer scientists, policymakers, researchers, scholars, practitioners, instructors, and students.

This book gathers recent research work on emerging Artificial Intelligence (AI) methods for processing and storing data generated by cloud-based Internet of Things (IoT) infrastructures. Major topics covered include the analysis and development of AI-powered mechanisms in future IoT applications and architectures. Further, the book addresses new technological developments, current research trends, and industry needs. Presenting case studies, experience and evaluation reports, and best practices in utilizing AI applications in IoT networks, it strikes a good balance between theoretical and practical issues. It also provides technical/scientific information on various aspects of AI technologies, ranging from basic concepts to research grade material, including future directions. The book is intended for researchers, practitioners, engineers and scientists involved in the design and development of protocols and AI applications for IoT-related devices. As the book covers a wide range of mobile applications and scenarios where IoT technologies can be applied, it also offers an essential introduction to the field.

Recently, artificial intelligence (AI), the internet of things (IoT), and cognitive technologies have successfully been applied to various research domains, including computer vision, natural language processing, voice recognition, and more. In addition, AI with IoT has made a significant breakthrough and a shift in technical direction to achieve high efficiency and adaptability in a variety of new applications. On the other hand, network design and optimization for AI applications addresses a complementary topic, namely the support of AI-based systems through novel networking techniques, including new architectures, as well as performance models for IoT systems. IoT has paved the way to a plethora of new application domains, at the same time posing several challenges as a multitude of devices, protocols, communication channels, architectures, and middleware exist. Big data generated by these devices calls for advanced learning and data mining techniques to effectively understand, learn, and reason with this volume of information, such as cognitive technologies. Cognitive technologies play a major role in developing successful cognitive systems which mimic “cognitive” functions associated with human intelligence, such as “learning” and “problem solving.” Thus, there is a continuing demand for recent research in these two linked fields. The Handbook of Research on Innovations and Applications of AI, IoT, and Cognitive Technologies discusses the latest innovations and applications of AI, IoT, and cognitive-based smart systems. The chapters cover the intersection of these three fields in emerging and developed economies in terms of their respective development situation, public policies, technologies and intellectual capital, innovation systems, competition and strategies, marketing and growth capability, and governance and relegation models. These applications span areas such as healthcare, security and privacy, industrial systems, multidisciplinary sciences, and more. This book is ideal for technologists, IT specialists, policymakers, government officials, academics, students, and practitioners interested in the experiences of innovations and applications of AI, IoT, and cognitive technologies.

The recent advancements in the field of the internet of things (IoT), AI, big data, blockchain, augmented reality (AR)/virtual reality (VR), cloud platforms, quantum computing, cybersecurity, and telecommunication technology enabled the promotion of conventional computer-aided industry to the metaverse ecosystem that is powered by AR/VR-driven technologies. In this paradigm shift, the integrated technologies of IoT and AI play a vital role to connect the cyberspace of computing systems and virtual environments. AR/VR supports a huge range of industrial applications such as logistics, the food industry, and manufacturing utilities. AI-Based Technologies and Applications in the Era of the Metaverse discusses essential components of the metaverse ecosystem such as concepts, methodologies, technologies, modeling, designs, statistics, implementation, and maintenance. Covering key topics such as machine learning, deep learning, quantum computing, and blockchain, this premier reference source is ideal for computer scientists, industry professionals, researchers, academicians, scholars, practitioners, instructors, and students.

Today’s business world is changing with the adoption of the internet of things (IoT). IoT is helping in prominently capturing a tremendous amount of data from multiple sources. Realizing the future and full potential of IoT devices will require an investment in new technologies. The Handbook of Research on Deep Learning Techniques for Cloud-Based Industrial IoT demonstrates how the computer scientists and engineers of today might employ artificial intelligence in practical applications with the emerging cloud and IoT technologies. The book also gathers recent research works in emerging artificial intelligence methods and applications for processing and storing the data generated from the cloud-based internet of things. Covering key topics such as data, cybersecurity, blockchain, and artificial intelligence, this premier reference source is ideal for industry professionals, engineers, computer scientists, researchers, scholars, academicians, practitioners, instructors, and students.

The agriculture industry is facing significant challenges in meeting the increasing demand for food while also ensuring sustainable development. Traditional agricultural methods are not equipped to meet the demands of the modern world. To overcome these challenges, Advanced Technologies and AI-Equipped IoT Applications in High-Tech Agriculture provides an in-depth analysis of the opportunities and challenges for AI-powered management tools and IoT-equipped techniques for the high-tech agricultural ecosystem. The Handbook of Research on AI-Equipped IoT Applications in High-Tech Agriculture explores advanced methodologies, models, techniques, technologies, and applications along with the concepts of real-time supporting systems to help agricultural producers adjust plans or schedules for taking care of their farms. Additionally, it discusses the role of IoT technologies and AI applications in agricultural ecosystems and their potential to improve product quality and market competitiveness. The book includes discussions on the application of blockchain, biotechnology, drones, robotics, data analytics, and visualization in high-tech agriculture. It is an essential reference for anyone interested in the future of high-tech agriculture, including agricultural analysts, investment analysts, scholars, researchers, academics, professionals, engineers, and students.

Technology is constantly evolving, and machine learning is positioned to become a pivotal tool with the power to transform industries and revolutionize everyday life. This book underscores the urgency of leveraging the latest machine learning methodologies and theoretical advancements, all while harnessing a wealth of realistic data and affordable computational resources. Machine learning is no longer confined to theoretical domains; it is now a vital component in healthcare, manufacturing, education, finance, law enforcement, and marketing, ushering in an era of data-driven decision-making. Academic scholars seeking to unlock the potential of machine learning in the context of Industry 5.0 and advanced IoT applications will find that the groundbreaking book, Methodologies, Frameworks, and Applications of Machine Learning, introduces an unmissable opportunity to delve into the forefront of modern research and application. This book offers a wealth of knowledge and practical insights across a wide array of topics, ranging from conceptual frameworks and methodological approaches to the application of probability theory, statistical techniques, and machine learning in domains as diverse as e-government, healthcare, cyber-physical systems, and sustainable development, this comprehensive guide equips you with the tools to navigate the complexities of Industry 5.0 and the Internet of Things (IoT).