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The rapid advancement of the Internet of Technology (IoT) and smart technologies poses significant challenges for academic scholars. With the emergence of pervasive sensing, machine learning, cloud computing, and energy efficiency, pioneers in this field face the complexity of meeting new requirements such as reliability, quality of service, and energy efficiency. Navigating these challenges and keeping up with the latest advancements can be overwhelming, hindering scholarly contributions in this dynamic area of study. To address these challenges, AIoT and Smart Sensing Technologies for Smart Devices, edited by Fadi Alturjman, offers an invaluable solution for academic scholars. This comprehensive book serves as a knowledge hub, bringing together a diverse range of research and professional contributions. By providing a platform for knowledge exchange and collaboration, it enables scholars to delve into topics such as IoT-oriented applications, sustainable development, machine learning, wireless networks, and more. It is ideal for experts, researchers, and students, as this book equips readers with the necessary insights and understanding to navigate the complexities of IoT and smart technologies. Covering diverse areas like IoT paradigms in sustainable education systems, network security, machine learning approaches, and wireless network protocols, it serves as a guide to unlocking the potential of these new technologies and their many applications. With this resource at their disposal, scholars can stay informed, explore innovative approaches, and make meaningful contributions to the advancement of IoT and smart technologies. AIoT and Smart Sensing Technologies for Smart Devices is a compelling solution for academic scholars grappling with the challenges of AIoT and smart technologies. By consolidating a wealth of research and professional contributions, this book provides a platform for collaboration and knowledge exchange. With its comprehensive coverage of key topics, it empowers experts, researchers, and students to navigate the complexities of AIoT, foster innovation, and contribute to the development of this transformative field.

The ever-evolving industrial landscape poses challenges for businesses, particularly in the field of robotics. Performance optimization, data security, and harnessing emerging technologies are crucial for staying competitive. Traditional approaches fall short in addressing these complexities, leaving industries searching for innovative solutions. AI and Blockchain Applications in Industrial Robotics is an exceptional book which presents the transformative potential of combining artificial intelligence (AI) and blockchain technologies to revolutionize industrial robotics. The book provides comprehensive insights into how AI enhances predictive models and pattern recognition while blockchain ensures secure and immutable data transactions. By synergizing these technologies, businesses can achieve enhanced transparency, trust, and efficiency in their robotic processes. It offers practical applications, use cases, and real-world examples that cater to postgraduate students, researchers, industry professionals, undergraduate students, and freelance developers, empowering them to embrace the possibilities of AI and blockchain in industrial robotics. With AI and Blockchain Applications in Industrial Robotics, many industries can overcome the challenges they face in optimizing performance, ensuring data security, and embracing the potential of emerging technologies. This book serves as a beacon of knowledge, equipping readers with the tools and understanding to implement AI and blockchain solutions, driving innovation, efficiency, and competitiveness in the industrial sector.

'Deep Learning Techniques for Cloud-Based Industrial IoT aims to demonstrate how 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'--

There is no doubt that there has been much excitement regarding the pioneering contributions of artificial intelligence (AI), the internet of things (IoT), and blockchain technologies and tools in visualizing and realizing smarter as well as sophisticated systems and services. However, researchers are being bombarded with various machine and deep learning algorithms, which are categorized as a part and parcel of the enigmatic AI discipline. The knowledge discovered gets disseminated to actuators and other concerned systems in order to empower them to intelligently plan and insightfully execute appropriate tasks with clarity and confidence. The IoT processes in conjunction with the AI algorithms and blockchain technology are bound to lay out a stimulating foundation for producing and sustaining smarter systems for society. Advancing Smarter and More Secure Industrial Applications Using AI, IoT, and Blockchain Technology articulates and accentuates various AI algorithms, fresh innovations in the IoT, and blockchain spaces. The domain of transforming raw data to information and to relevant knowledge is gaining prominence with the availability of data ingestion, processing, mining, analytics algorithms, platforms, frameworks, and other accelerators. Covering topics such as blockchain applications, Industry 4.0, and cryptography, this book serves as a comprehensive guide for AI researchers, faculty members, IT professionals, academicians, students, researchers, and industry professionals.

In recent years, mobile technology and the internet of objects have been used in mobile networks to meet new technical demands. Emerging needs have centered on data storage, computation, and low latency management in potentially smart cities, transport, smart grids, and a wide number of sustainable environments. Federated learning's contributions include an effective framework to improve network security in heterogeneous industrial internet of things (IIoT) environments. Demystifying Federated Learning for Blockchain and Industrial Internet of Things rediscovers, redefines, and reestablishes the most recent applications of federated learning using blockchain and IIoT to optimize data for next-generation networks. It provides insights to readers in a way of inculcating the theme that shapes the next generation of secure communication. Covering topics such as smart agriculture, object identification, and educational big data, this premier reference source is an essential resource for computer scientists, programmers, government officials, business leaders and managers, students and faculty of higher education, researchers, and academicians.

Internet of things (IoT) is an emerging research field that is rapidly becoming an important part of our everyday lives including home automation, smart buildings, smart things, and more. This is due to cheap, efficient, and wirelessly-enabled circuit boards that are enabling the functions of remote sensing/actuating, decentralization, autonomy, and other essential functions. Moreover, with the advancements in embedded artificial intelligence, these devices are becoming more self-aware and autonomous, hence making decisions themselves. Current research is devoted to the understanding of how decision support systems are integrated into industrial IoT. Decision Support Systems and Industrial IoT in Smart Grid, Factories, and Cities presents the internet of things and its place during the technological revolution, which is taking place now to bring us a better, sustainable, automated, and safer world. This book also covers the challenges being faced such as relations and implications of IoT with existing communication and networking technologies; applications like practical use-case scenarios from the real world including smart cities, buildings, and grids; and topics such as cyber security, user privacy, data ownership, and information handling related to IoT networks. Additionally, this book focuses on the future applications, trends, and potential benefits of this new discipline. This book is essential for electrical engineers, computer engineers, researchers in IoT, security, and smart cities, along with practitioners, researchers, academicians, and students interested in all aspects of industrial IoT and its applications.

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.

Deep learning, as a recent AI technique, has proven itself efficient in solving many real-world problems. Deep learning algorithms are efficient, high performing, and an effective standard for solving these problems. In addition, with IoT, deep learning is in many emerging and developing domains of computer technology. Deep learning algorithms have brought a revolution in computer vision applications by introducing an efficient solution to several image processing-related problems that have long remained unresolved or moderately solved. Various significant IoT technologies in various industries, such as education, health, transportation, and security, combine IoT with deep learning for complex problem solving and the supported interaction between human beings and their surroundings. Examining the Impact of Deep Learning and IoT on Multi-Industry Applications provides insights on how deep learning, together with IoT, impacts various sectors such as healthcare, agriculture, cyber security, and social media analysis applications. The chapters present solutions to various real-world problems using these methods from various researchers'points of view. While highlighting topics such as medical diagnosis, power consumption, livestock management, security, and social media analysis, this book is ideal for IT specialists, technologists, security analysts, medical practitioners, imaging specialists, diagnosticians, academicians, researchers, industrial experts, scientists, and undergraduate and postgraduate students who are working in the field of computer engineering, electronics, and electrical engineering.