Artificial Intelligence-of-Things (AIoT) in Precision Agriculture


Book Description

The merging of Artificial Intelligence (AI) and Internet-of-Things is known as Artificial Intelligence-of-Things (AIoT). IoT consists of interlinked computing devices and machines which can acquire, transfer, and execute field/industrial operations without human involvement, while AI processes the acquired data and helps extract the required information. The technologies work in synergy: AI enriches IoT through machine learning and deep learning-based data analysis and learning capabilities, whereas IoT enriches AI through data acquisition, connectivity, and data exchange. Precision agriculture is becoming critically important for sustainable food production to meet the growing food demand. In recent decades, AI and IoT techniques have played an increasing role within industrial operations (e.g. autonomous manufacturing, automated supply chain management, predictive maintenance, smart energy grids, smart home appliances, and wearables), however, agricultural field operations are still heavily dependent on human labor. This is because these operations are ill-defined, unstructured, and susceptible to variation in natural conditions (e.g. illumination, landscape, atmosphere) plus the biological nature of crops (fruits, stems, leaves, and/or shoots continuously change their shape and/or color as they grow).







Artificial Intelligence of Things (AIoT)


Book Description

This book is devoted to the new standards, technologies, and communication systems for Artificial Intelligence of Things (AIoT) networks. Smart and intelligent communication networks have gained significant attention due to the combination of AI and IoT networks to improve human and machine interfaces and enhance data processing and services. AIoT networks involve the collection of data from several devices and sensor nodes in the environment. AI can enhance these networks to make them faster, greener, smarter, and safer. Computer vision, language processing, and speech recognition are some examples of AIoT networks. Due to a large number of devices in today’s world, efficient and intelligent data processing is essential for problem-solving and decision-making. AI multiplies the value of these networks and promotes intelligence and learning capabilities, especially in homes, offices, and cities. However, several challenges have been observed in deploying AIoT networks, such as scalability, complexity, accuracy, and robustness. In addition, these networks are integrated with cloud, 5G networks, and blockchain methods for service provision. Many different solutions have been proposed to address issues related to machine and deep learning methods, ontology-based approaches, genetic algorithms, and fuzzy-based systems. This book aims to contribute to the state of the art and present current standards, technologies, and approaches for AIoT networks. This book focuses on existing solutions in AIoT network technologies, applications, services, standards, architectures, and security provisions. This book also introduces some new architectures and models for AIoT networks.




Advanced IoT Technologies and Applications in the Industry 4.0 Digital Economy


Book Description

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.




Artificial Intelligence and Internet of Things for Smart Agriculture


Book Description

Smart agriculture combines modern science and technology with agricultural cultivation, to achieve unmanned, automatic, intelligent management of agricultural production, such as intelligent irrigation, intelligent fertilization, and intelligent spraying. It is the application of artificial intelligence (AI) and Internet of Things (IoTs) in the field of modern agriculture. Agricultural AI (AAI) is the application of various information technologies and their cross-application in the field of agriculture, including intelligent equipment, IoTs, agricultural unmanned aerial vehicle, intelligent perception, deep learning, digital twin network, expert systems, agricultural cognitive computing, etc. With the rapid development of smart agriculture, agricultural applications combined with deep learning are quite common, such as crop disease-pest detection, growth environment monitoring, automatic crop picking, unmanned farm management, etc. Edge computing can provide efficient and reliable new data processing solutions for multi-scenario and complex tasks in agriculture. At present, cloud computing, deep learning and digital twinning have been widely used in agricultural fields, such as plant identification and detection, pest diagnosis and recognition, remote sensing regional classification and monitoring, fruit carrier detection and agricultural product classification, animal identification and posture detection, etc.




Semantic Web Technologies and Applications in Artificial Intelligence of Things


Book Description

The confluence of Artificial Intelligence of Things (AIoT) and Semantic Web technologies is nothing short of revolutionary. The profound impact of this synergy extends far beyond the realms of industry, research, and society; it shapes the very fabric of our future. Semantic Web Technologies and Applications in Artificial Intelligence of Things is a meticulously crafted reference that not only acknowledges this significance but also serves as a guide for those navigating the complexities of Industry 4.0 and AIoT. This curated compendium of cutting-edge technologies acts as a veritable knowledge base for future developments. As academics, scholars, and industry professionals, the ideal audience of this book, will find meticulously curated content that caters to their diverse interests and expertise, covering topics ranging from smart agriculture, manufacturing, industry, health sciences, and government. Seasoned academics, students, and visionary industry leaders, will find this book to be an indispensable guide that paves the way for innovation and progress.




Convergence of Artificial Intelligence and Internet of Things for Industrial Automation


Book Description

This book begins by discussing the fundamentals of Artificial Intelligence, the Internet of Things, and their convergence. It then covers techniques, algorithms, and methods of analysing and processing data over the Artificial Intelligence of Things. The text elaborates on important concepts such as body sensor networks for safety in smart factories, smart energy management, smart robotic assistive systems, and service-oriented smart manufacturing. This book: • Discusses the security and privacy aspect of Artificial Intelligence of Things (AIoT) for smart real-time applications. • Explores challenges and issues of Artificial Intelligence and the Internet of Things in the field of industrial automation. • Includes case studies in Artificial Intelligence of Things (AIoT) convergence for data processing. • Showcases algorithms, techniques, and methods of analysing and processing data over the Artificial Intelligence of Things. • Highlights operation management using human-robot, smart maintenance, and autonomous production. It will serve as an ideal reference text for senior undergraduate, graduate students, and professionals in fields including industrial engineering, production engineering, manufacturing engineering, operations research, and computer engineering.




Explainable AI (XAI) for Sustainable Development


Book Description

This book presents innovative research works to automate, innovate, design, and deploy AI fo real-world applications. It discusses AI applications in major cutting-edge technologies and details about deployment solutions for different applications for sustainable development. The application of Blockchain techniques illustrates the ways of optimisation algorithms in this book. The challenges associated with AI deployment are also discussed in detail, and edge computing with machine learning solutions is explained. This book provides multi-domain applications of AI to the readers to help find innovative methods towards the business, sustainability, and customer outreach paradigms in the AI domain. • Focuses on virtual machine placement and migration techniques for cloud data centres • Presents the role of machine learning and meta-heuristic approaches for optimisation in cloud computing services • Includes application of placement techniques for quality of service, performance, and reliability improvement • Explores data centre resource management, load balancing and orchestration using machine learning techniques • Analyses dynamic and scalable resource scheduling with a focus on resource management The reference work is for postgraduate students, professionals, and academic researchers in computer science and information technology.




Artificial Intelligence to Solve Pervasive Internet of Things Issues


Book Description

Artificial Intelligence to Solve Pervasive Internet of Things Issues discusses standards and technologies and wide-ranging technology areas and their applications and challenges, including discussions on architectures, frameworks, applications, best practices, methods and techniques required for integrating AI to resolve IoT issues. Chapters also provide step-by-step measures, practices and solutions to tackle vital decision-making and practical issues affecting IoT technology, including autonomous devices and computerized systems. Such issues range from adopting, mitigating, maintaining, modernizing and protecting AI and IoT infrastructure components such as scalability, sustainability, latency, system decentralization and maintainability. The book enables readers to explore, discover and implement new solutions for integrating AI to solve IoT issues. Resolving these issues will help readers address many real-world applications in areas such as scientific research, healthcare, defense, aeronautics, engineering, social media, and many others. - Discusses intelligent techniques for the implementation of Artificial Intelligence in Internet of Things - Prepared for researchers and specialists who are interested in the use and integration of IoT and Artificial Intelligence technologies




Advanced Businesses in Industry 6.0


Book Description

In an era dominated by technology, our world is experiencing a radical transformation through the relentless expansion of industrial generations. The advent of the fourth industrial generation unleashed transformative technologies that revolutionized businesses, enabling access to unprecedented data and analytical capabilities. As we transition into the fifth industrial generation, concepts like sustainability, resilience, and value take center stage, laying the foundation for what is now known as Industry 6.0. In this landscape, processes are intelligently managed without human intervention, and artificial intelligence burgeons, promising a future where calculations and analyses occur at unprecedented speeds through quantum computing. Advanced Businesses in Industry 6.0 emerges as a comprehensive guide to decipher the intricacies of Industry 6.0. With a focus on ultra-advanced concepts, we aim to provide a roadmap for scholars and professionals, offering insights into the opportunities and challenges within this ultra-smart environment. Tailored for students and professionals alike, this book delves into essential topics such as super smart businesses, supply chain advancements, smart factories, production, procurement, information logistics, distribution, interactions, marketing, finance, agriculture, and health systems in Industry 6.0.