This book discusses the effect that artificial intelligence (AI) and Internet of Things (IoT) have on industry. The authors start by showing how the application of these technologies has already stretched across domains such as law, political science, policy, and economics and how it will soon permeate areas of autonomous transportation, education, and space exploration, only to name a few. The authors then discuss applications in a variety of industries. Throughout the volume, the authors provide detailed, well-illustrated treatments of each topic with abundant examples and exercises. This book provides relevant theoretical frameworks and the latest empirical research findings in various applications. The book is written for professionals who want to improve their understanding of the strategic role of trust at different levels of the information and knowledge society, that is, trust at the level of the global economy, of networks and organizations, of teams and work groups, of information systems and, finally, trust at the level of individuals as actors in the networked environments. Presents research in various industries and how artificial intelligence and Internet of Things is changing the landscape of business and management; Includes new and innovative features in artificial intelligence and IoT that can help in raising economic efficiency at both micro and macro levels; Examines case studies with tried and tested approaches to resolution of typical problems in each application of study.
Healthcare and technology are at a convergence point where significant changes are poised to take place. The vast and complex requirements of medical record keeping, coupled with stringent patient privacy laws, create an incredibly unwieldy maze of health data needs. While the past decade has seen giant leaps in AI, machine learning, wearable technologies, and data mining capacities that have enabled quantities of data to be accumulated, processed, and shared around the globe. Transforming Healthcare with Big Data and AI examines the crossroads of these two fields and looks to the future of leveraging advanced technologies and developing data ecosystems to the healthcare field. This book is the product of the Transforming Healthcare with Data conference, held at the University of Southern California. Many speakers and digital healthcare industry leaders contributed multidisciplinary expertise to chapters in this work. Authors’ backgrounds range from data scientists, healthcare experts, university professors, and digital healthcare entrepreneurs. If you have an understanding of data technologies and are interested in the future of Big Data and A.I. in healthcare, this book will provide a wealth of insights into the new landscape of healthcare.
Big data and artificial intelligence (AI) are at the forefront of technological advances that represent a potential transformational mega-trend—a new multipolar and innovative disruption. These technologies, and their associated management paradigm, are already rapidly impacting many industries and occupations, but in some sectors, the change is just beginning. Innovating ahead of emerging technologies is the new imperative for any organization that aspires to succeed in the next decade. Faced with the power of this AI movement, it is imperative to understand the dynamics and new codes required by the disruption and to adapt accordingly. AI and Big Data’s Potential for Disruptive Innovation provides emerging research exploring the theoretical and practical aspects of successfully implementing new and innovative technologies in a variety of sectors including business, transportation, and healthcare. Featuring coverage on a broad range of topics such as semantic mapping, ethics in AI, and big data governance, this book is ideally designed for IT specialists, industry professionals, managers, executives, researchers, scientists, and engineers seeking current research on the production of new and innovative mechanization and its disruptions.
INTELLIGENT CONNECTIVITY AI, IOT, AND 5G Explore the economics and technology of AI, IOT, and 5G integration Intelligent Connectivity: AI, IoT, and 5G delivers a comprehensive technological and economic analysis of intelligent connectivity and the integration of artificial intelligence, Internet of Things (IoT), and 5G. It covers a broad range of topics, including Machine-to-Machine (M2M) architectures, edge computing, cybersecurity, privacy, risk management, IoT architectures, and more. The book offers readers robust statistical data in the form of tables, schematic diagrams, and figures that provide a clear understanding of the topic, along with real-world examples of applications and services of intelligent connectivity in different sectors of the economy. Intelligent Connectivity describes key aspects of the digital transformation coming with the 4th industrial revolution that will touch on industries as disparate as transportation, education, healthcare, logistics, entertainment, security, and manufacturing. Readers will also get access to: A thorough introduction to technology adoption and emerging trends in technology, including business trends and disruptive new applications Comprehensive explorations of telecommunications transformation and intelligent connectivity, including learning algorithms, machine learning, and deep learning Practical discussions of the Internet of Things, including its potential for disruption and future trends for technological development In-depth examinations of 5G wireless technology, including discussions of the first five generations of wireless tech Ideal for telecom and information technology managers, directors, and engineers, Intelligent Connectivity: AI, IoT, and 5G is also an indispensable resource for senior undergraduate and graduate students in telecom and computer science programs.
In the current day and age of technology, buzzwords such as artificial intelligence (AI), the internet of things (IoT), and cloud computing are often used. AI is the technology that tries to make computers or other machines equal to the human brain, making them capable of learning and problem-solving in the same way that humans do. Applications based on AI may be readily connected with other developing technologies such as the Internet of Things (IoT), the cloud, Big Data, and Blockchain. The Internet of Things refers to a network of interconnected, internet-enabled items or things that are able to gather and share data with one another. In recognition of the idea of the Internet of items, a significant number of tangible items are now being connected with the internet at an exceptionally rapid pace. By the year 2025, there will be more than 30 billion Internet of Things connections, with approximately four Internet of Things devices per person on average, according to reports and current trends. Cloud computing provides a means through which the huge amounts of data created by these Internet of Things applications may be sent to their respective endpoints. The use of cloud computing is widely acknowledged to be a facility for the processing and storage of data. Just-in-time processing and lightning fast response times are necessities for any and all real-time applications that make use of the Internet of Things. Researchers, academics, and industrialists in the fields of health care, agriculture, telecommunications, online and mobile commerce, and transportation have shown a significant amount of interest in AI and IoT-based data. In today's world, AI-based methodologies increase the role that IoT plays in business monitoring, health-care monitoring, illness prediction, bioinformatics, research and development, stock market prediction, social network analysis, weather analysis, agriculture, transportation, and resource optimization. The implementation of these applications needs a certain amount of processing capability as well as data storage, both of which are often given by cloud-based services. The data that has been saved is processed in a high-precision and just-in-time way with the help of AI algorithms. The cloud is a strong instrument that can send data not only via the standard channels of the internet but also through a dedicated direct connection. The Internet of Things becomes the source of creating enormous amounts of data, and the cloud becomes an essential component for data storage. As a result, the Internet of Things and clouds have become deeply intertwined in order to provide commercial business services. 1 | P a ge This configuration is sometimes referred to as cloud-based IoT. As a result of their success in providing cloud-based Internet of Things (IoT) services, companies like Amazon Web Services (AWS), Google, and Microsoft have become industry leaders. This makes the task much more rewarding. In addition, the cloud-based Internet of items is utilized to link a broad variety of intelligent items for usage in different applications. Artificial intelligence (AI), the internet of things (IoT), and cloud computing all play significant roles in a variety of domains in the present and will continue to do so in the future. The goal of AI is to analyze and collect the data produced through cloud-based Internet of Things devices by gathering data from a variety of businesses. Integrating AI, IoT, and the cloud has resulted in a transformation of both the entire storage capacity and the digital world, and as a result, it has become a subject of intense interest among academics and academicians. The purpose of this chapter is to place an emphasis on the function that AI plays in data storage that is based on the cloud and IoT. The remaining parts of the chapter are broken down into the following sections: storing of data on the cloud is the primary emphasis. examines the function that IoT plays in cloud environments. In addition, the part that AI plays in the Internet of Things (IoT) and cloud data storage is discussed in. Section 6 brings the chapter to a close by discussing the applications of AI, IoT, and clouds in a variety of industries.
This book provides a deeper understanding of the relevant aspects of AI and DAI impacting each other's efficacy for better output. It will bridge the gap between research solutions and key technologies related to data analytics to ensure Industry 4.0 requirements and at the same time ensure proper network communication and security of big data.
Engineering plays a major role in solving real-world problems, from small inconveniences to societal or global concerns around food scarcity, water shortages, environmental damage, problems in housing or infrastructure and more. In today's rapidly evolving world, the development of the latest generation of engineering and technology is crucial for maintaining productivity, innovation, and improving our overall quality of life. Intelligent Engineering Applications and Applied Sciences for Sustainability is an essential research book that serves as a compilation of cutting-edge research and advancements in engineering, science, and technology, and more importantly, how the application of these advancements will guide the path to a more sustainable future. This book focuses on intelligent engineering applications, which encompass the design and implementation of embedded technologies in various domains. It covers a wide range of fields and their influence on the Sustainable Development Goals (SDGs), fostering interdisciplinary approaches and innovative solutions, including additive manufacturing technologies, aerospace science and engineering, agricultural advancements, computer science for sustainable development, applied biosciences, applied mathematics, industrial engineering, robotics and automation, transportation, future mobility, and much more. As an academic, rigorous exploration of various disciplines, this book serves as an invaluable resource for researchers, scholars, and professionals seeking to advance the frontiers of intelligent engineering applications and applied sciences for a sustainable future.
In the dynamic and ever-changing financial landscape, the seamless integration of artificial intelligence (AI) and machine learning (ML) has presented unprecedented challenges for the banking and finance industry. As we embrace the era of Industry 5.0, financial institutions find themselves confronted with intricate decisions pertaining to investments, macroeconomic analysis, and credit evaluation, necessitating innovative technologies to navigate this complexity. Additionally, the mounting volume of financial transactions calls for efficient data processing and analysis. Considering these pressing concerns, scholars, academicians, and industry practitioners are eagerly seeking comprehensive insights into the transformative potential of AI and ML, specifically in bolstering resilience, fostering sustainable development, and adopting human-centric approaches within the financial sector. Offering a compelling solution to these critical challenges, The Impact of AI Innovation on Financial Sectors in the Era of Industry 5.0, edited by esteemed scholars Mohammad Irfan, Mohammed Elmogy, M. Shabri Abd. Majid, and Shaker El-Sappagh, embark on an in-depth exploration of the multifaceted functions and applications of AI and ML algorithms in the realm of finance. With a keen focus on Industry 5.0 principles such as resilience, human centricity, and sustainable development, this comprehensive compendium presents a collection of groundbreaking research papers that unveil the remarkable potential of AI/ML technologies in revolutionizing the financial services industry. By catering to a diverse audience comprising researchers, academicians, industrialists, investors, and regulatory bodies, this book actively invites contributions from industry practitioners and scholars, facilitating ongoing discussions on the efficacy of ML algorithms in efficiently processing vast financial data. As the financial landscape charts an ambitious course into Industry 5.0, the book emerges as an indispensable resource, empowering the industry with transformative advancements that will indelibly shape the future of finance.
