Presents new applications, techniques, and algorithms in AI and soft computing for intelligent, such as deep learning, robotics, machine learning, blockchain, emerging cloud, edge computing, Practical Byzantine Fault Tolerance consensus, CNN architecture, Splunk, genetic algorithms, and more.
This volume demonstrates the diverse state-of-the-art applications that combine artificial intelligence with soft computing, which has great potential for creating smart personalized healthcare services. The book showcases the myriad uses of AI and computer techniques in healthcare that employ deep learning, robotics, machine learning, blockchain, emerging cloud, edge computing, Practical Byzantine Fault Tolerance consensus, CNN architecture, Splunk, genetic algorithms (GA), DurBhashan, and many more. These technologies can be used in healthcare for enhanced data sharing, remote health monitoring, tele-rehabilitation, connecting rural populations with healthcare services, identifying diseases and health issues, automated medical diagnosis, analyzing information in surgical videos, ensuring timely communication and transportation during health disasters and emergencies, for optimizing expenditures, and more.
With the ever-increasing threat of cyber-attacks, especially as the COVID-19 pandemic helped to ramp up the use of digital communications technology, there is a continued need to find new ways to maintain and improve cybersecurity. This new volume investigates the advances in artificial intelligence and soft computing techniques in cybersecurity. It specifically looks at cybersecurity during the COVID-19 pandemic, the use of cybersecurity for cloud intelligent systems, applications of cybersecurity techniques for web applications, and cybersecurity for cyber-physical systems. A diverse array of technologies and techniques are explored for cybersecurity applications, such as the Internet of Things, edge computing, cloud computing, artificial intelligence, soft computing, machine learning, cross-site scripting in web-based services, neural gas (GNG) clustering technique, and more.
Understanding the complex interplay between food safety, nutrition, bioscience, and data algorithms is crucial for effectively managing autoimmune diseases. However, the current literature often needs a comprehensive resource that integrates these disciplines, leaving researchers, clinicians, and industry professionals needing a clearer understanding of how to apply these concepts in practice. This gap in knowledge hinders the development of personalized nutrition plans and precision health interventions, ultimately limiting the effectiveness of autoimmune disease management strategies. Nutrition Controversies and Advances in Autoimmune Disease brings to the table more than a mere theoretical guide. It offers practical applications and case studies that bring to life the latest research and developments in the fields of food safety, nutrition, bioscience, and data algorithms. By integrating these disciplines, the book provides readers with the knowledge and tools to develop personalized nutrition plans and implement precision health interventions for autoimmune diseases, making it a valuable resource for anyone in the field.
This book focuses on the fusion of artificial intelligence and machine learning in advanced image processing, data analysis, and cyber security, as well as compiles and discusses various engineering solutions using various artificial intelligence paradigms. It looks at recent technological advancements and considers how artificial intelligence, machine learning, deep learning, soft computing, and evolutionary computing techniques can be used to design, implement, and optimize advanced image processing, data analysis, and cyber security engineering solutions. It will readers develop the insight required to use the tools of digital imaging to solve new problems. The book is divided into sections that deal with Artificial intelligence and machine learning in medicine and healthcare Intelligent decision-making and analysis technology Machine learning and deep learning for agriculture Artificial intelligence and machine learning for security solutions Automation in image processing Fusion of Artificial Intelligence and Machine Learning for Advanced Image Processing, Data Analysis, and Cyber Security offers a selection of chapters on the application of artificial intelligence and machine learning for advanced image processing, data analysis, and cyber security. This book will surely enhance the knowledge of readers interested in these areas.
Due to advances in technology, particularly in artificial intelligence and robotics, the service sector is being reshaped, and AI may even be necessary for survival of the service industries. Innovations in digital technology lead to improving processes and, in many situations, are a solution to improving the efficiency and the quality of processes and services. This volume examines in depth how AI innovation is creating knowledge, improving efficiency, and elevating quality of life for millions of people and how it applies to the service industry. This volume addresses advances, issues, and challenges from several points of view from diverse service areas, including healthcare, mental health, finance, management, learning and education, and others. The authors demonstrate how service practices can incorporate the subareas of AI, such as machine learning, deep learning, blockchain, big data, neural networks, etc. The diverse roster of chapter authors includes 48 scholars from different fields, (management, public policies, accounting, information technologies, engineering, medicine) along with executives and managers of private enterprises and public bodies in different sectors, from life sciences to healthcare. Several chapters also evaluate AI’s application in service industries during the COVID-19 era. This book, Incorporating AI Technology in the Service Sector: Innovations in Creating Knowledge, Improving Efficiency, and Elevating Quality of Life, provides professionals, administrators, educators, researchers, and students with useful perspectives by introducing new approaches and innovations for identifying future strategies for service sector companies.
In a world where automation is quickly becoming a standard, a significant challenge arises – the need for robots to overcome their inherent limitations in processing power and storage. This bottleneck restricts their potential for innovation and collaboration, hindering the realization of true autonomous capabilities. The burgeoning field of Cloud Robotics promises a revolutionary solution by seamlessly integrating robots with cloud-based technologies. This integration empowers robots to offload computation tasks, tap into vast data resources, and engage in real-time collaboration with their mechanical counterparts. Existing literature often falls short of providing a holistic understanding of the complex interplay between robotics and cloud computing. Researchers, academics, and industry professionals find themselves grappling with fragmented insights, hindering their ability to harness the full potential of cloud-enhanced robotics. The lack of a centralized resource leaves a void, impeding progress and innovation in this groundbreaking field. Without a roadmap to navigate the challenges and opportunities presented by cloud robotics, stakeholders risk being left behind in an era where interdisciplinary collaboration is paramount. Enter Shaping the Future of Automation With Cloud-Enhanced Robotics, a beacon of knowledge designed specifically for academics, researchers, and industry professionals seeking to unlock the transformative power of cloud robotics. From fundamental principles to advanced applications, each chapter meticulously unravels the intricacies of cloud infrastructure, communication protocols, data management, human-robot interaction, and more. By addressing challenges and proposing solutions, this book not only disseminates recent advancements but also equips readers with actionable insights. Real-world examples and case studies illuminate the practical applications and benefits of cloud-enhanced robotics, making it an indispensable guide for professionals aiming to implement these innovations in their operations.
With a need to find alternatives to the traditional face-to-face teaching and learning during the pandemic, this topical volume discusses the best use of technologies in higher education, addressing the growing role of AI in the digital transformation of higher education systems. With chapters from eminent professors, researchers, and others involved in higher education from a selection of different countries, the volume looks at blockchain and IoT technologies to create smart universities now and for the future.
The digital transformation of the health sector consistently presents unique challenges. As technologies like artificial intelligence, big data, and telemedicine rapidly evolve, healthcare systems need to keep up with advancements and data protection. This rapid evolution, compounded by the complexities of managing patient data and ensuring cybersecurity, creates a daunting task for healthcare providers and policymakers. The COVID-19 pandemic has also highlighted the urgent need for digital solutions, amplifying the pressure on an already strained sector. Improving Security, Privacy, and Connectivity Among Telemedicine Platforms is a comprehensive guide to navigating the digital revolution in healthcare. It offers insights into identifying vital digital technologies and understanding their impact on the Health Value Chain. Through an analysis of empirical evidence, this book provides a roadmap for effectively managing change, transition, and digital value creation in healthcare. With a focus on business sustainability, change management, and cybersecurity, it equips scholars, researchers, and practitioners with the tools needed to thrive in a rapidly evolving digital landscape.
