Bioinspiration is recognized by the World Health Organization as having great promise in transforming and democratizing health systems while improving the quality, safety, and efficiency of standard healthcare in order to offer patients the tremendous opportunity to take charge of their own health. This phenomenon can enable great medical breakthroughs by helping healthcare providers improve patient care, make accurate diagnoses, optimize treatment protocols, and more. Unfortunately, the consequences can be serious if those who finance, design, regulate, or use artificial intelligence (AI) technologies for health do not prioritize ethical principles and obligations in terms of human rights and preservation of the private life. Advanced Bioinspiration Methods for Healthcare Standards, Policies, and Reform is the fruit of the fusion of AI and medicine, which brings together the latest empirical research findings in the areas of AI, bioinspiration, law, ethics, and medicine. It assists professionals in optimizing the potential benefits of AI models and bioinspired algorithms in health issues while mitigating potential dangers by examining the complex issues and innovative solutions that are linked to healthcare standards, policies, and reform. Covering topics such as genetic algorithms, health surveillance cameras, and hybrid classification algorithms, this premier reference source is an excellent resource for AI specialists, hospital administrators, health professionals, healthcare scientists, students and educators of higher education, government officials, researchers, and academicians.

The internet of things (IoT) has drawn great attention from both academia and industry, since it offers a challenging notion of creating a world where all things around us are connected to the internet and communicate with each other with minimal human intervention. Another component for helping IoT to succeed is cloud computing. The combination of cloud computing and IoT will enable new monitoring services and powerful processing of sensory data streams. These applications, alongside implementation details and challenges, should also be explored for successful mainstream adoption. IoT is also fueled by the advancement of digital technologies, and the next generation era will be cloud-based IoT systems. Integration and Implementation of the Internet of Things Through Cloud Computing studies, analyzes, and presents cloud-based IoT-related technologies, protocols, and standards along with recent research and development in cloud-based IoT. It also presents recent emerging trends and technological advances of cloud-based IoT, innovative applications, and the challenges and implications for society. The chapters included take a strong look at the societal and social aspects of this technology along with its implementations and technological analyses. This book is intended for IT specialists, technologists, practitioners, researchers, academicians, and students who are interested in the next era of IoT through cloud computing.

The damaging effects of cyberattacks to an industry like the Cooperative Connected and Automated Mobility (CCAM) can be tremendous. From the least important to the worst ones, one can mention for example the damage in the reputation of vehicle manufacturers, the increased denial of customers to adopt CCAM, the loss of working hours (having direct impact on the European GDP), material damages, increased environmental pollution due e.g., to traffic jams or malicious modifications in sensors' firmware, and ultimately, the great danger for human lives, either they are drivers, passengers or pedestrians. Connected vehicles will soon become a reality on our roads, bringing along new services and capabilities, but also technical challenges and security threats. To overcome these risks, the CARAMEL project has developed several anti-hacking solutions for the new generation of vehicles. CARAMEL (Artificial Intelligence-based Cybersecurity for Connected and Automated Vehicles), a research project co-funded by the European Union under the Horizon 2020 framework programme, is a project consortium with 15 organizations from 8 European countries together with 3 Korean partners. The project applies a proactive approach based on Artificial Intelligence and Machine Learning techniques to detect and prevent potential cybersecurity threats to autonomous and connected vehicles. This approach has been addressed based on four fundamental pillars, namely: Autonomous Mobility, Connected Mobility, Electromobility, and Remote Control Vehicle. This book presents theory and results from each of these technical directions.

Artificial intelligence and its various components are rapidly engulfing almost every professional industry. Specific features of AI that have proven to be vital solutions to numerous real-world issues are machine learning and deep learning. These intelligent agents unlock higher levels of performance and efficiency, creating a wide span of industrial applications. However, there is a lack of research on the specific uses of machine/deep learning in the professional realm. Machine Learning and Deep Learning in Real-Time Applications provides emerging research exploring the theoretical and practical aspects of machine learning and deep learning and their implementations as well as their ability to solve real-world problems within several professional disciplines including healthcare, business, and computer science. Featuring coverage on a broad range of topics such as image processing, medical improvements, and smart grids, this book is ideally designed for researchers, academicians, scientists, industry experts, scholars, IT professionals, engineers, and students seeking current research on the multifaceted uses and implementations of machine learning and deep learning across the globe.

Throughout the world, artificial intelligence is reshaping businesses, trade interfaces, economic activities, and society as a whole. In recent years, scholarly research on artificial intelligence has emerged from a variety of empirical and applied domains of knowledge. Computer scientists have developed advanced deep learning algorithms to leverage its utility in a variety of fields such as medicine, energy, travel, education, banking, and business management. Although a growing body of literature is shedding light on artificial intelligence-enabled difficulties, there is still much to be gained by applying fresh theory-driven techniques to this vital topic. Revolutionizing Business Practices Through Artificial Intelligence and Data-Rich Environments provides a comprehensive understanding of the business systems, platforms, procedures, and mechanisms that underpin different stakeholders' experiences with reality-enhancing technologies and their transformative application in management. The book also identifies areas in various business processes where artificial intelligence intervention would not only transform the business but would also make the business more sustainable. Covering key topics such as blockchain, business automation, and manufacturing, this reference work is ideal for computer scientists, business owners, managers, industry professionals, researchers, academicians, scholars, practitioners, instructors, and students.

Clinical Engineering: A Handbook for Clinical and Biomedical Engineers, Second Edition, helps professionals and students in clinical engineering successfully deploy medical technologies. The book provides a broad reference to the core elements of the subject, drawing from a range of experienced authors. In addition to engineering skills, clinical engineers must be able to work with both patients and a range of professional staff, including technicians, clinicians and equipment manufacturers. This book will not only help users keep up-to-date on the fast-moving scientific and medical research in the field, but also help them develop laboratory, design, workshop and management skills. The updated edition features the latest fundamentals of medical technology integration, patient safety, risk assessment and assistive technology.

Advances in Imaging and Electron Physics, Volume 227 in the Advances in Imaging and Electron Physics series, merges two long-running serials, Advances in Electronics and Electron Physics and Advances in Optical and Electron Microscopy. The series features articles on the physics of electron devices (especially semiconductor devices), particle optics at high and low energies, microlithography, image science, digital image processing, electromagnetic wave propagation, electron microscopy and the computing methods used in all these domains.

Medical and information communication technology professionals are working to develop robust classification techniques, especially in healthcare data/image analysis, to ensure quick diagnoses and treatments to patients. Without fast and immediate access to healthcare databases and information, medical professionals' success rates and treatment options become limited and fall to disastrous levels. Advanced Classification Techniques for Healthcare Analysis provides emerging insight into classification techniques in delivering quality, accurate, and affordable healthcare, while also discussing the impact health data has on medical treatments. Featuring coverage on a broad range of topics such as early diagnosis, brain-computer interface, metaheuristic algorithms, clustering techniques, learning schemes, and mobile telemedicine, this book is ideal for medical professionals, healthcare administrators, engineers, researchers, academicians, and technology developers seeking current research on furthering information and communication technology that improves patient care.

Edge computing and analytics are fascinating the whole world of computing. Industry and business are keenly embracing this sound concept to develop customer-centric solutions by enhancing their operations, offerings, and outputs. There is a bevy of advancements in this domain that came with the arrival of IoT devices. The seamless convergence of microservices and serverless computing creates vast opportunities. With the help of IoT devices and these other developments, there has become a deep interest in business automation and additional improvisations in edge computing. With the steady growth of edge devices and applications of IoT fog/edge computing and analytics, there are also distinct challenges and threats. Research has been keenly focused on identifying and understanding these issues and shortcomings to bring viable solution approaches and algorithms. Cases on Edge Computing and Analytics describes the latest innovations, improvements, and transformations happening with edge devices and computing. It addresses the key concerns of the edge computing paradigm, how they are processed, and the various technologies and tools empowering edge computing and analytics. While highlighting topics within edge computing such as the key drivers for implementation, computing capabilities, security considerations, and use-cases, this book is ideal for IT industry professionals and project managers, computer scientists, computer engineers, and practitioners, stakeholders, researchers, academicians, and students looking for research on the latest trends and transitions in edge computing.

Unmanned Aerial Vehicle (UAV) has extended the freedom to operate and monitor the activities from remote locations. It has advantages of flying at low altitude, small size, high resolution, lightweight, and portability. UAV and artificial intelligence have started gaining attentions of academic and industrial research. UAV along with machine learning has immense scope in scientific research and has resulted in fast and reliable outputs. Deep learning-based UAV has helped in real time monitoring, data collection and processing, and prediction in the computer/wireless networks, smart cities, military, agriculture and mining. This book covers artificial techniques, pattern recognition, machine and deep learning - based methods and techniques applied to different real time applications of UAV. The main aim is to synthesize the scope and importance of machine learning and deep learning models in enhancing UAV capabilities, solutions to problems and numerous application areas. This book is ideal for researchers, scientists, engineers and designers in academia and industry working in the fields of computer science, computer vision, pattern recognition, machine learning, imaging, feature engineering, UAV and sensing.

Through an array of detailed case studies, this book explores the vibrant digital expressions of diverse groups of Muslim cybernauts: religious clerics and Sufis, feminists and fashionistas, artists and activists, hajj pilgrims and social media influencers. These stories span a vast cultural and geographic landscape—from Indonesia, Iran, and the Arab Middle East to North America. These granular case studies contextualize cyber Islam within broader social trends: racism and Islamophobia, gender dynamics, celebrity culture, identity politics, and the shifting terrain of contemporary religious piety and practice. The book’s authors examine an expansive range of digital multimedia technologies as primary “texts.” These include websites, podcasts, blogs, Twitter, Facebook, Instagram, YouTube channels, online magazines and discussion forums, and religious apps. The contributors also draw on a range of methodological and theoretical models from multiple academic disciplines, including communication and media studies, anthropology, history, global studies, religious studies, and Islamic studies.

Handbook of Research on Blockchain Technology presents the latest information on the adaptation and implementation of Blockchain technologies in real world business, scientific, healthcare and biomedical applications. The book's editors present the rapid advancements in existing business models by applying Blockchain techniques. Novel architectural solutions in the deployment of Blockchain comprise the core aspects of this book. Several use cases with IoT, biomedical engineering, and smart cities are also incorporated. As Blockchain is a relatively new technology that exploits decentralized networks and is used in many sectors for reliable, cost-effective and rapid business transactions, this book is a welcomed addition on existing knowledge. Financial services, retail, insurance, logistics, supply chain, public sectors and biomedical industries are now investing in Blockchain research and technologies for their business growth. Blockchain prevents double spending in financial transactions without the need of a trusted authority or central server. It is a decentralized ledger platform that facilitates verifiable transactions between parties in a secure and smart way.

The application of artificial intelligence technology to 5G wireless communications is now appropriate to address the design of optimized physical layers, complicated decision-making, network management, and resource optimization tasks within networks. In exploring 5G wireless technologies and communication systems, artificial intelligence is a powerful tool and a research topic with numerous potential fields of application that require further study. Applications of Artificial Intelligence in Wireless Communication Systems explores the applications of artificial intelligence for the optimization of wireless communication systems, including channel models, channel state estimation, beamforming, codebook design, signal processing, and more. Covering key topics such as neural networks, deep learning, and wireless systems, this reference work is ideal for computer scientists, industry professionals, researchers, academicians, scholars, practitioners, instructors, and students.