Durgesh Srivastava – författare

The book focuses on developments in artificial intelligence (AI) and internet of things (IoT) integration for smart healthcare, with an emphasis on current methodologies and frameworks for the design, growth, implementation, and creative use of such convergence technologies to provide insight into smart healthcare service demands. Concepts like signal recognition, computation, internet of health stuff, and so forth and their applications are covered. Development in connectivity and intelligent networks allowing for social adoption of ambient intelligence is also included.Features:•Introduces Intelligent IoT as applicable to the key areas of smart healthcare.•Discusses computational intelligence and IoT-based optimizations of smart healthcare systems•Explores effective management of healthcare systems using dedicated IoT-based infrastructures•Includes dedicated chapters on securing patient’s confidential data •Reviews diagnosis of critical diseases from medical imaging using advanced deep learning-based approachesThis book is aimed at researchers, professionals, and graduate students in intelligent systems, big data, cloud computing, information security, and healthcare systems.

The book focuses on developments in artificial intelligence (AI) and internet of things (IoT) integration for smart healthcare, with an emphasis on current methodologies and frameworks for the design, growth, implementation, and creative use of such convergence technologies to provide insight into smart healthcare service demands. Concepts like signal recognition, computation, internet of health stuff, and so forth and their applications are covered. Development in connectivity and intelligent networks allowing for social adoption of ambient intelligence is also included.Features:•Introduces Intelligent IoT as applicable to the key areas of smart healthcare.•Discusses computational intelligence and IoT-based optimizations of smart healthcare systems•Explores effective management of healthcare systems using dedicated IoT-based infrastructures•Includes dedicated chapters on securing patient’s confidential data •Reviews diagnosis of critical diseases from medical imaging using advanced deep learning-based approachesThis book is aimed at researchers, professionals, and graduate students in intelligent systems, big data, cloud computing, information security, and healthcare systems.

Artificial Intelligence Technology in Healthcare: Security and Privacy Issues focuses on current issues with patients’ privacy and data security including data breaches in healthcare organizations, unauthorized access to patients’ information, and medical identity theft. It explains recent breakthroughs and problems in deep learning security and privacy issues, emphasizing current state-of-the-art methods, methodologies, implementation, attacks, and countermeasures. It examines the issues related to developing artifiicial intelligence (AI)-based security mechanisms which can gather or share data across several healthcare applications securely and privately. Features: Combines multiple technologies (i.e., Internet of Things [IoT], Federated Computing, and AI) for managing and securing smart healthcare systems. Includes state-of-the-art machine learning, deep learning techniques for predictive analysis, and fog and edge computing-based real-time health monitoring. Covers how to diagnose critical diseases from medical imaging using advanced deep learning-based approaches. Focuses on latest research on privacy, security, and threat detection on COVID-19 through IoT. Illustrates initiatives for research in smart computing for advanced healthcare management systems.This book is aimed at researchers and graduate students in bioengineering, artificial intelligence, and computer engineering.

Artificial Intelligence Technology in Healthcare: Security and Privacy Issues focuses on current issues with patients’ privacy and data security including data breaches in healthcare organizations, unauthorized access to patients’ information, and medical identity theft. It explains recent breakthroughs and problems in deep learning security and privacy issues, emphasizing current state-of-the-art methods, methodologies, implementation, attacks, and countermeasures. It examines the issues related to developing artifiicial intelligence (AI)-based security mechanisms which can gather or share data across several healthcare applications securely and privately. Features: Combines multiple technologies (i.e., Internet of Things [IoT], Federated Computing, and AI) for managing and securing smart healthcare systems. Includes state-of-the-art machine learning, deep learning techniques for predictive analysis, and fog and edge computing-based real-time health monitoring. Covers how to diagnose critical diseases from medical imaging using advanced deep learning-based approaches. Focuses on latest research on privacy, security, and threat detection on COVID-19 through IoT. Illustrates initiatives for research in smart computing for advanced healthcare management systems.This book is aimed at researchers and graduate students in bioengineering, artificial intelligence, and computer engineering.

This book examines the applications, trends and challenges of 5G Enabled technologies for Smart City and Urbanization systems. It addresses the challenges to bringing such capabilities of 5G-enabled technologies for smart cities and urbanisation into practice by presenting the theoretical as well as technical research outcomes with case studies. It covers key areas, including smart building, smart health care, smart mobility, smart living, smart surveillance, and IOT-based systems. It explains how these systems are connected using different technologies that support 5G access and control protocols.• Offers a comprehensive understanding of the emergence of 5G technology and its integration with IoT, Big Data, and Artificial Intelligence for smart city and urbanisation• Focuses on useful applications of Smart City and Urbanization, which can enhance different aspects of urban life• Explores the advantages of using massive IoT and predictive analytics approaches in smart cities• IoT, Bigdata, Deep learning and machine learning techniques are explained to fuel smart city and Urbanization system• Addresses both theoretical and technical research outcomes related to smart city and urbanisation with 5G technology.It serves as a valuable reference for graduate students, researchers, and m practitioners seeking to deepen their knowledge and engage with the latest advancements in the areas of Smart cities and Urbanization systems.

This book examines the applications, trends and challenges of 5G Enabled technologies for Smart City and Urbanization systems. It addresses the challenges to bringing such capabilities of 5G-enabled technologies for smart cities and urbanisation into practice by presenting the theoretical as well as technical research outcomes with case studies. It covers key areas, including smart building, smart health care, smart mobility, smart living, smart surveillance, and IOT-based systems. It explains how these systems are connected using different technologies that support 5G access and control protocols.• Offers a comprehensive understanding of the emergence of 5G technology and its integration with IoT, Big Data, and Artificial Intelligence for smart city and urbanisation• Focuses on useful applications of Smart City and Urbanization, which can enhance different aspects of urban life• Explores the advantages of using massive IoT and predictive analytics approaches in smart cities• IoT, Bigdata, Deep learning and machine learning techniques are explained to fuel smart city and Urbanization system• Addresses both theoretical and technical research outcomes related to smart city and urbanisation with 5G technology.It serves as a valuable reference for graduate students, researchers, and m practitioners seeking to deepen their knowledge and engage with the latest advancements in the areas of Smart cities and Urbanization systems.

The book is essential for anyone seeking to understand and leverage the transformative power of intelligent automation technologies, providing crucial insights into current trends, challenges, and effective solutions that can significantly enhance operational efficiency and decision-making within organizations. Intelligent automation systems, also called cognitive automation, use automation technologies such as artificial intelligence, business process management, and robotic process automation, to streamline and scale decision-making across organizations. Intelligent automation simplifies processes, frees up resources, improves operational efficiencies, and has a variety of applications. Intelligent automation systems aim to reduce costs by augmenting the workforce and improving productivity and accuracy through consistent processes and approaches, which enhance quality, improve customer experience, and address compliance and regulations with confidence. Handbook of Intelligent Automation Systems Using Computer Vision and Artificial Intelligence explores the significant role, current trends, challenges, and potential solutions to existing challenges in the field of intelligent automation systems, making it an invaluable guide for researchers, industry professionals, and students looking to apply these innovative technologies. Readers will find the volume: Offers comprehensive coverage on intelligent automation systems using computer vision and AI, covering everything from foundational concepts to real-world applications and ethical considerations;Provides actionable knowledge with case studies and best practices for intelligent automation systems, computer vision, and AI;Explores the integration of various techniques, including facial recognition, natural language processing, neuroscience and neuromarketing.Audience The book is designed for AI and data scientists, software developers and engineers in industry and academia, as well as business leaders and entrepreneurs who are interested in the applications of intelligent automation systems.

The main goal of Smart Agritech: Robotics, AI, and Internet of Things (IoT) in Agriculture is to explore how emerging technologies such as robotics, artificial intelligence (AI), and IoT can be leveraged to improve efficiency, sustainability, and productivity in agriculture. Agriculture has always been a vital sector of the global economy, providing food and raw materials for industries and households. However, with the growing population, changing climate conditions, and limited resources, the agriculture sector faces numerous challenges. To address these challenges, farmers and agricultural companies are turning to advanced technologies such as Robotics, Artificial Intelligence (AI), and the Internet of Things (IoT). This exciting new volume provides a comprehensive overview of the latest technological advances in agriculture, focusing on these three cutting-edge technologies. The book will explore the potential benefits of these technologies in improving agricultural efficiency, productivity, and sustainability. Whether for the veteran engineer, scientist in the lab, student, or faculty, this groundbreaking new volume is a valuable resource for researchers and other industry professionals interested in the intersection of technology and agriculture.

Fortify your digital defenses with this essential book, which provides a roadmap for moving beyond the limitations of traditional encryption by leveraging generative AI algorithms to proactively anticipate, detect, and mitigate the next generation of cyber threats in real-time. In recent years, encryption has shown limitations as the sole safeguard against cyber threats in an increasingly interconnected world. While encryption remains a crucial component of cybersecurity, it is no longer sufficient to combat the evolving tactics of malicious actors. This book advocates for a paradigm shift towards leveraging generative AI algorithms to anticipate, detect, and mitigate emerging threats in real-time. Through detailed case studies and practical examples, the book illustrates how these AI-driven approaches can augment traditional security measures, providing organizations with a proactive defense against cyberattacks. It explores the connections between artificial intelligence and cybersecurity, exploring how generative AI technologies can revolutionize security paradigms beyond traditional encryption methods. Authored by leading experts in both AI and cybersecurity, the book presents a comprehensive examination of the challenges facing modern digital security and proposes innovative solutions grounded in generative AI. By combining theoretical frameworks with actionable insights, this book serves as a roadmap for organizations looking to fortify their defenses in an era of unprecedented cyber threats, making it an essential resource for anyone invested in the evolving landscape of cybersecurity and AI.