Kashif Naseer Qureshi – författare

Artificial Intelligence-Based Smart Healthcare Systems: New Standards, Technologies, and Communication Systems delves into the transformative role of Artificial Intelligence (AI) in modern healthcare. The book sheds light on the integration of AI technologies into healthcare systems, significantly enhancing diagnostics, patient care, treatment, research, and administrative processes. It emphasizes AI's emergence as a crucial component of healthcare, where advanced AI-powered networks improve data communication, sensing, and monitoring capabilities, setting new standards for healthcare efficiency and accuracy.In addition to discussing AI's applications in patient monitoring, medical image analysis, human pose estimation, speech recognition, and disease diagnosis, the book explores architectural frameworks like software-defined networks, cloud and edge-based architectures, and mobility-based systems. It stresses the need for scalable, flexible, energy-efficient, and interoperable designs to support AI integration. Furthermore, the importance of robust security, privacy standards, and policies in AI-based healthcare systems is highlighted, considering the unique challenges and requirements of this domain.Covers the design of AI-powered predictive analytics which can be used to identify health issues and intervene at an early stageAddresses the critical issues of security and privacy concerning healthcare data and AI systemsDelves into how AI technologies can be used to tailor healthcare services and treatment plans to individual patients

Artificial Intelligence-based Renewable Energy Systems: Standards, Communication Systems, and Data Networks provides a comprehensive guide to integrating AI into renewable energy systems, addressing both fundamental principles and practical applications. Sections explore the evolution of AI in energy-efficient systems, advanced applications, architectural frameworks, standards, and distributed renewable energy networks while also delving into data communication systems, including networking protocols, advanced learning techniques, blockchain applications, big data analytics, green communication solutions, cybersecurity, and privacy challenges. Combining theoretical foundations with practical insights, this book offers students, researchers, and engineers a holistic perspective on AI communication and data networks for renewable energy systems.Presents a new release in the Advances in Intelligent Energy Systems seriesSupports foundational learning in AI technologies, applications, and opportunities in the energy sectorIncludes in-depth case studies, applications, and proposed standards for data network and communication systems on the grid

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.

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.

In this comprehensive and cutting-edge volume, Qureshi and Jeon bring together experts from around the world to explore the potential of artificial intelligence models in research and discuss the potential benefits and the concerns and challenges that the rapid development of this field has raised.The international chapter contributor group provides a wealth of technical information on different aspects of AI, including key aspects of AI, deep learning and machine learning models for AI, natural language processing and computer vision, reinforcement learning, ethics and responsibilities, security, practical implementation, and future directions. The contents are balanced in terms of theory, methodologies, and technical aspects, and contributors provide case studies to clearly illustrate the concepts and technical discussions throughout. Readers will gain valuable insights into how AI can revolutionize their work in fields including data analytics and pattern identification, healthcare research, social science research, and more, and improve their technical skills, problem-solving abilities, and evidence-based decision-making. Additionally, they will be cognizant of the limitations and challenges, the ethical implications, and security concerns related to language models, which will enable them to make more informed choices regarding their implementation.This book is an invaluable resource for undergraduate and graduate students who want to understand AI models, recent trends in the area, and technical and ethical aspects of AI. Companies involved in AI development or implementing AI in various fields will also benefit from the book’s discussions on both the technical and ethical aspects of this rapidly growing field.

In this comprehensive and cutting-edge volume, Qureshi and Jeon bring together experts from around the world to explore the potential of artificial intelligence models in research and discuss the potential benefits and the concerns and challenges that the rapid development of this field has raised.The international chapter contributor group provides a wealth of technical information on different aspects of AI, including key aspects of AI, deep learning and machine learning models for AI, natural language processing and computer vision, reinforcement learning, ethics and responsibilities, security, practical implementation, and future directions. The contents are balanced in terms of theory, methodologies, and technical aspects, and contributors provide case studies to clearly illustrate the concepts and technical discussions throughout. Readers will gain valuable insights into how AI can revolutionize their work in fields including data analytics and pattern identification, healthcare research, social science research, and more, and improve their technical skills, problem-solving abilities, and evidence-based decision-making. Additionally, they will be cognizant of the limitations and challenges, the ethical implications, and security concerns related to language models, which will enable them to make more informed choices regarding their implementation.This book is an invaluable resource for undergraduate and graduate students who want to understand AI models, recent trends in the area, and technical and ethical aspects of AI. Companies involved in AI development or implementing AI in various fields will also benefit from the book’s discussions on both the technical and ethical aspects of this rapidly growing field.

This book first discusses cyber security fundamentals then delves into security threats and vulnerabilities, security vigilance, and security engineering for Internet of Everything (IoE) networks. After an introduction, the first section covers the security threats and vulnerabilities or techniques to expose the networks to security attacks such as repudiation, tampering, spoofing, and elevation of privilege. The second section of the book covers vigilance or prevention techniques like intrusion detection systems, trust evaluation models, crypto, and hashing privacy solutions for IoE networks. This section also covers the security engineering for embedded and cyber-physical systems in IoE networks such as blockchain, artificial intelligence, and machine learning-based solutions to secure the networks. This book provides a clear overview in all relevant areas so readers gain a better understanding of IoE networks in terms of security threats, prevention, and other security mechanisms.