Yousef Farhaoui – författare

The goal of medical informatics is to improve life expectancy, disease diagnosis and quality of life. Medical devices have revolutionized healthcare and have led to the modern age of machine learning, deep learning and Internet of Medical Things (IoMT) with their proliferation, mobility and agility. This book exposes different dimensions of applications for computational intelligence and explains its use in solving various biomedical and healthcare problems in the real world. This book describes the fundamental concepts of machine learning and deep learning techniques in a healthcare system. The aim of this book is to describe how deep learning methods are used to ensure high-quality data processing, medical image and signal analysis and improved healthcare applications. This book also explores different dimensions of computational intelligence applications and illustrates its use in the solution of assorted real-world biomedical and healthcare problems. Furthermore, it provides the healthcare sector with innovative advances in theory, analytical approaches, numerical simulation, statistical analysis, modelling, advanced deployment, case studies, analytical results, computational structuring and significant progress in the field of machine learning and deep learning in healthcare applications.FEATURES Explores different dimensions of computational intelligence applications and illustrates its use in the solution of assorted real-world biomedical and healthcare problems Provides guidance in developing intelligence-based diagnostic systems, efficient models and cost-effective machines Provides the latest research findings, solutions to the concerning issues and relevant theoretical frameworks in the area of machine learning and deep learning for healthcare systems Describes experiences and findings relating to protocol design, prototyping, experimental evaluation, real testbeds and empirical characterization of security and privacy interoperability issues in healthcare applications Explores and illustrates the current and future impacts of pandemics and mitigates risk in healthcare with advanced analyticsThis book is intended for students, researchers, professionals and policy makers working in the fields of public health and in the healthcare sector. Scientists and IT specialists will also find this book beneficial for research exposure and new ideas in the field of machine learning and deep learning.

The goal of medical informatics is to improve life expectancy, disease diagnosis and quality of life. Medical devices have revolutionized healthcare and have led to the modern age of machine learning, deep learning and Internet of Medical Things (IoMT) with their proliferation, mobility and agility. This book exposes different dimensions of applications for computational intelligence and explains its use in solving various biomedical and healthcare problems in the real world. This book describes the fundamental concepts of machine learning and deep learning techniques in a healthcare system. The aim of this book is to describe how deep learning methods are used to ensure high-quality data processing, medical image and signal analysis and improved healthcare applications. This book also explores different dimensions of computational intelligence applications and illustrates its use in the solution of assorted real-world biomedical and healthcare problems. Furthermore, it provides the healthcare sector with innovative advances in theory, analytical approaches, numerical simulation, statistical analysis, modelling, advanced deployment, case studies, analytical results, computational structuring and significant progress in the field of machine learning and deep learning in healthcare applications.FEATURES Explores different dimensions of computational intelligence applications and illustrates its use in the solution of assorted real-world biomedical and healthcare problems Provides guidance in developing intelligence-based diagnostic systems, efficient models and cost-effective machines Provides the latest research findings, solutions to the concerning issues and relevant theoretical frameworks in the area of machine learning and deep learning for healthcare systems Describes experiences and findings relating to protocol design, prototyping, experimental evaluation, real testbeds and empirical characterization of security and privacy interoperability issues in healthcare applications Explores and illustrates the current and future impacts of pandemics and mitigates risk in healthcare with advanced analyticsThis book is intended for students, researchers, professionals and policy makers working in the fields of public health and in the healthcare sector. Scientists and IT specialists will also find this book beneficial for research exposure and new ideas in the field of machine learning and deep learning.

Tremendous growth in healthcare treatment techniques and methods has led to the emergence of numerous storage and communication problems and need for security among vendors and patients. This book brings together latest applications and state-of-the-art developments in healthcare sector using Blockchain technology. It explains how blockchain can enhance security, privacy, interoperability, and data accessibility including AI with blockchains, blockchains for medical imaging to supply chain management, and centralized management/clearing houses alongside DLT. Features: Includes theoretical concepts, empirical studies and detailed overview of various aspects related to development of healthcare applications from a reliable, trusted, and secure data transmission perspective. Provide insights on business applications of Blockchain, particularly in the healthcare sector. Explores how Blockchain can solve the transparency issues in the clinical research. Discusses AI with Blockchains, ranging from medical imaging to supply chain management. Reviews benchmark testing of AI with Blockchains and its impacts upon medical uses.This book aims at researchers and graduate students in healthcare information systems, computer and electrical engineering.

Tremendous growth in healthcare treatment techniques and methods has led to the emergence of numerous storage and communication problems and need for security among vendors and patients. This book brings together latest applications and state-of-the-art developments in healthcare sector using Blockchain technology. It explains how blockchain can enhance security, privacy, interoperability, and data accessibility including AI with blockchains, blockchains for medical imaging to supply chain management, and centralized management/clearing houses alongside DLT. Features: Includes theoretical concepts, empirical studies and detailed overview of various aspects related to development of healthcare applications from a reliable, trusted, and secure data transmission perspective. Provide insights on business applications of Blockchain, particularly in the healthcare sector. Explores how Blockchain can solve the transparency issues in the clinical research. Discusses AI with Blockchains, ranging from medical imaging to supply chain management. Reviews benchmark testing of AI with Blockchains and its impacts upon medical uses.This book aims at researchers and graduate students in healthcare information systems, computer and electrical engineering.

The Internet of things (IoT) is a network of connected physical objects or things that are working along with sensors, wireless transceiver modules, processors, and software required for connecting, processing, and exchanging data among the other devices over the Internet. These objects or things are devices ranging from simple handheld devices to complex industrial heavy machines. A thing in IoT can be any living or non-living object that can be provided capabilities to sense, process, and exchange data over a network. The IoT provides people with the ability to handle their household works to industrial tasks smartly and efficiently without the intervention of another human. The IoT provides smart devices for home automation as well as business solutions for delivering insights into everything from real-time monitoring of working systems to supply chain and logistics operations. The IoT has become one of the most prominent technological inventions of the 21st century.Due to the versatility of IoT devices, there are numerous real-world applications of the IoT in various domains such as smart home, smart city, health care, agriculture, industry, and transportation. The IoT has emerged as a paradigm-shifting technology that is influencing various industries. Many companies, governments, and civic bodies are shifting to IoT applications to improve their works and to become more efficient. The world is slowly transforming toward a "smart world" with smart devices. As a consequence, it shows many new opportunities coming up in the near "smart" future for IoT professionals. Therefore, there is a need to keep track of advancements related to IoT applications and further investigate several research challenges related to the applicability of IoT in different domains to make it more adaptable for practical and industrial use. With this goal, this book provides the most recent and prominent applications of IoT in different domains as well as issues and challenges in developing IoT applications for various new domains.

The Internet of things (IoT) is a network of connected physical objects or things that are working along with sensors, wireless transceiver modules, processors, and software required for connecting, processing, and exchanging data among the other devices over the Internet. These objects or things are devices ranging from simple handheld devices to complex industrial heavy machines. A thing in IoT can be any living or non-living object that can be provided capabilities to sense, process, and exchange data over a network. The IoT provides people with the ability to handle their household works to industrial tasks smartly and efficiently without the intervention of another human. The IoT provides smart devices for home automation as well as business solutions for delivering insights into everything from real-time monitoring of working systems to supply chain and logistics operations. The IoT has become one of the most prominent technological inventions of the 21st century.Due to the versatility of IoT devices, there are numerous real-world applications of the IoT in various domains such as smart home, smart city, health care, agriculture, industry, and transportation. The IoT has emerged as a paradigm-shifting technology that is influencing various industries. Many companies, governments, and civic bodies are shifting to IoT applications to improve their works and to become more efficient. The world is slowly transforming toward a "smart world" with smart devices. As a consequence, it shows many new opportunities coming up in the near "smart" future for IoT professionals. Therefore, there is a need to keep track of advancements related to IoT applications and further investigate several research challenges related to the applicability of IoT in different domains to make it more adaptable for practical and industrial use. With this goal, this book provides the most recent and prominent applications of IoT in different domains as well as issues and challenges in developing IoT applications for various new domains.

This book studies the evolution of sustainable green smart cities and demonstrates solutions for green environmental issues using modern industrial IoT solutions. It is a ready reference with guidelines and a conceptual framework for context-aware product development and research in the IoT paradigm and Big Data Analytics for a Green Environment. It brings together the most recent advances in IoT and Big Data in Green Environments, emerging aspects of the IoT and Big Data for Green Cities, explores key technologies, and develops new applications in this research field.Key Features:• Discusses the framework for development and research in the IoT Paradigm and Big Data Analytics.• Highlights threats to the IoT architecture and Big Data Analytics for a Green Environment.• Present the I-IoT architecture, I-IoT applications, and their characteristics for a Green Environment.• Provides a systematic overview of the state-of-the-art research efforts.• Introduces necessary components and knowledge to become a vital part of the IoT revolution for a Green Environment.This book is for professionals and researchers interested in the emerging technology of sustainable development, green cities, and Green Environment.

This book studies the evolution of sustainable green smart cities and demonstrates solutions for green environmental issues using modern industrial IoT solutions. It is a ready reference with guidelines and a conceptual framework for context-aware product development and research in the IoT paradigm and Big Data Analytics for a Green Environment. It brings together the most recent advances in IoT and Big Data in Green Environments, emerging aspects of the IoT and Big Data for Green Cities, explores key technologies, and develops new applications in this research field.Key Features:• Discusses the framework for development and research in the IoT Paradigm and Big Data Analytics.• Highlights threats to the IoT architecture and Big Data Analytics for a Green Environment.• Present the I-IoT architecture, I-IoT applications, and their characteristics for a Green Environment.• Provides a systematic overview of the state-of-the-art research efforts.• Introduces necessary components and knowledge to become a vital part of the IoT revolution for a Green Environment.This book is for professionals and researchers interested in the emerging technology of sustainable development, green cities, and Green Environment.

Emerging healthcare networks are interconnected physical systems that use cyber technologies for interaction and functionality. The proliferation of massive internet-of-things (IoT) devices enables remote and distributed access to cutting-edge diagnostics and treatment options in modern healthcare systems. New security vulnerabilities are emerging due to the increasing complexity of the healthcare architecture, in particular, threats to medical devices and critical infrastructure pose significant concerns owing to their potential risks to patient health and safety. In recent times, patients have been exposed to high risks from attacks capable of disrupting critical medical infrastructure, communications facilities, and services, interfering with medical devices, or compromising sensitive user data.This book seeks to present cyber risk and vulnerability models, considering a number of threats and examining how effective regulations could help guarantee medical device fidelity and trust. The book discusses the application of artificial intelligence and machine learning to provide practical learning-based solutions to address cyberattacks in emerging healthcare systems. The book focuses on the technical considerations, potential opportunities, critical cybersecurity challenges, the prospects and potential benefits of cybersecurity in emerging healthcare systems. Finally, the book presents case studies, highlighting critical lessons, and providing recommendations for designing AI-based cybersecurity architectures for emerging healthcare systems.Written by an international team of authors, this book is suitable for an audience of industry-based and academic researchers, scientists, and computer engineers working in data science, cybersecurity and wireless communications particularly those specialising in healthcare data science and those in related fields.

The latter makes use of applications and techniques related to data analysis in general and big data and smart city in particular.The book appeals to advanced undergraduate and graduate students, postdoctoral researchers, lecturers and industrial researchers, as well as anyone interested in big data analysis and smart city.

The latter makes use of applications and techniques related to data analysis in general and big data and smart city in particular.The book appeals to advanced undergraduate and graduate students, postdoctoral researchers, lecturers and industrial researchers, as well as anyone interested in big data analysis and smart city.

This book reviews the state of the art in big data analysis and networks technologies. It addresses a range of issues that pertain to: signal processing, probability models, machine learning, data mining, databases, data engineering, pattern recognition, visualization, predictive analytics, data warehousing, data compression, computer programming, smart cities, networks technologies, etc. Data is becoming an increasingly decisive resource in modern societies, economies, and governmental organizations. In turn, data science inspires novel techniques and theories drawn from mathematics, statistics, information theory, computer science, and the social sciences. All papers presented here are the product of extensive field research involving applications and techniques related to data analysis in general, and to big data and networks technologies in particular. Given its scope, the book will appeal to advanced undergraduate and graduate students, postdoctoral researchers,lecturers and industrial researchers, as well general readers interested in big data analysis and networks technologies.

This book reviews the state of the art of big data analysis, artificial intelligence, and smart environments. Data is becoming an increasingly decisive resource in modern societies, economies, and governmental organizations. Data science, artificial intelligence, and smart environments inspire novel techniques and theories drawn from mathematics, statistics, information theory, computer science, and social science. This book reviews the state of the art of big data analysis, artificial intelligence, and smart environments. It includes issues that pertain to signal processing, probability models, machine learning, data mining, database, data engineering, pattern recognition, visualization, predictive analytics, data warehousing, data compression, computer programming, smart city, etc. The papers in this book were the outcome of research conducted in this field of study. The latter makes use of applications and techniques related to data analysis in general and big data and smart city in particular.The book appeals to advanced undergraduate and graduate students, post-doctoral researchers, lecturers, and industrial researchers, as well as anyone interested in big data analysis and artificial intelligence.

This book is to provide a comprehensive reference for professionals in the field of data science and applications: artificial intelligence, big data, IoT, and blockchain.

This book is to provide a comprehensive reference for professionals in the field of data science and applications: artificial intelligence, big data, IoT, and blockchain.

This book presents the proceedings of 4th EAI International Conference on Smart Technology (MTYMEX), which took place March 28-29, 2024, Vancouver, B.C., Canada.

This book presents the proceedings of 4th EAI International Conference on Smart Technology (MTYMEX), which took place March 28-29, 2024, Vancouver, B.C., Canada. MTYMEX is an international conference aimed at demonstrating the potential of new applications for the Internet in the future. The authors offer perspectives on research on smart technologies in society, including the results of research projects on virtual reality, block chain, artificial intelligence, and smart cities. The book offers examples of applications with smart technologies in different knowledge areas. The conference brings together the academic, research and private sectors working on applications and smart devices for e-health and smart cities.

It includes issues that pertain to signal processing, probability models, machine learning, data mining, databases, data engineering, pattern recognition, visualization, predictive analytics, data warehousing, data compression, computer programming, smart city, etc.

This book covers a wide range of topics related to the integration of Artificial Intelligence, Big Data, IoT, and Blockchain: From Concepts to Applications. It begins by establishing a solid foundation and introducing the concepts and principles of each technology. The subsequent chapters delve into the various applications and use cases, providing readers with real-world examples of how AI, IoT, and Blockchain can be leveraged to address key challenges in Smart Environments. Data is becoming an increasingly decisive resource in modern societies, economies, and governmental organizations. Data science, Artificial Intelligence, and Smart Environments inspire novel techniques and theories drawn from mathematics, statistics, information theory, computer science, and social science. This book reviews the state of the art of big data analysis, Artificial Intelligence, and Smart Environments. It includes issues that pertain to signal processing, probability models, machine learning, data mining, databases, data engineering, pattern recognition, visualization, predictive analytics, data warehousing, data compression, computer programming, smart city, etc. The papers in this book were the outcome of research conducted in this field of study. The latter makes use of applications and techniques related to data analysis in general and big data and smart cities in particular. The authors hope that this book serves as a valuable resource and guide for readers, empowering them to navigate the intricate landscape of Artificial Intelligence, IoT, and Blockchain in Smart Environments. Let the authors embark on this transformative journey together, as the authors explore the concepts and applications that hold the potential to shape the future of Smart Environments. The book appeals to advanced undergraduate and graduate students, post-doctoral researchers, lecturers, and industrial researchers, as well as anyone interested in big data analysis and Artificial Intelligence.

It includes issues that pertain to signal processing, probability models, machine learning, data mining, databases, data engineering, pattern recognition, visualization, predictive analytics, data warehousing, data compression, computer programming, smart city, etc.

This book covers a wide range of topics related to the integration of Artificial Intelligence, Big Data, IoT, and Blockchain: From Concepts to Applications. It begins by establishing a solid foundation and introducing the concepts and principles of each technology. The subsequent chapters delve into the various applications and use cases, providing readers with real-world examples of how AI, IoT, and Blockchain can be leveraged to address key challenges in Smart Environments. Data is becoming an increasingly decisive resource in modern societies, economies, and governmental organizations. Data science, Artificial Intelligence, and Smart Environments inspire novel techniques and theories drawn from mathematics, statistics, information theory, computer science, and social science. This book reviews the state of the art of big data analysis, Artificial Intelligence, and Smart Environments. It includes issues that pertain to signal processing, probability models, machine learning, data mining, databases, data engineering, pattern recognition, visualization, predictive analytics, data warehousing, data compression, computer programming, smart city, etc. The papers in this book were the outcome of research conducted in this field of study. The latter makes use of applications and techniques related to data analysis in general and big data and smart cities in particular. The authors hope that this book serves as a valuable resource and guide for readers, empowering them to navigate the intricate landscape of Artificial Intelligence, IoT, and Blockchain in Smart Environments. Let the authors embark on this transformative journey together, as the authors explore the concepts and applications that hold the potential to shape the future of Smart Environments. The book appeals to advanced undergraduate and graduate students, post-doctoral researchers, lecturers, and industrial researchers, as well as anyone interested in big data analysis and Artificial Intelligence.

This book explores the integration of AI, data science, and emerging technologies to create innovative, practical solutions for smart environments.

The Intersection of Artificial Intelligence, Data Science, and Cutting-Edge Technologies: From Concepts to Applications in Smart Environments delves into the convergence of AI, data science, and innovative technologies within the realm of smart environments.

This book provides a comprehensive collection of recent research addressing practical and emerging challenges in intelligent technologies and smart environments. It highlights innovative methods, real-world applications, and interdisciplinary solutions that support the development of intelligent systems capable of improving efficiency, sustainability, and decision-making in modern digital ecosystems.This book brings together contributions that explore advanced approaches in artificial intelligence, data analytics, machine learning, Internet of Things (IoT), smart cities, cybersecurity, and intelligent automation. By presenting both theoretical developments and applied research, this book offers insights into how intelligent technologies can be designed, optimized, and deployed to solve complex problems in areas such as transportation, healthcare, energy management, environmental monitoring, and urban infrastructure.A distinctive aspect of this work is its focus on integrating artificial intelligence techniques with smart environment applications, emphasizing scalable, data-driven, and human-centered solutions. This book highlights novel algorithms, hybrid models, and intelligent architectures that address issues related to efficiency, sustainability, and digital transformation. This book also presents case studies and experimental frameworks that demonstrate the practical impact of these technologies in real-world scenarios.This book has a broad scope covering topics such as intelligent data processing, predictive analytics, computer vision, deep learning systems, smart sensing technologies, and decision-support platforms. By combining methodological advances with application-oriented research, the book provides a balanced perspective on both the scientific and practical aspects of intelligent systems.This book is intended for researchers, academics, graduate students, engineers, and industry practitioners interested in artificial intelligence and smart environments. It serves as a valuable reference for those working in interdisciplinary domains where intelligent technologies are applied to improve system performance, automation, and digital services.

This book provides a comprehensive collection of recent research addressing practical and emerging challenges in intelligent technologies and smart environments. It highlights innovative methods, real-world applications, and interdisciplinary solutions that support the development of intelligent systems capable of improving efficiency, sustainability, and decision-making in modern digital ecosystems.This book brings together contributions that explore advanced approaches in artificial intelligence, data analytics, machine learning, Internet of Things (IoT), smart cities, cybersecurity, and intelligent automation. By presenting both theoretical developments and applied research, this book offers insights into how intelligent technologies can be designed, optimized, and deployed to solve complex problems in areas such as transportation, healthcare, energy management, environmental monitoring, and urban infrastructure.A distinctive aspect of this work is its focus on integrating artificial intelligence techniques with smart environment applications, emphasizing scalable, data-driven, and human-centered solutions. This book highlights novel algorithms, hybrid models, and intelligent architectures that address issues related to efficiency, sustainability, and digital transformation. This book also presents case studies and experimental frameworks that demonstrate the practical impact of these technologies in real-world scenarios.This book has a broad scope covering topics such as intelligent data processing, predictive analytics, computer vision, deep learning systems, smart sensing technologies, and decision-support platforms. By combining methodological advances with application-oriented research, the book provides a balanced perspective on both the scientific and practical aspects of intelligent systems.This book is intended for researchers, academics, graduate students, engineers, and industry practitioners interested in artificial intelligence and smart environments. It serves as a valuable reference for those working in interdisciplinary domains where intelligent technologies are applied to improve system performance, automation, and digital services.

This book provides a comprehensive collection of recent research addressing practical and emerging challenges in intelligent technologies and smart environments. It highlights innovative methods, real-world applications, and interdisciplinary solutions that support the development of intelligent systems capable of improving efficiency, sustainability, and decision-making in modern digital ecosystems.This book brings together contributions that explore advanced approaches in artificial intelligence, data analytics, machine learning, Internet of Things (IoT), smart cities, cybersecurity, and intelligent automation. By presenting both theoretical developments and applied research, this book offers insights into how intelligent technologies can be designed, optimized, and deployed to solve complex problems in areas such as transportation, healthcare, energy management, environmental monitoring, and urban infrastructure.A distinctive aspect of this work is its focus on integrating artificial intelligence techniques with smart environment applications, emphasizing scalable, data-driven, and human-centered solutions. This book highlights novel algorithms, hybrid models, and intelligent architectures that address issues related to efficiency, sustainability, and digital transformation. This book also presents case studies and experimental frameworks that demonstrate the practical impact of these technologies in real-world scenarios.This book has a broad scope covering topics such as intelligent data processing, predictive analytics, computer vision, deep learning systems, smart sensing technologies, and decision-support platforms. By combining methodological advances with application-oriented research, the book provides a balanced perspective on both the scientific and practical aspects of intelligent systems.This book is intended for researchers, academics, graduate students, engineers, and industry practitioners interested in artificial intelligence and smart environments. It serves as a valuable reference for those working in interdisciplinary domains where intelligent technologies are applied to improve system performance, automation, and digital services.