Fadi Al-Turjman – författare

Drones in Smart-Cities: Security and Performance is the first book dedicated to drones in smart cities, helping address the many research challenges in bringing UAVs into practice. The book incorporates insights from the latest research in Internet of Things, big data, and cloud computing, 5G, and other communication technologies. It examines the design and implementation of UAV, focusing on data delivery, performability, and security. Intended for researchers, engineers, and practitioners, Drones in Smart-Cities: Security and Performance combines the technical aspects with academic theory to help implement the smart city vision around the globe.

Addresses UAV and IoT for smart cities applications Examines topics as UAV safety, challenges, localization methods. QoS, simulation tools, and more Collect the relevant knowledge in one resource, saving research time and effort

Security in IoT Social Networks takes a deep dive into security threats and risks, focusing on real-world social and financial effects. Mining and analyzing enormously vast networks is a vital part of exploiting Big Data. This book provides insight into the technological aspects of modeling, searching, and mining for corresponding research issues, as well as designing and analyzing models for resolving such challenges. The book will help start-ups grow, providing research directions concerning security mechanisms and protocols for social information networks. The book covers structural analysis of large social information networks, elucidating models and algorithms and their fundamental properties.

Moreover, this book includes smart solutions based on artificial intelligence, machine learning, and deep learning for enhancing the performance of social information network security protocols and models. This book is a detailed reference for academicians, professionals, and young researchers. The wide range of topics provides extensive information and data for future research challenges in present-day social information networks.

Provides several characteristics of social, network, and physical security associated with social information networks Presents the security mechanisms and events related to social information networks Covers emerging topics, such as network information structures like on-line social networks, heterogeneous and homogeneous information networks, and modern information networks Includes smart solutions based on artificial intelligence, machine learning, and deep learning for enhancing the performance of social information network security protocols and models

Sustainable Networks in Smart Grid presents global challenges in smart metering with renewable energy resources, micro-grid design, communication technologies, big data, privacy and security in the smart grid. Providing an overview of different available PLC technologies and configurations and their applications in different sectors, this book provides case studies and practical implementation details of smart grid technology, paying special attention to Advanced Metering Infrastructure (AMI) scenarios with the presence of Distribution Grid (DG) and Electric Vehicles (EV).

Covering regulatory policies for energy storage, management strategies for microgrid operation, and key performance indicators for smart grid development, this reference compiles up-to-date information on different aspects of the Internet of Smart Metering. In addition, innovative contributions on Data Analytics, Energy Theft Detection, Data-Driven Framework, Blockchain-IoT-enabled Sensor Networks, and Smart Contacts in the Blockchain are also included.

Includes case studies and practical implementation examples of different smart grid applications, their benefits, characteristics and requirements Provides a SWOT analysis of the impact of recent regulatory changes on the business case for energy storage (ES) Presents a comprehensive survey of privacy-preserving schemes for smart grid communications

XAI Based Intelligent Systems for Society 5.0 focuses on the development and analysis of Explainable Artificial Intelligence (XAI)-based models and intelligent systems that can be utilized for Society 5.0-characterized by a knowledge intensive, data driven, and non-monetary society. The book delves into the issues of transparency, explainability, data fusion, and interpretability, which are significant for the development of a super smart society and are addressed through XAI-based models and techniques. XAI-based deep learning models, fuzzy and hybrid intelligent systems, expert systems, and intrinsic explainable models in the context of Society 5.0 are presented in detail.The book also addresses-using XAI-based intelligent techniques-the privacy issues intrinsic in storing huge amounts of data or information in virtual space. The concept of Responsible AI, which is at the core of the future direction of XAI for Society 5.0, is also explored in this book. Finally, the application areas of XAI, including relevant case studies, are presented in the concluding chapter. This book serves as a valuable resource for graduate/post graduate students, academicians, analysts, computer scientists, engineers, researchers, professionals, and other personnel working in the area of artificial intelligence, machine learning, and intelligent systems, who are interested in creating a people-centric smart society.Defines the basic terminology and concepts surrounding explainability and related topics to bring coherence to the fieldFocuses on what techniques are available to improve explainability and how explainability can progress societyOffers a broad range of topics, addressing multiple facets of XAI within the context of Society 5.0

Security and smart spaces are among the most significant topics in IoT nowadays. The implementation of secured smart spaces is at the heart of this concept, and its development is a key issue in the next generation IoT. This book addresses major security aspects and challenges in realizing smart spaces and sensing platforms in critical Cloud and IoT applications. The book focuses on both the design and implementation aspects of security models and strategies in smart that are enabled by wireless sensor networks and RFID systems. It mainly examines seamless data access approaches and encryption and decryption aspects in reliable IoT systems.

The Internet of Nano-Things (IoNT) is a system of nano-connected devices, objects, or organisms that have unique identifiers to transfer data over a computer or cellular network wirelessly to the Cloud. Data delivery, caching, and energy consumption are among the most significant topics in the IoNT nowadays. The book addresses data routing and energy consumption challenges and proposes nano-sensing platforms in critical Wireless Body Area Networks (WBAN). This book covers both design and implementation aspects of data delivery models and strategies in a smart application enabled by the WBAN. It focuses on smart data delivery approaches and energy savings aspects in a reliable IoNT systems.

The Internet of Things (IoT) is a system of inter-connected devices, objects, and organisms. Among these devices, drones are gaining lots of interest. Drones are expected to communicate with cellular networks in the next generation networks (5G and beyond) which opens the door for another exciting research area. This book considers very important research areas in drone and cellular networks. It addresses major issues and challenges in drone-based solutions proposed for IoT-enabled cellular/computer networks, routing/communication protocols, surveillances applications, secured data management, and positioning approaches. It focuses mainly on smart and context-aware implementations.

The Cloud in IoT-enabled Spaces addresses major issues and challenges in IoT-based solutions proposed for the Cloud. It paves the way for IoT-enabled spaces in the next generation cloud computing paradigm and opens the door for further innovative ideas. Topics include Cloud-based optimization in the IoT era, scheduling and routing, medium access, data caching, secure access, uncertainty, home automation, machine learning in wearable devices, energy monitoring, and plant phenotyping in farming. Smart spaces are solutions where Internet of Things (IoT)-enabling technologies have been employed towards further advances in the lifestyle. It tightly integrates with the existing Cloud infrastructure to impact several fields in academia and industry.The Cloud in IoT-enabled Spaces provides an overview of the issues around small spaces and proposes the most up-to-date alternatives and solutions. The objective is to pave the way for IoT-enabled spaces in the next-generation Cloud computing and open the door for further innovative ideas.

Internet of Things (IoT)-enabled spaces have made revolutionary advances in the utility grid. Among these advances, intelligent and energy-efficient services are gaining considerable interest. The use of the smart grid is increasing day after day around us and is not only used in saving energy but also in our daily life for intelligent health, traffic, and even farming systems. The grid enabled with IoT features is also expected to communicate with cellular networks smoothly in the next-generation networks (6G and beyond). This will open the door for other interesting research areas. In this book, we consider the most significant and emergent research topics in this domain, addressing major issues and challenges in IoT-based solutions proposed for the smart grid. The chapters provide insight on comprehensive topics in IoT-based smart grids, combining technical aspects with the most up-to-date theory. It investigates the grid under varying and potential emerging paradigms such as edge/fog computing, in addition to big data aspects considerations in the IoT era. With comprehensive surveys and case studies, this book explores basic and high-level grid aspects in the emerging smart city paradigm, which makes it especially attractive to researchers, academics, and higher-level students. This authored book can be used by computer science undergraduate and postgraduate students, researchers and practitioners, city administrators, policymakers, and government regulators.

Internet of Things (IoT)-enabled spaces have made revolutionary advances in the utility grid. Among these advances, intelligent and energy-efficient services are gaining considerable interest. The use of the smart grid is increasing day after day around us and is not only used in saving energy but also in our daily life for intelligent health, traffic, and even farming systems. The grid enabled with IoT features is also expected to communicate with cellular networks smoothly in the next-generation networks (6G and beyond). This will open the door for other interesting research areas. In this book, we consider the most significant and emergent research topics in this domain, addressing major issues and challenges in IoT-based solutions proposed for the smart grid. The chapters provide insight on comprehensive topics in IoT-based smart grids, combining technical aspects with the most up-to-date theory. It investigates the grid under varying and potential emerging paradigms such as edge/fog computing, in addition to big data aspects considerations in the IoT era. With comprehensive surveys and case studies, this book explores basic and high-level grid aspects in the emerging smart city paradigm, which makes it especially attractive to researchers, academics, and higher-level students. This authored book can be used by computer science undergraduate and postgraduate students, researchers and practitioners, city administrators, policymakers, and government regulators.

The Internet of Things (IoT) has made revolutionary advances in the utility grid as we know it. Among these advances, intelligent medical services are gaining much interest. The use of Artificial Intelligence (AI) is increasing day after day in fighting one of the most significant viruses, COVID-19. The purpose of this book is to present the detailed recent exploration of AI and IoT in the COVID-19 pandemic and similar applications. The integrated AI and IoT paradigm is widely used in most medical applications, as well as in sectors that deal with transacting data every day. This book can be used by computer science undergraduate and postgraduate students; researchers and practitioners; and city administrators, policy makers, and government regulators. It presents a smart and up-to-date model for COVID-19 and similar applications. Novel architectural and medical use cases in the smart city project are the core aspects of this book. The wide variety of topics it presents offers readers multiple perspectives on a variety of disciplines. Prof. Dr. Fadi Al-Turjman received his PhD in computer science from Queen’s University, Kingston, Ontario, Canada, in 2011. He is a full professor and research center director at Near East University, Nicosia, Cyprus.

This book provides a comprehensive overview for the use of femtocells in smart Internet of Things (IoT) environments. Femtocells will help mobile operators to provide a basis for the next generation of services which are a combination of voice, video, and data services to mobile users. This book discusses modelling traffic and deployment strategies in femtocells and provides a review for the use of femtocells and their applications in IoT environments. Moreover, it highlights the efficient real-time medium access, data delivery, caching and security aspects in smart spaces. It concludes by presenting open research issues associated with smart IoT-femtocell based applications.

This book gives an overview of best effort data and real-time multipath routing protocols in WMSN. It provides results of recent research in design issues affecting the development of strategic multipath routing protocols that support multimedia data traffic in WMSN from an IoT perspective, plus detailed analysis on the appropriate traffic models.

Wireless Sensor Networks overcome the difficulties of other monitoring systems. However, they require further efficiencies for Outdoor Environment Monitoring (OEM) applications due to their harsh operational conditions, huge targeted areas, limited energy budget, and required 3D setups. A fundamental issue in defeating these practical challenges is deployment planning. The deployment plan is a key factor of many intrinsic properties of OEM networks, summarized in connectivity, lifetime, fault-tolerance, and cost-effectiveness. This book investigates the problem of WSNs deployments that address these properties in order to overcome the unique challenges and circumstances in OEM applications.

This book presents the Cognitive Information Centric Sensor Network (CICSN) framework for the IoT. This framework is built on top of cognitive nodes, capable of knowledge representation, learning, and reasoning, along with an information-centric approach for data delivery. It also discusses the most appropriate deployment strategy for these cognitive nodes under realistic assumptions that cares about the Quality of Information (QoI). In addition, it uses a QoI aware data delivery strategy, with Analytic Hierarchy Process (AHP) as the reasoning technique to identify data delivery paths that dynamically adapt to changing network conditions and user requirements.

Security and smart spaces are among the most significant topics in IoT nowadays. The implementation of secured smart spaces is at the heart of this concept, and its development is a key issue in the next generation IoT. This book addresses major security aspects and challenges in realizing smart spaces and sensing platforms in critical Cloud and IoT applications. The book focuses on both the design and implementation aspects of security models and strategies in smart that are enabled by wireless sensor networks and RFID systems. It mainly examines seamless data access approaches and encryption and decryption aspects in reliable IoT systems.

Smart Cities and intelligence are among the most significant topics in IoT. Intelligence in communication and infrastructure implementation is at the heart of this concept, and its development is a key issue in smart cities. This book addresses the challenges in realizing intelligence in smart cities and sensing platforms in the era of cloud computing and IoT, varying from cost and energy efficiency to availability and service quality. It focuses on both the design and implementation aspects of artificial intelligence approaches in smart cities and sensing applications that are enabled and supported by IoT paradigms, and mainly on data delivery approaches and their performability aspects.

The Internet of Things (IoT) has made revolutionary advances in the utility grid as we know it. Among these advances, intelligent medical services are gaining much interest. The use of Artificial Intelligence (AI) is increasing day after day in fighting one of the most significant viruses, COVID-19. The purpose of this book is to present the detailed recent exploration of AI and IoT in the COVID-19 pandemic and similar applications. The integrated AI and IoT paradigm is widely used in most medical applications, as well as in sectors that deal with transacting data every day. This book can be used by computer science undergraduate and postgraduate students; researchers and practitioners; and city administrators, policy makers, and government regulators. It presents a smart and up-to-date model for COVID-19 and similar applications. Novel architectural and medical use cases in the smart city project are the core aspects of this book. The wide variety of topics it presents offers readers multiple perspectives on a variety of disciplines. Prof. Dr. Fadi Al-Turjman received his PhD in computer science from Queen’s University, Kingston, Ontario, Canada, in 2011. He is a full professor and research center director at Near East University, Nicosia, Cyprus.

Computational Intelligence and Blockchain in Complex Systems: System Security and Interdisciplinary Applications provides readers with a guide to understanding the dynamics of AI, machine learning, and computational intelligence in blockchain, and how these rapidly developing technologies are revolutionizing a variety of interdisciplinary research fields and applications. This book examines the role of computational intelligence and machine learning in the development of algorithms to deploy blockchain technology across a number of applications, including healthcare, insurance, smart grid, smart contracts, digital currency, precision agriculture, and supply chain. The authors cover the unique and developing intersection between cyber security and blockchain in modern networks, as well as in-depth studies on cybersecurity challenges and multidisciplinary methods in modern blockchain networks. Readers will find mathematical equations throughout the book as part of the underlying concepts and foundational methods, especially the complex algorithms involved in blockchain security aspects for hashing, coding, and decoding. This book also provides readers with the most in-depth technical guide to the intersection of computational intelligence and blockchain, two of the most important technologies for the development of next-generation complex systemsCovers the research issues and concepts of machine learning technology in blockchainProvides in-depth information about handling and managing personal data by machine learning methods in blockchainHelps readers understand the links between computational intelligence, blockchain, complex systems, and developing secure applications in multidisciplinary sectors

Artificial Intelligence of Things (AIoT): Current and Future Trends brings together researchers and developers from a wide range of domains to share ideas on how to implement technical advances, create application areas for intelligent systems, and how to develop new services and smart devices connected to the Internet. Section One covers AIoT in Everything, providing a wide range of applications for AIoT methods and technologies. Section Two gives readers comprehensive guidance on AIoT in Societal Research and Development, with practical case studies of how AIoT is impacting cultures around the world. Section Three covers the impact of AIoT in educational settings.The book also covers new capabilities such as pervasive sensing, multimedia sensing, machine learning, deep learning, and computing power. These new areas come with various requirements in terms of reliability, quality of service, and energy efficiency.Provides readers with up-to-date and comprehensive information on the latest advancements in AIoT, including wireless technologies, pervasive sensing, multimedia sensing, machine learning, deep learning, and computing powerExplores the possibilities of new domains, services, and business models that can be created using AIoTDiscusses the potential impact of AIoT on society, including its potential to improve efficiency, reduce costs, and enhance quality of life

Quaternion-Sparse Image Processing: Advances in Multispectral Processing brings together the technologies, research, and managerial applications of quaternion-sparse based complex algebra in image processing. The book covers the entire range of complicated tasks performed on color images, including denoising, reconstruction, classification, hallucination, feature extraction, dimension reduction, and regularization. It provides easy understanding and smooth adaptability of basic and advanced concepts for graduate students, researchers, doctors, academics, and practitioners.Uncovers the innovative features of complex algebra, specifically the quaternion-sparse concept in image processing and how it can help in improving the computational efficiency of image processingDeals with the most common quaternion convolution neural network, quaternion wavelet, and sparse representation-based techniques in multispectral image processingFocuses on how evolution in algebraic concepts, i.e., quaternion and sparse, help in improving accuracy and efficiency of various color image restoration, reconstruction, and recognitionIllustrates how important features are extracted and complete information is stored in extracted features to help and process tasks in an easy and computationally efficient way

Intelligent Control in Smart Energy Systems provides a clear and practical guide to the implementation of Artificial Intelligent (AI) techniques in modern, sustainable energy systems. Building from essential theory to advanced application processes, this book outlines the essential challenge of control for renewable and distributed energy sources and applies a range of AI solutions from deep learning, data-driven decision-making, advanced control, and optimization algorithms for smart grids. Case studies and latest results cover control across design, development, and operation of smart energy systems, touching on control in generation, distribution, and supply.Catering to newly interdisciplinary researchers as well as those with a basic understanding of AI technologies, this book supports higher-stage undergraduates, graduate students, researchers, and system engineers in implementing best practice control techniques for a sustainable energy grid.Incorporates a stepped approach, from basic theoretical principles to advanced application examplesIncludes case studies in a variety of scenarios, from a global perspective of experts, for maximum versatilityAdds to the cutting-edge series Advances in Intelligent Energy Systems, which provides the latest research and best practice for utilizing AI to enable sustainable energy systems

Wireless Sensor Networks overcome the difficulties of other monitoring systems. However, they require further efficiencies for Outdoor Environment Monitoring (OEM) applications due to their harsh operational conditions, huge targeted areas, limited energy budget, and required 3D setups. A fundamental issue in defeating these practical challenges is deployment planning. The deployment plan is a key factor of many intrinsic properties of OEM networks, summarized in connectivity, lifetime, fault-tolerance, and cost-effectiveness. This book investigates the problem of WSNs deployments that address these properties in order to overcome the unique challenges and circumstances in OEM applications.

This book gives an overview of best effort data and real-time multipath routing protocols in WMSN. It provides results of recent research in design issues affecting the development of strategic multipath routing protocols that support multimedia data traffic in WMSN from an IoT perspective, plus detailed analysis on the appropriate traffic models.

Cancer Prediction for Industrial IoT 4.0: A Machine Learning Perspective explores various cancers using Artificial Intelligence techniques. It presents the rapid advancement in the existing prediction models by applying Machine Learning techniques. Several applications of Machine Learning in different cancer prediction and treatment options are discussed, including specific ideas, tools and practices most applicable to product/service development and innovation opportunities. The wide variety of topics covered offers readers multiple perspectives on various disciplines.Features• Covers the fundamentals, history, reality and challenges of cancer• Presents concepts and analysis of different cancers in humans• Discusses Machine Learning-based deep learning and data mining concepts in the prediction of cancer• Offers real-world examples of cancer prediction • Reviews strategies and tools used in cancer prediction• Explores the future prospects in cancer prediction and treatmentReaders will learn the fundamental concepts and analysis of cancer prediction and treatment, including how to apply emerging technologies such as Machine Learning into practice to tackle challenges in domains/fields of cancer with real-world scenarios. Hands-on chapters contributed by academicians and other professionals from reputed organizations provide and describe frameworks, applications, best practices and case studies on emerging cancer treatment and predictions.This book will be a vital resource to graduate students, data scientists, Machine Learning researchers, medical professionals and analytics managers.

Cancer Prediction for Industrial IoT 4.0: A Machine Learning Perspective explores various cancers using Artificial Intelligence techniques. It presents the rapid advancement in the existing prediction models by applying Machine Learning techniques. Several applications of Machine Learning in different cancer prediction and treatment options are discussed, including specific ideas, tools and practices most applicable to product/service development and innovation opportunities. The wide variety of topics covered offers readers multiple perspectives on various disciplines.Features• Covers the fundamentals, history, reality and challenges of cancer• Presents concepts and analysis of different cancers in humans• Discusses Machine Learning-based deep learning and data mining concepts in the prediction of cancer• Offers real-world examples of cancer prediction • Reviews strategies and tools used in cancer prediction• Explores the future prospects in cancer prediction and treatmentReaders will learn the fundamental concepts and analysis of cancer prediction and treatment, including how to apply emerging technologies such as Machine Learning into practice to tackle challenges in domains/fields of cancer with real-world scenarios. Hands-on chapters contributed by academicians and other professionals from reputed organizations provide and describe frameworks, applications, best practices and case studies on emerging cancer treatment and predictions.This book will be a vital resource to graduate students, data scientists, Machine Learning researchers, medical professionals and analytics managers.

Artificial Intelligence of Health-Enabled Spaces (AIoH) has made a number of revolutionary advances in clinical studies that we are aware of. Among these advances, intelligent and medical services are gaining a great deal of interest. Nowadays, AI-powered technologies are not only used in saving lives, but also in our daily life activities in diagnosing, controlling, and even tracking of COVID-19 patients. These AI-powered solutions are expected to communicate with cellular networks smoothly in the next-generation networks (5G/6G and beyond) for more effective/critical medical applications. This will open the door for other interesting research areas. This book focuses on the development and analysis of artificial intelligence (AI) model applications across multiple disciplines. AI-based deep learning models, fuzzy and hybrid intelligent systems, and intrinsic explainable models are also presented in this book. Some of the fields considered in this smart health-oriented book include AI applications in electrical engineering, biomedical engineering, environmental engineering, computer engineering, education, cyber security, chemistry, pharmacy, molecular biology, and tourism.This book is dedicated to addressing the major challenges in fighting diseases and psychological issues using AI. These challenges vary from cost and complexity to availability and accuracy. The aim of this book is hence to focus on both the design and implementation aspects of AI-based approaches in the proposed health-related solutions.Targeted readers are from varying disciplines who are interested in implementing the smart planet/environments vision via intelligent enabling technologies.

Artificial Intelligence of Health-Enabled Spaces (AIoH) has made a number of revolutionary advances in clinical studies that we are aware of. Among these advances, intelligent and medical services are gaining a great deal of interest. Nowadays, AI-powered technologies are not only used in saving lives, but also in our daily life activities in diagnosing, controlling, and even tracking of COVID-19 patients. These AI-powered solutions are expected to communicate with cellular networks smoothly in the next-generation networks (5G/6G and beyond) for more effective/critical medical applications. This will open the door for other interesting research areas. This book focuses on the development and analysis of artificial intelligence (AI) model applications across multiple disciplines. AI-based deep learning models, fuzzy and hybrid intelligent systems, and intrinsic explainable models are also presented in this book. Some of the fields considered in this smart health-oriented book include AI applications in electrical engineering, biomedical engineering, environmental engineering, computer engineering, education, cyber security, chemistry, pharmacy, molecular biology, and tourism.This book is dedicated to addressing the major challenges in fighting diseases and psychological issues using AI. These challenges vary from cost and complexity to availability and accuracy. The aim of this book is hence to focus on both the design and implementation aspects of AI-based approaches in the proposed health-related solutions.Targeted readers are from varying disciplines who are interested in implementing the smart planet/environments vision via intelligent enabling technologies.

The Cloud in IoT-enabled Spaces addresses major issues and challenges in IoT-based solutions proposed for the Cloud. It paves the way for IoT-enabled spaces in the next generation cloud computing paradigm and opens the door for further innovative ideas. Topics include Cloud-based optimization in the IoT era, scheduling and routing, medium access, data caching, secure access, uncertainty, home automation, machine learning in wearable devices, energy monitoring, and plant phenotyping in farming. Smart spaces are solutions where Internet of Things (IoT)-enabling technologies have been employed towards further advances in the lifestyle. It tightly integrates with the existing Cloud infrastructure to impact several fields in academia and industry.The Cloud in IoT-enabled Spaces provides an overview of the issues around small spaces and proposes the most up-to-date alternatives and solutions. The objective is to pave the way for IoT-enabled spaces in the next-generation Cloud computing and open the door for further innovative ideas.