Mohamed Lahby – författare

Thanks to rapid technological developments in terms of Computational Intelligence, smart tools have been playing active roles in daily life. It is clear that the 21st century has brought about many advantages in using high-level computation and communication solutions to deal with real-world problems; however, more technologies bring more changes to society. In this sense, the concept of smart cities has been a widely discussed topic in terms of society and Artificial Intelligence-oriented research efforts. The rise of smart cities is a transformation of both community and technology use habits, and there are many different research orientations to shape a better future.The objective of this book is to focus on Explainable Artificial Intelligence (XAI) in smart city development. As recently designed, advanced smart systems require intense use of complex computational solutions (i.e., Deep Learning, Big Data, IoT architectures), the mechanisms of these systems become ‘black-box’ to users. As this means that there is no clear clue about what is going on within these systems, anxieties regarding ensuring trustworthy tools also rise. In recent years, attempts have been made to solve this issue with the additional use of XAI methods to improve transparency levels. This book provides a timely, global reference source about cutting-edge research efforts to ensure the XAI factor in smart city-oriented developments. The book includes both positive and negative outcomes, as well as future insights and the societal and technical aspects of XAI-based smart city research efforts. This book contains nineteen contributions beginning with a presentation of the background of XAI techniques and sustainable smart-city applications. It then continues with chapters discussing XAI for Smart Healthcare, Smart Education, Smart Transportation, Smart Environment, Smart Urbanization and Governance, and Cyber Security for Smart Cities.

Thanks to rapid technological developments in terms of Computational Intelligence, smart tools have been playing active roles in daily life. It is clear that the 21st century has brought about many advantages in using high-level computation and communication solutions to deal with real-world problems; however, more technologies bring more changes to society. In this sense, the concept of smart cities has been a widely discussed topic in terms of society and Artificial Intelligence-oriented research efforts. The rise of smart cities is a transformation of both community and technology use habits, and there are many different research orientations to shape a better future.The objective of this book is to focus on Explainable Artificial Intelligence (XAI) in smart city development. As recently designed, advanced smart systems require intense use of complex computational solutions (i.e., Deep Learning, Big Data, IoT architectures), the mechanisms of these systems become ‘black-box’ to users. As this means that there is no clear clue about what is going on within these systems, anxieties regarding ensuring trustworthy tools also rise. In recent years, attempts have been made to solve this issue with the additional use of XAI methods to improve transparency levels. This book provides a timely, global reference source about cutting-edge research efforts to ensure the XAI factor in smart city-oriented developments. The book includes both positive and negative outcomes, as well as future insights and the societal and technical aspects of XAI-based smart city research efforts. This book contains nineteen contributions beginning with a presentation of the background of XAI techniques and sustainable smart-city applications. It then continues with chapters discussing XAI for Smart Healthcare, Smart Education, Smart Transportation, Smart Environment, Smart Urbanization and Governance, and Cyber Security for Smart Cities.

Rapid advancements in mobile computing and communication technology and recent technological progress have opened up a plethora of opportunities. These advancements have expanded knowledge, facilitated global business, enhanced collaboration, and connected people through various digital media platforms. While these virtual platforms have provided new avenues for communication and self-expression, they also pose significant threats to our privacy. As a result, we must remain vigilant against the propagation of electronic violence through social networks. Cyberbullying has emerged as a particularly concerning form of online harassment and bullying, with instances of racism, terrorism, and various types of trolling becoming increasingly prevalent worldwide.Addressing the issue of cyberbullying to find effective solutions is a challenge for the web mining community, particularly within the realm of social media. In this context, artificial intelligence (AI) can serve as a valuable tool in combating the diverse manifestations of cyberbullying on the Internet and social networks. This book presents the latest cutting-edge research, theoretical methods, and novel applications in AI techniques to combat cyberbullying. Discussing new models, practical solutions, and technological advances related to detecting and analyzing cyberbullying is based on AI models and other related techniques. Furthermore, the book helps readers understand AI techniques to combat cyberbullying systematically and forthrightly, as well as future insights and the societal and technical aspects of natural language processing (NLP)-based cyberbullying research efforts.Key Features:Proposes new models, practical solutions and technological advances related to machine intelligence techniques for detecting cyberbullying across multiple social media platforms.Combines both theory and practice so that readers (beginners or experts) of this book can find both a description of the concepts and context related to the machine intelligence.Includes many case studies and applications of machine intelligence for combating cyberbullying.

Rapid advancements in mobile computing and communication technology and recent technological progress have opened up a plethora of opportunities. These advancements have expanded knowledge, facilitated global business, enhanced collaboration, and connected people through various digital media platforms. While these virtual platforms have provided new avenues for communication and self-expression, they also pose significant threats to our privacy. As a result, we must remain vigilant against the propagation of electronic violence through social networks. Cyberbullying has emerged as a particularly concerning form of online harassment and bullying, with instances of racism, terrorism, and various types of trolling becoming increasingly prevalent worldwide.Addressing the issue of cyberbullying to find effective solutions is a challenge for the web mining community, particularly within the realm of social media. In this context, artificial intelligence (AI) can serve as a valuable tool in combating the diverse manifestations of cyberbullying on the Internet and social networks. This book presents the latest cutting-edge research, theoretical methods, and novel applications in AI techniques to combat cyberbullying. Discussing new models, practical solutions, and technological advances related to detecting and analyzing cyberbullying is based on AI models and other related techniques. Furthermore, the book helps readers understand AI techniques to combat cyberbullying systematically and forthrightly, as well as future insights and the societal and technical aspects of natural language processing (NLP)-based cyberbullying research efforts.Key Features:Proposes new models, practical solutions and technological advances related to machine intelligence techniques for detecting cyberbullying across multiple social media platforms.Combines both theory and practice so that readers (beginners or experts) of this book can find both a description of the concepts and context related to the machine intelligence.Includes many case studies and applications of machine intelligence for combating cyberbullying.

Recently, there has been a significant increase in the development and interest in applying generative AI across various domains, including education. The emergence of large language models (LLMs), such as the ChatGPT tool, fueled by advancements in generative AI, is profoundly reshaping education. The use of the ChatGPT tool offers personalized support, improves accessibility, and introduces innovative methods for students and educators to engage with information and learning materials. Furthermore, ChatGPT facilitates a wide range of language learning services, including language instruction, speech recognition, pronunciation feedback, and immersive virtual simulations for hands-on learning experiences.This book explores the transformative potential of the ChatGPT tool within education, shedding light on the opportunities that arise through the integration of the ChatGPT tool into various aspects of the learning process. It serves as a platform for the community to share cutting-edge research ideas concerning the use of the ChatGPT tool in digital education. Readers will discover how the ChatGPT tool can enhance student engagement, foster personalized learning experiences, facilitate intelligent tutoring systems, support virtual classroom interactions, and revolutionize assessment and feedback mechanisms.

Generative AI for Cybersecurity and Privacy offers a groundbreaking exploration of how generative artificial intelligence is reshaping the landscape of cybersecurity and privacy protection in an era of rapid digital transformation. As cyber threats grow in sophistication and scale, this book provides a timely and authoritative guide to harnessing generative AI to safeguard digital ecosystems, secure sensitive data, and address emerging challenges across diverse domains.Spanning a series of expertly curated chapters, this volume delves into cutting-edge advancements and practical applications of generative AI in cybersecurity. It covers critical areas such as AI-driven threat detection and response, privacy-preserving AI models, secure IoT and cloud computing frameworks, and robust defenses for cyber-physical systems, including Smart Cities and wireless networks. The book balances rigorous theoretical foundations with real-world case studies, making it an essential resource for researchers, security professionals, policymakers, and organizational leaders.The book offers comprehensive coverage of key topics, including:• Leveraging generative AI for proactive threat detection, risk analysis, and automated incident response• Innovative approaches to data privacy, compliance, and governance in AI-driven systems• Advanced methodologies for securing IoT, mobile applications, and cloud infrastructures• Practical frameworks for integrating generative AI into cybersecurity strategies for critical infrastructures• Emerging applications of generative AI in personalized, secure digital experiences, such as e-commerce and smart systemsAuthored by a global team of leading researchers and practitioners, this book stands out by not only addressing current cybersecurity and privacy challenges but also proposing forward-thinking, scalable solutions powered by generative AI. Unlike traditional resources, it emphasizes the transformative potential of AI in revolutionizing risk analysis, threat mitigation, and privacy preservation across multiple domains. Whether you’re navigating the complexities of IoT, cloud security, or emerging cyber threats, Generative AI for Cybersecurity and Privacy equips you with the knowledge and tools to build intelligent, secure, and future-ready strategies for a dynamic digital world.

The rapid advancement of Generative AI (GenAI) is revolutionizing and transforming a wide range of fields, with a notable impact on digital media and information dissemination. Digital platforms, including social media networks, have already grappled with the widespread proliferation of fake news at an increasing intensity are now facing an even bigger threat from machine-generated and machine-boosted fake news. With the increasing growth and sophistication of GenAI models for malicious ends, fake news is spreading rapidly, finding a fertile ground in digital media for largely unchecked dissemination of incorrect and misleading information. The scalability and diversity of current and emerging GenAI techniques present both opportunities and challenges in the field of fake news. On one hand, the ability to create highly realistic and persuasive content in large quantities with minimal effort, in real-time, makes GenAI a potent tool for spreading fake news and misinformation. On the other hand, those same capabilities can be harnessed to employ GenAI models to detect fake news and therefore hinder the spread. In this context, this book examines how GenAI techniques are contributing to combat fake news in digital media. A particular major challenge in combating fake news with GenAI is the explainability of the models: why a specific piece of news is determined to be fake or genuine. Tracing the origins of a specific piece of generated content—whether it stems from accurate or misleading data—requires extracting, interpreting, and representing in a legible manner vast parameter spaces and training data sources. This complexity of GenAI explainability makes it difficult to hold creators of fake news accountable and to ensure transparency in the content creation process. In this book, the authors focus on the positive potential of Generative AI and provide an overview of how it can be leveraged to combat fake news across diverse digital media platforms.The book is structured around the following key topics:• An overview of Generative AI and its relationship with fake news• How Generative AI can be utilized to fight the spread of fake news• Ensuring that the news we encounter on digital media platforms are not misleading or false• Methods for verifying the authenticity of news sources and tracing the origins of information to ensure its credibility• Practical insights into technological advancements and solutions related to the detection and analysis of fake news.Finally, this book serves as a platform for the community to share innovative research on the use of Generative AI in detecting and mitigating the impact of false information across digital platforms. Readers will explore how Generative AI can revolutionize fact-checking, automate the identification of misleading content, and provide adaptive solutions to prevent the spread of fake news.

We are pleased to present the proceedings of the International Conference on Advanced Data Analytics and Computing (ICADAC) 2025, a premier platform that brings together researchers, scholars, and industry professionals to share their latest findings, technological advancements, and practical applications in the field of data analytics and intelligent computing. ICADAC 2025 has received a remarkable number of high-quality submissions from across the globe, reflecting the growing interest and ongoing innovation in this dynamic domain. After a rigorous peer-review process by our esteemed technical committee, a curated selection of papers has been included in this volume. These contributions span various topics, including machine learning, artificial intelligence, big data processing, cloud computing, Internet of Things (IoT), cybersecurity, and their applications across various sectors including but not limited to Mechanical Engineering, Civil Engineering, Electrical Engineering, Electronics and Communications Engineering, Computer Science Engineering, Information Technology and other interdisciplinary areas

We are pleased to present the proceedings of the International Conference on Advanced Data Analytics and Computing (ICADAC) 2025, a premier platform that brings together researchers, scholars, and industry professionals to share their latest findings, technological advancements, and practical applications in the field of data analytics and intelligent computing. ICADAC 2025 has received a remarkable number of high-quality submissions from across the globe, reflecting the growing interest and ongoing innovation in this dynamic domain. After a rigorous peer-review process by our esteemed technical committee, a curated selection of papers has been included in this volume. These contributions span various topics, including machine learning, artificial intelligence, big data processing, cloud computing, Internet of Things (IoT), cybersecurity, and their applications across various sectors including but not limited to Mechanical Engineering, Civil Engineering, Electrical Engineering, Electronics and Communications Engineering, Computer Science Engineering, Information Technology and other interdisciplinary areas

This book presents the latest cutting-edge research, theoretical methods, and novel applications in the field of computational intelligence techniques and methods for combating fake news. Fake news is everywhere. Despite the efforts of major social network players such as Facebook and Twitter to fight disinformation, miracle cures and conspiracy theories continue to rain down on the net. Artificial intelligence can be a bulwark against the diversity of fake news on the Internet and social networks.This book discusses new models, practical solutions, and technological advances related to detecting and analyzing fake news based on computational intelligence models and techniques, to help decision-makers, managers, professionals, and researchers design new paradigms considering the unique opportunities associated with computational intelligence techniques. Further, the book helps readers understand computational intelligence techniques combating fake news in a systematic and straightforward way.

This book presents the latest cutting-edge research, theoretical methods, and novel applications in the field of computational intelligence techniques and methods for combating fake news. Fake news is everywhere. Despite the efforts of major social network players such as Facebook and Twitter to fight disinformation, miracle cures and conspiracy theories continue to rain down on the net. Artificial intelligence can be a bulwark against the diversity of fake news on the Internet and social networks.This book discusses new models, practical solutions, and technological advances related to detecting and analyzing fake news based on computational intelligence models and techniques, to help decision-makers, managers, professionals, and researchers design new paradigms considering the unique opportunities associated with computational intelligence techniques. Further, the book helps readers understand computational intelligence techniques combating fake news in a systematic and straightforward way.

This book contains high-quality and original research on computational intelligence for green smart cities research.

This book contains high-quality and original research on computational intelligence for green smart cities research.

This book emphasizes the need to analyze all the information through studies and research carried out in the field of computational intelligence, communication networks, and presents the best solutions to combat COVID and other pandemics.

This book emphasizes the need to analyze all the information through studies and research carried out in the field of computational intelligence, communication networks, and presents the best solutions to combat COVID and other pandemics.

The contributions in this carefully curated volume, present cutting-edge research in applied mathematical modeling for combating COVID-19 and other potential pandemics. Mathematical modeling and intelligent control have emerged as powerful computational models and have shown significant success in combating any pandemic. These models can be used to understand how COVID-19 or other pandemics can spread, analyze data on the incidence of infectious diseases, and predict possible future scenarios concerning pandemics. This book also discusses new models, practical solutions, and technological advances related to detecting and analyzing COVID-19 and other pandemics based on intelligent control systems that assist decision-makers, managers, professionals, and researchers. Much of the book focuses on preparing the scientific community for the next pandemic, particularly the application of mathematical modeling and intelligent control for combating the Monkeypox virus and Langya Henipavirus.

The contributions in this carefully curated volume, present cutting-edge research in applied mathematical modeling for combating COVID-19 and other potential pandemics. Mathematical modeling and intelligent control have emerged as powerful computational models and have shown significant success in combating any pandemic.

This book discusses the potential of the Internet of Unmanned Things (IoUT), which is considered a promising paradigm resulting in numerous applications including shipment of goods, home package delivery, crop monitoring, agricultural surveillance, and rescue operations. The authors discuss how IoUT nodes collaborate with each other in ad hoc manner through a Line-of-Sight (LoS) link to exchange data packets. Also discussed is how Unmanned Arial Vehicles (UAVs) can communicate with fixed ground stations, with an air traffic controller, or through a Non-Line-of-Sight (NLoS) link with a satellite-aided controller, generally based on preloaded missions. The authors go on to cover how to tackle issues that arise with dissimilar communication technologies. They cover how various problems can appear in inter-UAV and UAV-to-X communications including energy management, lack of security and the unreliability of wireless communication links, and handover from LoS to NLoS, and vice versa. In this book, the editors invited front-line researchers and authors to submit research exploring emerging technologies for IoUT and mission-based networking and how to overcome challenges.

This book discusses the potential of the Internet of Unmanned Things (IoUT), which is considered a promising paradigm resulting in numerous applications including shipment of goods, home package delivery, crop monitoring, agricultural surveillance, and rescue operations.

This book explores the transformative impact of generative artificial intelligence (GenAI) on teaching and learning, examining how recent advancements in GenAI are revolutionizing educational practices across disciplines.

This book explores the transformative impact of generative artificial intelligence (GenAI) on teaching and learning, examining how recent advancements in GenAI are revolutionizing educational practices across disciplines. The book is organized into three parts: an overview of GenAI in education, its application in diverse educational contexts, and future perspectives on how educators and GenAI can interface.The first part addresses the pressing concerns within the educational landscape, both the bridges GenAI allows us to build and the remaining as well as the emerging gaps. The middle part explores specific academic disciplines, such as history, sports medicine, mathematics, engineering, and the humanities, dissecting the influence of GenAI on each. The final part looks ahead, discussing the ethical implications, the evolving role of prompting, and innovative frameworks for personalized learning.By presenting a balanced view of the opportunities that are now within reach through GenAI and the challenges such leaps pose to the way we learn and teach, this book allows interested educators to learn from the early-adopting contributors to fruitfully and responsibly integrate such technologies into their pedagogical practices. It serves as a resource for anyone interested in the future of educational practices and research of education, offering insights that can spark further exploration and discussion within the academic community and educational policy makers.

This book explores the transformative role of Generative Artificial Intelligence (GenAI) in reshaping educational assessment in higher education. Through theoretical insights, practical applications, and ethical reflections, the book examines how emerging GenAI tools such as ChatGPT, DeepSeek, Gemini, and LLaMA are revolutionizing assessment practices. It focuses on the use of personalized, adaptive assessment strategies, automated feedback, and data-driven evaluation methods that are redefining how students learn and are evaluated across global contexts.The book is structured into three parts. The first part offers a foundational overview of GenAI in assessment, addressing its ethical, sociological, and security implications. The second part highlights how GenAI supports personalized learning, showcasing innovative tools like adaptive feedback systems and AI-powered tutoring environments. The final part presents case studies and practical applications from various countries all focused on assessments and Generative AI. These chapters collectively serve as a valuable resource for educators, researchers, and policymakers aiming to harness the power of Generative AI to improve educational assessment in a responsible and effective way.

This book examines the transformative potential of Generative Artificial Intelligence (GenAI) in addressing one of the most urgent global challenges: sustainable water management. It investigates how GenAI provides innovative tools for predicting water demand, optimizing resource allocation, and reducing the impacts of climate change. The book includes state-of-the-art contributions from experts in GenAI, optimization techniques, and water management, offering a comprehensive and interdisciplinary approach to the subject. The book explores key concepts, including the integration of advanced algorithms with real-world case studies, bridging the gap between cutting-edge technological innovation and practical water management strategies. The chapters delve into topics like government policy impacts, optimization techniques for pollution control, and AI-powered predictive models for aquaculture. This book is a must-read for those seeking to understand the role of GenAI in creating a smart and resilient future for water management. Essential for researchers, policymakers, and professionals in environmental science, agriculture, and sustainability, this book provides valuable knowledge and innovative approaches to addressing global water challenges

This book provides a comprehensive exploration of current theoretical research at the intersection of green technologies, computational intelligence, and sustainable systems design. This book delves into foundational insights, formal models, algorithmic developments, and simulation-based methodologies crucial for understanding intelligent, energy-efficient infrastructures. It covers advances in renewable energy modeling, artificial intelligence for green Internet of Things (IoT), green communication systems, and mathematical modeling within sustainability-driven frameworks. With a computational and systems-oriented perspective, contributors offer detailed examinations of principles enabling next-generation green technology design. Aimed at researchers, academics, and graduate students, this book provides deep insights into theoretical foundations and computational methodologies driving innovation in green and sustainable technologies.

This second volume in the Green Technologies and Sustainable Intelligence series focuses on practical implementations, case studies, and emerging challenges in the application of sustainable and intelligent systems. Featuring real-world examples across sectors such as smart cities, renewable energy systems, sustainable agriculture, eco-efficient industries, and environmental monitoring, this book demonstrates how cutting-edge technologies can be harnessed to address urgent environmental and societal needs.Emphasizing the transformative role of artificial intelligence (AI), machine learning (ML), and generative AI, the book explores their use in optimizing decision-making, automating environmental assessments, simulating complex systems, and designing smart, energy-efficient infrastructures aligned with sustainable development goals.In addition to concrete use cases, the book provides critical insight into future challenges—including integration, interoperability, and the socio-ethical dimensions of AI-driven green technologies. It also addresses cross-disciplinary methodologies, policy implications, and long-term strategies for climate adaptation and resource-efficient development.Designed as a key resource for researchers, engineers, practitioners, policymakers, and technology consultants, this book offers actionable knowledge for advancing digital governance, sustainable innovation, and intelligent environmental systems.