Sameena Naaz – författare

This book delves into the transformative potential of artificial intelligence (AI) and machine learning (ML) as game-changers in diagnosing and managing neurodisorder conditions. It covers a wide array of methodologies, algorithms, and applications in depth.Computational Intelligence Algorithms for the Diagnosis of Neurological Disorders equips readers with a comprehensive understanding of how computational intelligence empowers healthcare professionals in the fight against neurodisorders. Through practical examples and clear explanations, it explores the diverse applications of these technologies, showcasing their ability to analyze complex medical data, identify subtle patterns, and contribute to the development of more accurate and efficient diagnostic tools. The authors delve into the exciting possibilities of AI-powered algorithms, exploring their ability to analyze various data sources like neuroimaging scans, genetic information, and cognitive assessments. They also examine the realm of ML for pattern recognition, enabling the identification of early disease markers and facilitating timely intervention. Finally, the authors also address the critical challenges of data privacy and security, emphasizing the need for robust ethical frameworks to safeguard sensitive patient information.This book aims to spark a conversation and foster collaboration among researchers, clinicians, and technologists, and will assist radiologists and neurologists in making precise diagnoses with enhanced accuracy.

This book offers insights into how modern technologies are transforming agriculture with a focus on their effects in aiding sustainability. It explores the current applications of technologies such as AI, IoT, and machine learning, and their impact on improving crop yield, resource efficiency, and environmental impact. Through practical examples and case studies, it demonstrates how these technologies can address challenges in agriculture and enhance operational efficiency. Key Features:Analysis of how IoT devices and sensor networks are used for real-time monitoring of farm operations, soil conditions, and weather patterns.Studies emerging technologies like machine vision, predictive modelling, and natural language processing, for tasks such as crop monitoring and pest detection.Detailed discussion on machine learning algorithms, including supervised, unsupervised, and reinforcement learning, tailored for agricultural applications.Insights into how AI, IoT, and machine learning optimize resource use, improve crop yield and quality, and enhance sustainability.Case studies to highlight real-life examples from crop management to livestock and water conservation.Smart Agriculture for Sustainable Practices is for researchers, professionals, and policymakers interested in leveraging technology for sustainable agricultural practices.

This book explores the transformative role of Digital Twin technology in shaping next-generation smart cities and urban ecosystems. It provides a comprehensive overview of how digital twins—dynamic virtual representations of physical assets, systems, and environments—enable real-time monitoring, simulation, and data-driven decision-making in complex urban infrastructures. The book covers the foundational concepts of digital twins, their integration with enabling technologies such as Artificial Intelligence (AI), the Internet of Things (IoT), big data analytics, and cloud computing, and their practical applications across multiple domains of urban development. Key application areas discussed include transportation systems, energy management, healthcare services, infrastructure planning, public safety, and sustainable urban governance.Beyond conceptual foundations, the book highlights practical frameworks, real-world case studies, and technological architectures that demonstrate how digital twin ecosystems can improve urban efficiency, resilience, and sustainability. It examines the critical role of data integration, predictive analytics, and IoT-driven connectivity in enabling intelligent city management and proactive decision-making. By presenting global examples and interdisciplinary perspectives, the book bridges the gap between theory and practice, illustrating how digital twins can optimise resource utilisation, enhance citizen services, and support sustainable urban transformation.The book also addresses emerging challenges, ethical considerations, and future research directions in deploying digital twins for smart cities. Issues such as data governance, cybersecurity, interoperability, privacy, and implementation complexity are discussed alongside future trends, including AI-driven urban modelling, edge computing, immersive visualization, and next-generation connectivity. By combining technological insights with urban policy perspectives, this book serves as a valuable resource for researchers, policymakers, urban planners, and technology professionals seeking to understand and implement digital twin technologies for innovative and sustainable urban development.