Mamta Dahiya – författare

This book aims to provide readers with a comprehensive guide to the fundamentals of big data analytics and its applications in various industries and smart societies. What sets this book apart is its in-depth coverage of different aspects of big data analytics, including machine learning algorithms, spatial data analytics, and IoT-based smart systems for precision agriculture. The book also delves into the use of big data analytics in healthcare, energy management, and agricultural development, among others. The authors have used clear and concise language, along with relevant examples and case studies, to help readers understand the complex concepts involved in big data analytics.Key Features:Comprehensive coverage of the fundamentals of big data analyticsIn-depth discussion of different aspects of big data analytics, including machine learning algorithms, spatial data analytics, and IoT-based smart systemsPractical examples and case studies to help readers understand complex conceptsCoverage of the use of big data analytics in various industries, including healthcare, energy management, and agricultureDiscussion of challenges and legal frameworks involved in big data analyticsClear and concise language that is easy to understandThis book is a valuable resource for business owners, data analysts, students, and anyone interested in the field of big data analytics. It provides readers with the tools they need to leverage the power of big data and make informed decisions that can help their organizations succeed. Whether you are new to the field or an experienced practitioner, "Demystifying Big Data Analytics for Industries and Smart Societies" is must-read.

This book aims to provide readers with a comprehensive guide to the fundamentals of big data analytics and its applications in various industries and smart societies. What sets this book apart is its in-depth coverage of different aspects of big data analytics, including machine learning algorithms, spatial data analytics, and IoT-based smart systems for precision agriculture. The book also delves into the use of big data analytics in healthcare, energy management, and agricultural development, among others. The authors have used clear and concise language, along with relevant examples and case studies, to help readers understand the complex concepts involved in big data analytics.Key Features:Comprehensive coverage of the fundamentals of big data analyticsIn-depth discussion of different aspects of big data analytics, including machine learning algorithms, spatial data analytics, and IoT-based smart systemsPractical examples and case studies to help readers understand complex conceptsCoverage of the use of big data analytics in various industries, including healthcare, energy management, and agricultureDiscussion of challenges and legal frameworks involved in big data analyticsClear and concise language that is easy to understandThis book is a valuable resource for business owners, data analysts, students, and anyone interested in the field of big data analytics. It provides readers with the tools they need to leverage the power of big data and make informed decisions that can help their organizations succeed. Whether you are new to the field or an experienced practitioner, "Demystifying Big Data Analytics for Industries and Smart Societies" is must-read.

This book is discussing artificial intelligence-based smart systems for diagnosis and prediction of diseases, artificial intelligence in clinical decision-making, and artificial intelligence tools for clinical and healthcare data. It further highlights the importance of 5G and 6G communication for telemedicine applications and applications of machine learning and deep learning in pandemic epidemiology.This book:Discusses artificial intelligence-inspired Internet of Things-based solutions, and machine learning modeling for smart healthcareExplains the use of computer vision, natural language processing in healthcare, and artificial intelligence in clinical decision-makingIllustrates the role of artificial intelligence in telemedicine applicationsExamines medical image analysis using machine learning, and deep learning techniquesIt is primarily written for senior undergraduates, graduate students, and academic researchers in the fields including computer science and engineering, electronics and communications engineering, and biomedical engineering.

This book is discussing artificial intelligence-based smart systems for diagnosis and prediction of diseases, artificial intelligence in clinical decision-making, and artificial intelligence tools for clinical and healthcare data. It further highlights the importance of 5G and 6G communication for telemedicine applications and applications of machine learning and deep learning in pandemic epidemiology.This book:Discusses artificial intelligence-inspired Internet of Things-based solutions, and machine learning modeling for smart healthcareExplains the use of computer vision, natural language processing in healthcare, and artificial intelligence in clinical decision-makingIllustrates the role of artificial intelligence in telemedicine applicationsExamines medical image analysis using machine learning, and deep learning techniquesIt is primarily written for senior undergraduates, graduate students, and academic researchers in the fields including computer science and engineering, electronics and communications engineering, and biomedical engineering.

Progressive Computational Intelligence, Information Technology and Networking presents a rich and diverse collection of cutting-edge research, real-world applications, and innovative methodologies spanning across multiple domains of computer science, artificial intelligence, and emerging technologies. This comprehensive volume brings together different scholarly chapters contributed by researchers, practitioners, and thought leaders from around the globe.The book explores a wide array of topics including—but not limited to—machine learning, deep learning, cloud computing, cybersecurity, Internet of Things (IoT), blockchain, natural language processing, image processing, and data analytics. It addresses the practical implementation of technologies in sectors such as healthcare, agriculture, education, smart cities, environmental monitoring, finance, and more.Each chapter delves into specific challenges, frameworks, and experimental outcomes, making this book an essential reference for academicians, researchers, industry professionals, and students who aim to stay ahead in the rapidly evolving digital world.

Progressive Computational Intelligence, Information Technology and Networking presents a rich and diverse collection of cutting-edge research, real-world applications, and innovative methodologies spanning across multiple domains of computer science, artificial intelligence, and emerging technologies. This comprehensive volume brings together different scholarly chapters contributed by researchers, practitioners, and thought leaders from around the globe.The book explores a wide array of topics including—but not limited to—machine learning, deep learning, cloud computing, cybersecurity, Internet of Things (IoT), blockchain, natural language processing, image processing, and data analytics. It addresses the practical implementation of technologies in sectors such as healthcare, agriculture, education, smart cities, environmental monitoring, finance, and more.Each chapter delves into specific challenges, frameworks, and experimental outcomes, making this book an essential reference for academicians, researchers, industry professionals, and students who aim to stay ahead in the rapidly evolving digital world.

This book explores emerging advancements in intelligent computing, modern IT infrastructures, and next-generation networking technologies. The book presents contemporary theories, practical implementations, and research trends that integrate artificial intelligence, data-driven systems, and communication networks to solve real-world challenges in academia and industry.The book covers foundational and advanced topics in computational intelligence, including machine learning algorithms, deep learning architecture, evolutionary computing, and fuzzy systems. It further examines information technology frameworks such as cloud computing, big data analytics, cybersecurity mechanisms, and distributed systems. In the networking domain, it discusses Internet of Things (IoT), network security, and performance optimization techniques. Through case studies and applied research findings, the book highlights how intelligent models enhance automation, predictive analysis, and decision-making across sectors like healthcare, smart cities, finance, and education. Emphasis is placed on scalability, efficiency, and integration of AI-driven solutions with modern networking environments. The main findings demonstrate that the convergence of computational intelligence with IT and networking significantly improves system adaptability, resource management, and real-time data processing capabilities.This book is intended for postgraduate students, research scholars, academicians, and industry professionals in computer science, information technology, and electronics engineering. It is particularly valuable for those specializing in artificial intelligence, data science, networking, and cybersecurity who seek updated knowledge on emerging intelligent technologies and integrated computing systems.

This book explores emerging advancements in intelligent computing, modern IT infrastructures, and next-generation networking technologies. The book presents contemporary theories, practical implementations, and research trends that integrate artificial intelligence, data-driven systems, and communication networks to solve real-world challenges in academia and industry.The book covers foundational and advanced topics in computational intelligence, including machine learning algorithms, deep learning architecture, evolutionary computing, and fuzzy systems. It further examines information technology frameworks such as cloud computing, big data analytics, cybersecurity mechanisms, and distributed systems. In the networking domain, it discusses Internet of Things (IoT), network security, and performance optimization techniques. Through case studies and applied research findings, the book highlights how intelligent models enhance automation, predictive analysis, and decision-making across sectors like healthcare, smart cities, finance, and education. Emphasis is placed on scalability, efficiency, and integration of AI-driven solutions with modern networking environments. The main findings demonstrate that the convergence of computational intelligence with IT and networking significantly improves system adaptability, resource management, and real-time data processing capabilities.This book is intended for postgraduate students, research scholars, academicians, and industry professionals in computer science, information technology, and electronics engineering. It is particularly valuable for those specializing in artificial intelligence, data science, networking, and cybersecurity who seek updated knowledge on emerging intelligent technologies and integrated computing systems.