Abhinav Juneja – författare

Technology is moving at an exponential pace in this era of computational intelligence. Machine learning has emerged as one of the most promising tools used to challenge and think beyond current limitations. This handbook will provide readers with a leading edge to improving their products and processes through optimal and smarter machine learning techniques. This handbook focuses on new machine learning developments that can lead to newly developed applications. It uses a predictive and futuristic approach, which makes machine learning a promising tool for processes and sustainable solutions. It also promotes newer algorithms that are more efficient and reliable for new dimensions in discovering other applications, and then goes on to discuss the potential in making better use of machines in order to ensure optimal prediction, execution, and decision-making. Individuals looking for machine learning-based knowledge will find interest in this handbook. The readership ranges from undergraduate students of engineering and allied courses to researchers, professionals, and application designers.

Technology is moving at an exponential pace in this era of computational intelligence. Machine learning has emerged as one of the most promising tools used to challenge and think beyond current limitations. This handbook will provide readers with a leading edge to improving their products and processes through optimal and smarter machine learning techniques. This handbook focuses on new machine learning developments that can lead to newly developed applications. It uses a predictive and futuristic approach, which makes machine learning a promising tool for processes and sustainable solutions. It also promotes newer algorithms that are more efficient and reliable for new dimensions in discovering other applications, and then goes on to discuss the potential in making better use of machines in order to ensure optimal prediction, execution, and decision-making. Individuals looking for machine learning-based knowledge will find interest in this handbook. The readership ranges from undergraduate students of engineering and allied courses to researchers, professionals, and application designers.

Integration of IoT with Cloud Computing for Smart Applications provides an integrative overview of the Internet of Things (IoT) and cloud computing to be used for the various futuristic and intelligent applications. The aim of this book is to integrate IoT and cloud computing to translate ordinary resources into smart things. Discussions in this book include a broad and integrated perspective on the collaboration, security, growth of cloud infrastructure, and real-time data monitoring.Features: Presents an integrated approach to solve the problems related to security, reliability, and energy consumption. Explains a unique approach to discuss the research challenges and opportunities in the field of IoT and cloud computing. Discusses a novel approach for smart agriculture, smart healthcare systems, smart cities and many other modern systems based on machine learning, artificial intelligence, and big data, etc. Information presented in a simplified way for students, researchers, academicians and scientists, business innovators and entrepreneurs, management professionals and practitioners.This book can be great reference for graduate and postgraduate students, researchers, and academicians working in the field of computer science, cloud computing, artificial intelligence, etc.

Integration of IoT with Cloud Computing for Smart Applications provides an integrative overview of the Internet of Things (IoT) and cloud computing to be used for the various futuristic and intelligent applications. The aim of this book is to integrate IoT and cloud computing to translate ordinary resources into smart things. Discussions in this book include a broad and integrated perspective on the collaboration, security, growth of cloud infrastructure, and real-time data monitoring.Features: Presents an integrated approach to solve the problems related to security, reliability, and energy consumption. Explains a unique approach to discuss the research challenges and opportunities in the field of IoT and cloud computing. Discusses a novel approach for smart agriculture, smart healthcare systems, smart cities and many other modern systems based on machine learning, artificial intelligence, and big data, etc. Information presented in a simplified way for students, researchers, academicians and scientists, business innovators and entrepreneurs, management professionals and practitioners.This book can be great reference for graduate and postgraduate students, researchers, and academicians working in the field of computer science, cloud computing, artificial intelligence, etc.

Artificial intelligence (AI) technology is rapidly gaining popularity across various industries, not just in large corporations but also in our everyday lives. The healthcare sector has particularly benefited from the advancements in AI, as it has revolutionized the way diagnostic information is compiled and utilized to understand and treat diseases.Artificial Intelligence Methods and Applications Enabling Health 5.0 discusses the cutting-edge AI technology that is revolutionizing healthcare education. It explores how AI can enhance, broaden, and update the current healthcare standard, as it uncovers uncharted territory in the quest for the best applications of AI in healthcare. The book synthesizes recent advancements in healthcare decision-making and prediction, which are reshaping the focus of AI in this field. In addition, the book covers how AI is revolutionizing disease diagnosis and treatment within the medical community, providing unparalleled accuracy and efficiency. Lastly, real-time case studies and innovative work are included to offer a glimpse into the future possibilities and scope of AI in healthcare.This book will appeal to a wide range of readers, including those in healthcare, manufacturing, e-commerce, and automation, among others. Technology enthusiasts will also discover valuable insights into the significant progress being made in this field. There remains a constant pursuit of optimal solutions for real-time applications and this book aims to provide answers to this ongoing quest for innovation.

ENABLING HEALTHCARE 4.0 for PANDEMICS The book explores the role and scope of AI, machine learning and other current technologies to handle pandemics. In this timely book, the editors explore the current state of practice in Healthcare 4.0 and provide a roadmap for harnessing artificial intelligence, machine learning, and Internet of Things, as well as other modern cognitive technologies, to aid in dealing with the various aspects of an emergency pandemic outbreak. There is a need to improvise healthcare systems with the intervention of modern computing and data management platforms to increase the reliability of human processes and life expectancy. There is an urgent need to come up with smart IoT-based systems which can aid in the detection, prevention and cure of these pandemics with more precision. There are a lot of challenges to overcome but this book proposes a new approach to organize the technological warfare for tackling future pandemics. In this book, the reader will find: State-of-the-art technological advancements in pandemic management;AI and ML-based identification and forecasting of pandemic spread;Smart IoT-based ecosystem for pandemic scenario.AudienceThe book will be used by researchers and practitioners in computer science, artificial intelligence, bioinformatics, data scientists, biomedical statisticians, as well as industry professionals in disaster and pandemic management.

META-HEURISTIC ALGORITHMS FOR ADVANCED DISTRIBUTED SYSTEMS Discover a collection of meta-heuristic algorithms for distributed systems in different application domains Meta-heuristic techniques are increasingly gaining favor as tools for optimizing distributed systems—generally, to enhance the utility and precision of database searches. Carefully applied, they can increase system effectiveness, streamline operations, and reduce cost. Since many of these techniques are derived from nature, they offer considerable scope for research and development, with the result that this field is growing rapidly. Meta-Heuristic Algorithms for Advanced Distributed Systems offers an overview of these techniques and their applications in various distributed systems. With strategies based on both global and local searching, it covers a wide range of key topics related to meta-heuristic algorithms. Those interested in the latest developments in distributed systems will find this book indispensable. Meta-Heuristic Algorithms for Advanced Distributed Systems readers will also find: Analysis of security issues, distributed system design, stochastic optimization techniques, and moreDetailed discussion of meta-heuristic techniques such as the genetic algorithm, particle swam optimization, and many othersApplications of optimized distribution systems in healthcare and other key??industriesMeta-Heuristic Algorithms for Advanced Distributed Systems is ideal for academics and researchers studying distributed systems, their design, and their applications.

Ethical Decision-Making Using Artificial Intelligence: Challenges, Solutions, and Applications gives invaluable insights into the ethical complexities of artificial intelligence, empowering the navigation of critical decisions that shape our future in an era where AI’s influence on society is rapidly expanding. The significant impact of artificial intelligence on society cannot be overstated in a time of lightning-fast technical development and growing integration of AI into our daily lives. A new frontier of human potential has emerged with the development and application of AI technologies, pushing the limits of what is possible in the areas of innovation and efficiency. AI systems are increasingly trusted with complicated decisions that affect our security, well-being, and the fundamental foundation of our societies as they develop in intelligence and autonomy. These choices have substantial repercussions for both individuals and communities in a wide range of fields, including healthcare, finance, criminal justice, and transportation. The necessity for moral direction and deliberate decision-making procedures is critical as AI systems develop and become more independent. Ethical Decision-Making Using Artificial Intelligence: Challenges, Solutions, and Applications examines the complex relationship between artificial intelligence and the moral principles that guide its application. This book addresses fundamental concerns surrounding AI ethics, namely what moral standards ought to direct the creation and use of AI systems. In order to promote responsible AI development that is consistent with human values and goals, this book’s goal is to equip readers with the knowledge and skills they need to traverse the ethical landscape of AI decision-making.