C. Kishor Kumar Reddy - Böcker

The book explores the concepts and challenges in developing novel approaches using the Internet of Things, intelligent systems, machine intelligence systems, and data analytics in various industrial sectors such as manufacturing, smart agriculture, smart cities, food processing, environment, defense, stock market and healthcare. Further, it discusses the latest improvements in the industrial sectors using machine intelligence learning and intelligent systems techniques, especially robotics. Features: • Highlights case studies and solutions to industrial problems using machine learning and intelligent systems. • Covers applications in smart agriculture, smart healthcare, intelligent machines for disaster management, and smart manufacturing. • Provides the latest methodologies using machine intelligence systems in the early forecasting of weather. • Examines the research challenges and identifies the gaps in data collection and data analysis, especially imagery, signal, and speech. • Provides applications of digitization and smart processing using the Internet of Things and effective intelligent agent systems in manufacturing. • Discusses a systematic and exhaustive analysis of intelligent software effort estimation models.It will serve as an ideal reference text for graduate students, post-graduate students, IT Professionals, and academic researchers in the fields of electrical engineering, electronics and communication engineering, computer engineering, and information technology.

The book explores the concepts and challenges in developing novel approaches using the Internet of Things, intelligent systems, machine intelligence systems, and data analytics in various industrial sectors such as manufacturing, smart agriculture, smart cities, food processing, environment, defense, stock market and healthcare. Further, it discusses the latest improvements in the industrial sectors using machine intelligence learning and intelligent systems techniques, especially robotics. Features: • Highlights case studies and solutions to industrial problems using machine learning and intelligent systems. • Covers applications in smart agriculture, smart healthcare, intelligent machines for disaster management, and smart manufacturing. • Provides the latest methodologies using machine intelligence systems in the early forecasting of weather. • Examines the research challenges and identifies the gaps in data collection and data analysis, especially imagery, signal, and speech. • Provides applications of digitization and smart processing using the Internet of Things and effective intelligent agent systems in manufacturing. • Discusses a systematic and exhaustive analysis of intelligent software effort estimation models.It will serve as an ideal reference text for graduate students, post-graduate students, IT Professionals, and academic researchers in the fields of electrical engineering, electronics and communication engineering, computer engineering, and information technology.

The text emphasizes the need for data pre-processing, classification and prediction, cluster analysis, mining multimedia, and advanced machine learning techniques for scientific programming in Industry 5.0.Addresses how the convergence of intelligent systems and 5G wireless systems will solve industrial problems such as autonomous robots, and self-driving carsHighlights the methods of smart things in collaborative autonomous fleets and platforms for integrating applications across different business and industry domainsDiscusses important topics such as the Internet of robotic things, cloud robotics, and cognitive architecture for cyber-physical roboticsExplains image compression, and advanced machine learning techniques for scientific programming in Industry 5.0Presents a detailed discussion of smart manufacturing techniques, industrial Internet of things, and supply chain management in Industry 5.0The text is primarily written for graduate students and academic researchers in the fields of industrial engineering, manufacturing engineering, electrical engineering, production engineering, and mechanical engineering.

The book studies emerging and sustaining technologies for applications of Industry 5.0 to develop technological solutions to address numerous real-life challenges to solve sustainable development-related issues. It identifies limitations, pitfalls, and open research questions in industry 5.0, discusses real-time problems, and challenges with equivalent solutions with a focus on sustainable growth to develop, humanization and environmentally friendly intelligent system applications. It analyses applications enabled by Industry 5.0 such as healthcare, supply chain, smart framing, remote sensing, production in manufacturing, and cloud manufacturing. It also includes the difficulties and problems posed by the organization between robots and humans on the assembly line to maintain sustainability.Addresses key challenges in implementing intelligent systems in IoT-based applications, including issues ranging from cost and energy efficiency to availability and quality of serviceExplores the technologies to allow human-machine association and its impact on consumption and sustainabilityProvides sustainable solutions to emerging industrial problems, especially in healthcare, manufacturing, remote sensing, environmental engineeringExamines need for data pre-processing, classification & prediction, Cluster Analysis, Mining Multimedia, Text, and Web Data, Advanced machine learning techniques for scientific programming in IndustryPresents success stories in the form of case studies of IIoT, IIoRT, Big Data, Intelligent Systems, Deep Learning in Industry 5.0 eraThe text is for postgraduate students, professionals, and academic researchers working in the fields of computer science and information technology, especially for professionals and researchers interested in the technological side of sustainable development.

The book studies emerging and sustaining technologies for applications of Industry 5.0 to develop technological solutions to address numerous real-life challenges to solve sustainable development-related issues. It identifies limitations, pitfalls, and open research questions in industry 5.0, discusses real-time problems, and challenges with equivalent solutions with a focus on sustainable growth to develop, humanization and environmentally friendly intelligent system applications. It analyses applications enabled by Industry 5.0 such as healthcare, supply chain, smart framing, remote sensing, production in manufacturing, and cloud manufacturing. It also includes the difficulties and problems posed by the organization between robots and humans on the assembly line to maintain sustainability.Addresses key challenges in implementing intelligent systems in IoT-based applications, including issues ranging from cost and energy efficiency to availability and quality of serviceExplores the technologies to allow human-machine association and its impact on consumption and sustainabilityProvides sustainable solutions to emerging industrial problems, especially in healthcare, manufacturing, remote sensing, environmental engineeringExamines need for data pre-processing, classification & prediction, Cluster Analysis, Mining Multimedia, Text, and Web Data, Advanced machine learning techniques for scientific programming in IndustryPresents success stories in the form of case studies of IIoT, IIoRT, Big Data, Intelligent Systems, Deep Learning in Industry 5.0 eraThe text is for postgraduate students, professionals, and academic researchers working in the fields of computer science and information technology, especially for professionals and researchers interested in the technological side of sustainable development.

The text emphasizes the need for data pre-processing, classification and prediction, cluster analysis, mining multimedia, and advanced machine learning techniques for scientific programming in Industry 5.0.Addresses how the convergence of intelligent systems and 5G wireless systems will solve industrial problems such as autonomous robots, and self-driving carsHighlights the methods of smart things in collaborative autonomous fleets and platforms for integrating applications across different business and industry domainsDiscusses important topics such as the Internet of robotic things, cloud robotics, and cognitive architecture for cyber-physical roboticsExplains image compression, and advanced machine learning techniques for scientific programming in Industry 5.0Presents a detailed discussion of smart manufacturing techniques, industrial Internet of things, and supply chain management in Industry 5.0The text is primarily written for graduate students and academic researchers in the fields of industrial engineering, manufacturing engineering, electrical engineering, production engineering, and mechanical engineering.

This book provides a comprehensive exploration of Industry 6.0, which marks the convergence of intelligent systems, machine learning (ML), deep learning, and human–robot collaboration (HRC) in various sectors. It focuses on how these technologies enable businesses to harness insights from vast datasets, optimize operations, forecast maintenance requirements, and mitigate outages. In this comprehensive book, the authors cover the major aspects of Industry 6.0, including the latest advances in technology, new applications, and the many challenges that accompany the process that is changing it. This book acts as a compass, guiding readers through the labyrinth of Industry 6.0, revealing the complex interactions between technologies, new applications, innovations, and business ecosystems. From a multidisciplinary perspective, the book explores the far‑reaching impact of Industry 6.0 on the business world, revealing its potential to increase productivity, improve decision‑making, and open new opportunities for development. Discusses the transformative impact of Industry 6.0 driven by the convergence of artificial intelligence (AI), ML, and the industrial internet of things (IIoT) in manufacturing Explores the transformative potential of HRC in modern manufacturing, emphasizing the ability of HRC to boost productivity, flexibility, and safety Compares several service models in cloud computing, with a focus on private, public, and community cloud deployment methods Presents information about autism spectrum disorder (ASD) in children and the advanced technology of convolutional neural networks used to detect autism in children Describes the accurate diagnosis of Alzheimer’s disease through integrating state‑of‑the‑art technologies, especially deep learning Focuses on digital adaptation in India’s agricultural sector, especially Uttar Pradesh, highlighting challenges and prospects Presents a visionary leap into Agriculture 6.0, where technology and tradition converge for sustainable farming solutions Provides the mitigation strategies for climate change over multiple locations Explores the transformative impact of recent computational intelligence advancements in vehicle surveillance and recognition, particularly through CCTV analysis Focuses on the exploration and development of a supply chain network design (SCND) model of milk productsThis book will be of interest to researchers, academics, practitioners, technology providers, undergraduate and postgraduate students, scholars, consultants, advisors, and doctors. It can be used by undergraduate and postgraduate students pursuing Industry 6.0 programs in computer science and engineering across the globe.

What are the means to create a paradigm shift from conventional to intelligent companies? Industry 6.0: Technology, Practices, Challenges and Applications shows how integrating Industry 6.0 technology with data creates a framework for that shift. The book discusses the limitations, pitfalls, and open research questions in Industry 6.0, as well as the most recent advances, architectures, frameworks, applications, and novel practices, methods, and techniques. These are vital for resolving intelligent Internet of Things issues. There is a special focus on sustainable growth, humanization and environmentally friendly intelligent system applications, and an emphasis on the latest innovations in intelligent systems in classical machine learning, deep learning, Internet of Things (IoT), Industrial Internet of Things (IIoT), blockchain, knowledge representation, knowledge management, big data, and natural language processing (NLP).Features: Presents the latest trends in the fields of intelligent systems, machine intelligence, deep learning, and Industrial Internet of Things for smart environments. Discusses securing the mobile ad hoc network (MANET) by detecting the Intrusions using CSO and XGBoost model. Highlights the methods of smart things in collaborative autonomous fleets and platforms for integrating applications across different business and industry domains. Focuses on intelligent process manufacturing, automation using robotics, development of robotic appliances, and smart manufacturing. Covers data-driven agriculture, crop disease prediction, drip irrigation systems, pesticide and fertilizer sprinkling using the Industrial Internet of Things, and water estimation systems.With many contemporary articles from both scientists and practitioners working in many fields where intelligent systems and the IIoT can break new ground, the text is assembled to aim at a readership that includes researchers, statisticians, practitioners, scientists, and developers.

This book comprehensively explores the intersection between AI and neurology, focusing on the application of generative models in diagnosing, treating, and managing neurodegenerative diseases. It covers the principles of generative AI and its roles in neuroimaging, biomarker identification, medication development, and tailored treatment options. It examines how advanced AI approaches are leveraged to increase the detection and treatment of neurodegenerative illnesses. The concepts are supported by case studies and examples.Features:Focuses on the emerging field of generative models in neurology.Presents an interdisciplinary approach that bridges AI and medical applications.Examines the ability of neural diffusion models to generate genuine data to enhance healthcare AI.Discusses tools for the adaptation and augmentation of medical images and healthcare data domains.Includes case studies and practical impacts.This book is aimed at graduate students and researchers in biomedical and computer engineering, artificial intelligence, and health informatics.

Soft computing and Industry 5.0 are two distinct concepts that, when combined, can have a significant impact on sustainability initiatives within various industries. Soft computing is a subfield of artificial intelligence (AI) that aims to address problems characterized by uncertainty, imprecision, and partial truth. It encompasses various computational techniques, such as fuzzy logic, neural networks, genetic algorithms, and machine learning, which enable machines to deal with complex and uncertain data in a more human-like manner. Soft computing techniques are particularly valuable in sustainability efforts because they can handle non-linear relationships and uncertain data that often arise in environmental and social contexts. For example, they can be used to optimize energy consumption, waste management, and resource allocation in industries by considering various factors and trade-offs.The book highlights the latest innovations in intelligent systems in classical machine learning, deep learning, Internet of Things (IoT), Industrial Internet of Things (IIoT), blockchain, knowledge representation, knowledge management, big data, and natural language processing. (NLP). The book contains many contemporary articles from both scientists and practitioners working in many fields where soft computing, intelligent systems and the IIoT can break new ground. Intelligent systems and the Internet of Things are now essential technologies in almost every field. From agriculture to industry to healthcare, the scope of smart systems and IIoT is as wide as the horizon. Nowadays, these technologies are extensively used in developed countries, but they are still at an early stage in emerging countries.The primary market of this book is senior undergraduate students, post graduate students, practitioners, researchers, academicians, industrialists, and professionals working in areas of core computer science, electrical engineering, mechanical engineering, environmental engineering and agricultural engineering. The secondary audience of this book is individuals working in the areas of manufacturing, agriculture, remote sensing, environmental engineering, health care, smart cities, smart farming, remote sensing, supply chain management and hydrology.

This book offers a thorough examination of the revolutionary capabilities of quantum computing in the context of Industry 6.0, with a specific emphasis on its use in disaster management. The aim of this proposed book is to clarify how quantum computing, in conjunction with other Industry 6.0 technologies, might profoundly transform our comprehension, preparedness, and response to natural disasters. In the era of Industry 6.0, there is a pressing need for creative solutions to tackle the increasing difficulties caused by natural disasters. This proposed book explores the distinctive characteristics and capacities of quantum computing that make it especially suitable for improving disaster management procedures. The proposed book examines the potential of quantum algorithms to enhance resource allocation, enhance forecasting precision, and facilitate real-time decision-making in the context of rapidly changing crisis scenarios. This proposed book proposes a comprehensive strategy for catastrophe management that is adaptable, robust, and efficient by utilizing quantum computing in conjunction with other advanced technologies.This proposed book offers a comprehensive analysis of the specific ways in which quantum computing can be utilized in different areas of disaster management. It covers topics such as risk assessment, early warning systems, and infrastructure resilience. By examining real-world case studies and examples, readers can acquire valuable insights into the practical implementation and effectiveness of quantum-powered crisis management solutions, showcasing their potential impact. This proposed book acknowledges the ethical consequences of implementing sophisticated technologies in disaster management. It focuses on important ethical and societal factors, including data privacy, algorithmic bias, and fair access to technology. The aim is to ensure that quantum-powered solutions prioritize ethical principles and cater to the requirements of all communities. This proposed book provides readers with a clear understanding of the potential areas for future study, innovation, and collaboration in the field of quantum-powered crisis management systems.

This book investigates the dynamic relationship between artificial general intelligence (AGI) and quantum computing.

This book explores how autonomous AI systems are reshaping human decision-making across various industries and society. The book delves into the concept of Agentic AI—AI systems that can act independently and make decisions without human intervention. Unlike existing literature that speculates about superintelligent systems, this book offers practical insights into how current AI systems are already transforming sectors like health care, finance, and law. It highlights the growing impact of these technologies on professional roles and governance, offering a balanced view of both the opportunities and challenges presented by AI autonomy. The book's findings show that Agentic AI enhances decision-making by improving efficiency, accuracy, and scalability. However, it also presents ethical concerns related to accountability, transparency, and the shifting nature of human responsibility in AI-mediated environments. It emphasizes the need for robust ethical frameworks and governance structures to ensure that AI systems align with human values. By focusing on real-world applications and current AI technologies, the book provides actionable insights for decision-makers, helping businesses, policymakers, and technologists navigate the evolving AI landscape. It offers a roadmap for understanding the present-day capabilities of autonomous systems and prepares professionals for the ethical and operational challenges of integrating these technologies. Readers will gain a comprehensive understanding of how Agentic AI is poised to redefine human life and decision-making, making it essential for anyone interested in the future of technology, ethics, and innovation. Unlike traditional AI, which typically requires human supervision or input, Agentic AI introduces the concept of autonomy—AI systems that can act, learn, and make decisions independently. This paradigm shift challenges the conventional human-centered approach to decision-making, positioning AI as a true partner in complex cognitive tasks. The book also explores the ethical and societal implications of AI autonomy in ways that extend beyond typical discussions.