Srinath Doss – författare

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.

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.

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.

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.

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 service Explores the technologies to allow human-machine association and its impact on consumption and sustainability Provides sustainable solutions to emerging industrial problems, especially in healthcare, manufacturing, remote sensing, environmental engineering Examines need for data pre-processing, classification & prediction, Cluster Analysis, Mining Multimedia, Text, and Web Data, Advanced machine learning techniques for scientific programming in Industry Presents success stories in the form of case studies of IIoT, IIoRT, Big Data, Intelligent Systems, Deep Learning in Industry 5.0 era The 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 service Explores the technologies to allow human-machine association and its impact on consumption and sustainability Provides sustainable solutions to emerging industrial problems, especially in healthcare, manufacturing, remote sensing, environmental engineering Examines need for data pre-processing, classification & prediction, Cluster Analysis, Mining Multimedia, Text, and Web Data, Advanced machine learning techniques for scientific programming in Industry Presents success stories in the form of case studies of IIoT, IIoRT, Big Data, Intelligent Systems, Deep Learning in Industry 5.0 era The 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.

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.

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 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 products

This 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.

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 products

This 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.

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.

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.

Intelligent Cyber Defense: AI, Autonomous Systems, and the Future of Digital Security presents a comprehensive and multidisciplinary exploration of how artificial intelligence is redefining modern cybersecurity. As cyber threats grow in scale, complexity, and autonomy, conventional rule-based and signature-driven security mechanisms are increasingly inadequate. This book advances a new paradigmintelligence-driven, adaptive, and trustworthy cyber defense systemscapable of anticipating, learning from, and responding to evolving threats in real time.The volume brings together cutting-edge research and applied perspectives across key domains, including AI-enabled threat detection, reinforcement learning-based defense systems, federated and privacy-preserving learning, explainable artificial intelligence, behavioral biometrics, intelligent honeypots, malware evolution analysis, and AI-powered Security Operations Centers. Emerging application areas such as cloud security, Internet of Things (IoT) protection, zero-trust architectures, synthetic data generation, and metaverse security are examined in depth, reflecting the expanding digital attack surface of contemporary cyber ecosystems.Special emphasis is placed on trust, transparency, ethics, and governance, addressing critical challenges such as model explainability, data privacy, bias mitigation, regulatory compliance, and responsible AI deployment. Through theoretical foundations, real-world case studies, benchmark datasets, and future outlooks, the book bridges the gap between academic research and operational cybersecurity practice.Designed for researchers, postgraduate students, cybersecurity professionals, system architects, and policymakers, this edited volume serves as both a reference and a roadmap for building resilient, intelligent, and ethically grounded cyber defense infrastructures. It is a timely contribution for those seeking to understand and shape the future of AI-enabled cybersecurity in an increasingly interconnected and automated digital world.