C. Kishor Kumar Reddy – författare

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.

The 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 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.

The 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.

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:

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:

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.

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.

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.

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.