Marlia Mohd Hanafiah – 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.

This volume discusses topics of global sustainability involving sustainability indicators, stakeholders'' participation, and technological and strategic advances with the goal of "thinking locally to act globally". Scientists, academics, policymakers, and planners are currently focused on escalating global socioeconomic and ecological issues, such as rising inequality, adverse anthropogenic impacts on the environment, and deficiencies in natural resources. These variables are pushing the earth system''s resistance capacity past its breaking point, with additional pressures incurred by a global pandemic. Therefore, this book looks to impart knowledge on participatory learning action research for human and environmental health and well-being. Sustainable development planning and management are needed in these pressing circumstances, and they necessitate an analytical interpretation of ongoing processes, current and future challenges, and an understanding of available tools and technologies. The main sections of the book focus on challenges and management practices for global sustainability, promoting educational values, smart initiatives in urban contexts, and integrating emerging sustainability dimensions in policies and legislation. The primary audience for the work is policy makers, urban planners, social scientists, economists, NGOs, and students, researchers, and educators engaged in environmental social science and sustainability management. 

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.