Topics in Artificial Intelligence Applied to Industry 4.0
Forward thinking resource discussing emerging AI and IoT technologies and how they are applied to Industry 4.0
Topics in Artificial Intelligence Applied to Industry 4.0 discusses the design principles, technologies, and applications of emerging AI and IoT solutions on Industry 4.0, explaining how to make improvements in infrastructure through emerging technologies. Providing a clear connection with different technologies such as IoT, Big Data, AR and VR, and Blockchain, this book presents security, privacy, trust, and other issues whilst delving into real-world problems and case studies.
The text takes a highly practical approach, with a clear insight on how readers can increase productivity by drastically shortening the time period between the development of a new product and its delivery to customers in the market by 50%. This book also discusses how to save energy across systems to ensure competitiveness in a global market, and become more responsive in how they produce products and services for their consumers, such as by investing in flexible production lines.
Written by highly qualified authors, Topics in Artificial Intelligence Applied to Industry 4.0 explores sample topics such as:
* Quantum machine learning, neural network implementation, and cloud and data analytics for effective analysis of industrial data
* Computer vision, emerging networking technologies, industrial data spaces, and an industry vision for 2030 in both developing and developed nations
* Novel or improved nature-inspired optimization algorithms in enhancing Industry 5.0 and the connectivity of any components for smart environment
* Future professions in agriculture, medicine, education, fitness, R&D, and transport and communication as a result of new technologies
Aimed at researchers and students in the interdisciplinary fields of Smart Manufacturing and Smart Applications, Topics in Artificial Intelligence Applied to Industry 4.0 provides the perfect overview of technology from the perspective of modern society and operational environment.
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ISBN-13
978-1-394-21612-3 (9781394216123)
Schweitzer Klassifikation
Mahmoud Ragab AL-Refaey is a Professor of Data Science with the Information Technology Department, Faculty of Computing and Information Technology (FCIT), King Abdulaziz University (KAU), Jeddah, Saudi Arabia and the Mathematics Department, Faculty of Science, Al-Azhar University, Egypt. He obtained his PhD. from the faculty of Mathematics and Natural Sciences of the Christian-Albrechts-University at Kiel (CAU), Germany.
Amit Kumar Tyagi is an Assistant Professor of Department of Fashion Technology, National Institute of Fashion Technology, New Delhi, India. Previously he has worked as Assistant Professor (Grade-2) and Senior Researcher at the School of Computer Science and Engineering, Vellore Institute of Technology (VIT), Chennai, Tamilnadu, India. He received his PhD. Degree in 2018 from Pondicherry Central University, India.
Abdullah Saad AL-Malaise AL-Ghamdi is a Professor of Information Systems Department, Faculty of Computing and Information Technology (FCIT), King Abdulaziz University (KAU), Jeddah, Saudi Arabia and Information Systems Department, School of Engineering, Computing and Design, Dar Al-Hekma University, Jeddah, Saudi Arabia. He is the Secretary General of the Scientific Council at KAU. He received his PhD. degree in Computer Science, George Washington University, USA.
Swetta Kukreja is Associate Professor in the Computer Science and Engineering, Amity University, Mumbai, India. She has more than 10 years of teaching and research experience.
