Industry 4.0 and Machine Learning. Questo articolo non è disponibile.Industry 4.0 and Machine Learning

This book explores how machine learning algorithms can be applied to Industry 4.0 technologies to enhance their capabilities. It discusses how machine learning can be used for predictive maintenance in smart factories, optimizing supply chain management, and improving quality control through advanced data analytics and also:

• Presents advanced machine learning techniques such as deep learning, reinforcement learning, and ensemble methods specifically tailored for Industry 4.0 applications.
• Explores the integration of machine learning with other Industry 4.0 technologies such as the Internet of Things, big data analytics, cyber-physical systems, and cloud computing.
• Showcases in-depth case studies and real-world examples from various industrial sectors that illustrate successful implementations of machine learning in Industry 4.0.
• Addresses key challenges faced in implementing Industry 4.0 technologies, such as data integration, interoperability, cybersecurity, and scalability.
• Discusses artificial intelligence-driven automation, digital twins, autonomous systems, and the implications of these technologies for the future of manufacturing and industrial engineering.

The text is primarily written for senior undergraduates, graduate students, and academic researchers in electrical engineering, electronics and communication engineering, computer science and engineering, manufacturing engineering, and industrial engineering.

Vivek Singh Kushwah is presently working as Professor in the Department of Electronics and Communications Engineering, at Chaitanya Bharathi Institute of Technology affiliated to Osmania University, Hyderabad, India. He is a senior member of the Institute of Electrical and Electronics Engineers and a fellow of IETE. His areas of research interest include microwave engineering, microstrip antennas, and microstrip filters. He has published more than sixty research papers in journals of national and international reputation. He has also published more than twenty papers in conferences.

Ashish Bagwari is the head of the Electronics and Communications Engineering Department at the Women Institute of Technology Dehradun, India. His areas of research interest include cognitive radio networks, mobile communication, sensor networks, wireless networks, analog communication, wireless and 5G communication, digital communication, and mobile ad-hoc networks. He has published more than one hundred and twenty research papers in journals and conferences of national and international reputation.

K. Vasanth serves as Associate professor and head in the Department of Electronics and Communications Engineering, at Chaitanya Bharathi Institute of Technology affiliated to Osmania University, Hyderabad, India. His areas of research interest include signal processing, image processing, video processing, and VLSI signal processing. He has published more than a hundred research papers in journals and conferences of national and international reputation.

Jorge Luis Victória Barbosa serves as full Professor of applied computing at the University of Vale do Rio dos Sinos (UNISINOS), head of the university's Mobile Computing Lab, and a researcher at the Brazilian Council for Scientific and Technological Development. His main research interest is context prediction using context histories, mainly through similarity and pattern analysis. He has published research papers in journals and conferences of national and international repute.

Jose Alfredo Herrera Quispe serves as the Principal professor, and Director of the School of Computer Science, at National Major University of San Marcos, Peru. He is part of the professionalization program at MIT (Massachusetts Institute of Technology - USA), where he completed a ""Master's in Innovation & Design Thinking"". His lines of research are Artificial Intelligence, Data Mining, and Computing applied to the environment. He has published research papers in journals and conferences of national and international repute.