This book ** presents some of the most advanced leading-edge technology for the fourth Industrial Revolution -- known as Industry 4.0. The book provides a comprehensive understanding of the interconnections of AI, IoT, big data and cloud computing as integral to the technologies that revolutionize the way companies produce and distribute products and the way local governments deliver their services. The book emphasizes that at every phase of the supply chain, manufactures are found to be interweaving AI, robotics, IoT, big data/machine learning, and cloud computing into their production facilities and throughout their distribution networks. Equally important, the authors show how their research can be applied to computer vision, cyber security, database and compiler theory, natural language processing, healthcare, education and agriculture.

• Presents the fundamentals of AI, IoT, and cloud computing and how they can be incorporatedin Industry 4.0 applications
• Motivates readers to address challenges in the areas of speech communication and signal processing
• Provides numerous examples, case studies, technical descriptions, and approaches of AI/ML

Presents the fundamentals of AI, IoT, and cloud computing and how they can be incorporated Motivates readers to address challenges in the areas of speech communication and signal processing Provides numerous examples, case studies, technical descriptions, and approaches of AI/ML

Autorentext
Amy Neustein, Ph.D. is CEO and Founder of Linguistic Technology Systems, in Fort Lee, NJ (USA) - a think tank for database engineering, scientific computing, and programming language theory. She is the Volume Editor of Advances in Ubiquitous Computing: Cyber-Physical Systems, Smart Cities, and Ecological Monitoring (Elsevier 2020) and author/editor of 16 academic books covering a wide range of topics: speech technology, natural language processing, robotics in healthcare, mobile speech, text mining, voice technologies for speech reconstruction and enhancement, signal and acoustic modeling for speech and communication disorders, acoustic analysis of pathologies in infants and children, legal jurisprudence and child health-related issues, forensic speaker recognition, and data integration and conceptual space modeling for Covid, Cancer and Cardiac Care. She has authored many articles, chapters, and conference papers on this wide panoply of subjects. Dr. Neustein received her Ph.D. in Sociology (with a concentration in sociolinguistics and ethnomethodology) from Boston University. She has served as Editor-in-Chief of the International Journal of Speech Technology (Springer) from 2008 till present. She was featured in March 2018 in the SpringerNature "Women in STEM" joint campaign with the United Nations for women in science and technology during Women's History Month. Dr. Neustein serves as Series Editor of SpringerBriefs in Speech Technology: Studies in Signal Processing, Natural Language Understanding, and Machine Learning (Springer); Series Editor of two additional book series: Signals and Communication Technology (Springer); Speech Technology and Text Mining in Medicine and Healthcare (de Gruyter). ****

Dr Parikshit N. Mahalle is a senior member IEEE and is Professor, Dean Research and Development and Head - Department of Artificial Intelligence and Data Science at Vishwakarma Institute of Information Technology, Pune, India. He completed his Ph. D from Aalborg University, Denmark and continued as Post Doc Researcher at CMI, Copenhagen, Denmark. He has 23 + years of teaching and research experience. He is a member of the Board of Studies in Computer Engineering, Ex-Chairman Information Technology, Savitribai Phule Pune University and various Universities and autonomous colleges across India. He has 12 patents, 200+ research publications (Google Scholar citations-2600 plus, H index-23 and Scopus Citations are 1350 plus with H index -17, Web of Science citations are 438 with H index - 10) and authored/edited 50+ books with Springer, CRC Press, Cambridge University Press, etc. He is editor in chief for IGI Global -International Journal of Rough Sets and Data Analysis, Inter-science International Journal of Grid and Utility Computing, member-Editorial Review Board for IGI Global - International Journal of Ambient Computing and Intelligence and reviewer for various journals and conferences of the repute. His research interests are Machine Learning, Data Science, Algorithms, Internet of Things, Identity Management and Security. He is guiding 8 PhD students in the area of IoT and machine learning and recently, FIVE students have successfully defended their PhD under his supervision. He is also the recipient of "Best Faculty Award" by Sinhgad Institutes and Cognizant Technologies Solutions. He has delivered 200 plus lectures at national and international level.

Dr. Prachi M. Joshi obtained her B.E., MTech degree in Computer Engineering from COEP (College of Engineering, Pune), University of Pune, India. She has completed her Ph.D. in Computer Engineering in the area of Machine Learning from COEP, University of Pune. She has been in teaching and research area for more than 15 years. She has co-authored book on Artificial Intelligence (PHI) and written book chapters for Research Methodology, published by CRC. She has succe

Inhalt
Introduction.- Section 1: Fundamentals of the Industry 4.0.- Fundamental of IoT.- Architecture of IoT.- Automation.- Big data challenges.- Cloud computing services.- convergence of IoT and cloud computing.- Section 2: Emerging trends in Artificial Intelligence.- Knowledge representation.- Machine learning.- Deep learning.- AI based industry automation.- Section 3: AI based data management, architecture and framework.- Algorithms and techniques for data management and cloud.- Reference architectures.- Frameworks for integrating IoT, ML and Cloud.- Section 4: Software Portability and Virtual Machine Design.- Virtual Machine designs.- VM design and programming-language/compiler theory concerns.- Section 5: Security for industry 4.0.- Industry 4.0.- Artificial intelligence.- Machine Learning.- Signal Processing.- Multimedia.- Big data.- Software Portability.- Virtual Machines.- Conclusion.