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Applied AI and Multimedia Technologies for Smart Manufacturing and CPS Applications

Applied AI and Multimedia Technologies for Smart Manufacturing and CPS Applications
Author(s)/Editor(s): Emmanuel Oyekanlu (Drexel University, USA)
Copyright: ©2023
DOI: 10.4018/978-1-7998-7852-0
ISBN13: 9781799878520
ISBN10: 179987852X
EISBN13: 9781799878544


View Applied AI and Multimedia Technologies for Smart Manufacturing and CPS Applications on the publisher's website for pricing and purchasing information.


In the past decade, artificial intelligence (AI), data analytics, and multimedia technology methods for integrating cyber-physical systems (CPS), smart manufacturing, and Industry 4.0 applications in the manufacturing industries have been steadily growing in availability. However, for industrial leaders, finding applicable, cost effective, and readily implementable multimedia, AI, and data analytics methods for industrial applications remains a daunting, laborious, and very expensive endeavor since the ecosystem of these technologies keeps diverging.

Applied AI and Multimedia Technologies for Smart Manufacturing and CPS Applications provides a review of the state of the art regarding the integration of AI and multimedia technologies for smart manufacturing applications. It conducts a cost-benefit analysis regarding the benefits of the integration of specific AI and multimedia technologies in specific industrial manufacturing applications. Covering topics such as cognitive lead measurement, nonlinear filtering methods, and global product development, this premier reference source is a dynamic resource for business executives and managers, entrepreneurs, IT professionals, manufacturers, students and faculty of higher education, researchers, and academicians.

Author's/Editor's Biography

Emmanuel Oyekanlu (Ed.)

Emmanuel A. Oyekanlu (Member, IEEE) received the B.Tech. degree from the Ladoke Akintola University of Technology, Nigeria, in 2004, the M.Sc. degree in telecommunications from the Blekinge Institute of Technology (BTH), Karlskrona, Sweden, in 2009, the M.Sc. degree in signal processing and the third M.Sc. degree in electrical engineering from BTH, in 2010 and 2011, respectively, and the Ph.D. degree in electrical engineering from Drexel University, Philadelphia, PA, USA, in 2018.,In 2016, he became certified as a Data Scientist by the Massachusetts Institute of Technology (MIT), Cambridge, MA, USA. He also holds a Diploma in Leadership Principles from Harvard University, Cambridge, MA, USA, since May 2020. From 2014 to 2018, he was a Research Fellow with the Electrical Engineering Department, Drexel University, Philadelphia, PA, USA, where he was an Adjunct Professor with the Physics Department in 2018. In early 2019, he joined Comcast, Philadelphia, PA, USA, as a Data Science and Artificial Intelligence Engineer. Since late 2019, he has been with Corning Inc., New York, NY, USA, in the position of Smart Manufacturing, Software, Systems, and Industrial IoT Engineer. He is the author of a book chapter in the area of artificial intelligence integration in complex engineering systems. He also has several peer-reviewed conference and journal publications. His technical interests include software engineering for complex systems, artificial intelligence integration in large systems, embedded machine learning, data science applications in engineering systems, 5G, smart manufacturing, as well as in-building networks and Industrial IoT. In 2016, he was a member of a team assembled by the U.S. Department of Energy (DOE) to design an R&D roadmap for transforming the U.S. electrical power system into a smart grid.,Dr. Oyekanlu is a member of the prestigious Electrical Engineering honors society—Eta Kappa Nu (HKN) and the prestigious Engineers honors society—Tau Beta Pi. He is an Editorial Board Member of the IEEE HKN Magazine and has served on the technical committees of the IEEE workshops and conferences.(Based on document published on 3 November 2020).Show Less


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