Today's business world is changing with the adoption of the internet of things (IoT). IoT is helping in prominently capturing a tremendous amount of data from multiple sources. Realizing the future and full potential of IoT devices will require an investment in new technologies. The Handbook of Research on Deep Learning Techniques for Cloud-Based Industrial IoT demonstrates how the computer scientists and engineers of today might employ artificial intelligence in practical applications with the emerging cloud and IoT technologies. The book also gathers recent research works in emerging artificial intelligence methods and applications for processing and storing the data generated from the cloud-based internet of things. Covering key topics such as data, cybersecurity, blockchain, and artificial intelligence, this premier reference source is ideal for industry professionals, engineers, computer scientists, researchers, scholars, academicians, practitioners, instructors, and students.

� propos de l?auteur:

P. Swarnalatha is an Associate Professor, in the School of Computing Science and Engineering, Vellore Institute of Technology at Vellore, India. She pursued her Ph.D degree in Image Processing and Intelligent Systems. She has published more than 120 papers in International Journals/International Conference Proceedings/National Conferences. She is having 20+ years of teaching experiences. She has filed two Patents and also awarded with Dr. APJ Abdul Kalam Award for Teaching Excellence. She is a senior member of IACSIT, CSI, ACM, IACSIT, IEEE (WIE), ACEEE. She is an Editorial board member/reviewer of reputed International/ National Journals and Conferences. Her current research interest includes Image Processing, Remote Sensing, Artificial Intelligence and Software Engineering.

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Deep Learning Techniques for Cloud-Based Industrial IoT

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