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Revolutionizing Industrial Automation Through the Convergence of Artificial Intelligence and the Internet of Things
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Author(s)/Editor(s): Divya Upadhyay Mishra (ABES Engineering College, Ghaziabad, India)and Shanu Sharma (ABES Engineering College, Ghaziabad, India)
Copyright: ©2023
DOI: 10.4018/978-1-6684-4991-2
ISBN13: 9781668449912
ISBN10: 1668449919
EISBN13: 9781668449936
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DescriptionWith the development of innovative technologies, the study of industrial automation is obtaining extraordinary attention from academia, governments, researchers, and various industrial communities. The technical innovations in advanced technologies such as deep learning, blockchain, artificial intelligence of things (AIOT), and more have unlocked the potential for bringing intelligent automation and efficiency to the industries to control their various operations. These new technologies provide an efficient and secure way for industries to manage and develop products intelligently. Revolutionizing Industrial Automation Through the Convergence of Artificial Intelligence and the Internet of Things includes the recent advancements in exploring and developing AIOT-powered strategies and mechanisms for future industrial automation and transforming industrial functions and architectures to help improve various industrial operations. Covering topics such as convolutional neural networks, smart urban logistics, and industrial automation, this premier reference source is an excellent resource for computer scientists, IT managers, engineers, business leaders and executives, logistics managers, students and faculty of higher education, libraries, researchers, and academicians.
Author's/Editor's Biography
Divya Mishra (Ed.)
Divya Upadhyay Mishra has worked as a full-time academician for the last 15 years. She works as a Professor and Head of Computer Science & Engineering at ABES Engineering College, Ghaziabad. She has a PhD (Engineering) from Amity University Uttar Pradesh MTech (Information Security) from Guru Gobind Singh Indraprastha University, New Delhi. She also holds B. Tech (Computer Science & Engineering) from Sant Longowal Institute of Engineering & Technology, IKJPTU, Punjab. She has published many research papers in reputed international journals and conferences with Scopus & SCI indexing. IEEE Sensors Council also appreciated her for the paper “Application of Non-Linear Gaussian Regression-Based Adaptive Clock Synchronization Technique for Wireless Sensor Network in Agriculture”, IEEE Sensors Journal, Vol. 18, No. 10, May 2018, paper being one of the 25 most downloaded Sensors Journal papers in February 2019. She is an active member of international societies like SM-IEEE and IAENG and an organizing committee for many international conferences, workshops, and seminars to enhance teaching-learning. Her research area includes Networking, Cloud, Security, and IoT.
Shanu Sharma (Ed.)
Shanu Sharma
is an Assistant Professor in the Department of Computer Science & Engineering, ABES Engineering College, Ghaziabad (Affiliated to A.K.T University, Lucknow). She has a PhD from Amity University Uttar Pradesh and M.Tech (Intelligent Systems) from IIIT Allahabad. She has 13+ years of teaching and research experience and taught various courses at the graduate and under graduate level such as Image Processing, Data Mining, Machine Learning, Data Science, Data Structures, Analysis and Design of Algorithms, and Compiler Design. Her research areas include Cognitive Computing, Computer Vision, Pattern Recognition, and Machine Learning. She has published 40+ research papers in renowned Conferences and Journals and is currently associated with various reputed International Conferences and journals as a Reviewer. She has edited various special issues in Scopus indexed journals published by IGI Global, and Bentham Science. She has edited five books with renowned publishers such as Springer, IGI, CRC Press, and River Publishers. She is a senior member of IEEE and also an active member of other professional societies like ACM, Soft Computing Research Society (SCRS), EUSFLAT, and IAENG.
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