Convergence of Deep Learning and Internet of Things: Computing and Technology

Convergence of Deep Learning and Internet of Things: Computing and Technology

Copyright: © 2023 |Pages: 349
ISBN13: 9781668462751|ISBN10: 1668462753|ISBN13 Softcover: 9781668462768|EISBN13: 9781668462775
DOI: 10.4018/978-1-6684-6275-1
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MLA

Kavitha, T., et al., editors. Convergence of Deep Learning and Internet of Things: Computing and Technology. IGI Global, 2023. https://doi.org/10.4018/978-1-6684-6275-1

APA

Kavitha, T., Senbagavalli, G., Koundal, D., Guo, Y., & Jain, D. (Eds.). (2023). Convergence of Deep Learning and Internet of Things: Computing and Technology. IGI Global. https://doi.org/10.4018/978-1-6684-6275-1

Chicago

Kavitha, T., et al., eds. Convergence of Deep Learning and Internet of Things: Computing and Technology. Hershey, PA: IGI Global, 2023. https://doi.org/10.4018/978-1-6684-6275-1

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Digital technology has enabled a number of internet-enabled devices that generate huge volumes of data from different systems. This large amount of heterogeneous data requires efficient data collection, processing, and analytical methods. Deep Learning is one of the latest efficient and feasible solutions that enable smart devices to function independently with a decision-making support system.

Convergence of Deep Learning and Internet of Things: Computing and Technology contributes to technology and methodology perspectives in the incorporation of deep learning approaches in solving a wide range of issues in the IoT domain to identify, optimize, predict, forecast, and control emerging IoT systems. Covering topics such as data quality, edge computing, and attach detection and prediction, this premier reference source is a comprehensive resource for electricians, communications specialists, mechanical engineers, civil engineers, computer scientists, students and educators of higher education, librarians, researchers, and academicians.

Table of Contents

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Front Materials
Title Page
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Copyright Page
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Advances in Computational Intelligence and Robotics (ACIR) Book Series
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Editorial Advisory Board
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Preface
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Acknowledgment
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Chapters
Back Materials
Compilation of References
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About the Contributors
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Index
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