Handbook of Research on Machine Learning-Enabled IoT for Smart Applications Across Industries

Handbook of Research on Machine Learning-Enabled IoT for Smart Applications Across Industries

Indexed In: SCOPUS
Release Date: July, 2023|Copyright: © 2023 |Pages: 542
DOI: 10.4018/978-1-6684-8785-3
ISBN13: 9781668487853|ISBN10: 1668487853|EISBN13: 9781668487877
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Description & Coverage
Description:

Machine learning (ML) and the internet of things (IoT) are the top technologies used by businesses to increase efficiency, productivity, and competitiveness in this fast-paced digital era transformation. ML is the key tool for fast processing and decision making applied to smart city applications and next-generation IoT devices, which require ML to satisfy their working objective. IoT technology has proven efficient in solving many real-world problems, and ML algorithms combined with IoT means the fusion of product and intelligence to achieve better automation, efficiency, productivity, and connectivity.

The Handbook of Research on Machine Learning-Enabled IoT for Smart Applications Across Industries highlights the importance of ML for IoT’s success and diverse ML-powered IoT applications. This book addresses the problems and challenges in energy, industry, and healthcare and solutions proposed for ML-enabled IoT and new algorithms in ML. It further addresses their accuracy for existing real-time applications. Covering topics such as agriculture, pattern recognition, and smart applications, this premier reference source is an essential resource for engineers, scientists, educators, students, researchers, and academicians.

Coverage:

The many academic areas covered in this publication include, but are not limited to:

  • Agriculture
  • Equipment
  • HR Analytics
  • Internet of Things (IoT)
  • IoT in Healthcare
  • Machine Learning
  • Mechanization
  • Pattern Recognition
  • Smart Applications
  • Solar Panel Tilting System
Reviews & Statements

The Handbook of Research on Machine Learning-Enabled IoT for Smart Applications Across Industries fills a critical gap in AI and machine learning by demonstrating the practical significance of their convergence in real-world applications.

– Jimit Shukla, MCA student at Christ University, Bangalore
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Editor/Author Biographies
Neha Goel working as Associate Professor in the department of Electronics & Communication Engineering at RKGIT, Ghaziabad. She has completed her Phd from SRM university, Chennai in 2019. She has 18 years of rich experience in teaching. Her area of interest on VLSI design, CMOS design, Internet of things, Machine learning. She has guided several B.tech Projects and she has published 38 papers in various National/International journals and conferences. She has granted & published 3 patents. She has also attended various workshops, seminars in various fields.
Ravindra Kumar Yadav is a Professor & Head in the Department of Electronics & Communication Engineering at RKGIT, Ghaziabad. He is B.E., M.E., and PhD in the field of Electronics & Communication Engg. He has 26 years of rich experience in Teaching, Research & Development activities, Administration and Managing & Upbringing of higher Educational Institutions. He has guided several B. Tech and M. Tech project and also guiding PhD students form IIT Dhanbad as co guide. He published 90 papers to his credit in international/national journals, conferences and symposiums. Prof. Yadav is Reviewer for several National/International Journals of high repute. He has chaired/participated technical sessions at multiple international and national conferences / seminars held throughout the country.
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