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

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

Release Date: December, 2022|Copyright: © 2023 |Pages: 349
DOI: 10.4018/978-1-6684-6275-1
ISBN13: 9781668462751|ISBN10: 1668462753|EISBN13: 9781668462775
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Description & Coverage
Description:

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.

Coverage:

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

  • Attack Detection and Prediction
  • Behavioral Analysis
  • Data Quality
  • Distributed Deep Learning
  • Edge Computing
  • Intelligent Broker Design
  • Neural Networks
  • Quality of Service
  • Reinforcement Learning
  • Resource Consumption
  • Smart Healthcare
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Editor/Author Biographies

T. Kavitha is working as a Professor in the Dept. of Computer Engineering, New Horizon College of Engineering (Autonomous), VTU. She completed her Ph.D. in the Faculty of Information and Communication Engineering, Anna University Chennai, India in the year 2014. She received her M.E. degree in Systems Engineering and Operations Research from Anna University, Chennai India in the year 2006. B.E. in Electronics and Communication Engineering from Bharathidasan University, India in the year 2000. She has 21+ years of experience in Teaching and Research from Reputed Engineering Colleges. She is Anna University and VTU recognized supervisor for guiding Ph.D. and M.S. (by Research) Programme. Under her guidance, a scholar completed a Ph.D. at Anna University. She has received Funds from different agencies like ISTE-SRM, VTU-TEQIP, IE, VTU, AICTE-ISTE, and AICTE to organize FDP, workshops, Training, and conferences. She is also a Mentor for the projects who got funds from VTU and KSCKT. (4fa098a7-9f3a-44b8-8159-bb646cd1c22a)

Senbagavalli Ganesan is working as an Associate Professor in the Department of Electronics and Communication Engineering, AMC Engineering College,VTU. She completed her Ph.D in the Faculty of Electronics and Communication Engineering, VTU, Belagavi, India in the year 2021. She received her M.Tech. degree in VLSI system design from JNTU, Andhra Pradesh, India in the year 2008. B.E. in Electronics and Communication Engineering from Madras University, India in the year 2001. She has 18 years of experience in Teaching and Research from Reputed Engineering Colleges. She has published 3 indian patents, 15 research papers in National/International Conferences and various journals.Her field of interests includes Image and video processing, Computer vision and VLSI Design (db49152a-7dbb-4ba6-9e2b-cb3d05806f3c).

Deepika Koundal is currently associated with University of Petroleum and Energy Studies, Dehradun. She received the recognition and honorary membership from Neutrosophic Science Association from University of Mexico, USA. She is also selected as a Young scientist in 6th BRICS Conclave in 2021. She received the Master and Ph.D. degrees in computer science & engineering from the Panjab University, Chandigarh in 2015. She received the B. Tech. degree in computer science & engineering from Kurkushetra University, India. She is the awardee of research excellence award given by Chitkara University in 2019 and UPES in 2022. She has published more than 40 research articles in reputed SCI and Scopus indexed journals, conferences and two books. She is currently a guest editor in Computers & Electrical Engineering, Internet of Things Journals and IEEE Transaction of Industrial Informatics, Computational and Mathematical Methods in Medicine. She is also serving as Associate Editor in IET Image Processing and International Journal of Computer Applications. She also has served on many technical program committees as well as organizing committees and invited to give guest lectures and tutorials in Faculty development programs, international conferences and summer schools. Her Areas of Interest are Artificial Intelligence, Biomedical Imaging and Signals, Image Processing, Soft Computing, Machine Learning/ Deep Learning. She has also served as reviewer in many repudiated journals of IEEE, Springer, Elsevier, IET, Hindawi, Wiley and Sage (1be30547-6970-401d-adca-4435c969d29a).

Yanhui Guo received his Ph.D. degree in the Department of Computer Science, Utah State University, USA. He was a research fellow in the Department of Radiology at the University of Michigan and an assistant professor at St. Thomas University. Dr. Guo is currently an associate professor in the Department of Computer Science at the University of Illinois Springfield. Dr. Guo’s research area includes computer vision, machine learning, data analytics, neutrosophic set, computer-aided detection/diagnosis, and computer-assisted surgery. He has published 3 books, more than 110 journal papers and 40 conference papers, completed more than 10 grant-funded research projects, has 2 patents, and worked as an associate editor of different international journals, reviewers for top journals and conferences. Dr. Guo successfully applied neutrosophic set into image processing in 2008 and has published many research works in this area. Dr. Guo was a co-founder and chief scientist of MedSights Tech Inc., a high technology company focusing on a computer-assisted surgery system. Dr. Guo was awarded a University Scholar in 2019, the university system’s highest faculty honor, recognizing outstanding teaching and scholarship (988cecd2-b017-40fe-ba6c-7c2fecc22c3c).

Deepak Jain is working as an Associate Professor at Institute of Automation, Chongqing University of Posts and Telecommunications, Chongqing, China. He received the Bachelor of Engineering degree from Rajiv Gandhi Proudyogiki Vishwavidyalaya, India, in 2010, the Master of Technology degree from the Jaypee University of Engineering and Technology, India, in 2012, and the Ph.D. degree from the Institute of Automation, University of Chinese Academy of Sciences, Beijing, China. He was an awardee of CAS-TWAS Presidential fellowship from 2014-2018. He was invited as “Foreign Experts” by Shandong Taian Administration of foreign Expert Affairs. He was an Adjunct Associate Professor in Oriental University, Indore. He has presented several papers in peer-reviewed conferences and has published numerous studies in science cited journals. His research interests include deep learning, machine learning, pattern recognition, and computer vision (a315034e-65ed-40d2-99c9-ce4dd5e8458a).

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