"This book focuses on different algorithms and models related to AI, big data, and IoT used for various domains. It enables the reader to have a broader and deep understanding of several perspectives, about the dynamics, challenges, and opportunities regarding sustainable development using artificial intelligence, big data, and IoT"--
This book focuses on different algorithms and models related to AI, big data, and IoT used for various domains. It enables the reader to have a broader and deep understanding of several perspectives, about the dynamics, challenges, and opportunities regarding sustainable development using artificial intelligence, big data, and IoT.
This book focuses on different algorithms and models related to AI, big data and IoT used for various domains. It enables the reader to have a broader and deep understanding of several perspectives, about the dynamics, challenges, and opportunities regarding sustainable development using artificial intelligence, big data and IoT. Applications of Artificial Intelligence, Big Data and Internet of Things (IoT) in Sustainable Development, focuses on IT-based advancements in multidisciplinary fields like healthcare, finance, bioinformatics, industrial automation, and environmental science. The authors discuss the key issues of security, management, and the realization of possible solutions to hurdles in sustainable development. The reader will get basic concepts and deep insights of various algorithms and models for various applications such as health care, financial, education, smart cities, smart cars, etc. Finally, the book will also examine the applications and implementation of big data IoT, AI strategies to facilitate the sustainable development goals set by United Nations by 2030. This book is intended to help researchers, academics, and policymakers to analyze the challenges and future aspects for maintaining sustainable development through IoT, big data, and AI.
1. Introduction.
2. Artificial Intelligence for Sustainable Pedagogical
Development.
3. Deep Learning in Computer Vision: Progress and Threats.
4.
Smart Parking System UsingYOLOv3 Deep learning Model.
5. Enhancing Speaker
Diarization for Audio-only Systems using Deep Learning.
6. Food Image
Recognition using CNN, Faster R-CNN & YOLO.
7. Machine learning /deep
learning for Natural disasters.
8. A Recent Survey on LSTM Techniques for
Time-Series Data forecasting: Present State and Future Directions.
9.
Conflicting Statements Detection Using Bi-Directional LSTM.
10. Big Data and
Deep learning in Health Care.
11. Pattern recognition in EMG control of
Bionic Hands.
12. Application of IoT in Food Processing Industry.
13.
Emerging Technologies for Healthcare during the COVID-19 Pandemic.
14. Two
Layered Security Mechanism for Enhanced Biometric Security of IoT Based
Digital Wallet.
15. Fused Deep Learning for Distributed Denial of Service
Attack Detection In IoT.
16. Analyzing the Suitability of Deep Learning
Algorithms in Edge Computing.
17. Effectiveness of Machine and Deep Learning
for BlockChain Technology in Fraud Detection and Prevention.
18.
Advancements in Quantum-PSO and its Application in Sustainable Development.
Dr. Sam Goundar is an international academic having taught at twelve different universities in ten different countries. He is Editor-in-Chief of the International Journal of Blockchains and Cryptocurrencies (IJBC)Inderscience Publishers, Editor-in- Chief of the International Journal of Fog Computing (IJFC)IGI Publishers, Section Editor of the Journal of Education and Information Technologies (EAIT) Springer, and Editor-in-Chief (Emeritus) of the International Journal of Cloud Applications and Computing (IJCAC)IGI Publishers. He is also on the editorial review board of more than 20 high-impact factor journals. Professor Goundar is a senior member of IEEE; a member of ACS; a member of the IITP, New Zealand; Certi cation Administrator of ETA- I, USA; and past president of the South Pacific Computer Society. He also serves on the IEEE Technical Committee for Internet of Things, Cloud Communication and Networking, Big Data, Green ICT, Cybersecurity, Business Informatics and Systems, Learning Technology, and Smart Cities. He is a member of the IEEE Technical Society and a panelist with the IEEE Spectrum for Emerging Technologies.
Dr. Archana Purwar is currently working as Assistant Professor (Senior Grade) in Jaypee Institute of Information Technology, Noida (U.P.) and has been at the institute since 2011. Her areas of interest include database systems, information retrieval, and data mining, soft computing, and big data analytics.
Dr. Ajmer Singh earned his B Tech and M Tech degrees from Kurukshetra University and his PhD from the Deenbandhu Chhoturam University of Science and Technology (DCRUST), Murthal. He is presently working as an Assistant Professor in the Department of Computer Science and Engineering at DCRUST, Murthal, Sonepat, India. With more than 11 years of experience in academic and administrative affairs, he has published more than 20 research papers in various international/national journals and conferences. His research interests include software testing, information retrieval, and data sciences.
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