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Deep Learning Technologies for the Sustainable Development Goals

Issues and Solutions in the Post-COVID Era

  • Highlights deep learning techniques that impact the implementation strategies toward achieving the UNSDGs
  • Provides comprehensive survey on the major applications and research, based on deep learning techniques focused on SDGs
  • Discusses the implications of how deep learning enables the delivery agenda for sustainable development

Part of the book series: Advanced Technologies and Societal Change (ATSC)

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Table of contents (15 chapters)

  1. Front Matter

    Pages i-xii
  2. Leveraging Fog Computing for Healthcare

    • Avita Katal
    Pages 51-68
  3. Study of UAV Management Using Cloud-Based Systems

    • Sonali Vyas, Sourabh Singh Verma, Ajay Prasad
    Pages 97-110
  4. Contemporary Role of Blockchain in Industry 4.0

    • Shaurya Gupta, Sonali Vyas, Vinod Kumar Shukla
    Pages 111-122
  5. SDGs Laid Down by UN 2030 Document

    • Vishakha Goyal, Mridul Dharwal
    Pages 123-132
  6. Healthcare 4P: Systematic Review of Applications of Decentralized Trust Using Blockchain Technology

    • Deepika Sachdev, Shailendra Kumar Pokhriyal, Sylesh Nechully, Sai Shrinvas Sundaram
    Pages 133-156
  7. Implementation of an IoT-Based Water and Disaster Management System Using Hybrid Classification Approach

    • Abhishek Badholia, Anurag Sharma, Gurpreet Singh Chhabra, Vijayant Verma
    Pages 157-173
  8. Transportation Management Using IoT

    • Amit Singh
    Pages 203-226
  9. Enhancing Shoppers’ Loyalty by Prioritizing Customer-Centricity Drivers in the Retail Industry

    • Vishal Srivastava, Manoj Kumar Srivastava, R. K. Singhal
    Pages 227-246

About this book

This book provides insights into deep learning techniques that impact the implementation strategies toward achieving the Sustainable Development Goals (SDGs) laid down by the United Nations for its 2030 agenda, elaborating on the promises, limits, and the new challenges. It also covers the challenges, hurdles, and opportunities in various applications of deep learning for the SDGs. A comprehensive survey on the major applications and research, based on deep learning techniques focused on SDGs through speech and image processing, IoT, security, AR-VR, formal methods, and blockchain, is a feature of this book. In particular, there is a need to extend research into deep learning and its broader application to many sectors and to assess its impact on achieving the SDGs. The chapters in this book help in finding the use of deep learning across all sections of SDGs. The rapid development of deep learning needs to be supported by the organizational insight and oversight necessary for AI-based technologies in general; hence, this book presents and discusses the implications of how deep learning enables the delivery agenda for sustainable development.

Editors and Affiliations

  • University of Petroleum and Energy Studies, Dehradun, India

    Virender Kadyan, T. P. Singh

  • University of Port Harcourt, Port Harcourt, Rivers State, Nigeria

    Chidiebere Ugwu

About the editors

Dr. Virender Kadyan is currently working as Associate Professor in Informatics Cluster , School of Computer Science, University of Petroleum and Energy Studies, Dehradun, Uttarakhand, India. He has completed his Ph.D. and M.Tech. from Chitkara University, Punjab, in 2018 and Kurukshetra University, Kurukshetra, in 2013.  His research interest includes automatic speech recognition and speaker identification & verification.

Dr. T P Singh is currently positioned as Professor and Head, School of Computer Science, University of Petroleum & Energy Studies, Dehradun, Uttarakhand, India. He holds a Doctorate in Computer Science from Jamia Millia Islamia University, New Delhi. He carries 26 years of rich experience with him. To his credit there are more than 35 research publications and 6 edited books. Dr. Singh is a senior member of IEEE, member of various professional bodies including ACM, IEI, ISTE, IAENG, etc., and also on the editorial/reviewer panelof different journals. He is Fellow of IETA-India. His research interests are pattern recognition, machine learning and bulding intelligent hybrid systems.

Prof. Chidiebere Ugwu is currently Director, Information & Communication Technology Centre(ICTC), University of Port Harcourt, Rivers State, Nigeria. He has successfully supervised many Ph.D., M.Sc, B.Sc projects and is currently supervising some. He is a Fellow, Nigeria Computer Society (FNCS); Member, Nigeria Professional Registration Council of Nigeria (MCPN); Member, Institute of Electrical and Electronics Engineers (MIEEE); Member, International Research and Development Institute (MIRDI); and Fellow, Institute of Corporate Administration of Nigeria (FICAN). 


Bibliographic Information

Buy it now

Buying options

eBook USD 79.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book USD 99.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book USD 129.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Other ways to access