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Blockchain, IoT, and AI Technologies for Supply Chain Management: Apply Emerging Technologies to Address and Improve Supply Chain Management 1st ed. [Pehme köide]

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  • Formaat: Paperback / softback, 544 pages, kõrgus x laius: 235x155 mm, 58 Illustrations, black and white; XXII, 544 p. 58 illus., 1 Paperback / softback
  • Ilmumisaeg: 01-Aug-2024
  • Kirjastus: APress
  • ISBN-13: 9798868803147
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Blockchain, IoT, and AI Technologies for Supply Chain Management: Apply Emerging Technologies to Address and Improve Supply Chain Management 1st ed.Suurem pilt
  • Formaat: Paperback / softback, 544 pages, kõrgus x laius: 235x155 mm, 58 Illustrations, black and white; XXII, 544 p. 58 illus., 1 Paperback / softback
  • Ilmumisaeg: 01-Aug-2024
  • Kirjastus: APress
  • ISBN-13: 9798868803147
Teised raamatud teemal:
Püsilink: https://www.kriso.ee/db/9798868803147.html
Märksõnad:
Examine the synergistic possibilities of combining blockchain, IoT, and AI technologies in supply chain management. This book will address the difficulties and possibilities of integrating these technologies and offer helpful implementation advice.





The current state of supply chain management involves several challenges, including lack of transparency, limited visibility into product movements, inefficient inventory management, and difficulty in tracking and tracing products. Blockchain, IoT, and AI can potentially address some of these challenges and improve supply chain management.





To help illustrate this, case studies and actual instances of businesses implementing or experimenting with blockchain, IoT, and AI technology in their supply chains are included in the book. Youll review helpful advice on implementation and highlight successful deployments, lessons learned, and the impact of these technologies on supply chain visibility, agility, sustainability, and customer experience. This book further elaborates the fundamental concepts of AI and ML algorithms and demonstrates how AI can process enormous volumes of supply chain data to produce actionable insights, improve inventory control, forecast demand, and increase forecasting precision.





This collective work will serve as a comprehensive guide for supply chain professionals, researchers, and technology enthusiasts interested in understanding the potential of blockchain, IoT, and AI technologies in revolutionizing supply chain management practices.





What You Will Learn













Discuss the evolving landscape of technology, potential advancements, and how Blockchain, IoT, and AI can shape the future of supply chains Gain Insight into upcoming developments and prepare for changing dynamics of the industry Understand intricate details of blockchain, IoT, and AI Technologies in real-life scenarios

















Who Is This Book For





Industry Professionals working in the domain of supply chain management who would be interested in understanding how these technologies can enhance efficiency, transparency, and optimization in their supply chains.

Chapter 1: Supply Chain Management Strategy and Practices: Traditional Vs Advanced.
Chapter 2: Convergence of IoT, Artificial Intelligence and Blockchain Approaches for Applications in Supply Chain Management.
Chapter 3: Value Creation in Blockchain-Driven Supply Chain Financing Opportunities.
Chapter 4: Artificial Intelligence Applications for Demand Forecasting & Optimization.
Chapter 5: AI-Enabled Supply Chain Planning and Execution: A Pathway to Sustainability.
Chapter 6: Leveraging IOT In Supply Chain Sustainability: A Provenance Perspective.
Chapter 7: AI And Machine Learning in Supply Chain Optimization: Mapping the Territory.
Chapter 8: Blockchain and IoT Integration Based Transparency of Supply Chain Social Sustainability.
Chapter 9: Integration of Blockchain, IoT, And AI In Supply Chain Management: A New Paradigm for Supply Chain Integration and Collaboration.
Chapter 10: Challenges of Supply Chain Management Post COVID-19: Mitigation Strategies and Practical Lessons Learned.
Chapter 11: Supply Chain 4.0: Autonomous Vehicles and Delivery Robots in Supply Chain Management.
Chapter 12: Blockchain for the Future of Sustainable Supply Chain Management in Industry 4.0.
Chapter 13: Managing the Dynamics of New Technologies in The Global Supply Chain.
Chapter 14: Future Trends and Challenges in Supply Chain Technology.
Chapter 15: Real-World Applications of Generative AI for Data Augmentation.
Chapter 16: Case Studies and Best Practices in Supply Chain Management.

Dr. Veena Grover is a Professor in Department of Management at Noida Institute of Engineering & Technology, India. Her interests include Micro Finance, Sustainability, Macro Economic Variables, and Innovation Strategy. She has published multiple articles in various journals and presented papers in various conferences. At present, she is guiding four research scholars and serves as an Editor of International Journal of Advanced Trends in Technology, Management & Applied Science.





Dr. Balamurugan Balusamy is currently working as Associate DeanStudent Engagement in Shiv Nadar University, India. He has 15 years of experience in the field of computer science. His areas of interest are Internet of Things, Big data, Networking. He has published more than 100 papers and contributed multiple book chapters.





Dr. Mariofanna Milanova is a Professor in Computer Science at the University of Arkansas at Little Rock, USA. She has 30 years of experience in the field of artificial intelligence. Dr. Milanova has extensive academic experience at various academic and research organizations worldwide. Dr. Milanova is an IEEE Senior Member, Fulbright U.S. Scholar, and NVIDIA Deep Learning Institute University Ambassador. Dr. Milanovas work is supported by NSF, NIH, DARPA, DoD, Homeland Security, and NATO as well as Nokia Bell Lab, NJ, USA and NOKIA, Finland. She has published more than 130 publications, over 53 journal papers, 35 book chapters, and numerous conference papers. She also has two patents.





Dr. A. Yovan Felix has mentored students in the project areas of Big Data, Deep Learning, and Data Mining. He has published technical papers in national and international journals. He has over 17 years of experience and expertise in data analytics, smart prediction systems, and deep learning algorithms. He also coordinated in organizing several events at both national and international levels.