The integration of Artificial Intelligence (AI) into supply chain management (SCM) is transforming traditional operations into intelligent, resilient, and sustainable ecosystems. This book explores the application of AI-driven models to enhance decision-making, optimize logistics, and minimize environmental impact across various stages of the supply chain. Emphasis is placed on how machine learning, deep learning, and predictive analytics enable proactive demand forecasting, waste reduction, and resource optimization. The research proposes a sustainability-centered framework that combines AI-based optimization with environmental, social, and governance (ESG) principles to achieve transparency, traceability, and ethical sourcing. The findings demonstrate that AI adoption not only strengthens supply chain agility and resilience but also contributes significantly to achieving Sustainable Development Goals (SDGs) by promoting circular economy practices and carbon footprint minimization.
Features:
• Includes a step-by-step procedure for developing the Blockchain Internet of Things for industries using D-APP and hyperledgers.
• Covers different blockchain and Internet of Things-based sustainable supply chain management merits, demerits, challenges, and risks.
• Delves into the integration of artificial intelligence into smart contracts to foster responsible and efficient operations across industries.
• Showcases the use of artificial intelligence algorithms within smart contract frameworks to optimize decision-making processes and ensure ethical considerations are prioritized in automated contract executions.
• Explores how artificial intelligence-driven solutions are being tailored to meet the unique demands of different sectors, including manufacturing, healthcare, retail, agriculture, and logistics.
It is primarily written for senior undergraduates, graduate students, and academic researchers in electrical engineering, electronics and communications engineering, computer science and engineering, supply chain management, manufacturing engineering, and industrial engineering.
The book explores the application of AI-driven models to enhance decision-making, optimize logistics, and minimize environmental impact across various stages of the supply chain. Emphasis is placed on how machine learning, deep learning, and predictive analytics enable proactive demand forecasting, waste reduction, and resource optimization.
Chapter
1. AI and Blockchain-IoT (BIoT) for Supply Chain Sustainability.
Chapter
2. Integrating Artificial Intelligence and Blockchain-IoT for
Sustainable Supply Chain Practices.
Chapter
3. Redefining Efficiency and
Resilience in Supply Chain Management.
Chapter
4. Explainable AI for All:
Sustainable Supply Chains and Inclusive Accessibility for Persons with
Disabilities.
Chapter
5. Resilient and Sustainable Supply Chains: Leveraging
AI and IoT for Real-Time Risk Intelligence.
Chapter
6. Ethical and Social
Implications of AI in Sustainable Supply Chain Management.
Chapter
7.
Responsible AI and Blockchain-Based Smart Contracts for Industries.
Chapter
8. The Evolution of Supply Chains and the Role of Blockchain in Transforming
Transparency, Trust, and Efficiency.
Chapter
9. Blockchain and IoT:
Successful Enablers of Sustainable Food Supply Chain.
Chapter
10. Deep
Learning based Barcode and Quick Response code Recognition for Real-Time
Supply Chain Management applications.
Chapter
11. Revolutionizing Supply
Chain Management with AI-Driven Digital Twin Networks in 6G Era
N. Nasurudeen Ahamed received his Bachelors Degree in Computer Science and Engineering, followed by a Masters Degree in Computer Science and Engineering. He also earned a PhD in Computer Science and Engineering. Currently, he serves as a postdoctoral fellow at the United Arab Emirates University, UAE. He has accumulated 11 years of teaching experience. His research interests are diverse, encompassing areas such as Blockchain, Cybersecurity, Supply Chain Management, and Industry 4.0.
P. Karthikeyan is currently working as an Associate Professor in SoCSE at RV University, Bangalore, India. He possesses a high level of proficiency in project development and research, specializing in the domains of Cloud computing and the practical application of deep learning. He is well-versed in programming languages, including Java, Python, R, and C.
Polinpapilinho F. Katina is an Associate Professor in the Department of Informatics and Engineering Systems at the University of South Carolina Upstate (Spartanburg, South Carolina, USA). His areas of research/teaching interests include, among others, Complex System Governance, Critical Infrastructure Systems, Decision Making and Analysis (under uncertainty), Emerging Technologies, Energy Systems (Smart Grids), Engineering Management, Infranomics, Manufacturing Systems, System-of-Systems, Systems Engineering, Systems pathology, and Systems Thinking.
