Neuromorphic Computing-Enabled Digital Twin Framework for Sustainable IT Supply Chain Integration in Smart Urban Ecosystems
DOI:
https://doi.org/10.64229/q5g7dh32Keywords:
Neuromorphic Computing, Digital Twin Framework, Sustainable Supply Chain, Smart Urban Ecosystems, Green Technology Adoption, Circular EconomyAbstract
The convergence of neuromorphic computing, digital twin technologies, and sustainable supply chain management presents unprecedented opportunities for transforming urban cyber-physical systems. This viewpoint paper introduces a novel conceptual framework that integrates neuromorphic computing architectures with digital twin methodologies to optimize sustainable IT supply chain operations within smart urban ecosystems. The proposed framework addresses critical issues related to real-time data processing, energy-efficient computation, and adaptive decision-making for green technology adoption across complex urban supply networks. Through theoretical analysis and conceptual modeling, we demonstrate how brain-inspired computing paradigms can enhance digital twin capabilities for monitoring, predicting, and optimizing supply chain sustainability metrics. The framework incorporates spatiotemporal knowledge graph embeddings, hybrid intelligence systems, and circular economy principles to create responsive, self-adapting supply chain networks. Our approach offers significant implications for urban planners, supply chain managers, and technology implementers seeking to advance computational sustainability science. The integration of neuromorphic processing units with digital twin architectures enables unprecedented energy efficiency improvements of up to 1000x compared to traditional computing approaches while maintaining real-time responsiveness for critical supply chain decisions. This research plays role in emerging urban sector computational sustainability by contributing a foundational framework for next-generation smart city supply chain management systems.
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Copyright (c) 2025 Viraj P. Tathavadekar, Nitin R. Mahankale (Author)
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