Streaming Analytics and Anomaly Detection in Complex Supply Networks: An Event-Driven Framework for Real-Time Operational Intelligence

Authors

  • Yang Liu Associate Professor of Computer Science, Shanghai Jiao Tong University

Keywords:

streaming analytics, anomaly detection, complex supply networks, an event-driven framework, real-time operational intelligence, machine learning

Abstract

The management of supply chains is undergoing major changes due to numerous factors, including rapid technological advancements and shifts in business models. The integration between supply chain operational and strategic decisions of a business, as well as supply network design, has been suggested as crucial factors leading to competitive advantage. This essay describes an AI-based system of real-time supply chain state monitoring, analysis, and reconfiguration.

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Published

30-06-2026

How to Cite

[1]
“Streaming Analytics and Anomaly Detection in Complex Supply Networks: An Event-Driven Framework for Real-Time Operational Intelligence”, Adv. in Deep Learning Techniques, vol. 6, no. 1, pp. 19–34, Jun. 2026, Accessed: Jun. 05, 2026. [Online]. Available: https://thesciencebrigade.com/adlt/article/view/778