RFID-Enabled Inventory State Estimation and Automated Replenishment: A Real-Time Machine Learning Framework for Retail Inventory Tracking and Management

Authors

  • Michael Cooney Associate Professor of Cybersecurity, Queensland University of Technology (QUT)

Keywords:

rfid-enabled inventory state estimation, automated replenishment, real-time machine learning framework, retail inventory tracking

Abstract

An agile, lean, and responsive inventory is an inevitable aspect of enabling efficient and effective consumer service and satisfaction under the contemporary turbulent, competitive, and uncertain business environment. Due to its numerous dependencies on the internal as well as external complex business environment of an organization, inventory management is always a matter of focal concern for practitioners and researchers.

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Published

30-06-2026

How to Cite

[1]
“RFID-Enabled Inventory State Estimation and Automated Replenishment: A Real-Time Machine Learning Framework for Retail Inventory Tracking and Management”, Cybersecurity & Net. Def. Research, vol. 6, no. 1, pp. 1–11, Jun. 2026, Accessed: Jun. 05, 2026. [Online]. Available: https://thesciencebrigade.com/cndr/article/view/886