Journal of Electrical Engineering and Automation
IRO Journals
Volume 6 — Issue 4 — December 2024

Automated Inventory Tracking and Alert System

https://doi.org/10.36548/jeea.2024.4.003
Parthiban R.
Assistant Professor, Department of Computer Science and Engineering, Erode Sengunthar Engineering College, Perundurai,
Bincy S.
Department of Computer Science and Engineering, Erode Sengunthar Engineering College, Perundurai,
Ilamathi D.
Department of Computer Science and Engineering, Erode Sengunthar Engineering College, Perundurai
Deva Priya T.
Department of Computer Science and Engineering, Erode Sengunthar Engineering College, Perundurai
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How to Cite

R., Parthiban, Bincy S., Ilamathi D., and Deva Priya T. 2025. “Automated Inventory Tracking and Alert System”. Journal of Electrical Engineering and Automation 6 (4): 300-314. https://doi.org/10.36548/jeea.2024.4.003.
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Keywords

— IoT
— Cloud Infrastructure
— Machine Learning
— Streaming
— Network
— Deep Learning
Published: 29-01-2025

Abstract

The research is on inventory management systems, focusing on IoT-based solutions, RFID technology, and machine learning applications. The study examines various systems, including automated inventory tracking, real-time monitoring, and predictive analytics for demand forecasting. The survey highlights the benefits of these systems, such as improved inventory accuracy, reduced stockouts, and enhanced customer satisfaction. However, it also discusses challenges and limitations, including dependency on network connectivity, initial setup costs, and data accuracy concerns. This survey provides a comprehensive overview of the current state of inventory management systems, identifying opportunities for future research and development.

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