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International Journal of Creative and Open Research in Engineering and Management

A Peer-Reviewed, Open-Access International Journal Supporting Multidisciplinary Research, Digital Publishing Standards, DOI Registration, and Academic Indexing.
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ISSN: 3108-1754 (Online)
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ISO Certification: 9001:2015
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License: CC BY 4.0
Peer Review: Double Blind
Volume 02, Issue 10

Published on: October 2026

A DATA DRIVEN IOT FRAMEWORK FOR REAL-TIME INVENTORY TRACKING AND PREDICTIVE MANAGEMENT

PARKAVI M SADHANA S SURUTHI A

MOGANAPRIYA L

Department of Computer Science and Engineering, E.G.S.Pillay  Engineering College, Nagapattinam, Tamilnadu, India

Article Status

Plagiarism Passed Peer Reviewed Open Access

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Abstract

The increasing demand for efficient inventory management has made manual stock tracking difficult and time-consuming. This paper proposes a data-driven IoT framework for real-time inventory tracking and predictive management. The system monitors inventory data, detects stock abnormalities, and generates alerts when stock levels require attention. Machine Learning (ML) techniques are used to analyze historical inventory data and predict future stock requirements.

Keypoints — Internet of Things, Inventory Management, Real-Time Tracking, Machine Learning, Predictive Analytics

How to Cite this Paper

M, P., S, S. & A, S. (2026). A Data Driven IOT Framework for Real-Time Inventory Tracking and Predictive Management. International Journal of Creative and Open Research in Engineering and Management, <i>02</i>(10), 1-9. https://doi.org/10.55041/ijcope.v2i10.192

M, PARKAVI, et al.. "A Data Driven IOT Framework for Real-Time Inventory Tracking and Predictive Management." International Journal of Creative and Open Research in Engineering and Management, vol. 02, no. 10, 2026, pp. 1-9. doi:https://doi.org/10.55041/ijcope.v2i10.192.

M, PARKAVI,SADHANA S, and SURUTHI A. "A Data Driven IOT Framework for Real-Time Inventory Tracking and Predictive Management." International Journal of Creative and Open Research in Engineering and Management 02, no. 10 (2026): 1-9. https://doi.org/https://doi.org/10.55041/ijcope.v2i10.192.

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  • •All submissions are screened under plagiarism detection.
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  • •Peer Review Type: Double-Blind Peer Review
  • •Published on: Oct 28 2026
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