Manuscript received December 6, 2023; revised January 22, 2024; accepted March 5, 2024; published July 20, 2024
Abstract—Inventory tracking and monitoring is one of the most time-consuming tasks in maintaining a large product or commodity-based facility. Using computer vision techniques to track inventory in these facilities has a great potential because it tries to minimize manual labor, execution time and ensures safety in working facilities. There exist number of solutions which use state of the art computer vision methods and other technologies to track inventory in different warehouses as each man-made scenarios in large warehouse differ from one another. Also, a fully generalized method which applies to all categories of warehouses is still not been outlined. In this paper, we surveyed the computer vision techniques applied in the field of inventory tracking. While surveying, the need for a well-structured documentation that compares the features and different techniques in automated inventory tracking was felt. This work will offer the future developers to understand all the challenges that are associated with this topic and hopefully guide them to find a generalized computer vision-based solution for automated inventory tracking.
Keywords—automated inventory Tracking System (AITS), computer vision, image processing, machine vision
Cite: Md Munimul Hasan Pranto and Jiangjiang Liu, "A Survey on Automated Inventory Tracking Systems ," International Journal of Machine Learning vol. 14, no. 3, pp. 65-69, 2024.
Copyright © 2024 by the authors. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).