Improving Barcode Vision Scanning Process using a Drone-based Tracking PID Controller for Warehouse in Industry 4.0

Samer  Al-hamadani; Izzat Al-Darraji; Houssem Jerbi

doi:10.22153/kej.2025.11.002

Vol. 21 No. 2 (2025), Articles

Vol. 21 No. 2 (2025)

Improving Barcode Vision Scanning Process using a Drone-based Tracking PID Controller for Warehouse in Industry 4.0

Articles

Received 2024-05-23,

Revised 2024-10-03,

Accepted 2024-11-10,

Published 2025-06-01

Samer Al-hamadani⁺⁻
Izzat Al-Darraji⁺⁻
Houssem Jerbi⁺⁻

Samer Al-hamadani

Department of Automated Manufacturing ,Al-Khwarizmi College of Engineering, University of Baghdad, Baghdad,

Izzat Al-Darraji

Department of Automated Manufacturing, Al-Khwarizmi College of Engineering, University of Baghdad, Baghdad,

Houssem Jerbi

Department of Industrial Engineering, College of Engineering, University of Hail, Hail, Saudi Arabia

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Keywords

Drone; barcode scanning; vision camera; PID controller; warehouse; industry 4.0

How to Cite

Improving Barcode Vision Scanning Process using a Drone-based Tracking PID Controller for Warehouse in Industry 4.0. (2025). Al-Khwarizmi Engineering Journal, 21(2), 72-92. https://doi.org/10.22153/kej.2025.11.002

Abstract

Drones play a vital role in the fundamental aspects of Industry 4.0 by converting conventional warehouses into intelligent ones, particularly in the realm of barcode scanning. Various potential issues frequently arise during barcode scanning by drones, specifically when the drone camera has difficulty obtaining distinct images due to certain factors, such as distance, capturing the image whilst flying, noise in the environment and different barcode dimensions. In addressing these challenges, this study proposes an approach that combines a proportional–integral–derivative (PID) controller with image processing techniques. The PID controller is responsible for continuously monitoring the camera’s input, detecting the difference between the planned and the real barcode image dimensions, and making immediate changes to the drone position to improve the process of detecting the potential barcode. The aforementioned procedure is implemented on the DJI Tello drone to verify the practical performance of the methodology introduced in this study. Results showed that drones can achieve remarkable barcode scanning performance by incorporating sophisticated computer vision technologies into PID controllers. PID computer vision algorithms are capable of analysing visual data acquired from the drone’s cameras and retrieving barcode information under a variety of situations, such as the size of the barcode, location of the barcode and noise of the warehouse environment.

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