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Article | Open Access

Development of a Novel Noise Reduction Algorithm for Smart Checkout RFID System in Retail Stores

Shazielya Shamsul1Mohammed A. H. Ali1,2( )Salwa Hanim Abdul-Rashid1,2Atef M. Ghaleb3Fahad M. Alqahtani4
Department of Mechanical Engineering, Faculty of Engineering, Universiti Malaya, Kuala Lumpur, 50603, Malaysia
Centre for Sustainable and Smart Manufacturing (CSSM), Faculty of Engineering, Universiti Malaya, Kuala Lumpur, 50603, Malaysia
Department of Industrial Engineering, College of Engineering, Alfaisal University, Riyadh, 11533, Saudi Arabia
Department of Industrial Engineering, College of Engineering, King Saud University, P. O. Box 800, Riyadh, 11421, Saudi Arabia
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Abstract

This paper presents a smart checkout system designed to mitigate the issues of noise and errors present in the existing barcode and RFID-based systems used at retail stores’ checkout counters. This is achieved by integrating a novel AI algorithm, called Improved Laser Simulator Logic (ILSL) into the RFID system. The enhanced RFID system was able to improve the accuracy of item identification, reduce noise interference, and streamline the overall checkout process. The potential of the system for noise detection and elimination was initially investigated through a simulation study using MATLAB and ILSL algorithm. Subsequently, it was deployed in a small-scale environment to validate its real-world performance. Results show that RFID with the proposed new algorithm ILSL and AI basket is capable of accurately detecting the related items while eliminating noise originating from unrelated objects, achieving an accuracy rate of 88%.

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Computers, Materials & Continua
Pages 1277-1304

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Cite this article:
Shamsul S, Ali MAH, Abdul-Rashid SH, et al. Development of a Novel Noise Reduction Algorithm for Smart Checkout RFID System in Retail Stores. Computers, Materials & Continua, 2024, 80(1): 1277-1304. https://doi.org/10.32604/cmc.2024.049257

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Received: 01 January 2024
Accepted: 06 May 2024
Published: 18 July 2024
© The Author 2024.

This work is licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.