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American Scientific Publishing Group

verified Journal

Journal of Cognitive Human-Computer Interaction

ISSN
Online: 2771-1463 Print: 2771-1471
Frequency

Continuous publication

Publication Model

Open access journal. All articles are freely available online with no APC.

Journal of Cognitive Human-Computer Interaction
Full Length Article

Volume 2Issue 2PP: 65-71 • 2022

Counterfeit Product Detection System Using One-Time QR code

Ramgude Akshay Dili 1* ,
K. Vengatesa 1 ,
Kunal Joshi 1 ,
Chaitanya Tekane 1
1Department of Computer Engineering, Sanjivani College of Engineering, Kopargaon, India
* Corresponding Author.
Received:December29, 2021 Accepted:April 09, 2022

Abstract

Counterfeit goods have become particularly crucial issue in the product manufacturing industry in recent years. This phenomenon has an impact on company sales and profits. This problem affects a variety of industries, including pharmaceuticals, electronics, jewellery, and cosmetics. We also recognize that in today's fast changing digital environment, smartphones have become both common and necessary. Various smartphone applications have been developed, allowing us to increase our productivity while also saving time. In recent years, several digital technologies have been introduced, such as QR codes, barcodes, OTP verification, call verification, and so on for detecting falsified products. However, due to reasons such as complicated functionality, easy cheating, and poor user experience, they were unable to implement these ideas on a large scale. A one-time QR code-based solution is used to ensure the identification of real products across the supply chain and at the consumer end, avoiding product counterfeiting. By using this system, consumers can easily differentiate between genuine and tampered or counterfeit product without any registration. The proposed system also helps the organization get data of the customers based on the region where their product is being sold. The given approach is quite scalable, fool-proof and cost effective as it uses centralized database, QR code generator and scanner.

Keywords

Counterfeit QR code Centralized Database Scratch label

References

[1] M. Bala Krishna and Arpit Dugar, “Product Authentication Using QR Codes: A Mobile Application to Combat Counterfeiting”, Aug 2016.
[2] M. C. Jayaprasanna, V. A. Soundharya, M. Suhana and S. Sujatha, "A Block Chain based Management System for Detecting Counterfeit Product in Supply Chain," 2021 Third International Conference on Intelligent Communication Technologies and Virtual Mobile Networks (ICICV), 2021, pp. 253-257, doi: 10.1109/ICICV50876.2021.9388568.
[3] Kentaroh Toyoda, P. Takis Mathiopoulos, I. Sasase and TomoakiOhtsuki, “A Novel Blockchain-Based Product Ownership ManagementSystem (POMS) for Anti-Counterfeits in the Post Supply Chain,” June2017.
[4] Jinhua ma, Shih-Ya Lin, Xin Chen, Hung-min-sun, Yeh-Cheng Chen, Huaxiong Wang” A Block Chain Based Application For Product AntiCounterfeiting” Feb,2020.
[5] Muhammad Asif Habib, Muhammad Bilal Sardar, Sohail Jabbar, C M Nadeem Faisal, Nasir Mahmood and ,” Block chain-based Supply Chain for the Automation of Transaction Process: Case Study based Validation”,March,2020
[6] JiewuLeng, Pingyu Jiang, Kailin Xu, Qiang Liu, J.Leon Zhao, YiyangBian,Rui Shi” Makerchain: A Block Chain With Chemical Signature For Self Organizing Process In Social Manufacturing”, June 2019.
[7] Ghaith Khalil, Robin Doss, Morshed Chowdhury” A New Novel RFID Based Anti-Counterfeiting Scheme for Retail Environment”, March 2020
[8] N. Alzahrani, and N.Bulusu” Block-Supply Chain: A New AntiCounterfeiting Supply Chain Using NFC And Blockchain”, July 2018.
[9] P. Kavitha , R. Subha Shini , R. Priya, "An Implementation Of Statistical Feature Algorithms For The Detection Of Brain Tumor", Journal of Cognitive Human-Computer Interaction, 2021, DOI: https://doi.org/10.54216/JCHCI.010202.
[10] Sonia Jenifer Rayen, "Survey On Smart Cane For Visually Impaired Using IOT", Journal of Cognitive Human- Computer Interaction, 2021, DOI: https://doi.org/10.54216/JCHCI.010205.

Cite This Article

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Dili, Ramgude Akshay, Vengatesa, K., Joshi, Kunal, Tekane, Chaitanya. "Counterfeit Product Detection System Using One-Time QR code." Journal of Cognitive Human-Computer Interaction, vol. Volume 2, no. Issue 2, 2022, pp. 65-71. DOI: https://doi.org/10.54216/JCHCI.020205
Dili, R., Vengatesa, K., Joshi, K., Tekane, C. (2022). Counterfeit Product Detection System Using One-Time QR code. Journal of Cognitive Human-Computer Interaction, Volume 2(Issue 2), 65-71. DOI: https://doi.org/10.54216/JCHCI.020205
Dili, Ramgude Akshay, Vengatesa, K., Joshi, Kunal, Tekane, Chaitanya. "Counterfeit Product Detection System Using One-Time QR code." Journal of Cognitive Human-Computer Interaction Volume 2, no. Issue 2 (2022): 65-71. DOI: https://doi.org/10.54216/JCHCI.020205
Dili, R., Vengatesa, K., Joshi, K., Tekane, C. (2022) 'Counterfeit Product Detection System Using One-Time QR code', Journal of Cognitive Human-Computer Interaction, Volume 2(Issue 2), pp. 65-71. DOI: https://doi.org/10.54216/JCHCI.020205
Dili R, Vengatesa K, Joshi K, Tekane C. Counterfeit Product Detection System Using One-Time QR code. Journal of Cognitive Human-Computer Interaction. 2022;Volume 2(Issue 2):65-71. DOI: https://doi.org/10.54216/JCHCI.020205
R. Dili, K. Vengatesa, K. Joshi, C. Tekane, "Counterfeit Product Detection System Using One-Time QR code," Journal of Cognitive Human-Computer Interaction, vol. Volume 2, no. Issue 2, pp. 65-71, 2022. DOI: https://doi.org/10.54216/JCHCI.020205
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