Abstract

This paper presents a block-chain enabled inkjet-printed ultrahigh frequency radiofrequency identification (UHF RFID) system for the supply chain management, traceability and authentication of hard to tag bottled consumer products containing fluids such as water, oil, juice, and wine. In this context, we propose a novel low-cost, compact inkjet-printed UHF RFID tag antenna design for liquid bottles, with 2.5 m read range improvement over existing designs along with robust performance on different liquid bottle products. The tag antenna is based on a nested slot-based configuration that achieves good impedance matching around high permittivity surfaces. The tag was designed and optimized using the characteristic mode analysis. Moreover, the proposed RFID tag was commercially tested for tagging and billing of liquid bottle products in a conveyer belt and smart refrigerator for automatic billing applications. With the help of block-chain based product tracking and a mobile application, we demonstrate a real-time, secure and smart supply chain process in which items can be monitored using the proposed RFID technology. We believe the standalone system presented in this paper can be deployed to create smart contracts that benefit both the suppliers and consumers through the development of trust. Furthermore, the proposed system will paves the way towards authentic and contact-less delivery of food, drinks and medicine in recent Corona virus pandemic.

Details

Title
Making assembly line in supply chain robust and secure using UHF RFID
Author
Sharif Abubakar 1 ; Kumar, Rajesh 2 ; Ouyang, Jun 3 ; Abbas, Hasan T 4 ; Alomainy Akram 5 ; Arshad Kamran 6 ; Assaleh Khaled 6 ; Althuwayb Ayman 7 ; Imran Muhammad Ali 8 ; Abbasi, Qammer H 4 

 University of Electronic Science and Technology of China (UESTC), School of Electronic Science and Engineering, Chengdu, China (GRID:grid.54549.39) (ISNI:0000 0004 0369 4060); Government College University Faisalabad, Department of Electrical Engineering and Technology, Faisalabad, Pakistan (GRID:grid.411786.d) (ISNI:0000 0004 0637 891X); University of Glasgow, James Watt School of Engineering, Glasgow, UK (GRID:grid.8756.c) (ISNI:0000 0001 2193 314X) 
 UESTC, Yangtze Delta Region Institute (Huzhou), Huzhou, China (GRID:grid.8756.c) 
 University of Electronic Science and Technology of China (UESTC), School of Electronic Science and Engineering, Chengdu, China (GRID:grid.54549.39) (ISNI:0000 0004 0369 4060) 
 University of Glasgow, James Watt School of Engineering, Glasgow, UK (GRID:grid.8756.c) (ISNI:0000 0001 2193 314X) 
 Queen Mary University of London, School of Electronic Engineering and Computer Science, London, UK (GRID:grid.4868.2) (ISNI:0000 0001 2171 1133) 
 Ajman University, College of Engineering and IT, Ajman, United Arab Emirates (GRID:grid.444470.7) (ISNI:0000 0000 8672 9927) 
 Jouf University, Electrical Engineering Department, Sakaka, Kingdom of Saudi Arabia (GRID:grid.440748.b) (ISNI:0000 0004 1756 6705) 
 University of Glasgow, James Watt School of Engineering, Glasgow, UK (GRID:grid.8756.c) (ISNI:0000 0001 2193 314X); Ajman University, Artificial Intelligence Research Center (AIRC), Ajman, United Arab Emirates (GRID:grid.444470.7) (ISNI:0000 0000 8672 9927) 
Publication year
2021
Publication date
2021
Publisher
Nature Publishing Group
e-ISSN
20452322
Source type
Scholarly Journal
Language of publication
English
ProQuest document ID
2571042680
Copyright
© The Author(s) 2021. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.