IoT enabled vehicle recognition system using inkjet-printed windshield tag and 5G cloud network

Lubna, , Mufti, N., Ullah, S., Sharif, A., Nawaz, M. W., Alkhayyat, A., Imran, M. A. and Abbasi, Q. H. (2023) IoT enabled vehicle recognition system using inkjet-printed windshield tag and 5G cloud network. Internet of Things, 23, 100873. (doi: 10.1016/j.iot.2023.100873)

Abstract

An IoT-enabled vehicle recognition system is developed and tested in this work, besides the tag antenna design and prototype for the vehicle windshield. Firstly, a flexible, surface-tolerant, low-profile, and low-cost passive UHF-RFID windshield tag inlay is designed. The tag is prototyped as wet-inlay with silver conductive-ink inkjet printed antenna on Polyethylene-Terephthalate layer, bonded with Higgs-EC IC. The dimension of the antenna is 0.25 x 0.05 λ0 . The overall inlay structure is around 0.27 x 0.06 λ0 . The antenna is designed at ETSI band, with a return loss of -14 dB at 900 MHz and a read range of 13.3 m and 8 m over lower and upper bands, respectively. The antenna demonstrates an omnidirectional radiation pattern and a maximum gain of 1.92 dBi. The developed prototype is tested in both indoor and outdoor environments. Secondly, the data is sent over the IoT cloud where decision-making is made for authorization. The reader data is transmitted over MQTT broker, via the Scotland 5G network to the MongoDB database using Python module Pymongo. The algorithm for vehicle recognition is written and verified by testing the dummy registered tags for access authorization, with a 100% recognition accuracy. We achieved higher read ranges, surface tolerance, and low profile features, comparatively. The overall system shows optimally great results.

• Item Type: Articles
• Status: Published
• Refereed: Yes
• Glasgow Author(s) Enlighten ID: -, Lubna and Imran, Professor Muhammad and Nawaz, Mr Muhammad Waqas and Abbasi, Professor Qammer
• Authors: Lubna, , Mufti, N., Ullah, S., Sharif, A., Nawaz, M. W., Alkhayyat, A., Imran, M. A., and Abbasi, Q. H.
• College/School: College of Science and Engineering > School of Engineering > Autonomous Systems and Connectivity; College of Science and Engineering > School of Engineering > Electronics and Nanoscale Engineering
• Journal Name: Internet of Things
• Publisher: Elsevier
• ISSN: 2543-1536
• ISSN (Online): 2542-6605
• Published Online: 08 July 2023
• Copyright Holders: Copyright © 2023 The Authors
• First Published: First published in Internet of Things 23:100873
• Publisher Policy: Reproduced under a Creative Commons License