IoT-Enabled Vacant Parking Slot Detection System Using Inkjet-Printed RFID Tags

Lubna,; Zahid, Adnan; Mufti, Naveed; Ullah, Sadiq; Nawaz, Muhammad Waqas; Sharif, Abubakar; Imran, Muhammad Ali; Abbasi, Qammer H.

doi:10.1109/jsen.2023.3246382

Cited by 15 publications

(5 citation statements)

References 23 publications

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“…A cheap passive tag optimised for UHF RFIDband operation is proposed by Zahid et al, which may be placed into a plastic display for parking spots [19]. Using the Python package Pymongo, we gather data from the RFID readers and send it to the MongoDB database using the message queuing telemetry transport (MQTT) protocol and the Scotland 5G-network so that we can make decisions and show open parking spots to passing drivers.…”

Section: Related Workmentioning

confidence: 99%

AOA based Masked Region-CNN model for Detection of Parking Space in IoT Environment

et al. 2024

Int. Res. J. multidiscip. Technovation

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Uneven illumination has a significant impact on vision-based automatic parking systems, making it impossible to conduct a correct assessment of parking places in the presence of complicated picture data. In to address this issue, this work provides a deep learning-based system for visual recognition of parking spaces and picture processing. Artificial intelligence (AI) approaches can be used to identify a less expensive and easier-to-implement solution to the parking spot identification challenge, especially since the discipline of deep learning is reshaping the world. Using deep learning techniques, this study offers a dynamic, straightforward, and cost-effective algorithm for the detection of parking spots. In order to determine which parking spots are available and which are occupied, this method employs a Masked Region Based Convolutional Neural Network (MR-CNN) and the intersection over union approach. Cars in the training dataset were spaced more apart than those actually seen, which increased the accuracy of the identification between cars and parking spots. The AOA mechanism enhances the model's ability to focus on relevant regions within an image, improving accuracy in detecting parking spaces. This leads to precise identification of parking slots, reducing false positives and negatives. The sequence and quantity of parking spots, as well as the capacity to predict empty spots, were tested in a case study and found to be accurate. In the experimental results as the AOA based MR-CNN model stretched the accuracy as 98.50 and the recall value as 40.59 then the precision as 96.34 F1-measure as 57.95 correspondingly.

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Section: Related Workmentioning

confidence: 99%

AOA based Masked Region-CNN model for Detection of Parking Space in IoT Environment

et al. 2024

Int. Res. J. multidiscip. Technovation

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“…101 One application of inkjetprinted antennas is RFID tagging. [102][103][104][105][106][107][108] In biomedical applications, RFID tagging is used for smart blood storage/blood bag tagging and patient monitoring. 109 The tags are combined with a sensor, such as a strain sensor, to monitor patient parameters and transmit them to providers.…”

Section: Applications Of Inkjet Antennasmentioning

confidence: 99%

Sensors for Smart Agriculture and Beyond…

2023

Electrochem. Soc. Interface

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“…Inkjet printing leads all additive manufacturing methods in the production of high quality electrical conductors [1][2][3] interconnects [4,5] planar antennas [6][7][8], RFID systems [9][10][11], sensors/transducers [12][13][14] and a host of other electronic devices that utilize metals as the principal functional material. As such, development of printing processes has principally focused on achieving metallic structures with the highest possible electrical conductivity.…”

Section: Introductionmentioning

confidence: 99%

Fabrication of RC filters from a single printed Zn layer by reactive inkjet printing

Radwan,

Sui,

Zorman

2024

Flex. Print. Electron.

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This paper presents the development of planar zinc (Zn) resistor-capacitor (RC) filters from a single printed layer that are both printed and treated at room temperature. The fabrication process involves screen printing the resistor, capacitor and interconnects in a single patterned layer on kraft paper substrates using a Zn microparticle ink. In order to form a distinct resistor and capacitor in the patterned structure, reactive inkjet printing was performed to selectively dispense acetic acid on the RC filter pattern to achieve regions with highly contrasting resistance. The required high degree of spatial contrast was achieved using the positional control of the inkjet printer combined with the number of print passes and drop spacing used to dispense the acetic acid droplets. X-ray diffraction and scanning electron microscopy showed the crystal structure and grain size of Zn microparticles remained unchanged with increasing acetic acid exposure while the prominence of cold-welding increased with increasing exposure. Zn-based RC filters sharing a common set of dimensions but with a wide range of corner frequencies were successfully fabricated using this process. For a fixed filter geometry, the corner frequencies could be tuned from ~7 kHz to ~1 MHz as the number of print passes used to form the resistor increased in a stepwise manner. To the best of our knowledge, this is the first room temperature printing process to produce side-by-side resistors and conductors from the same printed layer and the first printing process of any type to produce RC filters with such a wide range of corner frequencies.

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IoT-Enabled Vacant Parking Slot Detection System Using Inkjet-Printed RFID Tags

Cited by 15 publications

References 23 publications

AOA based Masked Region-CNN model for Detection of Parking Space in IoT Environment

AOA based Masked Region-CNN model for Detection of Parking Space in IoT Environment

Sensors for Smart Agriculture and Beyond…

Fabrication of RC filters from a single printed Zn layer by reactive inkjet printing

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