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Applications of Radio Frequency Identification (RFID) in Wireless Communication Networks

A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Sensor Networks".

Deadline for manuscript submissions: 10 May 2025 | Viewed by 887

Special Issue Editors


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Guest Editor

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Guest Editor
School of Information technology, University of Melbourne, Burwood, VIC 3125, Australia
Interests: security; RFID; WSN; protocol design
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

RFID (radio frequency identification) is an automatic recognition technology that utilizes wireless communication. Generally, a system or a part that employs an IC tag to identify or control various items via wireless communication is called RFID.

RFID stands for “Radio Frequency Identification”, which is a technology that employs radio waves to transmit data between devices. RFID technology possesses a wide range of potential applications and is often cited as a key technology for the “Internet of Things”.

The aim of this Special Issue is to connect researchers and developers from business and academia to offer their perspectives on current trends and challenges in RFID technologies and emerging applications. We welcome the submission of papers that address the fundamental and practical challenges of wireless technologies and emerging applications that propose novel and efficient solutions and techniques.

Potential topics may include, but are not limited to, the following:

  • wireless sensor networks (WSN);
  • cognitive radio (CR);
  • Radio frequency identifier (RFID);
  • Internet of things (IoT);
  • radio frequency (RF);
  • emerging applications.

Prof. Dr. Jemal Abawajy
Dr. Ghaith Khalil
Guest Editors

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Published Papers (1 paper)

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19 pages, 8698 KiB  
Article
The Design of a Vision-Assisted Dynamic Antenna Positioning Radio Frequency Identification-Based Inventory Robot Utilizing a 3-Degree-of-Freedom Manipulator
by Abdussalam A. Alajami and Rafael Pous
Sensors 2025, 25(8), 2418; https://doi.org/10.3390/s25082418 - 11 Apr 2025
Viewed by 287
Abstract
In contemporary warehouse logistics, the demand for efficient and precise inventory management is increasingly critical, yet traditional Radio Frequency Identification (RFID)-based systems often falter due to static antenna configurations that limit tag detection efficacy in complex environments with diverse object arrangements. Addressing this [...] Read more.
In contemporary warehouse logistics, the demand for efficient and precise inventory management is increasingly critical, yet traditional Radio Frequency Identification (RFID)-based systems often falter due to static antenna configurations that limit tag detection efficacy in complex environments with diverse object arrangements. Addressing this challenge, we introduce an advanced RFID-based inventory robot that integrates a 3-degree-of-freedom (3DOF) manipulator with vision-assisted dynamic antenna positioning to optimize tag detection performance. This autonomous system leverages a pretrained You Only Look Once (YOLO) model to detect objects in real time, employing forward and inverse kinematics to dynamically orient the RFID antenna toward identified items. The manipulator subsequently executes a tailored circular scanning motion, ensuring comprehensive coverage of each object’s surface and maximizing RFID tag readability. To evaluate the system’s efficacy, we conducted a comparative analysis of three scanning strategies: (1) a conventional fixed antenna approach, (2) a predefined path strategy with preprogrammed manipulator movements, and (3) our proposed vision-assisted dynamic positioning method. Experimental results, derived from controlled laboratory tests and Gazebo-based simulations, unequivocally demonstrate the superiority of the dynamic positioning approach. This method achieved detection rates of up to 98.0% across varied shelf heights and spatial distributions, significantly outperforming the fixed antenna (21.6%) and predefined path (88.5%) strategies, particularly in multitiered and cluttered settings. Furthermore, the approach balances energy efficiency, consuming 22.1 Wh per mission—marginally higher than the fixed antenna (18.2 Wh) but 9.8% less than predefined paths (24.5 Wh). By overcoming the limitations of static and preprogrammed systems, our robot offers a scalable, adaptable solution poised to elevate warehouse automation in the era of Industry 4.0. Full article
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