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RFID Technology for Sensing, Biosensing, and the Internet of Things
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RFID Technology for Sensing, Biosensing, and the Internet of Things

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

Deadline for manuscript submissions: closed (20 December 2022) | Viewed by 5039

Special Issue Editor

Dr. Riccardo Colella

E-Mail Website
Guest Editor
Department of Engineering for Innovation, University of Salento, 73100 Lecce, Italy
Interests: wearable antenna design; RFID technology for healthcare; backscattering-based sensing; 3D-printing/bioprinting in electromagnetics; RF and microwave healthcare systems; medical-IoT

Special Issue Information

Dear Colleagues,

The aim of this Special Issue is to inspire experts focused on RFID Technology for Sensing and the Internet of Things to propose innovative strategies, techniques, and technologies enabling the design of RFID wireless sensing devices and antennas for next-generation IoT systems. The topics of interest include but are not limited to the following:

Compact RFID chip-less or battery-free sensor tags;

Efficient RF power management systems for RFID sensing;

Backscattering-based microwave remote sensors;

Reconfigurable antennas and smart antennas for RFID, RFID sensing, and the IoT;

Non-invasive RFID sensors and biosensors for e-health;

Flexible RFID sensors and antennas;

Novel materials and techniques for sensor RFID tag manufacturing (3D printing, additive manufacturing, etc.);

Fully-integrated RFID components for sensing and communication in the IoT;

Pervasive next-generation IoT and 5G wireless sensing based on RFID concepts.

Dr. Riccardo Colella
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Sensors is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Published Papers (2 papers)

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Research

13 pages, 3855 KiB  
Article
Deployment of Smart Specimen Transport System Using RFID and NB-IoT Technologies for Hospital Laboratory
by Ngoc Thien Le, Mya Myet Thwe Chit, Thanh Le Truong, Atchasai Siritantikorn, Narisorn Kongruttanachok, Widhyakorn Asdornwised, Surachai Chaitusaney and Watit Benjapolakul
Sensors 2023, 23(1), 546; https://0-doi-org.brum.beds.ac.uk/10.3390/s23010546 - 03 Jan 2023
Cited by 4 | Viewed by 2531
Abstract
In this study, we propose a specimen tube prototype and smart specimen transport box using radio frequency identification (RFID) and narrow band–Internet of Things (NB-IoT) technology to use in the Department of Laboratory Medicine, King Chulalongkorn Memorial Hospital. Our proposed method replaces the [...] Read more.
In this study, we propose a specimen tube prototype and smart specimen transport box using radio frequency identification (RFID) and narrow band–Internet of Things (NB-IoT) technology to use in the Department of Laboratory Medicine, King Chulalongkorn Memorial Hospital. Our proposed method replaces the existing system, based on barcode technology, with shortage usage and low reliability. In addition, tube-tagged barcode has not eliminated the lost or incorrect delivery issues in many laboratories. In this solution, the passive RFID tag is attached to the surface of the specimen tube and stores information such as patient records, required tests, and receiver laboratory location. This information can be written and read multiple times using an RFID device. While delivering the specimen tubes via our proposed smart specimen transport box from one clinical laboratory to another, the NB-IoT attached to the box monitors the temperature and humidity values inside the box and tracks the box’s GPS location to check whether the box arrives at the destination. The environmental condition inside the specimen transport box is sent to the cloud and can be monitored by doctors. The experimental results have proven the innovation of our solution and opened a new dimension for integrating RFID and IoT technologies into the specimen logistic system in the hospital. Full article
(This article belongs to the Special Issue RFID Technology for Sensing, Biosensing, and the Internet of Things)
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17 pages, 2304 KiB  
Article
A Bit-Tracking Knowledge-Based Query Tree for RFID Tag Identification in IoT Systems
by Yuan-Cheng Lai, Shan-Yung Chen, Zelalem Legese Hailemariam and Chih-Chung Lin
Sensors 2022, 22(9), 3323; https://0-doi-org.brum.beds.ac.uk/10.3390/s22093323 - 26 Apr 2022
Cited by 7 | Viewed by 1768
Abstract
In an IoT (Internet of Things) system where each IoT device has one/many RFID tags, there might be many RFID tags. However, when multiple tags respond to the reader’s interrogation at the same time, their signals collide. Due to the collision, the reader [...] Read more.
In an IoT (Internet of Things) system where each IoT device has one/many RFID tags, there might be many RFID tags. However, when multiple tags respond to the reader’s interrogation at the same time, their signals collide. Due to the collision, the reader must request the colliding tags to retransmit their IDs, resulting in higher communication overhead and longer identification time. Therefore, this paper presents a Bit-tracking Knowledge-based Query Tree (BKQT), which uses two techniques: knowledge, which stores all the tag IDs that can possibly occur, and bit tracking, which allows the reader to detect the locations of the collided bits in a collision slot. BKQT constructs a query tree for all possible tags, called a k-tree, by using knowledge while it constructs bit-collision cases and the corresponding actions for each node in this k-tree by using bit tracking. In the identification process, BKQT traverses this constructed k-tree and thus identifies the colliding tags faster by taking the actions according to the happening bit-collision cases. From the simulation results, BKQT can improve the identification time by 44.3%, 46.4%, and 25.1%, compared with the previous knowledge-based protocols, Knowledge Query Tree (KQT), Heuristic Query Tree (H-QT), Query Tree with Shortcutting and Couple Resolution (QTSC), respectively. Full article
(This article belongs to the Special Issue RFID Technology for Sensing, Biosensing, and the Internet of Things)
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