S&M Young Researcher Paper Award 2020
Recipients: Ding Jiao, Zao Ni, Jiachou Wang, and Xinxin Li [Winner's comments]
Paper: High Fill Factor Array of Piezoelectric Micromachined
Ultrasonic Transducers with Large Quality Factor

S&M Young Researcher Paper Award 2021
Award Criteria
Notice of retraction
Vol. 32, No. 8(2), S&M2292

Print: ISSN 0914-4935
Online: ISSN 2435-0869
Sensors and Materials
is an international peer-reviewed open access journal to provide a forum for researchers working in multidisciplinary fields of sensing technology.
Sensors and Materials
is covered by Science Citation Index Expanded (Clarivate Analytics), Scopus (Elsevier), and other databases.

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S&M2638 Research Paper of Special Issue

Hybrid Predetection Technique for Efficient Tag Identification in Radio-frequency Identification Systems

Kuo-Sen Hsu and Chiu-Kuo Liang

(Received March 22, 2021; Accepted June 10, 2021)

Keywords: anticollision algorithm, predetection technique, radio-frequency identification (RFID) systems

Radio-frequency identification (RFID) is a noncontact automatic identification technology that has been widely used in various modern industries. Due to the continuous improvement in sensing capabilities, energy autonomy, affordability, and usability, RFID is one of the key enabling technologies in realizing the Internet of Things (IoT). With their non-line-of-sight wireless transmission, wireless power, and sensing capability, lightweight RFID sensor tags can be connected to people or objects, which is crucial for future IoT applications such as healthcare, logistics, and manufacturing. The RFID approach with the simultaneous reading of multiple tag features can quickly identify connected “things” for further data communication and integration. Reducing the identification processing time for many tags located inside the interrogation range of the reader is essential. Therefore, an effective protocol must be developed to prevent collisions and reduce useless queries between the reader and tags to achieve rapid identification. Predetection tree-based algorithms, which are based on certain small predetection timeslots that tags can respond to, can eliminate unnecessary idle slots and prevent collision slots. In this paper, an efficient predetection-based anticollision algorithm has been proposed to achieve outstanding tag identification performance. The numbers of collision slots and idle slots are reduced by exploiting a novel predetection mechanism and slot size adjustment technique. Simulation results indicate that the proposed scheme reduces the tag identification time by approximately 30–60% compared with previously proposed predetection-based protocols. Moreover, the numbers of query cycles, collisions, and slots are smaller in the proposed scheme than in the previously proposed protocols.

Corresponding author: Chiu-Kuo Liang

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