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Lookup NU author(s): Dr Jun Zhang, Professor Gui Yun TianORCiD, Adi Marindra, Ali Sunny, Aobo Zhao
This work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0).
© 2017 by the authors; licensee MDPI, Basel, Switzerland. In recent few years, the antenna and sensor communities have witnessed a considerable integration of radio frequency identification (RFID) tag antennas and sensors because of the impetus provided by internet of things (IoT) and cyber-physical systems (CPS). Such types of sensor can find potential applications in structural health monitoring (SHM) because of their passive, wireless, simple, compact size, and multimodal nature, particular in large scale infrastructures during their lifecycle. The big data from these ubiquitous sensors are expected to generate a big impact for intelligent monitoring. A remarkable number of scientific papers demonstrate the possibility that objects can be remotely tracked and intelligently monitored for their physical/chemical/mechanical properties and environment conditions. Most of the work focuses on antenna design, and significant information has been generated to demonstrate feasibilities. Further information is needed to gain deep understanding of the passive RFID antenna sensor systems in order to make them reliable and practical. Nevertheless, this information is scattered over much literature. This paper is to comprehensively summarize and clearly highlight the challenges and state-of-the-art methods of passive RFID antenna sensors and systems in terms of sensing and communication from system point of view. Future trends are also discussed. The future research and development in UK are suggested as well.
Author(s): Zhang J, Tian GY, Marindra AMJ, Sunny AI, Zhao AB
Publication type: Review
Publication status: Published
Journal: Sensors
Year: 2017
Volume: 17
Issue: 2
Online publication date: 29/01/2017
Acceptance date: 23/01/2017
ISSN (print): 1424-8220
ISSN (electronic): 1424-8220
Publisher: MDPI AG
URL: https://doi.org/10.3390/s17020265
DOI: 10.3390/s17020265
Data Access Statement: http://dx.doi.org/10.17634/111827-3
