SHI Guolong, SHEN Xinyi, GU Lichuan, RAO Yuan, JIAO Jun, HE Yigang. Review of chipless RFID cross-domain sensing for smart agriculture[J]. Transactions of the Chinese Society of Agricultural Engineering (Transactions of the CSAE), 2023, 39(7): 10-23. DOI: 10.11975/j.issn.1002-6819.202212196
    Citation: SHI Guolong, SHEN Xinyi, GU Lichuan, RAO Yuan, JIAO Jun, HE Yigang. Review of chipless RFID cross-domain sensing for smart agriculture[J]. Transactions of the Chinese Society of Agricultural Engineering (Transactions of the CSAE), 2023, 39(7): 10-23. DOI: 10.11975/j.issn.1002-6819.202212196

    Review of chipless RFID cross-domain sensing for smart agriculture

    • Detection technologies have been essential to detect the agro-environmental, plant, and animal ontological indicators in smart agriculture, due to the cost saving, long life, low power consumption, and miniaturization at room temperature. Especially, the agricultural scenarios can also be beyond the wired connections to the circuits. Among them, chipless radio frequency identification (CRFID) has been widely used for its lightweight, affordability, and universality, particularly with the integration of device sensing and wireless communication. The integrated circuits can also be removed as one of the most important media for the fusion of identification and sensing information. The CRFID technology can fully meet the sensing and identification needs of the agricultural environment, such as food safety inspection, logistics, and transportation. In this study, a critical review was proposed on the chipless RFID cross-domain sensing for smart agriculture. Firstly, the system components of CRFID technology were introduced for the fundamentals of cross-domain sensing. Electromagnetic characteristics of the CRFID sensor were used to perceive the change in the physical parameters. The electromagnetic response of the CRFID tag was collected to test the physical/chemical parameters. The sensitive materials were selected to change the conductivity, dielectric constant, or permeability of the tag antenna load. CRFID cross-domain sensing was then realized via the change analysis of the physical parameters to be measured and the resonance response. Secondly, the commonly-used sensitive materials were summarized for the CRFID cross-domain sensing devices and their dielectric properties. The load-sensitive material was one of the key elements of the CRFID sensor. The performance of the sensitive material was represented by the physical, chemical, or biological changes of environmental factors. The sensitive material of the CRFID tag was installed in the structure of the tag sensor, and then served as the base plate of the tag, and the connecting material of the tag antenna. As such, the variable load module was sensitive to environmental parameters. Furthermore, humidity (referring to the content and degree of moisture in the environment) was one of the key indicators to affect the respiration and growth of crops during agricultural production. An appropriate temperature environment was conducive to the healthy growth of crops for the high yield and quality of agricultural products. The CRFID temperature sensor was used to reduce the deployment cost of sensor nodes in the temperature monitoring of large-area agricultural environments suitable for deployment in scenarios, where a circuit-wired connection was unavailable. In addition, carbon dioxide dominated the process of crop growth, especially in a greenhouse environment. Ammonia gas was used as a key detection indicator in the process of microbial meat decomposition. The common gas was found in the process of agricultural planting and protein decomposition of agricultural products, but ammonia gas posed a potential health threat to humans, animals, and plants. Thirdly, CRFID cross-domain sensing was carried out in recent years. Moreover, the latest research progress was summarized on the CRFID sensors for the detection of humidity, temperature, gas (CO2, NH3, and ethylene), pH, and food (pork, beef, fish, fruits and vegetables, and milk). The detection principle of the CRFID tag sensor was analyzed to determine the key performance indicators of relevant sensors. Finally, the current technology was limited in security, networking, mass production, and deployment. The technical and fabrication challenges were proposed for the future trend in smart agriculture scenarios. The successful application of CRFID technology can provide great potential and exciting promise to improve the intelligence of agricultural scene sensing.
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