面向智慧农业的无芯片射频跨域感知研究进展

随着传统农业逐渐向智慧农业转型，室温条件下具有低成本、长寿命、低功耗、小型化的检测手段对于农业环境及动植物本体指标检测至关重要，尤其对于无法进行电路有线连接的农业场景。随着器件传感和无线通信的整合，无芯片射频识别（chipless radio frequency identification, CRFID）因为具有轻量、价格合理、普适性等优势被广泛应用，CRFID标签具有理论上的“无限”寿命，代替了集成电路，成为标识传感信息融合的重要媒介，适用于农业环境、动植物生长监测、物流运输、食品品质检测等。该研究首先介绍了CRFID系统构成，以及其基本原理，指出天线是CRFID实现跨域感知的关键要素之一，随着农业场景中气体、环境温湿度、pH值等变化，天线负载敏感材料的电导率、磁导率、介电常数变化，引起CRFID标签的反向散射信号变化；其次，基于时频域标签，介绍了CRFID用于湿度、温度、气体（二氧化碳、氨气、乙烯）、pH和食品（猪肉、牛肉、鱼肉、果蔬、牛奶）检测的国内外最新研究进展，对比了相关传感器的关键性能指标；最后，针对CRFID技术的成功案例，指出了该类型传感器面临的主要研究挑战、未来研究...

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.