关键词:
Chipless RFID-inspired
Smart agriculture
Internet of Things
Environmental detection
Passive sensor
摘要:
As traditional agriculture gradually transitions into smart agriculture, cost-effective, long-lasting, and low-power sensing methods under ambient conditions hold significant value for environmental monitoring, particularly in agricultural scenarios lacking wired circuit connections. With the integration of sensor and wireless communication capabilities, chipless radio-frequency identification (CRFID) technology has found widespread application due to its portability, affordability, and versatility. CRFID tags, devoid of integrated circuits, theoretically offer an unlimited lifespan, making them well-suited to meet sensing requirements in agricultural environments, including monitoring, logistics, transportation, and food safety checks. In our study, we introduce the sensor system components of CRFID's sensing technology and the fundamental principles behind achieving crossdomain sensing. Since sensitive materials are a crucial component of CRFID-inspired sensing technology, we present materials that undergo significant physical or chemical changes in the environment, such as humidity, temperature, gases, and acidity. Subsequently, we delve into the latest research advancements in CRFID-inspired sensing for humidity, temperature, gases (carbon dioxide, ammonia, and ethylene), and pH detection, based on both time-domain and frequency-domain CRFID-inspired sensors. The detection mechanism of the CRFIDinspired sensor is analyzed across various detection targets, and a comparative evaluation of key performance indicators for these sensors is presented. Furthermore, this study offers a comprehensive summary of the challenges associated with CRFID technology, encompassing sensitive materials, interference suppression, coding capabilities, and manufacturing processes. In conclusion, it underscores the emerging trends of low power consumption and enhanced pervasiveness as promising facets for the future of smart agriculture detection.