可穿戴计算机
接口(物质)
钥匙(锁)
可穿戴技术
计算机科学
资源(消歧)
系统工程
智能传感器
工程类
人机交互
精准农业
传感器融合
嵌入式系统
活动识别
持续监测
无线传感器网络
结构健康监测
用户界面
传感器网络
实时计算
光学传感
数据采集
作者
Fu Zhang,YAN Guangxin,Baoping Yan,Zifei Yang,Yakun Zhang,Yue Wang,Sanling Fu,Ni Ren,Weiwei Li
出处
期刊:Sensor Review
[Emerald Publishing Limited]
日期:2026-07-22
卷期号:: 1-24
标识
DOI:10.1108/sr-03-2026-0341
摘要
Purpose This review aims to highlight the importance of acquiring continuous, in situ physiological information during plant growth through plant monitoring technologies. Compared with noncontact techniques such as optical imaging and remote sensing, wearable sensors offer superior temporal and spatial resolution. However, conventional rigid sensors often damage plant tissues. Flexible sensors, with their excellent flexibility, biocompatibility and interface adaptability, present a promising alternative. This study analyzes the applications, challenges and future directions of wearable flexible sensors in plant monitoring. Design/methodology/approach This review focuses on the key technologies involved in fabricating flexible wearable sensors, including sensor materials and structural design. It then discusses the monitoring roles of these devices in plant growth, covering the surveillance of microclimate, gases and growth processes. Particular attention is given to the working principles, performance, advantages and disadvantages of different sensor types. Data were collected via Web of Science and then manually organized, analyzed and summarized. Findings Current challenges for wearable sensors in plant growth monitoring include the damage caused by rigid sensors to plant tissues, as well as the need for improved long-term stability, better suppression of environmental interference, and enhanced multisensor collaborative optimization in flexible sensing systems. Originality/value This review proposes future development directions such as the development of novel materials and structures for plant sensors, improving the output performance of power supply components, and the integration of multiple parameter indicators. These innovations aim to enhance production efficiency and resource management in smart agriculture, thereby advancing precision agriculture and intelligent ecosystems.
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